Water table management effects on photosynthesis ... · controlled drainage-subirrigation prevents...

Retrospective Theses and Dissertations Iowa State University Capstones, Theses andDissertations

1994

Water table management effects on photosynthesis,chlorophyll, crop yield, and water qualityMohammad Saffar MirjatIowa State University

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Water table management effects on photosynthesis, chlorophyll, crop yield, and water quality

Mirjat, Mohammad SafFar, Ph.D.

Iowa State University, 1994

U M I 300 N. ZeebRd. Ann Arbor, MI 48106

Water table management effects on photosynthesis,

chlorophyll, crop yield, and water quality

by

Mohammad Saffar Mirjat

A Dissertation Submitted to the

Graduate Faculty in Partial fulfillment of the

Requirements for the Degree of

DOCTOR OF PHILOSOPHY

Department: Agricultural and Biosystems Engineering Major: Agricultural Engineering

Approved:

In Charge of Major Work

For the Major Department

For the Graduate College

Iowa State University Ames,Iowa

1994

Signature was redacted for privacy.



ii

TABLE OF CONTENTS Page

GENERAL INTRODUCTION 1

Objectives 4

Explanation of dissertation format 5

REVIEW OF LITERATURE 6

Water table management 6

Water table depth and crop production 8

Photosynthesis response and crop yield 11

Stomatal conductance under different moisture conditions 13

Relationship between chlorophyll content and crop yield 15

Water table management for NO3-N improvement 18

Pesticides in the groundwater 24

Factors affecting fate and behavior of pesticides 26

Pesticide control through water table management 29

PAPER I. EFFECTS OF WATER TABLE DEPTHS ON DIFFERENT PLANT PHYSIOLOGICAL PARAMETERS 32

ABSTRACT 33

in

Page

INTRODUCTION 35

MATERIALS AND METHODS 40

Description of experimental sites 40

Experimental setup at Ames site 40

Experimental setup at Ankeny site 42

Water table management treatments 43

Measurements of plant physiological parameters 44

Chlorophyll Measurements 45

SPAD-502 chlorophyll meter (principle description) 46

Plant culture 47

RESULTS AND DISCUSSION 48

Photosynthesis response to water table depths 48

Effect of water table depth on stomatal conductance 52

Effects of WTD on transpiration rate 55

Effects of WTD on intercellular COj (Ci) 58

Effects of WTD on chlorophyll content 59

Crop canopy temperature and water table depth 62

Relationships between photosynthesis and chlorophyll readings 65

iv

Paqe Relations between stomatal conductance and transpiration rate 68

Crop yield 72

CONCLUSIONS 74

PAPER II. EFFECTS OF WATER TABLE DEPTHS ON THE TRANSPORT OF NO3-N INTO GROUNDWATER 95

ABSTRACT 96

INTRODUCTION 98



Experimental setup at Ames site 105

Experimental setup at Ankeny site 107


Groundwater sampling 109

Soil sampling and analysis methods 110

Soil nitrate extraction and analysis 111

Plant culture 112

RESULTS AND DISCUSSIONS 114

NO3-N concentrations in piezometer water samples at the Ankeny site 114

NO3-N concentrations in suction tube water samples at the Ankeny site 116

V

Page NO3-N concentrations in piezometer water samples at the Ames site 119

NO3-N concentrations in suction tube water samples at the Ames 121

Distribution of NO3-N in the soil profile 123

Crop yield 126

CONCLUSIONS 128

PAPER III. MOVEMENT OF PESTICIDES INTO SHALLOW GROUNDWATER AS AFFECTED BY WATER TABLE MANAGEMENT 146

ABSTRACT 147

INTRODUCTION 149




Groundwater sampling 159

Herbicide extraction procedures 160

Analysis of herbicide 160

Planting, harvesting, and chemical management system 161

RESULTS AND DISCUSSION 162

Atrazine concentrations in piezometer water samples at the Ames site 162

Atrazine concentrations in suction tube water samples at the Ames site 164

vi

Page Atrazine concentrations in piezometer water samples at the Ankeny site 166

Atrazine concentrations in suction tube water samples at the Ankeny site 168

Alachlor concentrations at the Ames site 170

Alachlor concentrations at the Ankeny site 171

Atrazine and alachlor distribution pattern in the soil profile 173

Crop yield 174

CONCLUSIONS 177

OVERALL CONCLUSIONS 197

Physiological parameters and WTDs 197

NO3-N concentrations in groundwater 199

Pesticide concentrations in groundwater 200

Corn yield 201

RECOMMENDATIONS FOR FUTURE WORK 202

REFERENCES 204

ACKNOWLEDGEMENTS 220

APPENDIX: SUMMARIZED DATA ON PLANT PHYSIOLOGICAL PARAMETERS NO3-N AND PESTICIDE 223

1

GENERAL INTRODUCTION

Agricultural production systems in the humid regions of the U.S.A.

historically have been influenced by high rainfall, occasional flooding, and

seasonal drought. These factors contribute to the degradation of

environmentally sensitive areas, such as wetlands and lowlands, and productive

estuarine areas and marshes. Although farmers in the U.S. have been using

subsurface drainage methods to allow cultivation of poorly drained soils for the

past 2 centuries (Fausey et al., 1990), more sophisticated agricultural water-

management techniques are now possible to accommodate crop water needs.

Excess water on the field surface and in the root zone restricts production

of about 25% of U.S. cropland. According to a USDA publication (1987), an

estimated 44 million hectares of agricultural land in the United States benefits

from artificial drainage. The capital value of all U.S. farm drainage is estimated

to be over 40 billion dollars. For example, about 40% of Iowa's corn and

soybean acreage are artificially drained (Kalita and Kanwar, 1992). Thus,

drainage is of vital importance to the sustainability of the current level of

agricultural production and is still needed on much of the corn and soybean land

in the U.S. For instance in Ohio, about 3 million hectares or over 60% of the

cropland needs drainage (Nolte, 1976).

Artificial drainage can provide a suitable environment for plant growth

during the growing season, but excessive drainage is undesirable because it

2

reduces the soil water available to growing plants and can leach fertilizers and

pesticides into receiving streams or deeper groundwater systems where these

chemicals might act as pollutants (Kanwar et al., 1991). Since herbicides are

used on approximately 98% of the corn and soybean acreage in Iowa, the

potential for groundwater contamination from artificially drained soils is high

(Kanwar et al., 1988). Groundwater contamination as a result of nitrate and

pesticide leaching has been reported in Iowa, Minnesota, Ohio and in several

other eastern states (Hallberg, 1986; Kanwar et al., 1988; Kanwar and Baker

1991; Baker and Johnson, 1977; Baker and Johnson, 1981; Bengtson et al.,

1984; Gilliam and Skaggs, 1986; Wright et al., 1989; Kalita and Kanwar,

1990). To control the rate of future contamination, water table management

(WTM) practices have been implemented in many areas of the U.S. such as the

eastern coastal plain, and the mid-western region.

Water table management for improved agricultural production has

progressed from the concept of drainage alone to that of surface and

subsurface drainage, controlled drainage, controlled drainage-subirrigation

(combined drainage and subirrigation). Controlled drainage-subirrigation

maintains shallow water table depths in the field during certain periods of the

growing season. Water table management with controlled drainage or

controlled drainage-subirrigation prevents indiscriminate drainage of wetlands

and also provides water quality benefits by promoting the growth of denitrifying

3

bacteria (Shirmohammadi et al., 1992).

Compared with conventional drainage systems, WTM can provide better

flood control, improved water conservation, optimized water conditions for crop

growth, and improved water quality (Thomas et al., 1992). WTM is especially

suited to areas where high water tables persist for long periods, and has the

potential to increase net farm returns by improving crop yield and reducing

chemical use (Kalita and Kanwar, 1990).

WTM maintains adequate soil-moisture and soil-air in the crop root-zone

and creates favorable plant growth conditions. The quantity of soil-moisture

and soil-air in the root-zone, however, depends on the depth at which the

water-table is maintained. Based on the availability of soil-moisture and soil-air

in the root zone, crop physiological growth differs significantly. Transpiration

rates, photosynthesis rates, stomatal conductance, chlorophyll content, and

canopy temperatures may vary. Numerous studies have been conducted to

establish relationships between the average seasonal water-table depths, crop

physiological parameters, and crop yield. In such a study, Wesseling (1974)

reported that the reduced oxygen supply to roots resulting from shallow water-

table depths led to decreased rates of transpiration, nutrient uptake,

photosynthesis, and crop growth. Similar results have been reported by Evans

and Skaggs (1985), Kanwar (1988), and Carter et al. (1988).

Recent studies conducted in Iowa by Kalita and Kanwar (1992) have

4

shown that photosynthesis rates were higher for shallow water-table depths

than for deeper water-table depths during the dry season. Photosynthesis rates

were not significantly different during the wet season. The influence of the

water table depth on photosynthèse water-use efficiency (PWUE), however,

was highly significant in both dry and wet seasons.

More information is needed on the performance of water table

management systems in sustainable agriculture. Information on the movement

of pesticides in water table management systems is particularly scarce but

critically needed. Therefore, better management techniques and improved

information for technology transfer are important to the successful use of water

table management across the U.S.

Objectives

To develop a better understanding of water-table management practices

on crop growth and groundwater quality, this study was conducted with the

following main objectives:

1. To investigate photosynthesis response to different water table management

practices and their effect on crop growth.

2. To investigate the effect of various water-table management practices on

5

chlorophyll content and corn yield.

3. To evaluate the transport of nitrate-nitrogen and pesticides into shallow

groundwater in response to various water-table depths.

Explanation of dissertation format

This dissertation reports the candidate's original work on water table

management effects on plant physiological parameters, groundwater quality,

and corn yield. The entire dissertation contains three separate papers. Each

paper was written by the author in a format suitable for submission for

publication to a referred technical journal.

The first paper has been proposed for presentation at the mid-central

meeting of the American Society of Agricultural Engineers.

Each paper contains an abstract, introduction, materials and methods,

results and discussion, and conclusions. All three papers are preceded by a

general introduction and review of literature and are followed by overall

conclusions. The references for the introduction, materials and methods, and

results and discussion of all three papers and sections of the general

introduction and review of literature are cited at the end of the dissertation.

6

REVIEW OF LITERATURE

Water table management

The management of soil water in agricultural cropland in humid and

semi-humid areas of the U.S. is complicated by the erratic spatial and temporal

occurrence of rainfall. In many humid areas, such as the mid-western regions of

the U.S., periods of surplus and deficit soil water conditions occur within the

same cropping season. This sometimes leads to production losses. Therefore,

proper soil and water management have become one of the most important

challenges in these and the other humid areas of the U.S. to reduce soil

productivity losses.

The primary purposes of water table control are to minimize the time of

surplus or deficit soil-water conditions in the root-zone and to maximize the use

of natural rainfall, thus minimizing the amount of subirrigation water required

from external sources. Water table management which includes both irrigation

and drainage, can improve productivity in humid and semi-humid climates,

where weather extremes can result in crop losses and in arid areas where

salinity control is necessary for sustained agricultural production.

The objective of water table management is to provide a root

environment that results in optimum crop yields. In the past, the direct aim of

water table management systems in humid regions was to lower the moisture

7

content of upper layers of the soil so that air could penetrate into the soil more

easily and become available to roots of the plants. At the same time, carbon

dioxide produced by roots, by microorganisms, or by chemical reactions in the

soil were able to diffuse through the air-filled pores to the surface.

The water table should not be lowered so deep that a severe water

deficiency will cause death or reduced plant production. Therefore, water table

management systems have been used to maintain the required water table

depths in the field during certain periods of the growing season. These systems

are known by various names such as drainage, controlled drainage, drainage-

subirrigation, controlled drainage-subirrigation, controlled and reversible drainage

(Shirmohammadi et al., 1992).

Research to improve water table management was given considerable

emphasis in the United States during the 1970s. Ideas developed by Schwab

(1951) and van Schilfgaarde (1965) led to improved system development by

others (Skaggs, 1974; Doty and Parsons, 1979). Water table management

research has primarily been conducted during the last decade in states such as

Iowa, Michigan, Ohio, Indiana, Louisiana, and North Carolina (Hallberg, 1986;

Kanwar et al., 1988; Kanwar and Baker 1991; Kalita and Kanwar, 1992);

Bengtson et al., 1993; Fausey, 1991; Sabbagh et al., 1991 ; Gilliam and

Skaggs, 1986; Cooper et al., 1991; Wright et al., 1989. Most of this research

has focussed on crop yields, economic benefits, and modeling the flow

8

systems. However, in the last decade a few researchers have initiated studies

on the effect of water table management practices on groundwater quality.

Much of this research is being conducted in the north-central (Gish et al., 1991;

Southwick et al., 1992; Southwick et al., 1993; Bengtson et al., 1993), and

mid-western states including Iowa (Kalita and Kanwar, 1993). Water table

management in the artificially drained areas of Iowa is very important to

sustainable agriculture because about 40 percent of the state's corn and

soybean acreage being currently drained.

Water table depth and crop production

Numerous field and laboratory experiments on the effects of water table

depth on crop yields have been conducted at various locations, but it is difficult

to transfer the results from one location to another because of different soil

types, climatic conditions, and irrigation methods. A water table depth 15 cm

below the soil surface has produced maximum yield for certain crops under

certain conditions while other crops have performed best with the water table at

90 cm or an intermediate depth.

Crop response to water table depth from earlier studies has been reported

in the literature. Williamson (1964) studied different plant species under

different water table depths of 15, 30, 46, 61, and 76 cm below the soil

surface. He found that the yields of grain sorghum, soybean, cabbage, sweet

9

corn, and dwarf field corn for the 15 cm water table depth were reduced by 25,

35, 40, 65, and 75%, respectively. Coins et al. (1966) found that tomato

yields increased as the water table was lowered from 15 to 80 cm. There was

no statistically significant difference among soil types. In a lysimeter study

conducted in North Carolina, Williamson (1968) found that the yield for

stringbeans and cabbage in fine sandy loam was maximum with the water table

at 30 and 45 cm, respectively, van Schilfgaarde and Williamson (1965) found

the maximum yield of soybeans in fine sandy loam when subsurface irrigation

occurred when the water table depth was at 30 cm below the soil surface.

Williamson and Khz (1970) found that optimum water-table depth under

different soil types was a major factor contributing crop production for many

crop species.

Gosnel (1971) studied the effect of water table elevations on the growth

of sugarcane and observed that sugarcane germination was significantly

reduced if the water table depth was at 25 cm from the soil surface. However,

he found good germination and higher yield when the water table depth was

lowered to about 50 cm from the soil surface. Wesseling (1974) reported that

shallow water-table depths reduced oxygen supply to the roots and decreased

nutrient uptake and crop growth.

Meek et al. (1980) determined the growth of cotton under three different

water table depths (30, 60, 90 cm). They found optimum yield with a water

10

table depth of 90 cm. At water table depths of 30 and 60 cm, cotton yield was

reduced by 43 and 25%, respectively.

Kanwar et al. (1983, 1984) found that inadequate drainage of heavy soil

reduced crop yield by about one-third of the potential yield. Cavazza and Pisa

(1988) found the maximum yield of wheat with a 1.25 m water table depth.

Any drop in the water depth beyond this level caused moisture shortages in the

root zone which significantly reduced crop yield.

Recently, water table management by controlled drainage or controlled

drainage-subirrigation practices have received renewed attention because

excessive soil water has become a major factor affecting crop growth and yield.

Numerous field and lysimeter experiments (Ahmed et al., 1992; Kalita and

Kanwar, 1992; Evans et al., 1990; Kanwar et al., 1988; Mukhtar et al., 1990)

have been conducted to determine crop responses under different water table

management practices.

Bhuiyan and Alagcan (1990) investigated the growth response of corn to

changes in the shallow water table in fields near irrigation canals or rice areas.

They found that lowering the water table a small amount produced a strong

negative response in both plant height and yield. The investigators indicated

that during the vegetative growth stage of corn, yields above 7.3 t/ha could be

achieved by controlling the average water-table depth at 15 cm.

In Iowa, Kalita and Kanwar (1992) studied response of corn to water

11

table depths of 20, 30, 60, 90, and 110 cm below the soil surface. They found

that corn yields increased with increasing water table depths. For water table

depths of 20 and 30 cm, corn yield decreased significantly compared with

yields from plots with deeper water table depths. Dry and wet seasons

significantly affected grain yield. Plant water use efficiency and grain yield

were significantly related. Ahmed et al. (1992) investigated effects of soil

surface submergence and a water table depth at 15 cm on corn vegetative

growth. They observed that plant growth was significantly affected by

excessive water stress due to soil submergence as compared to that under 15

cm depth.

Photosynthesis response and crop yield

Photosynthesis is the ultimate physiological factor limiting the plant

growth, which in turn affects crop production. Crop growth and yield depend

upon the production and partitioning of carbon assimilates. The rate of

photosynthesis as measured by COg uptake per unit area of leaf surface,

depends on the plant's photosynthetic capacity, and on environmental factors

such as CO2 level, solar radiation, air and leaf temperature, soil moisture

availability, nutrient availability etc. (Gimenez et al., 1992). Photosynthesis rate

also depends on variety of plant parameters such as genotype, plant stage, leaf

age, leaf orientation and position, plant density, and assimilate demand by sink

12

(Dwyer et al., 1989). Differences among genotypes may be due to morphology,

resulting in different mesophyll resistances, or they may be explained by the

timing and size of carbohydrate requirement of other parts of the plant,

particularly the grain (Hunt and van der Poorten, 1985; Hesketh, 1963).

Photosynthesis responses for a wide variety of crops including maize

have been documented in the literature (Bhagsari and Harmon, 1982; Bhagsari,

1988; Dwyer and Stewart, 1986; Dywer et al., 1991; Thiagarajah et al., 1981).

Constable and Rawson (1980), observed that the photosynthesis rates of 40

day old tall fescue leaves were only 20% of their maximum photosynthesis rate,

whereas, for 60 day old cotton leaves, it was 30% of the maximum

Photosynthesis rate (Jewiss and Woledge, 1967). Bhagsari (1988) reported

decreases in net photosynthesis and stomatal conductance with increasing leaf

age for sweet potato under field conditions in full sunlight (above 1500 u mole

m ̂ s'^). Dwyer et al. (1989) reported cultiver differences in photosynthèse

rates as a function of plant age, and pointed that late-maturing cultivars had

higher photosynthetic rates than early-maturing cultivars at comparable growth

stages.

Pearson et al. (1984) observed that the photosynthesis rate for the upper

canopy leaves of 85-day-old maize was three to six times higher than for the

lower canopy leaves. However, Thiagarajah et al. (1981) observed that the COg

exchange rate (CER) of newly matured leaves of hybrid corn was lower for

13

leaves produced in the early stages of ontogeny than for older ones.

Under non-stressed conditions, irradiance is the most important

environmental factor causing variations in photosynthetic rates (Reed et al.,

1976; Hari et al., 1981). Dwyer and Stewart (1986) observed that the

dependence of photosynthetic rate on irradiance was a nonlinear function best

described by a rectangular hyperbolic equation.

Photosynthesis also varies in response to other environmental factors.

Cristy and Porter (1982) found that the net photosynthesis rate of soybean was

significantly reduced by cloud cover, cold temperatures, and water limitations.

Water stress reduced photosynthesis by increasing the resistance of COg

diffusion into the leaf surfaces by closure and "Patchiness" of stomata

(Downton at al., 1988; Sharicey and Seemann, 1989). Kalita and Kanwar

(1992) compared photosynthesis rates under varying water table depths and

observed higher photosynthesis rates when the soil moisture was not limiting.

Stomatal conductance under different moisture conditions

Processes such as photosynthesis are slowed as leaves age. The

photosynthesis decline rate appears to be related to a decrease in stomatal

conductance (Atkinson et al., 1989). Finn and Burn (1980) observed that

stomatal conductance directly affects transpiration rate and photosynthesis and

indirectly influence Nj fixation. Several other studies have reported a linear

14

relationship between stomatal conductance and photosynthesis (Field, 1987;

Wong et al., 1979; Farquhar and Wong, 1984).

The two most important environmental factors most likely to have the

greatest effect on the stomatal behavior of many field crops are light and water.

Water deficits cause stomata to close which reduces transpiration and

photosynthesis activities {Selmani and Wassom, 1992). Stomatal conductance

may be more closely related to soil water availability, however, than to short-

term variation in leaf water potential (Osonubi, 1985; Turner et al., 1985;

Gollan et al., 1986; Kûppers et al., 1988). Tan and Layne (1991) reported

lower leaf stomatal conductance in mature peaches under low soil moisture

conditions compared with high soil moisture conditions.

Kalita and Kanwar (1992) evaluated the water table management effects

on corn growth using energy balance concept. They observed that crop

physiological parameters (stomatal conductance, transpiration rate, and net

radiation) were very sensitive to the water table depth during the vegetative and

flowering stages of corn. The highest values of stomatal conductance,

transpiration rate, and net radiation were observed for a water table depth of

0.3 m. On the contrary, a shallow water table depth of 0.2 caused

waterlogging in the root zone and resulted in the poorest plant growth and the

lowest values of stomatal conductance, transpiration rate, and net radiation.

Their results indicate that plant physiological parameters could be used to

15

evaluate and develop the best management practices.

Relationship between chlorophyll content and crop yield

The greenness of a plant is an indicator of its health. Since healthy

plants contain more chlorophyll, the amount of chlorophyll present in plant

leaves can serve as an indicator of the overall condition of the plant. If a

reliable measurement of chlorophyll content can be made in-season and

correlated with the nitrogen content of a plant, then supplemental nitrogen

fertilizer can be added without time-consuming sampling and laboratory

analysis.

The application of fertilizer N for optimum crop production is important,

but, contamination of surface and groundwater due to leaching of applied

nitrogen fertilizers has become a growing concern. Accurate predictions of N

status in the field are needed to efficiently use fertilizer N and minimize surface

and groundwater contamination. Soil tests for this purpose have successfully

been used in regions of low rainfall, such as the western U.S. where minimal

NO3-N leaching occurs (Wood et al., 1992a). Several methods have been used

to assess N status in the soil and plant that could help improve N management

(Binford et al., 1990; Blackmer et al., 1989; Fox et al., 1989; Hong et al.,

1990; Piekielek and Fox, 1992). AH these N testing methods involve collecting

soil or tissue samples, drying, grinding and screening the samples, and

16

analyzing the samples with laboratory or field instruments. From this

information, fertilization programs for the specific field and crop conditions can

be developed. Too little N early in the growing season may limit vegetative

growth and cause a yield reduction, while excess N may promote vegetative

growth and delay maturity.

Recently, hand held meters that rapidly determine leaf chlorophyll have

become available in the U.S. One commercial meter, the SPAD-502 chlorophyll

meter (Soil-Plant Analysis Development, Minolta Camera Co. Ltd. Japan) is

effective for determining the N status of major crops. There is generally a

positive correlation between leaf chlorophyll content (as determined by the

chlorophyll meter), crop N uptake, leaf N concentration, and grain yield.

In contrast, Schepers et al. (1992) concluded that using the SPAD-502

chlorophyll meters to determine crop N status may not be practical because of

the unique "greenness" characteristics of different hybrids. They recommended

calibrating the meter using direct measurements of leaf N to standardize the

meter test for different hybrids, locations, and growth stages. This

standardization process can be done by comparing chlorophyll meter readings

from well fertilized plants to readings from plants in the test area.

Wood et al. (1992a) found significant relationships between SPAD-502

readings and corn grain yield during two years of study. At maximum

agronomic yields of 6898 kg ha^ in 1990 and 9233 kg ha"^ in 1991, SPAD-502

17

readings were 56 and 56.8, respectively, at the VI0 stage of growth. Readings

at the midsilk stage were 60.2 and 62.3, respectively. Chlorophyll

measurements at V10 were especially promising because supplemental N could

easily be applied at that stage of growth. In another experiment. Wood et al.

(1992b) compared leaf blade N and chlorophyll meter readings at three growth

stages for cotton, first square, first bloom, and midbloom. The chlorophyll

meter readings were highly correlated to leaf blade N concentration at all three

stages. Chlorophyll readings were a good predictor of seed cotton yield. Leaf

chlorophyll readings at maximum economic yield were 39, 49, and 47 at first

square, first bloom, and midbloom stages, respectively. At midbloom, the

chlorophyll meter reading were lower for irrigated cotton than for non-irrigated

cotton.

Follett et al. (1992) in a study conducted in Colorado compared dry land

winter wheat yield, leaf N concentration, soil N tests, and SPAD-502 chlorophyll

meter readings. There was a positive association between grain yield and

chlorophyll meter readings, N leaf concentration, and soil combined NH^-N and

NO3-N. The authors stressed the need for additional studies to evaluate other

factors such as difference among locations, cultivars, soil moisture and profile N

status. Reeves et al. (1993) conducted a field study on wheat in east-central

Alabama. Leaf chlorophyll meter readings were significantly correlated to tissue

N concentration and grain yield. The best predictor of grain yield was N uptake

18

at growth stage 5, but chlorophyll meter reading and dry matter at growth stage

5 were also good predictors of yield.

Estill et al. (1991) evaluated alfalfa leaf chlorophyll response to different

moisture regimes for two color variants (pale and dark). The chlorophyll

concentration of pale variants remained the same for the moisture extremes,

While the chlorophyll in the dark variants was 20% lower in the low moisture

regime compared with the high moisture treatments.

Water table management for NO3-N improvement

Although, the use of fertilizers and pesticides is currently an integral part

of crop production in the U.S.A. and elsewhere. The contamination of surface

and groundwater due to the leaching of these chemicals is becoming a serious

threat to human health, wildlife and the environment (Prunty and Montgomery,

1991). Particularly, nitrate leaching into groundwater has become one of the

major pollution concerns facing agriculture today (Hallberg, 1984). Studies

during the past decade have documented the detrimental effects of agriculture

on water quality (Hallberg, 1989; Schaller and Baily, 1983; Hamlett et al.,

1990). These studies suggest that surface and groundwater resources are

vulnerable to non-point pollution from agricultural activities.

Nitrate-nitrogen (NO3-N) concentrations exceeding the 10 mg/L safe

drinking water limit, have been detected in both surface and groundwater

19

supplies all across the midwestern and in other states in the U.S. (Hubbard and

Sheridan, 1989). The public is especially concerned because the NO3-N

concentrations in excess of 10 mg/L in drinking waters cause serious health

problems (such as methemoglobinemia) to infants who drink this water. The

problems receiving the most attention from researchers are the contribution of

nutrients to eutrophication of surface water resources, and the increased levels

of NO3-N in the drinking water. In the past two decades, much work has been

done to characterize nutrient losses through drainage systems and the effect of

these losses on water quality and crop productivity. Several studies conducted

in Iowa (Baker and Johnson, 1981; Kanwar et al., 1985; Kanwar et al., 1988;

Kanwar, 1991; Kanwar and Baker, 1991) have shown that great quantities of

NO3-N were rapidly leaching to shallow groundwaters. In 1988 through 1989,

a survey of private rural wells in Iowa found that 18% of the water in all wells

had NO3-N concentrations above the 10 mg/L drinking water standard, while

35% of the samples from wells less than 50 ft deep had NO3-N concentrations

above the standard (Anonymous, 1990). These and other studies all across the

U.S., have reported that NO3-N concentrations in subsurface drainage from row-

crop land usually exceeded the 10 mg/L drinking water standard, and, as

fertilization increased, NO3-N concentrations in tile drainage water sometimes

approached 100 mg/L (Kanwar, 1991). Ritter and Manger (1985) and

Lowrance (1981) reported that NO3-N concentrations in subsurface drainage

20

from agriculturally influenced areas ranged from 20 to 47 mg/L on coastal plain

soils. Skaggs et al. (1982) found wide variability in NO3-N losses from drainage

systems on muck and clay soils in North Carolina.

Water-table management (WTIVI) practices, especially controlled drainage

and drainage-subirrigation, have shown potential for inducing denitrification and

reducing the concentration of agricultural chemicals reaching water supplies

(Skaggs and Gilliam, 1981; Gilliam and Skaggs, 1986; Evans and Skaggs,

1989; Wright et al., 1989; Wright, 1990; Kalita and Kanwar, 1989; Kanwar and

Kalita, 1990; Kalita and Kanwar, 1993).

During the last few years, several studies have addressed the effects of

WTIVI practices under different soils, crops, and climatic conditions, such as, in

Iowa (Kanwar, 1990; Kalita and Kanwar, 1992), Michigan (Belcher and Merva,

1991), Ohio (Fausey et al., 1991), North Carolina (Skaggs et al., 1991),

Louisiana (Bengtson et al., 1991), Georgia (Thomas et al., 1987a, 1992). The

main focus in these studies has been crop yields, economic benefits, and

groundwater modeling. Few other studies have been reported in the literature

which address the benefits of WTIVI practices in relation to reducing nutrient

transport in drainage outflow.

Bengtson et al. (1988) studied the influence of subsurface drainage

practices on nitrogen and phosphorus losses on a Commerce clay soil in the

lower Mississippi River Valley. Compared to undrained areas, they found that

21

subsurface drainage reduced surface runoff by 34%, erosion by 30%, and

nitrogen and phosphorus losses by 20 and 36%, respectively.

Thomas et al. {1987b, 1991) measured NO3-N concentrations in shallow

subsurface wells and outlets of a controlled drainage-subirrigation system in a

blueberry field in the Georgia flatwoods. Their results showed that NO3-N

concentrations were less than the 10 mg/L maximum contaminant level (MCL)

for public drinking supplies for all outflow samples, although 6% of the shallow

groundwater samples within the field exceeded this limit.

Evans et al. (1989a) presented a compilation of data from North Carolina

supporting the classification of controlled drainage as a best management

practice. Their data showed that controlled drainage reduced both surface and

subsurface nitrogen losses as opposed to uncontrolled drainage. They

concluded that denitrification accounted for the reduced nitrogen transport from

controlled drainage site in eastern North Carolina where conditions are

conducive to denitrification. In another study, Evans et al. (1989b) reported

that the controlled drainage reduced the annual transport of total nitrogen (NO3-

N and TKN) at the field edge by 46.5% and total phosphorus by 44%. In

previous studies, similar results have been reported using simulation methods

(Skaggs and Gilliam, 1981; Deal et al., 1986).

Gilliam et al. (1979) compared nitrate concentrations from uncontrolled

and controlled drained fields, and found nearly a 50% reduction in nitrate losses

22

under controlled drainage. While comparing nitrate transport from controlled

and conventional drainage systems, Gilliam and Skaggs (1986) observed a 32%

reduction in nitrate outflow with controlled drainage as compared to

conventional drainage.

Hubbard et al. (1991) determined transport of NO3-N by surface runoff,

and shallow subsurface flow on a sandy coastal plain soil having plinthic sub

soil material. They observed that most of the NO3-N leached from the upper 30

cm of the root zone within 1 % month after N application. NO3-N

concentrations in surface runoff were very small, with monthly loads not

exceeding 0.3 kg ha \ However, NO3-N concentrations in shallow groundwater

(at the 0.9 to 1.8 m sampling depth) were between 11 to 19 mg/L.

Weight et al. (1992) simulated a controlled drainage-subirrigation (CD-SI)

system to investigate the effects of different WTM practices on water quality.

The results from their CD-SI simulations indicate that raising the water table

during the fallow season can reduce nitrogen leaching by increasing

denitrification. It can also increase the amount of nitrogen lost in runoff and in

sediment. They pointed out that, water table management using a CD-SI

system increased predicted runoff nitrogen by 340% and increased predicted

sediment nitrogen loss by 118%, it decreased nitrogen leaching by 35.1 %.

They concluded that, the predicted total average nitrogen non-point source

pollution losses were 17.8% less for the CD-SI system than for the subsurface

23

drainage system.

Studying effects of WTM on NO3-N transport to shallow groundwater,

Kalita and Kanwar (1993) found that nitrate concentrations were reduced by

maintaining shallow water table depths in the range of 0.3 to 0.6 m. In the

unsaturated zone of the soil profile, NO3-N concentrations as high as 285 mg/L

were observed, but the average NO3-N concentrations in the groundwater never

exceeded the 10 mg/L drinking water standard. Drury et al. (1991); and Myrold

and Tiedje (1985), found that the average NO3-N concentrations in groundwater

were generally lower where shallow water table depths were maintained.

Bottcher et al. (1981) measured mean annual sediment, nitrogen, and

phosphorus losses of 94, 8.66, and 0.22 kg/ha, respectively, from a subsurface

drained area near Woodburn, Indiana. Their results showed that losses of

sediment and nutrient were reduced by subsurface drainage. They

recommended that on a suitable soil, subsurface drainage may well be preferred

as a best management practice for water quality control. Kladivko et al. (1991)

determined field scale NO3-N losses to subsurface drainage on a low organic

matter and poorly structured silt loam soil under typical agricultural management

practices in Indiana. They found that the annual NO3-N losses in subsurface

drain flow ranged from 18 to 70 kg/ha.

24

Pesticides in the groundwater

IVIodern agriculture is heavily dependent on the use of agrichemicals,

particularly fertilizers and pesticides. As of 1982, the pesticide usage in the

United States was nearly 300 million kilograms, and 85 percent of this usage

was in corn belt states such as Iowa, Illinois, Indiana, Ohio, and Michigan

(Hallberg, 1986). A major concern is that low concentrations of less soluble but

widely used pesticides have been detected in shallow aquifers under a wide

range of agricultural and climatic conditions. In 1986 the Environmental

Protection Agency (EPA) reported the presence of 17 pesticides in groundwater

in 23 states (Cohen et al., 1986). However, during recent years this figure has

gone up, and the reported cases increased to 77 pesticides in groundwater in

39 states (Williams et al 1988).

During the past decade numerous studies have been conducted to

characterize the fate and movement of applied pesticides and their impact on

surface and groundwater. This is of particular concern because groundwater is

the predominant source of domestic water in most rural areas in the United

States (National, 1985). It is estimated that 97% of the nation's rural

population relies on groundwater as its source of drinking water (Moody, 1990).

According to Fitter (1986), widely used herbicides such as atrazine,

alachlor, metalachlor, and cyanazine have been detected in groundwater

systems of several states. He further reported that atrazine and alachlor

25

together accounted for 25 percent of all pesticides sold in U.S. during 1982.

Isensee et al. (1988) reported that three corn production herbicides,

atrazine [2-chloro-4-(ethylamlno)-6-(isopropylamino)-S-triazine], alachlor [2-

chloro-2',6'-diethyl-N-(methoxymethyl) acetanilide], and cyanazine [2-chloro-4-

(cyano-1-methylamino)-6-ethylamino-S-triazine], have been detected in

groundwater in many states because of their wide application. They found that

atrazine concentration in shallow groundwater was between 0.2 to 1.8 ppb and

that of alachlor was 0.3 ppb. These concentrations were far below the health

advisory limits for atrazine (3 //g/L) and alachlor (2 //g/L).

Alachlor has been found to be less persistent than atrazine in soil profiles

(Buhler et al., 1993). In their tests of drain outflow, alachlor was found in only

2% of samples whereas atrazine was detected in 97% of the samples taken in a

6 year period. Alachlor has been reported in groundwater samples in Iowa,

Nebraska, Maryland, and Pennsylvania at residue levels of 0.1-10 //g/L (Cohen

et al., 1986). Alachlor concentration in groundwater as high as 16 /vg/L was

found in Iowa (Kelley et al., 1986). Libra et al. (1986); and Kelley et al. (1986)

reported that atrazine concentrations of 10 //g/L were detected in a karst aquifer

in Iowa.

In a study. Smith et al. (1990) found that atrazine concentration in the

soil water, at a depth of 0.61 m, reached 350//g/L 19 days after application.

They also reported atrazine concentration as high as 90 //g/L were observed

26

in the shallow groundwater 16 months after application, however, alachlor was

not detected in the soil below 0.36 m. They hypothized that apparently most of

the alachlor had degraded during their experimental period.

Factors affecting fate and behavior of pesticides

The four major mechanisms that determine the fate of a pesticide are

adsorption, degradation, volatilization, and leaching/runoff. The rate of these

mechanisms is influenced by management practices, environmental conditions,

and physical and chemical properties of the applied chemical. Jury (1986a)

described physical and chemical properties effecting the fate and transport of

pesticides in a porous media. Those properties are solubility, vapor pressure,

toxicity, adsorption rate, and soil reactivity. The environmental conditions

influencing the fate of atrazine include rainfall, temperature, soil properties, and

rate of erosion. Whereas, rate of pesticide application, method of application,

cropping method, irrigation and/or drainage practices, and chemical used and its

formulation also influence the fate and transport of pesticide. For example, in a

study on atrazine leaching, Schriber et al. (1993) observed significant reduction

in the loss of atrazine from a starch encapsulated formulation as compared to

those from liquid formulations. Wienhold and Gish (1992) reported the relation

between water potential, temperature, soil microbial activity and release of

starch encapsulated atrazine and alachlor. They concluded that escapusulated

27

formulation resulted in slow release of the herbicide and the rate of release

declined with declining water potential. A study conducted by Shirmohammadi

et al. (1992) also showed higher concentrations of atrazine at depths shallower

than 8 cm in the field treated with encapsulated atrazine. Below the 8 cm

depth the concentration of atrazine was higher in the fields supplied with

conventional application of the pesticide (liquid formulation).

Smith et al. (1988) mentioned some of the soil properties that influence

pesticide transport are water content, bulk density, permeability, clay content,

organic matter content, and water retention. Gish et al. (1991) pointed out that

soil texture may play an important role in preventing pesticide movement to

deeper depths in the soil profile. They reported from their study that only 1 %

of applied atrazine was detected below the 45 cm depth. However, there were

no textural, hydraulic and physical properties available to express this pattern of

movement. Wietersen et al. (1993) monitored transport mechanisms of

atrazine, alachlor, and metolachlor through soil columns of Sparta sand and

Plainfield sand in Wisconsin. They observed that all pesticides were more

mobile through the Sparta sand as compared to the Plainfield sand. Atrazine

concentration was 15 times greater in the leachate from Sparta sand than from

Plainfield. Similar results were found for alachlor and metolachlor. The relative

order of mobility for each soil was found to be atrazine > metolachlor >

alachlor. The factors found to contribute to increased mobility of pesticides

28

through the Sparta sand include higher hydraulic conductivity, smaller water

holding capacity, and less atrazine adsorption. The hydraulic conductivity of

the upper root-zone (0-20 cm) of the Sparta sand was 5 time greater than the

Plainfield sand.

Jury (1986b) reported that precipitation, evapo-transpiration, and

temperature were among some of the environmental factors influencing

pesticide transport. Plant processes affecting pesticide transport are very

complex. Donigian and Rao (1986) explained that the uptake, translocation,

accumulation, and transformation of pesticides by plants affect the availability

of pesticides for transport processes and the potential exposure to pesticide

residues by the consumers of the vegetation, fruits, etc. Plant processes can

serve both as a sink and a source of pesticide residues available for transport.

Plant cover has been observed to influence pesticide persistence as a

result of lower soil temperature during summer. Birk and Roadhouse (1964)

found atrazine to be more persistent in soil planted to corn than in fallow land.

This was attributed to transpiration of the crop maintaining relatively dry soil

and reducing the microbiological degradation of the herbicide. In contrast, Sikka

and Davis (1966) found that uptake and metabolism by the crop reduced

atrazine persistence in soil planted to corn. Lower atrazine concentration was

found in the top 0.15 m depth of cropped plots than in fallow plots at all

sampling dates up to 6 months after planting. Pesticide leaching may be

29

affected by the amount and type of vegetation on the soil surface. Sigua et al.

(1993) reported that covering soil cores with 2000 or 8000 kg ha'^ of crop

residue reduced atrazine leaching by 26% to 37%, respectively, compared with

soil cores without crop residue. Furthermore, they also observed that the soil

cores covered with recently harvested vegetation reduced atrazine leaching by

39% compared with cores covered with aged crop residue.

Hiltbold (1974) hypothized that soil flooding and temporary anaerobiosis

may permit reductive degradation of certain pesticides and markedly alter their

persistence. Results of field experiments by Guenzi et al. (1971) and laboratory

experiments by Castro and Yoshida (1971) showed that flooding influenced

biodégradation rather than chemical degradation of pesticides.

Pesticide control through water table management

There is scant literature on pesticide management with water table

management practices. However, recently these management practices have

received attention as potential measures to reduce pollution hazards to

groundwater systems. Few studies have shown that WTM practices that

include controlled drainage, and controlled drainage-subirrigation can reduce

pesticide concentrations in shallow groundwater and improve crop yield (Baker,

1980; Baker and Johnson, 1976; Bengtson et al., 1990; Evans et al., 1989;

Fausey et al., 1990; Kanwar, 1990; Kanwar et al., 1988; Kalita and Kanwar,

30

1989, 1990; and Kalita, 1992).

Baker (1980) and Baker and Johnson (1976) found that the concentration

of most herbicides and insecticides were higher in surface runoff than in

subsurface drainage, but chemicals that were not adsorbed, such as anionic

herbicides, usually had higher concentrations in the subsurface drainage.

Kladivko et al. (1991) determined field scale pesticide losses to

subsurface drainage on a low organic matter and poorly structured silt loam soil

under typical agricultural management practices. They observed small amounts

of carbofuran, atrazine, cyanazine, and alachlor in subsurface drain flow within

3 weeks of pesticide application. The annual carbofuran losses in subsurface

drain flow ranged from 0.8 to 14.1 g/ha, whereas, the losses of all other

pesticides were ^ 0.06% of the amount applied.

Bengtson et al. (1990) reported that atrazine and metolachlor losses were

reduced by 55 and 51 percent, respectively, in the areas where subsurface

drainage systems were used. They concluded that subsurface drainage

substantially reduced atrazine losses, and about 2/3 of the losses occurred

within 30 days after herbicide application. They also found that atrazine

concentrations were substantially greater than EPA's advisory level for drinking

water. In another study, Bengtson et al. (1993) reported that subsurface

drainage reduced alachlor and norflurazon losses by 34 and 31%, respectively.

In a recent study conducted in Iowa, Kalita (1992) observed that under

31

different water table depths, pesticide concentrations were lower at shallow

water table depths, however pesticide concentrations in the groundwater

increased with lowering water table depths. Higher concentrations of atrazine

and alachlor were observed when water table depths were maintained at 0.9 m

or deeper. Results of this and other studies have stressed the need for further

research on the use of WTM practices to reduce groundwater contamination

caused through the use of pesticides.

32

PAPER I. EFFECTS OF WATER TABLE DEPTHS ON DIFFERENT PLANT

PHYSIOLOGICAL PARAMETERS

33

ABSTRACT

A study was conducted to evaluate the effects of various water table

depth (WTD) practices on plant physiological parameters. Data for 1992 and

1993 were collected from field experiments conducted at two sites in Iowa

(Ankeny and Ames). At the Ankeny site, water table depths were maintained at

0.2, 0.3, 0.6, 0.9, and 1.1 m depths on a 0.5 ha subirrigation field, whereas

water table depths of 0.3, 0.6, and 0.9 m were maintained in lysimeter plots at

the Ames site. Measurements on different physiological parameters

(photosynthesis, stomatal conductance, transpiration, intercellular COg (Ci), and

canopy temperatures) were taken on a biweekly basis using leaf chamber

techniques, and those on chlorophyll were taken using a SPAD-502 chlorophyll

meter. The yield data were collected at harvest.

Analysis of the data revealed that photosynthesis rates, stomatal

conductances, transpiration rates. Ci, canopy temperatures, and chlorophyll

were correlated with various WTDs during the growing season. The values of

these parameters were significantly affected at WTDs of 0.2 and 1.1 m as

compared to those at WTDs of 0.3, 0.6, and 0.9 m. The 0.3 WTD resulted in

larger values of these physiological parameters, and these values decreased

with the lowered WTD. In 1993, an extremely wet year, the values of

physiological parameters were lower than those in 1992 under all WTDs.

34

The statistical analysis of the data showed that means for photosynthesis

between WTDs for the Ames site were significantly different at the 0.05

probability level during both years, whereas those were not significant for 1993

at Ankeny site. However, the means for chlorophyll readings between WTDs

were significantly different at the 0.05 probability level at both sites for both

years. The stomatal conductances were not significant at the 0.05 probability

level.

Relationships between different parameters were developed by fitting

lines of linear regression. The regression analysis showed strong positive

relations between photosynthesis and leaf chlorophyll readings for 1992 and

1993, at both experimental sites. Results of these analyses revealed that leaf

chlorophyll could be used as a good predictor of photosynthesis rates regardless

of water table treatment depth. Also, a strong positive relation between

stomatal conductance and transpiration rates was observed. The regression

analysis revealed that the transpiration rates were highly dependent on the

stomatal behavior.

35

INTRODUCTION

The management of soil water for agricultural cropland in humid and

semi-humid areas of the U.S. is complicated by the erratic spatial and temporal

occurrence of rainfall. In many humid areas, such as the mid-western region of

the U.S., periods of excess and deficit soil water conditions occur within the

same cropping season, which sometimes lead to production losses in those

areas. Therefore, proper soil and water management are one of the most

important challenges in those and other humid areas to reduce soil productivity

losses and excessive off-site impacts. One technique to counter these

challenges is the efficient management of water in agricultural soils.

The primary purposes of water table control are to minimize the time of

excess or deficit soil-water conditions in the root-zone, and to maximize the use

of natural rainfall, thus minimizing the amount of subirrigation water required

from external sources for irrigated systems. Water table management which

includes both irrigation and drainage, can improve productivity in humid and

semi-humid climates, where weather extremes can result in crop loss, and in

arid areas, where salinity control is necessary for sustainable agriculture.

Research to improve water table management was given considerable

emphasis in the United States during the 1970s. Ideas developed by Schwab

(1951) and van Schilfgaarde (1965) led to improved systems development by

36

others (Skaggs, 1974; Doty and Parsons, 1979). In the past, the direct aim of

water table management systems in humid regions was to lower the moisture

content of upper layers of the soil so that air can penetrate into the soil easily

and become available to plant roots. At the same time, it is necessary that

carbon dioxide produced by roots, by microorganisms, or by chemical reactions

in the soil can diffuse through the air-filled pores to the surface. On the other

hand, the water table should not be lowered so deep that a severe deficiency of

moisture may cause death or reduced plant production.

Water table management research has primarily been conducted during

the last decade in states such as Iowa, Michigan, Ohio, Indiana, Louisiana, and

North Carolina. Most of this research has focussed on crop yields, economic

benefits and modeling of the flow systems. Water table management such as

drainage, drainage-subirrigation, controlled drainage-subirrigation, controlled and

reversible drainage have received renewed attention because the excessive soil

water has become a major factor affecting crop growth and yield. Numerous

field and lysimeter experiments (Ahmed et al., 1992; Kalita and Kanwar, 1992;

Evans et al., 1990; Kanwar et al., 1988; Mukhtar et al., 1990) have been

conducted to determine crop yield response to water table management.

However, the data on the effects of water table management practices on crop

physiological parameters such as photosynthesis rates, stomatal conductance,

intercellular COg, transpiration rates, chlorophyll content, and canopy

37

temperatures are rather scanty.

It has been recognized that processes such as photosynthesis is an

ultimate physiological factor limiting the plant growth which in turn affects crop

production. Photosynthesis CO; assimilation per unit area of leaf surface

depends on the capacity of the plant's photosynthetic mechanism and on those

environmental factors such as CO; supply and radiation which are the

substrates for the process, and on those (e.g. moisture availability, and nutrient

deficiency etc.) that affect the mechanism (Gimenez et al., 1992). Besides

these factors, photosynthesis rate also depends on a variety of plant parameters

such as, genotype, plant stage, leaf age, leaf orientation and position, plant

density, and assimilate demand by sink (Dwyer et al., 1989). Photosynthesis

responses for a variety of crops from several previous studies in general, and

maize in particular have been documented in the literature (Bhagsari and

Harmon, 1982; Bhagsari, 1988; Dwyer and Stewart, 1986; Dywer et al., 1991;

Thiagarajah et al., 1981). Constable and Rawson (1980), observed that the

photosynthesis rates of 40 day old tall fescue leaves were only 20% of their

maximum photosynthesis rate, whereas, for 60 days old cotton leaves, were

30% of the maximum Photosynthesis rates (Jewiss and Woledge, 1967).

Bhagsari (1988) reported decrease in net photosynthesis and stomatal

conductance with increasing leaf age for sweet potato under field conditions in

full sunlight (above 1500 // mole m ̂ s'^). An important factor to this decline in

38

photosynthesis in nnany species appears to be decrease in stomatal

conductance (Atkinson et al. 1989). Owyer et al. (1989) reported cultiver

differences in photosynthetic rates as a function of plant age, and pointed that

late-maturing cultivars had higher photosynthesis rates than early-maturing

cultivars at comparable phenological stages. Finn and Burn (1980) observed

that stomatal conductance directly affects transpiration and photosynthesis

rates and indirectly influence Ng fixation. Several other studies have reported a

linear relationship between stomatal conductance and photosynthesis rates

(Field, 1987; Wong et al. 1979; Farquhar and Wong, 1984). These studies

have indicated that light and water are the two most important environmental

factors most likely to have the greatest effect on stomatal behavior of many

field crops. These studies have shown that water deficits cause stomata to

close which in turn reduces transpiration and photosynthesis activities (Selmani

and Wassom, 1992). However, recent studies on different species have shown

that stomatal conductance may be more closely related to soil water availability

than the short-term variation in leaf water potential (Osonubi, 1985; Turner et

al. 1985; Gollan et al. 1986; Kùppers et al. 1988). In a study, Tan and Layne

(1991) reported lower leaf stomatal conductance in mature peaches under low

soil moisture conditions as compared to one under high soil moisture conditions.

In a recent study, Kalita and Kanwar (1992) compared photosynthesis rates

under varying water table depths and observed higher photosynthesis rates

39

under shallow water table depths than deeper ones.

Chlorophyll Is also important plant physiological parameter which

indicates the nitrogen status of the plant. Therefore, accurate predictions of N

status by measuring chlorophyll in the field can led to efficient utilization of

fertilizer N and protection of surface and groundwaters against contamination.

Several studies have been conduced to assess N status in the soil and plant that

could help improve N management (Binford et al., 1990; Blackmer et al., 1989;

Fox et al., 1989; Hong et al., 1990, Piekielek and Fox, 1992). Few other

studies have related chlorophyll readings with crop yield (Wood et al., 1992;

Follett et al., 1992; Reeves et al., 1993). However, previous studies have not

reported the effects of excess soil-water, water-table management and/or

drainage practices on chlorophyll content.

With the aim of developing better understanding of water table

management practices on plant physiological parameters, this study was

initiated with the following main objectives:

1. To investigate photosynthesis and chlorophyll responses to different water

table depths.

2. To determine the effects of different water depths on stomatal conductance,

transpiration rate, intercellular COg, and canopy temperature.

3. To recommend the best plant parameter for future plant growth

measurements on the basis of this study.

40

MATERIALS AND METHODS

Description of experimental sites

The experimental sites for this study were located on land owned by

Iowa State University near Ames and Ankeny. The experiments at these sites

were conducted during 1992 and 1993. The soils at these sites are

predominantly Nicollet loam in the Clarion-Nicollet-Webster soil association.

Table 1 lists some of the physical properties of the soils at these two sites.

Experimental setup at Ames site

Nine experimental plots with surface slopes ranging from 1 to 3% were used

to construct field lysimeters. The lysimeters (each 3 m wide and 6 m long)

were installed during 1986. A 0.2 m wide and 1.2 m deep trench around the

perimeter of each lysimeter was made using a Ditch Witch^ trencher, and the

bottom of the trench was finished manually with a "tile trench crumber. " The

lysimeter soil remained undisturbed during trench the digging process.

Following the digging of the trench, the each lysimeter was completely enclosed

using a plastic barrier (0.25-mm-thick, polyethylene sheet) which extended from

the soil surface to the bottom of the trench. The purpose of this plastic barrier

^Name of commercial products given for the benefit of readers only. Iowa State University does not endorse any of these products for benefit.

41

was to "isolate" the lysimeter from its surroundings and to minimize any lateral

subsurface water movement between plots. A corrugated, perforated plastic

tube ( 100-mm diameter) was installed at the bottom of the trench inside the

plastic barrier. A 0.9 m wide ditch was dug to a depth of 1.35 m with a back

hoe mounted on the Ditch Witch trencher to install a 1.5 m tall corrugated

plastic pipe (0.46-m OD X 0.032-m wall) at the corner of each lysimeter. The

bottom of 1.5 m tall sump was located 1.35 below the soil surface, and the top

of the sump was 0.15 m above the soil surface. The two ends of the

perforated plastic tubes at right angles to each other were inserted into the

sump at a height of 0.15 m from the bottom of the sump. The trenches were

back-filled with the excavated soil. In 1989, all lysimeters were enclosed with

another 0.25 mm-thick PVC (poly-vinyl-chloride) flexible liner to a depth of 1.7

m. Each liner encased a square area (9 m X 9 m) with the 3 X 6 m original field

lysimeter located in the center of the enclosed area to ensure that subsurface

water did not move laterally between lysimeters to a depth of 1.7 m. A detailed

procedure for the lysimeter installation is described by Kalita and Kanwar

(1990), and is also shown in Figure 1. Figure 1 shows an isometric view of the

lysimeter with installed sump and float assembly. A float mechanism was

installed in each sump to maintain the desired water level in the lysimeter plot

area. Each lysimeter was connected to the main water-supply tank using a 75-

mm diameter PVC irrigation pipe. The niain water-supply tank {1.6-m high and

42

1.3-m inside diameter) was raised 2 m from the soil surface on a concrete floor

to maintain sufficient hydraulic head for gravity flow of water from the tank to

all lyslmeters for maintaining water tables in the plot area. The layout of the

experimental area is shown in Figure 2.

Experimental setup at Ankeny site

In 1988, a dual pipe subirrigation system was installed at this site on a

0.5-ha area with significant natural ground slope of 2.5 percent. The basic

concept of the dual-pipe subirrigation system is illustrated in Figure 3. Shallow

irrigation pipes (51-mm diameter) were installed at a depth of 0.5 to 0.6 m

parallel to and midway between drainage pipes, which were installed at a depth

of 1.2 m. Drainage lines discharged into a sump from which water is pumped

into a storage reservoir. The storage reservoir has a storage capacity of

approximately 900 cubic meters. During irrigation, water is pumped from the

reservoir into a head tank at the top of the plot area, where the water is

distributed to the laterals by a sub-main line equipped with valves to control

pressure in the supply line. Because of the natural ground slope along the

length of the field, water tables could be maintained at various depths below

the soil surface by controlling the subsurface drainage outflows and by

supplying irrigation water through the subirrigation pipes.

43

Water table management treatments

At the Ames site, water table depths were maintained at 0.3, 0.6, and

0.9 m in 1992 and 1993. Each water table depth treatment was replicated

three times. Water table depths were maintained to the desired depths from

day 49 to 110th day after planting (DAP) during the growing season of 1992,

and from 50 to 98 DAP during the growing season of 1993. The elapsed time

of about 50 days from planting to the start of water-table treatment allowed

corn roots to develop within 0.3 to 0.9 m soil profile, it took almost three days

to bring the water tables to the required depths during 1992, whereas, during

1993, the record wet year, there was no problem in bringing the water tables

near the surface but many times water tables had to be lowered using a sump

pump. Observation wells (25-mm diameter and 1.2-m long PVC pipes) were

installed in the center of each lysimeter to monitor water levels.

At the Ankeny site, the average water table depths at five major locations

marked as A, B, C, D, and E (where monitoring devices were installed in the

subirrigation) were maintained at 0.2, 0.3, 0.6, 0.9, and 1.1 m, respectively.

However, the water table depths ranged from 0.05 to 1.2 m during the growing

season. A maximum water-table depth of 1.2 m was observed at the highest

elevation site (north boundary) of the field at the beginning of the 1992 season.

The minimum water table depth of 0.05 m was observed at the lowest elevation

site of the field twice during the growing season of 1992, and most of the time

44

during growing season of 1993 due to heavy rainfall.

Each major location was divided into three subplots, where the

monitoring devices were installed. This combination provided three replications

per each depth treatment along the row. Water table depths, however, were

maintained from 49 to 110 DAP in 1992 and from 50 to 98 DAP In 1993. An

elapsed period of about 50 days between planting and start of subirrigation

allowed corn roots to develop uniformly in this field to a depth of 0.2 to 1.1 m.

Measurements of plant physiological parameters

Measurements on photosynthesis rate, stomatal conductance, leaf

transpiration, intercellular CO;, were taken with a LICOR-6200^ portable

photosynthesis system. Details of this measurement system are given in

LICOR-6200: Technical Reference (1987), therefore, only the details peculiar to

this work are given here. This system consists of a COg analyzer, a system

console, and a sensor housing with interchangeable leaf chambers. The CO;

analyzer is a differential, non-dispersive, infrared-type (NDIR) instrument

calibrated for measurements of 0-1100 ppm. A portable photosynthesis system

(Model 6200, LICOR, Inc. Lincoln, NE) calculated Rs to water vapor and net

photosynthèse rate (±) based on the change in water vapor, rate of change in

CO2, leaf area enclosed, air and leaf temperatures, and volume of leaf chamber.

PAR, ambient COg, leaf and air temperature, and relative humidity were also

45

recorded using this instrument at the time of photosynthèse measurement.

Measurements on plant physiological parameters were made on a

biweekly basis at both experimental sites (Ames and Ankeny) during the two

years of study. All measurements were made between 1000 and 1400 hours

of the day generally under clear sky. If clouds appeared during any

measurement, the observed data changed significantly and were therefore

discarded and new measurements were taken later on the same plant. Nine

plants in each treatment (3 plants per replication) were randomly

selected and marked, and measurements were taken on these plants during the

entire growing season.

The net exchange of CO; between leaf and the atmosphere was

measured by enclosing midsection of a latest fully developed leaf (generally

third or fourth leaf from the top) in the leaf-chamber and monitoring the

exchange rate in COg concentration of the air in the chamber during a short

interval of 15 to 20 s.

Chlorophyll measurements

Leaf chlorophyll measurements were made with a Minolta SPAD 502

chlorophyll meter. The SPAD-502^ chlorophyll meter, is a nondestructive, hand

held meter available for measurement of the green color intensity in crop leaves

which is directly related to leaf chlorophyll content (Tabkebe and Yoneyama,

46

1989). The meter is light weight (225 g), powered by two AA alkaline

batteries, has a 2-second interval between measurements, and can store up to

30 measurements.

SPAD-502 chlorophyll meter (principle description)

The principle of measurement is based on the difference in light

attenuation at wavelengths 430 and 750 nm. The 430 nm wavelength is a

spectral transmittance peak for chlorophyll, while the 750 nm wavelength is in

the near-infrared region, where no transmittance occurs. The ratio of the light

transmittance at these wavelengths, is processed by the instrument to produce

a reading shown on a digital display. This reading is in SPAD (Soil Plant

Analysis Development) units ranging from 0 to 80, which are values defined by

Minolta to indicate the relative amount of chlorophyll contained in plant leaves.

The chlorophyll measurements were made on 15 randomly selected

plants per treatment (five plants per replication). The latest fully developed leaf

(generally 3rd or 4th leaf from the top) was used for chlorophyll measurements.

The leaf chlorophyll measurements were made on a biweekly basis at both

experimental sites during the two years of study. Measurements on plant

heights were also made on the same plants used for the chlorophyll

measurements.

47

Plant culture

The corn variety Pioneer 3379 was planted at both sites (with no till

practices). In 1992, seeds were planted on May 8, while, they were planted on

May 21 in 1993 at both sites. The plant population was 67,000 per ha with a

row-to-row spacing of 0.75 m and seed-to-seed distance of 0.2 m at each site.

Plants were hand harvested on November 6 in 1992 in the lysimeter plots at

Ames site, and were harvested using a combine on the same day at Ankeny. In

1993, the plants were hand harvested on October 21 in the lysimeter plots at

Ames site, and were harvested on October 31 using a combine at Ankeny.

Grain yield was determined by harvesting and shelling all the ear heads in each

plot. The moisture content of the grain was determined and all yields were

adjusted to 15.5 percent moisture content basis (wet basis). Urea nitrogen

[N = (46-0-0) HgNCONHg], phosphorus [P = (0-43-0) PgOg], and potassium

[K = (0-0-54) KgO] fertilizers were surface applied at planting time at both sites

every year at the rate of 200 kg-N ha'\ 60 kg ha'\ and 40 kg ha \ respectively.

Herbicides atrazine and lasso were applied at the rate of 2.2 kg ha'\ in both

years at the Ankeny and Ames sites.

48

RESULTS AND DISCUSSION

Photosynthesis response to water table depths

The data on the effects of water table depth (WTD) on photosynthesis

rate as a function of time and days after planting (DAP) for the Ankeny and

Ames sites are plotted in Figures 4 and 5, respectively. As shown in Figure 4

the photosynthesis rates at the Ankeny site during 1992 were higher at the 0.3

m depth than for 0.2, 0.6, 0.9, and 1.1m depths. The photosynthesis rates

increased with time for all WTDs until mid August, 86 DAP, and thereafter

decreased with small variations between water table depths. In a previous

study Kalita and Kan war (1992) found maximum photosynthesis rates on 48

DAP during 1990 at this site (Table 3). During 1993, the WTDs fluctuated in

time from 0.05 to 1.2 m due to the combined effects of field slope, high rainfall,

and subirrigation practices. The photosynthesis rates were significantly

affected at the 0.2 m depth (Fig. 4). Due to heavy rainfall, the plots at WTD of

0.2 m remained flooded during most of the growing season. These results and

those from previous studies conducted at the same location by Kalita and

Kanwar (1992) reveal that a very high water table restricts oxygen supply to

the roots and soil microorganisms. Root growth requires metabolic energy that

is generated in aerobic conditions, but in the absence of oxygen, this energy is

significantly reduced (Cannel and Jackson, 1981). Therefore, less

49

photosynthesis rates due to excessive water stress at 0.2 m depth and due to

moisture deficit at 1.1 m depth could be anticipated.

Comparison of photosynthesis rates at the Ankeny site show that

photosynthesis rates were higher in 1992 than in 1993. In 1992, at the 0.3 m

depth photosynthesis rates varied from 30 to 52 // mol m^ s'\ and in the

extremely wet growing season of 1993, those varied from 30 to 40 // mol m ̂ s

\ The maximum photosynthesis rates at the water table depths of 1.1, 0.9,

0.6, and 0.2 m were 39.7, 42.9, 47.4, and 38 fj mol m^ s'\ respectively, and

those were 35.6, 38.6, 40.6, and 34// mol m"^ s"^ during 1993 for the same

plant phenological age.

The analysis of variance (ANOVA) was performed using SAS procedures

on the entire data set to determine the differences between photosynthesis

means under five WTD treatments for individual year. The ANOVA results are

presented in Table 2. The ANOVA results for 1992 show that the means for

0.2, 0.3, 0.6, 0.9, and 1.1 m depths were 30.1, 34.2, 32.3, 30.7, and 28.9//

mol m^ s \ respectively, with F-value = 12.8, and Pr > F = 0.0006, which

indicates that the means were significantly different at the 0.05 probability

level. In 1993, the means were 23.7, 29.5, 28.8, 26.8, and 24.0 // mol m'^ s'^

for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively, with F-value = 7.95,

and Pr > F = 0.0038, which indicates that these means were significantly

different at the 0.05 probability level.

50

Photosynthesis rates as a function of time and water table depth for the

Ames site are plotted in Figure 5. Figure 5 shows that during 1992, the

photosynthesis rates were higher for the 0.3 m water table depth than for the

0.6 and 0.9 m depths. The 0.3 m shallow water table supplied more water to

the plant-root system than did 0.6 and 0.9 m WTDs. In a study, Good and Bell

(1980) also reported that higher photosynthesis rates could be enhanced by

providing adequate water supply that prevents stress. This may explain why

higher photosynthesis rates were observed at the 0.3 m WTD. The

photosynthesis rates increased after water table treatments were started. The

increasing trend continued until mid August, 86 DAP, and then dropped slowly.

Almost similar trends were observed by Kalita and Kanwar (1992), they found

maximum photosynthesis rates on 70 DAP during the growing season of 1989

and those between 77 to 84 DAP during 1990 at the Ames site (Table 3). The

highest photosynthesis rates of 47.7, 39.8, and 35 on 86 DAP were observed

for 0.3, 0.6, and 0.9 m WTDs, respectively. As mentioned earlier, the 1993

season was a very wet season, therefore, the water table at this site was

maintained by continuous pumping from the sumps (during rain events).

Figure 5 shows the photosynthesis rates as a function of time and WTD

for 1993. This figure shows that similar trends were observed during 1993.

The photosynthesis rates were higher for the 0.3 m depth than for 0.6, and 0.9

m depths. Comparison of photosynthesis rates for 1992 and 1993 at the Ames

51

site on 40, 56, 71, 86, 98, and 110 DAP show that photosynthesis rates were

higher in 1992 than in 1993. In 1992, for 0.3, 0.6 and 0.9 m WTDs, the

photosynthesis rates varied from 25.2 to 47.7, 25.5 to 39.8, and 22.2 to 35 //

mol m^ s'\ respectively. Whereas, in an extremely wet growing season of

1993, they varied from 12.1 to 39, 11.9 to 34.6, and 10.1 to 30.2// mol m"^ s"

\ respectively, for the same phenological plant age. For 1992, the maximum

photosynthesis rates at 0.3, 0.6, and 0.9 m depths were 47.7, 39.8 and 35 //

mol m^ s'\ respectively, and those were 39, 34.6, and 30.2 // mol m^ s'^ in

1993. As compared to growing season of 1993, the 1992 season was

relatively dry. Therefore, during dry season of 1992 plants at the 0.3 depth

were neither restricted to water supply nor were subjected to excessive water

supply, hence, photosynthesis rates were higher than at 0.6 and 0.9 m WTDs.

In fact, the 1992 data show positive effect of subirrigation on photosynthesis.

In the very wet year of 1993, the soil moisture in the soil profile remained

above field capacity, due to continuous rainfall, during the growing season

between May through October. Therefore, water table elevation had little

influence on water supply, to the plants, and due to excessive soil moisture

conditions low photosynthesis rates were observed during the year. These

findings did not agree with previous results by Kalita and Kan war (1992) for the

same location. They reported high photosynthesis rates during a wet year as

compared to a dry year. Therefore, the effects of water table depth on

52

photosynthesis in a wet season still remain inconclusive and in question.


on the entire data set to determine the differences between photosynthesis

means under three WTD treatments for individual year. The ANOVA results are


0.3, 0.6, and 0.9 m depths were 29.2, 26.1, and 25.1 // mol m^ s \

respectively, with F-value = 10.72, and Pr > F = 0.0104, which indicates that

these means were significantly different at the 0.05 probability level. For 1993,

the means were 27.3, 25.9, and 24.1 // mol m'^ s"^ for 0.3, 0.6, and 0.9 m

depths, respectively, with F-value = 2.67, and Pr > F = 0.1482, which

indicates that these means were not significantly different at the 0.05

probability level.

Effect of water table depth on stomatal conductance

The data on leaf stomatal conductance measured during the two year

study period at the Ankeny and Ames sites are illustrated in Figures 6 and 7.

Leaf stomatal conductivity was significantly affected by WTD. Plants with a

shallow water table depth of 0.3 always showed higher stomatal conductance

than with deep WTDs. Figure 6 shows the relationship between WTD and

stomatal conductance with respect to time, for the growing seasons of 1992

and 1993 for the subirrigation field at the Ankeny site. This figure shows that

53

stomatal conductance values increased by almost 2 times only 6 days after

water table treatment was lowered to 0.3 and 0.6 m depths. It increased by

approximately 1.5 times or more for 1.1, 0.9, and 0.2 m WTDs. These values

increased with time and peaked to 0.94, 0.76, 0.70, and 0.63 mol m^ s'^ on

86 DAP for 0.3, 0.6, 0.9, and 1.1 m depths, respectively, and then declined.

However, for the 0.2 m WTD the highest value of 0.62 mol m'^ s'^ was

observed on 98 DAP. The stomatal conductance values decreased towards the

end of the season and reached almost one value of 0.33 mol m ̂ s'\

The relationship between stomatal conductance and WTD as a function

of time for 1993 is also shown in Figure 6. Almost similar trends were also

observed during this year. The stomatal conductance values increased with

time until 86 DAP and then decreased. The maximum values of 0.72, 0.93,

0.72, 0.79, and 0.71 mol m'^ s'^ were observed for 0.2, 0.3, 0.6, 0.9, and 1.1

m WTDs, respectively, on 86 DAP. It could be seen in Figure 6 that values of

stomatal conductance were not significantly different between treatments

except that of the 0.3 m depth. This might be due to excessive wet conditions

during the year.


on the entire data set to determine the differences between stomatal

conductance means under five WTD treatments for individual year. The

ANOVA results are presented in Table 2. The ANOVA results for 1992 show

54

that the means for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths were 0.49, 0.62, 0.58,

0.55, and 0.50 mol m"^ s"\ respectively, with F-value = 9.50, and Pr > F =

0.0019, which indicates that these means were significantly different at the

0.05 probability level. In 1993, the means were 0.56, 0.63, 0.56, 0.61 and

0.52 mol m'^ s'^ for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively, with F-

value = 1.59, and Pr > F = 0.2500, which indicates that these means were

not significantly different at the 0.05 probability level.

Figure 7 shows that the 0.3 m WTD gave higher stomatal conductance

values than did 0.6, and 0.9 m WTDs during 56 to 110 DAP in lysimeter plots

at Ames site in 1992. This figure shows that stomatal conductivity increased

by almost 1.5 times in all treatments only 6 days after water table treatments

began. It increased with time until mid August, 86 DAP, and peaked to 0.77,

0.72 mol m'^ s'^ for 0.3 and 0.6 m depths, respectively, and then dropped off.

For the 0.9 m depth it peaked to 0.67 mol m'^ s'^ on 98 DAP. However, during

1993, the highest stomatal conductance values of 0.94, 0.89, and 0.79 mol m'^

s'^ were observed on 86 DAP for 0.3, 0.6, and 0.9 m WTDs, respectively. A

comparison between years in Figure 7 shows that stomatal conductance values

on 40, 56, 71, 86, 98, and 110 DAP were significantly different for the two

study years (1992 and 1993) for the same plant phenological age.


on the entire data set to determine the differences between stomatal

55

conductance means under three WTD treatments for individual year. The

ANOVA results are presented in Table 2. The ANOVA results for 1992 show

that the means for 0.3, 0.6, and 0.9 m depths were 0.52, 0.50, and 0.45 mol

m'^ s'\ respectively, with F-value = 3.39, and Pr > F = 0.1033, which

indicates that these means were not significantly different at the 0.05

probability level. For 1993, the means were 0.63, 0.59, and 0.53 mol m'^ s'^

for 0.3, 0.6, and 0.9 m depths, respectively, with F-value = 4.80, and Pr > F

= 0.0568, which indicates that these means were not significantly different at

the 0.05 probability level.

Effects of WTD on transpiration rate

The effects of WTD on day time leaf transpiration from 56 to 110 DAP

showed significant differences for subirrigation field at Ankeny site during 1992

as indicated in Figure 8. This figure shows that 0.2 and 1.1 m WTDs always

showed lower transpiration rates than did 0.3, 0.6, and 0.9 m depths. The

lower transpiration rates at the 0.2 m depth were due to excessive water supply

which in turn caused the stress, whereas, the reduction in transpiration rates at

1.1 m depth could be attributed to increased stress due to deficit water supply

to plant roots. These results are in agreement with the previous findings by

Kalita and Kan war (1992), they observed low transpiration rates under 0.2 and

1.1 m WTDs. Cannel and Jackson (1981) also reported that waterlogging

56

causes shoot wilting in a very short time, which in turn causes physiological

drought to the plant leaves by increasing resistance to water flow to the roots.

When stomata are open wide enough transpiration rates are higher, and in

contrast, when roots reduce water supply to the leaves, the plant leaves wilt

and as a result, transpiration rate slows down significantly.

However, the plants with the 0.3 m depth showed significantly higher

transpiration rates, throughout water table treatment period between 56 to 110

DAP, than did the plants with 0.2, 0.6, 0.9, and 1.1 m depths. The

transpiration rate increased, by about 1.5 times in almost all but the 1.1 m WTD

only 6 days after water table treatments were initiated. The plants with a 1.1

m WTD, however, showed no immediate response in transpiration rates. The

maximum transpiration rates at the peak hour during day time were 13.9, 22.8,

16.2, 16.3, and 12.7 mm/day for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths,

respectively, on 86 DAP. Transpiration rates decreased with plant age after 86

DAP under all WTD treatments. These rates were 5.1, 8.7, 7.2, 6.9, and 4.6

mm/day for 0.2, 0.3, 0.6, 0.9, and 1.1m depths, respectively, during the peak

day time hours on 110 DAP.

The transpiration rates as a function of time and WTD for the

subirrigation field at Ankeny for 1993 are also plotted in Figure 8. This figure

shows that no significant differences among treatments were found during this

year. This was because of extremely wet conditions caused by heavy rainfalls

57

during the entire growing season. However, the transpiration rates increased

between 56 and 86 DAP. The highest transpiration rates were 12.3, 12.7,

13.6, 11.7, 10.1 mm/day for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths on 86 DAP.

These rates decreased with plant age thereafter. Comparison between two

years in Figure 8 shows that transpiration rates were significantly higher in

1992 than in 1993 for the same plant growth stage. This could be anticipated

because of low temperatures and overcast conditions during 1993.

The data on transpiration rate for the lysimeter plots at the Ames site are

plotted in Figure 9. This figure shows that the transpiration rates were

significantly affected by WTDs. In 1992, the transpiration rates increased by

almost 2 times or more only 6 days after water table was raised to desired

depths of 0.3, 0.6, 0.9 m. Figure 9 shows that transpiration rates were

significantly higher during 56 to 98 DAP with the 0.3 WTD in comparison with

0.6 and 0.9 m WTDs. The maximum transpiration rates during the peak day

time hours on 86 DAP for 0.3, 0.6, and 0.9 m depths were 22, 14.7, and 12.3

mm/day, respectively. These rates then decreased with the plant age.

During 1993, similar trends were observed. The plants with the 0.3 m

WTD always showed higher transpiration rates then did the plants with 0.6 and

0.9 m WTD. The maximum transpiration rates during the peak day time hour on

86 DAP were 15.1, 13.6, and 11.2 for 0.3, 0.6, and 0.9 depths, respectively.

However, these rates were statistically significant at the 0.5 probability level.

58

As mentioned earlier, 1993 was an extremely wet year, the water table depths

at this site during excessive rainfall were maintained by pumping the water,

therefore, the treatment responses at this site were clear and measurable during

wet year.

Effects of WTD on intercellular 00% (Ci)

The relationships between Ci as function of time and WTD are shown in

Figure 10 . Leaf intercellular COj (Ci) was affected by WTDs. Plants with the

0.3 m water table depth most of the time showed higher Ci than did the

shallow or deep WTDs for the subirrigation field at Ankeny during the growing

season of 1992. Figure 10 shows that the 0.3 m WTD gave higher Ci than did

0.2, 0.6, 0.9, and 1.1 m depths. The highest Ci observed on 71 DAP under

0.3 m depth was 266 ppm. It was 246, 253, 243, and 238 ppm for 0.2, 0.6,

0.9, and 1.1 m depths, respectively, on 71 DAP. The Ci decreased with age

after 71 DAP. Almost similar trends were observed during the growing season

of 1993. Figure 10 shows that Ci increased with time after 56 DAP and peaked

on 86 DAP and then decreased thereafter. The maximum Ci obtained on 86

DAP was 235, 264, 266, 260, and 238 ppm for 0.2, 0.3, 0.6, 0.9, and 1.1 m

depths, respectively.

Figure 11 shows Ci as function of time and WTD for lysimeter plots at

the Ames site for 1992 and 1993. According to this figure. Ci values increased

with time and peaked on 86 DAP as 356.6, 339.3, and 350.2 ppm for 0.3, 0.6,

and 0.9 m depths, respectively, and then dropped with the plant age. The

decrease in Ci with plant age was a result of increased stomatal resistance.

Although, Ci values were higher with 0.3 m depth in comparison with 0.6 and

0.9 m depths, but, statistically these differences were not significant.

Relationship between Ci and water table depths for 1993 is also shown in

Figure 11. This figure shows that the Ci increased with time until 71 DAP for

0.3 m depth, and until 86 DAP for 0.6 and 0.9 m depths and decreased

thereafter. Figure 11 also indicates that the 0.3 m depth gave slightly higher Ci

values than did 0.6 and 0.9 m WTDs during 56 to 98 DAP. However,

statistically the differences were not significant between treatments at the 0.05

probability level.

Effects of WTD on chlorophyll content

Leaf chlorophyll content was determined on the same leaves used for

photosynthesis, transpiration, and stomatal conductance measurements.

Comparison of chlorophyll meter readings as a function of time and WTD at the

Ankeny site for 1992 and 1993 are shown in Figure 12. Figure 12 shows that

chlorophyll meter readings significantly increased under all WTDs after water

treatment began in 1992. As the growing season progressed, chlorophyll

readings increased with time until 86 DAP, and then decreased thereafter. The

60

highest chlorophyll readings observed on 86 DAP were 50.9, 55.3, 53.8, 52.5,

and 50.3 for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively. The 0.3 m

depth showed higher chlorophyll readings as compared to all other WTDs for

the period between 56 through 110 DAP. Comparison between chlorophyll

readings for 1993 under different WTDs is also shown in Figure 12. Similar

trends were observed in 1993. The chlorophyll readings increased for 0.3, 0.6,

0.9, and 1.1 m depths as the growing season progressed and peaked on 86

DAP and then decreased. However, no significant response in chlorophyll

readings was observed at 0.2 m depth. Flooded conditions due to heavy

rainfalls were the major cause of no response in chlorophyll readings at this

particular depth. The highest values observed on 86 DAP were 43.4, 51.9,

51.2, 50.9, and 44.8 for 0.2, 0.3, 0.6, 0.9, and 1.1 m depths, respectively.

Although comparison of chlorophyll readings between WTDs showed higher

chlorophyll values at 0.3 m depth in comparison with other depths. These

values were not significantly different between 0.3, 0.6, and 0.9 m depths, but

were significantly different than 0.2 and 1.1 m depths at 0.05 probability level

during 56 to 110 DAP.


on the entire data set to determine the differences between chlorophyll means

under five WTD treatments for individual year. The ANOVA results are


61

0.2, 0.3, 0.6, 0.9, and 1.1 m depths were 43.0, 47.1, 45.5, 44.6, and 42.5

SPAD unit, respectively, with F-value = 8.82, and Pr > F = 0.0026, which

indicates that these means were significantly different at the 0.05 probability

level. In 1993, the means were 39.3, 47.5, 45.5, 45.6 and 41.6 at 0.2, 0.3,

0.6, 0.9, and 1.1 m depths, respectively, with F-value = 6.39, and Pr > F =

0.0081, which indicates that these means were significantly different at the

0.05 probability level.

Relation between chlorophyll meter readings as a function of time and

WTDs for lysimeter plots at the Ames site for 1992 and 1993 are shown in

Figure 13. Also, similar trends were observed at this site. Higher chlorophyll

meter readings were obtained at shallow water depth of 0.3 m. These values

decreased with lowering WTD. Previous studies have also reported a decrease

in chlorophyll concentration for alfalfa when moisture decreased from 70 to

40% (Parjol et al. 1976 and Estill et al. 1991).

At the 0.3 m depth, chlorophyll meter readings were higher than at 0.6

and 0.9 m depths in both years (Fig. 13). This figure shows that, in 1992, the

highest chlorophyll readings as 57.7, 54 and 49.1 for 0.3, 0.6, and 0.9 m

depths were observed on 86 DAP, respectively, and those for 1993 were 53.3,

50.1, and 40.1 at 0.3, 0.6, and 0.9 m depths, respectively, for the same plant

phenological age.


62

on the entire data set to determine the differences between chlorophyll means

under three WTD treatments for individual year. The ANOVA results are


0.3, 0.6, and 0.9 m depths were 49.56, 48.17, and 44.35 SPAD unit,


these means were significantly different at the 0.05 probability level. For 1993,

the means were 46.1, 44.0, and 38.5 for 0.3, 0.6, and 0.9 m depths,


these means were significantly different at the 0.05 probability level.

Crop canopy temperature and water table depth

Canopy temperature is used to characterize drought stress effects in

many field crops. When stomata close, transpiration is reduced and

consequently the cooling effect is diminished leading to leaf temperature

increases. Diurnal variation in evaporative demand is also mainly due to leaf

temperature. The closer the leaf temperature stays to air temperature, the

closer the evaporative demand experienced by the leaf reflects the saturation

vapor deficit of the air. Reduction in leaf temperature has another indirect

benefit in terms of photosynthesis. The cooler the leaf the larger is the stomatal

conductivities corresponding to any given evaporation rate.

In this study, A portable photosynthesis system was used to measure the

63

leaf (Te) and air (Ta) temperatures inside the canopy. Leaf and air temperatures

differentials during growing seasons of two years for the Ankeny and Ames

sites are presented in Figures 14 and 15. Leaf air temperature differentials for

the subirrigation field at the Ankeny site under various WTDs are shown in

Figure 14. Figure 14 shows that, in 1992, leaf temperatures were lower than

air temperatures until 86 DAP under all but 0.2 m WTD, whereas, the higher

leaf temperature values were observed from 71 through 130 DAP. The 0.3 m

depth always showed higher leaf-air temperatures as compared to 0.2, 0.6, 0.9,

and 1.1 m depths. The highest leaf-air temperature differential as -1.6°C was

observed at the 0.3 m depth only 6 days after WTD was raised, and was

significantly different than all other WTDs. The leaf-air temperature differentials

for 0.2, 0.6, 0.9, and 1.1 m depths were -0.6, -1.0, -1.1, and -0.6°C,

respectively. The temperature differentials decreased with the plant age after

56 DAP. In 1993, the temperature differentials were positive for all

subirrigation plots before the treatment began. After WTDs were raised, the

leaf temperatures were higher than air temperatures in all treatment plots but

were not significantly different between WTDs. The leaf temperature increased

thereafter and remained above the air temperature for 0.2 and 1.1 m depths

during the rest of the growing season. For 0.3, 0.6, and 0.9 m depths, the leaf

temperature remained above air temperature after 86 DAP. It was because of

water table fluctuations due to heavy rainfall during the entire growing season

of 1993 which in turn caused excessive soil moisture conditions in the root

zone. Therefore increased leaf temperature could be anticipated.

Figure 15 shows the effects of water table depth on leaf-air temperature

in the lysimeter plots at Ames site for 1992 and 1993. This figure shows that

leaf temperatures were lower than air temperatures in all three WTDs. The leaf-

air temperature differentials were negative for all the lysimeter plots before

water table treatment began in 1992. After water table depths were raised to

0.3, 0.6, and 0.9 m depth, Tc - Ta significantly decreased in all treatment plots.

The maximum temperature differentials recorded on 56 DAP were -0.2, -1.0,

and -0.7°C for 0.3, 0.6, and 0.9 m depths, respectively, and were significantly

different for different water tables at the 0.05 probability level. In 1993, the

temperature differentials were positive for all the lysimeter plots before the start

of water table depth (Fig. 15). Almost similar trends were observed in 1993. A

significant decrease in Tc - Ta was observed on 56 DAP after water table

treatment began. The maximum Tc - Ta differentials observed on 56 DAP for

0.3, 0.6, and 0.9 m depths were -0.8, -0.7, -0.2°C, respectively. The 0.3 and

0.6 m depths showed lower leaf temperatures between 56 to 98 DAP, whereas,

the higher leaf temperature were recorded for 0.9 m depth between 71 to 98

DAP.

The data on leaf and air temperature as a function of WTD for 1992 and

1993 at the Ankeny and Ames sites were subjected to linear regression

65

analysis. Figure 16 gives a relationship between leaf and air temperatures along

with the upper and lower 95% confidence intervals. It can be seen from Figure

16 that a strong correlation exists between leaf and air temperatures and the

upper and lower 95% confidence intervals form a very narrow band on the

predicted line. The data points are almost (falling) on the line of best fit, and

the correlation is high. The value of the coefficient of correlation (R^) is 0.98.

The regression equation for the relationship between leaf and air temperature Is

given below:

T-Leaf = 1.43 + 0.94 T-Air

where T-Leaf is leaf temperature and T-Air is air temperature. The 45° dashed

line describes a relation if leaf temperature (Tc) is equal to air temperature (Ta).

Relationships between photosynthesis and chlorophyll readings

Linear regression was used to determine the "best fit" relationships on

average values of photosynthesis versus chlorophyll readings and are shown in

Figures 17 and 18 for the Ankeny and Ames sites, respectively. The

corresponding regression equations and their respective R-square values for

different WTDs are given below:

66

Ankeny site 1992

WTD = 0.2 m, PHO - 1.17 CHL- 19.8 R2 = 0.77

WTD = 0.3 m, PHO = 1.34 CHL- 28.6 R2 0.89

WTD = 0.6 m. PHO = 1.27 CHL- 25.6 R2 0.87

WTD = 0.9 m, PHO — 1.07 CHL- 16.8 R2 0.91

WTD = 1.1 m, PHO = 1.16 CHL- 20.3 R2 = 0.85

Ankeny site 1993

WTD = 0.2 m. PHO = 0.88 CHL- 11.5 R2 = 0.47

WTD = 0.3 m, PHO 1.48 CHL- 40.6 R2 = 0.50

WTD = 0.6 m, PHO 1.52 CHL- 40.4 R2 = 0.82

WTD = 0.9 m, PHO 1.17 CHL- 26.6 R2 = 0.53

WTD = 1.1 m, PHO 1.19 CHL- 25.0 R2 = 0.58

Ames site 1992

WTD = 0.3 m, PHO = 1.57 CHL - 48.7 R2 = 0.61

WTD = 0.6 m, PHO = 1.68 CHL - 54.9 R2 = 0.65

WTD = 0.3 m, PHO = 2.04 CHL - 65.4 R2 = 0.84

Ames site 1993

WTD = 0.3 m, PHO = 1.52 CHL- 42.6 R2 = 0.70

WTD = 0.6 m, PHO = 1.54 CHL - 42.2 R2 = 0.86

WTD = 0.3 m, PHO 2.38 CHL- 67.5 R2 0.79

where WTD is water table depth, PHO is photosynthesis rate in /y mol m"^ s \

67

and CHL is chlorophyll reading in SPAD units. These models show a positive

correlation between photosynthesis versus chlorophyll readings for all WTDs at

Ankeny and Ames sites, for 1992, and 1993.

Leaf chlorophyll readings at Ankeny site for 1992 were a good predictor

of photosynthesis rates, accounting for, on the average 86% of the variation in

photosynthesis rates (Fig. 17). The higher values under all depths indicate

that the linear models were appropriate to explain the relationship between

these parameters. Comparison between WTDs based on values showed that

the 0.9 m depth y ie lded h igher R^ va lues than d id 0.2, 0 .3, 0 .6, and 1 .1m

depths, but, the differences were not significant, suggesting that all models

were fitting the data well.

In 1993, significant positive relationships between photosynthesis and

chlorophyll were observed (Fig. 17). Although, leaf chlorophyll readings were

good predic tor o f photosynthesis rates, and accounted for , on the average 59%

of the variation in photosynthesis rates, but were not as good as those of 1992.

The R^ values were very much close for all WTDs except for 0.6 m depth,

which showed higher R^ values. This model was a good predictor of

photosynthesis rates as compared to other models.

A positive correlation between photosynthesis and chlorophyll for 0.3,

0.6, and 0.9 m WTDs for the Ames site were observed in 1992 and 1993 (Fig.

18). The equations of linear regression were appropriate to explain the

68

relationship between photosynthesis rates versus chlorophyll readings,

accounting for, on the average 70 and 78% of the variation in photosynthesis

rates for 1992 and 1993, respectively. Leaf chlorophyll readings were good

predictor of photosynthesis rates, and accounted for 61, 65, and 84% in 1992,

and 70, 86, and 79% of the variation in photosynthesis rates in 1993 at 0.3,

0.6, 0.9 m depths, respectively.

Linear regression was used also performed to determine the "best fit"

re lat ionships between photosynthesis versus ch lorophyl l readings us ing raw

data for the individual year and are shown in Figures 17a and 18a for the

Ankeny and Ames sites, respectively. The corresponding regression equations

and their respective R-square values for different WTDs are also given in Figures

17a and 18a. These best fit lines show trends similar to those observed with

average values of these parameters and a strong positive relationship between

photosynthesis and chlorophyll were observed. However, the coefficient of

correlation (R^' values using raw data were lower than those observed using

average data.

Relations between stomatal conductance and transpiration rates

Relationships between transpiration rates and stomatal conductance as

determined by linear regression analysis for Ankeny and Ames sites are shown

in Figures 19 and 20, respectively. The corresponding regression equations and

69

their respective R-square values for different WTDs are given below:

Ankeny site 1992

WTD = 0.2 m, TR = 29.79 COND • 7.48 R2 = 0.68

WTD = 0.3 m, TR = 24.26 COND - 4.14 R2 = 0.81

WTD = 0.6 m, TR = 19.88 COND - 2.64 R2 = 0.68

WTD = 0.9 m, TR = 26.09 COND - 5.37 R2 = 0.66

WTD = 1.1 m, TR 21.38 COND - 2.03 R2 = 0.61

Ankeny site 1993

WTD = 0.2 m, TR = 23.10 COND - 7.07 R2 = 0.84

WTD = 0.3 m, TR = 13.42 COND - 1.27 R2 = 0.90

WTD = 0.6 m, TR = 18.20 COND - 2.42 R2 = 0.82

WTD = 0.3 m, TR = 15.37 COND - 2.15 R2 = 0.80

WTD = 1.1 m, TR 19.33 COND - 4.81 R2 = 0.94

Ames site 1992

WTD = 0.3 m, TR = 32.79 COND - 6.18 R2 = 0.92

WTD = 0.6 m, TR = 23.87 COND - 2.61 R2 = 0.95

WTD = 0.9 m, TR = 21.51 COND - 3.69 R2 = 0.77

Ames site 1993

WTD = 0.3 m, TR = 22.33 COND - 3.61 R2 = 0.75

WTD = 0.6 m, TR 20.77 COND - 3.81 R2 = 0.80

WTD = 0.9 m, TR = 19.11 COND - 2.74 R2 = 0.88

70

where WTD is water table depth, TR is transpiration rate in mm/day, and COND

is stomatal conductance in mol m^ s \ These models show a positive

correlation between transpiration versus stomatal conductance values for all

WTDs at the Ankeny and Ames sites, for 1992, and 1993.

Stomatal conductance values at Ankeny site for 1992 were a good

predictor of transpiration rates, accounting for, on the average 69% of the

variation in transpiration rates (Fig. 19). The high values for under all depths

indicate that the linear models were appropriate to explain the relationship

between these parameters and were fitting well to their respective data sets.

Comparison between WTDs based on R^ values showed that the 0.3 m depth

yielded higher R^ values than did 0.2, 0.3, 0.6, and 1.1m depths. This

provides the evidence that adequate supply of water to the root zone

accelerates the stomatal conductivity that in turn increases the transpiration

rates. The lower values of R^ with 1.1 m depth, might explain that water stress

did affect the stomatal conductivity that reduced the transpiration rates.

In 1993, significant positive relationships between transpiration rates and

stomatal conductance were observed {Fig. 17). Although, stomatal

conductances values were good predictor of transpiration rates, and accounted

for, on the average 86% of the variation in transpiration rates, but no significant

differences were found between water table depth treatments, due to extremely

wet conditions. Regardless of WTD, the models were good predictors of

71

transpiration rates.

A positive correlation between transpiration rate and stomatal

conductance for 0.3, 0.6, and 0.9 m WTDs for Ames site were observed in

1992 and 1993 (Fig. 20). The equations of linear regression were appropriate

to explain the relationship between transpiration rates versus stomatal

conductance values, accounting for, on the average 88 and 77% of the

variation In transpiration rates for 1992 and 1993, respectively. In 1992,

stomatal conductance responses under 0.3, 0.6, and 0.9 m were very clear and

models were good predictor of transpiration rates, and accounted for, on the

average 92, 95, and 77% of the variation, respectively. Although, stomatal

conductances values were good predictor of transpiration rates, and accounted

for, on the average 77% of the variation in transpiration rates regardless of

WTD, during 1993, but opposite trends In values were observed. The 0.9 m

depth showed high correlation coefficient than did 0.3 and 0.6 m depth. The

excessive soil moisture conditions in the root zone, due to heavy rainfalls, at

0.3 m depth might have caused plant leaves to go under stress which in turn

resulted in stomata closure. The relationships between transpiration rate and

stomatal conductance for 1992, 1993 suggest that effects of water table

management can be predicted during dry seasons.

72

Crop yield

Corn yields for 1992, and 1993 for the Ankeny and Ames sites are

presented in Table 4. At the Ankeny site, the highest corn yield was obtained

from the plots under the 0.9 and 1.1m depths, and the lowest yield was

obta ined f rom the p lots under the 0.2 m depth in 1992. In 1993, however , 1 .1

m depth gave the highest, and 0.2 m depth gave the lowest yield. At 0.2 m

depth crop yield was very poor in both years. High rainfalls caused almost

surface flooding conditions for a few days during 1992, and almost all the time

during the growing season of 1993, at the 0.2 m depth, which in turn

significantly affected the yield at this location. Yields for 1992 were higher

than those for 1993. The extremely wet condition were responsible for the

decrease in the yield for 1993. However, the 0.3 m depth showed slightly

higher yields than did the 0.6 m depth for both years. Relationships between

chlorophyll and yield as a function of WTD for 1992 and 1993 are shown in

Figure 21. This figure shows that corn yield increased with lowering WTD.

However the relationship between chlorophyll and yield was not clear and data

points are more scattered rather than following any specific trends.


to determine the differences between yield means under five WTD treatments

for individual year. The ANOVA showed no significant differences between the

means under different WTDs at the 0.05 probability level during 1992.

73

However, the means were significantly different between 0.2, 0.9, and 1.1m

WTDs at the 0.05 probability level, but those were not significantly different

between 0.3, 0.6, 0.9, and 1.1m WTDs during 1993.

At the Ames site, the highest yield was obtained from the plots under the

0.9 m depth, and the lowest yield was obtained from the plots under the 0.3 m

depth during both study years (Table 4). Almost similar results were observed

during both years at this site. The water tables were maintained by pumping

the excessive rainfall water at this site, therefore, no significant differences in

corn yields between two years were observed. Relationships between

chlorophyll readings and yield under different WTDs for 1992 and 1993 are

shown in Figure 21. This figure shows that corn yield increased with lowering

WTD. The relationship between chlorophyll and yield was not clear at the 0.3

and 0.6 m WTDs and data points are more scattered rather than following any

specific trend. However, Figure 21 shows that yield increased with increasing

chlorophyll readings at the 0.9 m WTD.


to determine the differences between yield means under three WTD treatments


means observed at the 0.6 and 0.9 m depths at the 0.05 probability level during

both study years. However, the means for the 0.3 and 0.9 m depths were

significantly different at the 0.05 probability level during both study years.

74

CONCLUSIONS

Field experiments were conducted to study the effects of water table

depths on various plant physiological parameters. Data for 1992 and 1993

were collected at two experimental farms owned by the Iowa State University.

These two research sites were located near Ankeny and Ames. This study

resulted in the following conclusions:

1. Photosynthesis rates, stomatal conductance, transpiration rates, intercellular

COj, and chlorophyll were significantly affected at a WTD of 0.2 m due to

surplus water and at 1.1 m depth due to inadequate supply of water. In 1993,

an extremely wet year, values of these parameters were lower than those in

1992 under all WTDs at the Ankeny site. Almost similar trends were observed

at the Ames site. The 0.3 m WTD showed higher values of these plant

parameters as compared to those observed at 0.6 and 0.9 m WTDs during both

study years.

2. Photosynthesis, stomatal conductance, transpiration, intercellular COg,

canopy temperatures, and chlorophyll exhibited similar relations with various

WTDs during the growing season. The highest values of these physiological

parameters were observed on 86 DAP under all WTDs and then decreased

thereafter. However, the 0.3 m WTD had higher values of these physiological

parameters as compared to all other WTDs.

75

3. Corn yields significantly increased as WTDs were lowered from 0.3 to 0.9 m

at the Ames site during both study years. At the Ankeny site, yields increased

as WTDs were lowered from 0.2 to 1.1 m. However, yields were not

significantly different between WTDs at the 0.05 probability level for the

growing season of 1992. In contrast, yields were significantly different

between WTDs at the 0.05 probability level during 1993, and shallow water-

table depths (0.2 and 0.3 m) significantly reduced corn yield due to excessive

wet conditions.

4. Statistical analysis of the data showed the means for photosynthesis

between WTDs for the Ames site were significantly different at the 0.05

probability level during both years, whereas those differences were not

significant for 1993 at Ankeny site. However, the means for chlorophyll

readings between WTDs were significantly different at the 0.05 probability level

for both years at the Ankeny site. The stomatal conductances were not

significant at the 0.05 probability level, except for 1992 at Ames site, where,

these differences were significant.

5. Relationships between different plant parameters were developed by fitting



1993, at both experimental sites. Finding of these analysis reveal that leaf

chlorophyll could be used as a good predictor of photosynthesis rates regardless

76

of water table treatment depth. Also, a strong positive relation between

stomatal conductance and transpiration rates was observed. The regression

analysis revealed that the transpiration rates were highly dependent on the

stomatal behavior.

6. The overall results of this study indicate that leaf chlorophyll should be the

best single plant parameter which can be related to crop yields and

photosynthesis rates with confidence.

Table 1. Selected physical properties of the soils at the Ankeny and Ames experimental sites

Depth Sand m %

Silt %

Clay %

PH Bulk density Mg m'3

Organic matter %

Nicollet loam soil at the Ankeny site*

0.15 29.5 44.3 26.2 5.9 1.25 3.2

0.30 31.5 40.4 28.1 6.6 1.49 2.3

0.60 38.6 34.1 27.3 7.1 1.46 1.5

Nicollet loam soil at the Ames site^

0.15 31.3 43.6 25.1 7.3 1.20 4.3

0.30 31.2 42.8 26.0 6.7 1.30 4.0

0.60 27.7 42.2 30.1 6.9 1.35 2.9

^Charkhabi (1990); ^Kanwar et al. (1988)

Table 2. Analysis of variance comparing means of different plant physiological parameters at Ankeny and Ames sites

WTD

Site Year Parameter 0.2 0.3 0.6 0.9 1.1 LSD F Pr >

Ankeny 1 2

PHO PHO

30. r 23. r

34.4= 29.5*

32.3" 28.8*

30.7"c 26.8*"

28.y 24.0"c

1.87 2.06

12.8 7.9

0.0006 0.0038

1 2

CON CON

0.49c 0.56'"

0.62» 0.63*

0.57*" 0.56*"

0.55*" 0.61*"

0.50' 0.52"

0.06 0.10

9.5 1.6

0.0019 0.2500

1 2

CHL CHL

43.0"' 39.3c

47.1* 47.5*

45.5*" 45.5*"

44.6"c 45.6*

42.5" 41.3"'

1.97 4.25

8.8 6.4

0.0026 0.0081

Ames 1 2

PHO PHO

29.2* 27.3'

26.1" 25.8*

25.2" 24.1*

2.20 3.36

10.7 2.7

0.0104 0.1482

1 2

CON CON

0.52* 0.63*

0.50*" 0.60*"

0.45" 0.54"

0.06 0.08

3.4 4.8 .

0.1033 0.0568

1 2

CHL CHL

49.6* 46.1*

48.2* 44.0*"

44.3" 38.5*

3.61 4.73

6.8 8.3

0.0290 0.0187

PHO - Photosynthesis rate; CON - Stomatal conductance; CHL - Chlorophyll; 1 - 1992; 2 - 1993; means followed by same letter in a row are not significantly different at the 0.05 probability level

79

Table 3. Maximum photosynthesis rates (// mol m'^ s^) and their range as a function of time observed during four years study period

Ames site Ankeny site

Year DAP WTD Maximum Range DAP WTD Maximum Range

1989* 70 0.3 36.6 31.0-36.6

70 0.6 34.8 24.7-34.8

70 0.9 36.1 25.7-36.1

1990* 48 0.2 37.5 04.9-37.5

84 0.3 99.1 12.5-99.1 48 0.3 70.7 17.8-70.7

77 0.6 100.9 16.8-100.9 48 0.6 83.7 21.4-83.7

77 0.9 110.4 13.7-110.4 48 0.9 86.0 23.6-86.0

48 1.1 94.7 30.9-94.7

1992 86 0.2 38.0 15.9-38.0

86 0.3 47.7 8.8-47.7 86 0.3 52.0 21.2-52.0

86 0.6 39.8 7.1-39.8 86 0.6 47.4 18.3-47.4

86 0.9 35.0 6.3-35.0 86 0.9 42.9 19.0-42.9

86 1.1 39.7 15.5-39.7

1993 86 0.2 34.0 15.8-34,0

86 0.3 39.0 12.1-39.0 86 0.3 42.0 18.4-42.0

86 0.6 34.6 11.9-34.6 86 0.6 40.6 19.9-40.6

86 0.9 30.2 10.1-23.1 86 0.9 38.6 17.5-38.6

86 1.1 35.6 16.3-35.6

DAP - days after planting; WTD - water table depth;('After Kalita and Kanwar, 1992)

80

Table 4. Corn yield kg/ha as a function of water table depth at Annes and Ankeny sites for 1992 and 1993.

WTO, m Ames Ankeny

Year 1992

0.2 7033*

0.3 5216* 8400*

0.6 6970*" 8348*

0.9 8732" 9280*

1.1 9293*

Year 1993

0.2 3671*

0.3 4930* 5226*

0.6 7914" 5150*"

0.9 8860" 6960"'

1.1 7399"'

Means followed by same letter in a column are not significantly different at the 0.05 probability level within year and site

bilgailofi

Gudtn

S 120cm

CoffitgfttM M#»%k Sump (4icmOO) Coif ufaitd Hasiictik

(lOcmOO) r I pUsiU •ailier I—I (0 2$ mm lliuk)

00

12 j fVCfU.ihltlfcMt Sumpfump-

Figure 1. An isometric view of the lysimeter with sump and float assembly (after Kalita and Kanwar, 1992)

82

City of Amts Main Water Supply Line

Water Meter Pit

Hydrant

O 0

Additional Drain Valve

Oo-

Oo

60

Water Storage Tank (1.3 m diameter, 1.6 m height)

•PVC Main Irrigation Supply Pipe (diameter 7.5 cm)

Oo

Co

60

o'o I

"T" I

0 lo

I

O ' O

-CU

J— Irrigation ! Lateral

•Water Meter

I

a jo

1"" 0.25 mm Plastic Barrier (1.2 m deep)

I 3 m .

9m

36 m

O Corrugated Plastic Sump —— 0.25 mm PVC Flexible Liner o <3 Observation Weils (1.7 m deep)

Figure 2. Layout of the experimental plots at the Ames site (after Kalita and Kanwar, 1992)

f

Reservoir Pump

Irrigation Lines

Drainage Lines

Return

Drainage Pump

Figure 3 A schematic sketch of the dual-pipe subirrigation system at the Ankeny site (after Kallta and Kanwar, 1992)

60 WTD =0.2 m 1992

50

WTO =0.6 m

WTD=0.9m Ô40

•30

20

Water table treatment started 10

40 60 80 100 120 140

60 1993

SO WTD=0.6m

S 30

s. I 20

I Water table treatment started

10

40 80 100 140 60 120 Days after planting Days after planting

Figure 4. Photosynthesis rate for the subirrigation field at Ankeny site, 1992,93

60

WTD =0.3 m 1992

50 WTD=0.6 m

30

£20


40 60 80 100 120 140

60

1993

SO

5 30

1 20


40 80 60 100 120 140 Days after planting Days after planting

Figure 5. Photosynthesis rate for the lysimeter plots at Ames site, 1992, 93

1993

0.8

WTD=0.9m

S 0.6

0.4

0.2 40 60 80 100 120 140

1992

WTD=0.6 m 0.8

WTD =0.9 m

WTD = 1.1 m

•0.6

0.2 40 60 80

Days after planting 100 120 140

Figure 6. Stomatal conductance for the subirrigation field at Ankeny site, 1992,93

00 C7I

1992

WTD=0.9m M 0.8

0.6

EO.4

0.2 40 80 60 100 120 140

1993

w 0.8

0.6

0.2 40 60 80 100 120 140

Days after planting Days after planting

Figure 7. Stomatal conductance for the lysimeter plots at Ames site, 1992, 93

I

Water table treatment started

& • WTD =0.2 m

WTO =0.3 m

WTD =0.6 m

m WTD =0.9 m

ED WTD = 1.1 m

IIiBL 86 98 110

Days after planting 120 130

25

20

u

1993

_d?L

i l l

Water taWe treatment started

• Wn>=0.2m

WTD=0.3m

sa WTD=0.6 m

WTD=0.9m

• WTD = 1.1 m

40 56 71 86 98 Days after planting

rft fB. 110

Figure 8. Transpiration rate for the subirrigation field at Ankeny site, 1992, 93

25

ts

! 10

Water table treatment started • WTD =0.3 m

WTD =0.6 m

• WTD =0.9 m

71 86 98 110 120 Days after planting

130

25

20

I,. 5 10

Water table treatment started • WTD=0.3 m

ea WTD=0.6m

WTD=0.9 m

71 86 Days after planting

110

Figure 9. Transpiration rate for the lysimeter plots at Ames site, 1992, 93

00 O)

300

1992

WTD-0.3 m 280

WTD-0.6

o. 260

WTD-1.1

m 240

220

200 Water tfutment »t«ned

160

J. JL

1993

WTD-0.3 280

WTD-0.6m

o. 260 WTO-0.9

240

220

200 Water table treatment started

180

40 80 120 140 60 100


Figure 10. Intercellular C02for the subirrigation field at Ankeny site, 1992, 93

00

400 1992

WTD-0.3

WTD-0.6 m 350

WTO'0.9 m

I cT 300 u

1 £ 250

Water table treatment uarted 200

40 60 80 100 120 140

400 1993

WTD-0.3

350

WTO-0.9 m

O 300

250

200

40 60 80 120 140 Days after planting Days after planting

Figure 11. Intercellular COg for the lysimeter plots at Ames site, 1992, 93

60 1992

55

WTD-0.6 m

S 50

WTD-1.1 m

Water table treatment started U 35

30 40 60 80 100 120 140

60 1993

55

2 50

WTD-1.1

Water tabie treatment start;

w 35

30 40 60 80 100 120 140


Figure 12. Chlorophyll meter readings for the subirrigation field at Ankeny site, for 1992, 93

00 00

60 WTD-0.3 1993 WTD-0.6 8 55 WTDrO.9

S 50

Water table treatment started W 35

30 40 60 80 100 120 140

60

1992 WTD-0.3

2 55

WTD-0.9 m

f 50

S 45

Water taWe treatment started W 35

30 40 60 80 100 120 140


Figure 13. Chlorophyll meter readings for the lysimeter plots at Ames site, for 1992, 93

I I 1

Water table treatment stacted

40 56 86 98 no 120 130

WTD-0.2 m WTD«0.3m WTD-0.6m WTO«0.9m WTD-1.1 m

71 86 98 110 120

Days after planting

cP O S

I | . , . S


WTD-0.2 m WTD-0.3m WTD-0.6m WTD-03m WTD-1.1 m # —B e A —•

Days after planting

Figure 14. Leaf-air temperature differential for the subirrigatin field at Ankeny during 1992 and 93

00 CO

(P

s. E

Water

•0.5

•1.5

40 56 110 120 130

WTD-0.2 WTD-0.3ffl WTD-0.6

<F o.s -

71 B6 98 110

Days after planting


WTD-0.2 m WTD«0.3m WTD-0.6 m B O

Days after planting

Figure 15. Leaf-air temperature differential for the lysimeter plots at Ames during 1992 and 93

L95% Cl 34

U95% Cl T-Leaf = 1.41 + 0.94 T-Air 0.98 32

Predicted

30

28

= 26

24

22

20

20 22 24 26 28 32 30 34

Air temperature, °C

Figure 16. Relation between leaf and air temperature with upper and lower 95% confidence

intervals for the two study years at two sites (Ankeny and Ames)

I 40

L L PHO • 1.17 CHL-19.8 — PHO - 1.34 CHL-28.6

PHO - 1.27 CHL -25.6 PHO - 1 07 CHL . 16 8

— PHO - 1.16 CHL-20.3

40 45 50 Chlorophyl mctef fuding (SPAO Uniu)

55

-fi3 PHO 0.88 CM.-11.5 0.47 PHO - 1.48 CHL-40.6 0.50 PHO . 1.52 CM.- 40.4 0.82 PHO • 1.17 CHL • 26.6 0.52 PHO - 1.19CHL- 25.0 0.58

40 45 50 ChkMophy# m*t*f nodng (SPAO Uniu)

Figure 17. Relationship between photosynthesis and chlorophyll readings at Ankeny site, for 1992 and 1993

CO

60 1993

PHO - 1.52 CHL-4X6 0.70 PHO - 1.54 CHL" 42.2 0.86 PHO - 2.3^ Ck.. 67.5 0.79

SO

"E I ̂

20

I as 45 CNofophv# m#*#f r«4dmQ (SPAO Unitt) 60 60 Unitt)

60 1992

PHO - 1.57 CHL-48.7 PHO • 1.68 CHL-54.9 PHO - 2.04 CHL • 65.4

0.61 0.65 0.84

50

IE » i

I 40 CWofophy# mtur rtading ISPAO Uniu) 45 65 60

Figure 18. Relationship between photosynthesis and chlorophyll readings at Ames site, for 1992 and 1993

WTO - 1.1 m

WTD - 0.9 m

PHO - 1.21 CHL-22.6 PHO - 1.09 CHL-17.8 PHO - 1.09 CHL - 17.5

0.76 0.81 0.75

40 45 50

Chlofophyll meter reading ISPAO uruts)

55

WTO - 1.1 m

WTD » 0.9 m

WTD - 0.6 m - B -

WTO - 0.3 m

WTD « 0.2 m

PHO - 0.88 at PHO - 1.34 CHL PHO . 0.73 CHL PHO - 1.07 CHL PHO - 1.19CHL

40 45 50

Chlorophyll meter reacfing (SPAO units)

Figure 17a. Relationship between photosynthesis and chlorophyll readings at Ankeny site, for 1992 and 1993 (using raw data)

60

WTD « 0.9 m 1993

50 -WTD - 0.6

£ "I 40 - WTD « 0.3 m

i 30 -

»o

20 -

0.51 0.58 0.54

I PHO - 1.24 CHL-29.8 PHO - 1.11 CHL-23.0 PHO - 1.46 CHL-32.2

10

35 30 40 45 55 50 60

60 1992 WTO - 0.9

PHO « 1.41 CHL-39.9 0.63 PHO • 1.33 CHL-47.7 0.58 PHO - 1.22 CHL-29.1 0.44

50 WTD > 0.6

E

I 0.3 m

30 -

20 -

I 10 -

30 35 40 45 50 55 60

Chlorophyll meter reading (SPAD units) Chlorophyll meter reatfing (SPAO units)

Figure 18b. Relationship between photosynthesis and chlorophyll readings at Ames site, for 1992 and 1993 (using raw data)

25

20

. 15

m 10

1992

0.4 0.6

Stomatai conductance, mol m^s

0.8 •1

16

14

12

E 10

1993

0.4 0.8 1

1

Figure 19. Relationship between transpiration rate and stomatai conductance at Ankeny site, for 1992 and 1993

25

20

15

S

J g 10

2 5

1992

H

0.4 0.6 0.8 Stomatai conductance, moi m'^s*^

16

14

. 12

E 10

1993

0.4 0.6 Stomatai conductance, moi m'^s*^

0.8 1

Figure 20. Relationship between transpiration rate and stomatai conductance at Ames site, for 1992 and 1993

94

12000

Ankeny

10000 00

mm

00

8000

* • Jm

6000

o o m

IPWTO - 0.2 m 4000

WTO - 0.3 m

WTO " 0.8 m

2000 WTD - 0.9 m

I WTD « 1.1 m

•a

Ames

10000

P»' 8000 O .00"

o o- off6^(?" o

6000 o o o «#

4000

WTD • Ô.3 m

WTD - 0.6 m 2000

WTD - 0.9 m

35 25 30 40 46 50 55 60

Chlorophyll reading (SPAD unit)

Figure 21. Relationship between chlorophyll content and corn yield at Ankeny and Ames sites (pooled data for 1992 and 1992)

95

PAPER II. EFFECTS OF WATER TABLE DEPTHS ON THE TRANSPORT

OF NO3-N INTO GROUNDWATER

96

ABSTRACT

The field experiments were conducted at two researcli farms of Iowa

State University near Aniceny and Ames to study the effects of water table

management practices on groundwater quality. Data were collected during the

growing seasons of 1992 and 1993 at these research farms, and average NO3-

N concentrations in groundwater as affected by different WTDs were measured.

Water samples for NO3-N analysis were collected by using suction tubes and

piezometers installed at different depths in the soil profile. The average NO3-N

concentrations in groundwater were reduced by maintaining WTDs between 0.3

to 0.6 m during the two growing seasons. The average concentrations in

groundwater generally decreased with increased sampling depth and time during

the growing season. The highest NO3-N concentrations in groundwater were

mostly observed before the water table treatments began. However, NO3-N

concentrations were significantly reduced after WTD treatments started and in

most cases these concentrations in groundwater were less than 10 mg/L under

0.3 m WTD treatment. Generally decreasing trend of NO3-N concentration in

groundwater with increasing sampling depth under two sampling methods was

consistent in both study years at both experimental sites.

The residual soil NO3-N concentrations seem to be concentrated in the

upper 0.15 to 0.6 m of the soil profile and the NO3-N levels decreased with the

97

increased soil depth under all water table treatments. However, at the 0.9 m

WTD, the NO3-N concentrations were higher in comparison with those observed

at the 0.3 and 0.6 depths at the Ames site. At the Ankeny site, similar trends

were observed, the highest concentrations were observed at the 1.1 m WTD as

compared to other four WTDs. The soil samples collected at the time of harvest

showed low values of NO3-N concentrations with statistically significant

differences in the amounts for the different water table treatments.

Corn yields significantly increased as water-table depths lowered from

0.2 to 1.1 m in 1992 and 1993 at the Ankeny site. The highest yields were

observed at the 1.1 m WTD and the lowest yields were observed at the 0.2 m

WTD. The yields were also affected by wet conditions in 1993, and were less

than those observed during 1992 at this site. In the lysimeter plots at Ames,

crop yields were higher under a WTD of 0.9 m as compared to those observed

at 0.3 and 0.6 m WTDs during both study years. Findings of this study show

that, although, the 0.3 WTD is most suitable for groundwater quality control, it

is not appropriate for the highest crop yields are desired. For highest crop

yields a WTD between 0.6 to 1.1 m would be desired. Therefore, the results of

this study conclude that a WTD between 0.6 to 0.9 m would be the Best Water

Table Management Practice for crop productivity and groundwater quality

control.

98

INTRODUCTION

The use of fertilizers and pesticides is an integral part of crop production

in the U.S. and elsewhere. As a result of their use, crop quality and quantity

have improved tremendously in the past few decades, and the cost of food is

less than it would have been otherwise. But the question arises, however,

about the considerable impacts, direct or indirect, on the environment. There is

a growing public awareness over the long term threat to both surface and

groundwater quality from the contaminants derived from these chemicals. The

contamination of surface and groundwater due to the leaching of these

chemicals is becoming a serious threat to human health, wildlife, and the

environment (Prunty and Montgomery, 1991). Particularly, nitrate leaching into

groundwater has become one of the major pollution concerns facing agriculture

today (Hallberg, 1984). Though, it is practically impossible to uproot the

environmental pollution problem caused by fertilizers and pesticides, the growth

of this problem can be decelerated. Improved agricultural water table

management practices can undoubtedly reduce movement of these chemicals

into surface and groundwater systems. Active research are being carried out to

figure out the best possible alternatives, which will not hamper the crop

production system either quantitatively or qualitatively but will reduce their

potential threat to the environment.

99

Studies during the past decade have documented the detrimental effects

of agriculture on water quality (Hallberg, 1989; Schaller and Baily, 1983;

Hamlett et al., 1990). These studies suggest that surface and groundwater

resources are vulnerable to non-point pollution from agricultural activities. NO3-

N concentrations exceeding the 10 mg/L safe drinking water limit, have been

detected in both surface and ground water supplies all across the midwestern

and in other states in the U.S (Hubbard and Sheridan, 1989). The public is

especially concerned, because, the NO3-N concentrations in excess of 10 mg/L

in drinking waters cause serious health problems (such as methemoglobinemia)

in infants who drink this water. Therefore, the problems receiving the most

attention from researchers are the contribution of nutrients to eutrophication of

surface water resources, and the increased levels of NO3-N in the drinking

water. In the past two decades, much work has been done to characterize

nutrient losses through drainage systems and the effect of these losses on

water quality and crop productivity. Several studies conducted in Iowa (Baker

and Johnson, 1981; Kanwar et al., 1985; Kanwar et al., 1988; Kanwar, 1991;

Kanwar and Baker, 1991) have shown that great quantities of NO3-N were

rapidly leaching to shallow groundwater. In 1988 through 1989, a survey of

private rural wells in Iowa found that 18% of the water in all wells had NO3-

N concentrations above the 10 mg/L drinking water standard, over 35% of

the samples from wells less than 50 ft deep had NO3-N concentrations above

100

the standard (Anonymous, 1990). These and other studies across the U.S.,

have reported that NO3-N concentrations in subsurface drainage from row-crop

land usually exceeded the 10-mg/L drinking water standard, and as fertilization

increased, NO3-N concentrations in tile drainage water sometimes approached

100 mg/L (Kanwar, 1991). Fitter and IVIanger (1985) and Lowrance (1981)

reported that NO3-N concentrations in subsurface drainage from agriculturally

influenced areas ranged from 20 to 47 mg/L on coastal plain soils. Skaggs et

al. (1982) found wide variability in NO3-N losses from drainage systems on

muck and clay soils in North Carolina.

Water-table management (WTM) practices, especially controlled drainage

and drainage-subirrigation, have shown potential for inducing denitrification and

reducing the concentration of agricultural chemicals reaching water supplies

(Skaggs and Gilliam, 1981; Gilliam and Skaggs, 1986; Evans and Skaggs,

1985; Evans et al., 1989a; Kalita and Kanwar, 1990; Kanwar and Kalita, 1990;

Kalita and Kanwar, 1993; Wright et al., 1989; Wright, 1990).

During the last few years, several studies have addressed the effects of

WTM practices under different soils, crops, and climatic conditions, such

as, in Iowa (Kanwar, 1990; Kanwar et al., 1991; Kalita and Kanwar, 1993),

Michigan (Belcher and IVIerva, 1991), Ohio (Fausey et al., 1991), North Carolina

(Skaggs et al., 1991), Louisiana (Bengtson et al., 1991), Georgia (Thomas et

al., 1987a; Thomas et al., 1991). The main focus in these studies has been

101

crop yields, economic benefits, and ground water modeling. Few other studies

have been reported in the literature which address the benefits of WTM

practices in relation to reducing nutrient transport in drainage outflow.

Bengtson et al. (1988) studied the influence of subsurface drainage

practices on nitrogen and phosphorus losses on a Commerce clay soil in lower

Mississippi River Valley. Compared to undrained areas, they found that

subsurface drainage reduced surface runoff by 34%, erosion by 30%, and

nitrogen and phosphorus losses by 20 and 36%, respectively. Thomas et al.

(1987b, 1991) measured NO3-N concentrations in shallow subsurface wells and

outlets of a controlled drainage-subirrigation system in a blueberry field in the

Georgia flat-woods. Their results showed that NO3-N concentrations in the

groundwater were less than the 10 mg/L, the maximum contaminant level

(MCL) for public drinking supplies for all outflow samples, although 6% of the

shallow groundwater samples within the field exceeded this limit.

Evans et al. (1989a) presented a compilation of data from North

Carolina supporting the classification of controlled drainage as a best

management practice. Their data showed that controlled drainage reduced both

surface and subsurface nitrogen losses as opposed to uncontrolled drainage.

They found the average loss reduction resulting from drainage control in North

Carolina to be 45%. They concluded that denitrification accounted for the

reduced nitrogen transport from controlled drainage sites in eastern North

102

Carolina where conditions are conducive to denitrification. In another study,

Evans et al. (1989b) reported that controlled drainage reduced the annual

transport of total nitrogen (NO3-N and TKN) at the field edge by 46.5% and

total phosphorus by 44%. In previous studies, similar results have been

reported using simulation methods (Skaggs and Gilliam, 1981; Deal et al.,

1986).

Gilliam et al. (1979) compared nitrate concentration from uncontrolled

and controlled drained fields, and found nearly a 50% reduction under controlled

drainage. While comparing nitrate losses through controlled and conventional

drainage systems, Gilliam and Skaggs (1986) observed 32% reduction in nitrate

losses with controlled drainage as compared to conventional drainage. Bottcher

et al. (1981) measured mean annual sediment, nitrogen, and phosphorus losses

of 94.0, 8.7, and 0.2 kg ha \ respectively, from a subsurface drained area near

Woodburn, Indiana. Their results showed that losses of sediment and nutrient

were reduced by subsurface drainage. They recommended that on a suitable

soil, subsurface drainage may well be preferred as a best management practice

for water quality control. Kladivko et al. (1991) determined field scale NO3-N

losses to subsurface drainage on a low organic matter and poorly structured silt

loam soil under typical agricultural management practices in Indiana. They

found that the annual NO3-N losses in subsurface drain flow ranged from 18 to

70 kg ha \

103

Hubbard et al. (1991) determined transport of NO3-N by surface runoff,

and shallow subsurface flow on a sandy coastal plain soil having plinthic sub

soil material. They observed that most of the NO3-N leached from the upper 30

cm of the root zone within 1 % month after N application. NO3-N

concentrations in surface runoff were very small, with monthly loads not

exceeding 0.3 kg ha'\ However, NO3-N concentrations in shallow groundwater

(at 0.9 to 1.8 m sampling depth) were between 11 to 19 mg/L.

Weight et al. (1992) simulated controlled drainage-subirrigation (CD-SI)

system to investigate the effects of different WTM practices on water quality.

The results from their CD-SI simulations indicate that raising the water table

during the fallow season can reduce nitrogen leaching by increasing

denitrification. It can also increase the amount of nitrogen lost in runoff and in

sediment. They pointed that, water table management using a CD-SI system

increased predicted runoff nitrogen by 340% and increased predicted sediment

nitrogen loss by 118%, it decreased nitrogen leaching by 35.1%. They

concluded that, the predicted total average nitrogen non point source pollution

losses were 17.8% less for the CD-SI system than for the subsurface drainage

system.

Studying effects of WTM on NO3-N transport to shallow groundwater,

Kalita and Kan war (1993) found that nitrate concentration reduced by

maintaining a shallow WTD in the range of 0.3 to 0.6 m. In the unsaturated

104

zone of the soil profile NO3-N concentration as high as 285 nag/L was observed,

but the average NO3-N concentrations in the groundwater never exceeded the

10 mg/L drinking water standard. Drury et al. (1991); and Myrold and Tiedje

(1985), found that the average NO3-N concentrations in groundwater were

generally lower where shallow water table depths were maintained. Present

study was initiated in 1992 on the already established plots with the aim of

developing a better understanding of water-table management practices on crop

yield and groundwater quality, following were the specific objectives of this

study:

1. To evaluate the impacts of different water table depths on the movement of

NO3-N into the groundwater.

2. To determine the residual NO3-N distribution in the soil profile at various

depth.

3. To determine the crop yield responses under various water table depths.

105



The experiments were conducted during growing seasons of 1992 and

1993 on the research farms owned by Iowa State University. The experimental

sites are located near Ames and Ankeny. The soils at Ankeny site are Nicollet

loam, and those at Ames site are predominantly Nicollet loam (Aquic Hapludolls)

in the Clarion Nicollet-Webster soil association. Table 1 lists some of the

physical properties of the soils at these sites.

Experimental setup at the Ames site

Nine experimental plots with surface slopes ranging from 1 to 3% were used

to construct field lysimeters. The lysimeters (each 3 m wide and 6 m long)

were installed during 1986. A 0.2 m wide and 1.2 m deep trench around the

perimeter of each lysimeter was made using a Ditch Witch trencher, and the

bottom of the trench was finished manually with a "tile trench crumber." The

lysimeter soil remained undisturbed during trench the digging process.

Following the digging of the trench, the each lysimeter was completely enclosed

using a plastic barrier (0.25-mm-thick, polyethylene sheet) which extended from

the soil surface to the bottom of the trench. The purpose of this plastic barrier

was to "isolate" the lysimeter from its surroundings and to minimize any lateral

106

subsurface water movement between plots. A corrugated, perforated plastic

tube (lOO-mm diameter) was installed at the bottom of the trench inside the

plastic barrier. A 0.9 m wide ditch was dug to a depth of 1.35 m with a back

hoe mounted on the Ditch Witch trencher to install a 1.5 m tall corrugated

plastic pipe (0.46-m OD X 0.032-m wall) at the corner of each lysimeter. The

bottom of 1.5 m tall sump was located 1.35 below the soil surface, and the top

of the sump was 0.15 m above the soil surface. The two ends of the

perforated plastic tubes at right angles to each other were inserted into the

sump at a height of 0.15 m from the bottom of the sump. The trenches were

back-filled with the excavated soil. In 1989, all lysimeters were enclosed with

another 0.25 mm-thick PVC (poly-vinyl-chloride) flexible liner to a depth of 1.7

m. Each liner encased a square area (9 m X 9 m) with the 3 X 6 m original field

lysimeter located in the center of the enclosed area to ensure that subsurface

water did not move laterally between lysimeters to a depth of 1.7 m. A detailed






mm diameter PVC irrigation pipe. The main water-supply tank (1.6-m high and

1.3-m inside diameter) was raised 2 m from the soil surface on a concrete floor

107

to maintain sufficient hydraulic head for gravity flow of water from the tank to

all lysimeters for maintaining water tables in the plot area. The layout of the

experimental area is shown in Figure 2.

Experimental setup at Ankeny site

In 1988, a dual pipe subirrigation system was installed at this site on a

0.5-ha area with significant natural ground slope of 2.5 percent. The basic

concept of the dual-pipe subirrigation system is illustrated in Figure 3. Shallow

irrigation pipes (51-mm diameter) were installed at a depth of 0.5 to 0.6 m

parallel to and midway between drainage pipes, which were installed at a depth

of 1.2 m. Drainage lines discharged into a sump from which water is pumped

into a storage reservoir. The storage reservoir has a storage capacity of

approximately 900 cubic meters. During irrigation, water is pumped from the

reservoir into a head tank at the top of the plot area, where the water is

distributed to the laterals by a sub-main line equipped with valves to control

pressure in the supply line. Because of the natural ground slope along the

length of the field, water tables could be maintained at various depths below

the soil surface by controlling the subsurface drainage outflows and by

supplying irrigation water through the subirrigation pipes.

108



0.9 m in 1992 and 1993. Each water table depth treatment was replicated





corn roots to develop within 0.3 to 0.9 m soil profile. It took almost three days


1993, the record wet year, there was no problem in bringing the water tables

near the surface but many times water tables had to be lowered using a sump

pump. Observation wells (25-mm diameter and 1.2-m long PVC pipes) were

installed in the center of each lysimeter to monitor water levels.

At the Ankeny site, the average water table depths at five major locations

marked as A, B, C, D, and E (where monitoring devices were installed in the

subirrigation) were maintained at 0.2, 0.3, 0.6, 0.9, and 1.1 m, respectively.

However, the water table depths ranged from 0.05 to 1.2 m during the growing

season. A maximum water-table depth of 1.2 m was observed at the highest

elevation site (north boundary) of the field at the beginning of the 1992 season.

The minimum water table depth of 0.05 m was observed at the lowest elevation

site of the field twice during the growing season of 1992, and most of the time

109

during growing season of 1993 due to heavy rainfall.

Each major location was divided into three subplots, where the


per each depth treatment along the row. Water table depths, however, were

maintained from 49 to 110 DAP in 1992 and from 50 to 98 DAP in 1993. An

elapsed period of about 50 days between planting and start of subirrigation

allowed corn roots to develop uniformly in this field to a depth of 0.2 to 1.1 m.

Groundwater water sampling

Ground water samples were collected using suction tubes and

piezometers on a monthly basis in 1992 and 1993 from both sites for NO3-N

analysis. Solute suction tubes were made by coupling a 200-kPa porous

ceramic cup to the end of a 38-mm diameter PVC pipe. The top ends of these

tubes were sealed with rubber stoppers. At the Ames site, suction tubes were

installed at the center of all nine lysimeters (three replications per treatment) at

0.3, 0.6, 0.9, 1.5, and 2.1 m depths to collect water samples. A vacuum

pump was used to create a vacuum in the solute suction tubes one day before

sample collection, and water samples were collected the following day.

Piezometers were made of 25-mm diameter PVC pipes by making perforations

at the lower end to be placed in the ground. The lower ends were sealed with

rubber stoppers. The piezometers were installed in each lysimeter plot at 1.2,

110

1.8, and 2.4 m depths to collect groundwater samples and to monitor

piezometric heads. The piezometers were pumped out one day before sampling,

and water samples were collected on the following day. All water samples

collected; were then preserved in a cold chamber at 4 °C until analysis.

At the Ankeny site, solute suction tubes were installed at 0.9, 1.5, and

2.1 m depths at three locations (B, C, and D locations as shown in Figure 3)

with three replications at each location. Whereas, piezometers were installed at

three locations (A, C, E locations as shown in Figure 3) at 1.2, 1.8, 2.4 m

depths with three replications per location. Similar procedures (those at Ames

site) were followed to collect water samples.

Soil sampling and analysis methods

Soil samples at two experimental sites (Ankeny and Ames) were collected

from the middle quarter of each plot at 0.3, 0.6, 0.9, 1.2, 1.5, and 1.8 m

depths from the soil surface. The sampling locations in a plot were spaced

across most of this area and were consistent from plot to plot. All cores were

taken from row centers. After cores were removed, the resulting man-made

macropores in the soil were back filled with bentonite clay granules. In 1992, a

set of soil samples was collected on June 11,34 days after planting and N

fertilization. Another set of soil samples was collected in late summer on

October 31 at the time of harvest. In 1993, a set of soil samples was collected

I l l

on May 4,16 days before planting and N fertilization, and another set of soil

samples was collected in late summer on October 19 at the time of harvest at

both sites.

To collect soil samples, a zero-contamination hand sampler was pushed

into the soil, each core slide into a clean liner made of PETG (polyethlene

terephthalate, glycol-modified) plastic to protect the sample from contamination.

The samples were frozen promptly after collection. The cores were sectioned

into a set of 6 samples representing the following depths: 0-0.15, 0.15-0.3,

0.3-0.6, 0.6-0.9, 0.9-1.2, and 1.2-1.5 m. Three cores per treatment were

collected and were combined to yield a single composite sample for each

treatment at each soil sampling depth. The samples were wrapped in aluminum

foil, then over wrapped with a labelled polyethylene bag. The foil protected the

soil from any possible contamination by plasticizer in the plastic. The samples

were stored frozen until they were needed for laboratory analysis.

Soil nitrate extraction and analysis

A representative soil sample was used for soil moisture content. This

was done by weighing a subsample of soil, drying it at 104 "C for 24 hr,

reweighing the cooled sample, and calculating the soil moisture as the

percentage on a dry soil basis. For NO3-N analysis, a 100 g sample of wet soil

was mixed with 435 g of 2N (normal) KCI (potassium chloride). The mixture

112

was shaken for 65 minutes, then allowed to settle for overnight. The following

day solvent was filtered and poured into 100 ml test tube. The NO3-N in the

solvent was analyzed with a lachat Model AE ion analyzer. The analyzer first

converted the colorless NO3-N in the filtrate to a pink water soluble dye, and

then measured the color intensity by spectrophotometry. The color intensity

was proportional to the NO3-N concentration. Results are reported as mg/L

NO3-N on a dry soil basis.

Plant culture

The corn variety Pioneer 3379 was planted at both sites (with no till

practices). In 1992, seeds were planted on May 8, while, they were planted on

May 21 in 1993 at both sites. The plant population was 67,000 per ha with a

row-to-row spacing of 0.75 m and seed-to-seed distance of 0.2 m at each site.

Plants were hand harvested on November 6 in 1992 in the lysimeter plots at

Ames site, and were harvested using a combine on the same day at Ankeny. In

1993, the plants were hand harvested on October 21 in the lysimeter plots at

Ames site, and were harvested on October 31 using a combine at Ankeny.

Grain yield was determined by harvesting and shelling all the heads in each plot.

The moisture content of the grain was determined and all yields were adjusted

to 15.5 percent moisture content basis (wet basis). Urea nitrogen [N = (46-0-0)

HgNCONHg], phosphorus [P = (0-43-0) PgOg], and potassium [K = (0-0-54) KgO]

113

fertilizers were surface applied at planting time at both sites every year at the

rate of 200 kg-N ha'\ 60 kg ha'\ and 40 kg ha'\ respectively. Herbicides

atrazine and lasso were applied at the rate of 2.2 kg ha'\ in both years at the

Ankeny and Ames sites.

114

RESULTS AND DISCUSSIONS

The 1992 season was relatively dry as compared to 1993 season. The

rainfall between May through October totalled 475 mm and 427 mm at Ames

and Ankeny sites, respectively, during 1992. The 1993 season was an

extremely wet, with rainfall totals of 1199 mm and 1127 at the Ames and

Ankeny sites, respectively, for May through October. Monthly precipitation

patterns for the Ames and Ankeny sites during 1992 and 1993 are presented in

Table 2.

NO3-N concentrations in piezometer water samples at the Ankeny site

The average concentrations as a function of DAP and WTD in the

subirrigation field at Ankeny site are shown in Figure 4. The figure shows that

the NO3-N concentrations in groundwater samples were different at different

water table depths during the growing season of 1992. The 0.2 m depth

a l w a y s s h o w e d l o w e r N O 3 - N c o n c e n t r a t i o n s i n c o m p a r i s o n w i t h 0 . 6 a n d 1 . 1 m

depths. NO3-N concentration decreased with time under all WTDs. In the early

part of growing season of 1992, the higher NO3-N concentrations at 1.2, 1.8,

and 2.4 m piezometer depths were observed than in the later part of the

growing season. The higher concentrations are associated with greater

amounts of NO3-N available in the soil profile due to residual NO3-N and applied

115

N fertilizers. Therefore, higher NO3-N concentrations could be anticipated.

Figure 4 connpares the NO3-N concentrations at 1.2, 1.8, and 2.4 m piezometer

water sampling depths, under 0.2, 0.6, and 1.1m WTDs. Figure shows that

the NO3-N concentrations generally decreased with increased sampling depth in

the soil profile under all WTDs. The NO3-N concentrations at the 1.2 m

piezometer depth showed higher concentrations than did the 1.8 and 2.4 m

piezometer depths. The NO3-N concentrations decreased with time, however,

at all three piezometer depths in the soil profile. At the 1.2 piezometer depth,

concentrations of NO3-N in groundwater samples varied from 10.3 to 1.6, 11.7

to 4.5, and 23.8 to 4.9 mg/L for 0.2, 0.6, and 1.1 m WTDs, respectively.

Similarly, NO3-N varied from 7.5 to 1.6, 9.9 to 3.6, and 16.9 to 5.2 mg/L at 1.8

m piezometer depth, and 3.7 to 1.6, 7 to 3.5, and 8.5 to 3.3 mg/L at 2.4 m

piezometer depth for 0.2, 0.6, and 1.1m WTDs, respectively.

Figure 4 also shows the average concentrations of NO3-N in piezometer

water samples in 1993 as a function of WTD and DAP. Similar trends in NO3-N

concentrations were observed in 1993 in comparison with those observed in

1992. However, the highest NO3-N concentrations of 9.4, 11.7, 23.8 mg/L at

1.2 m piezometer depth in the soil profile were observed on 48 DAP (2 days

before the water table treatments began). The NO3-N concentrations were

significantly reduced after water table treatments were initiated. These

concentrations were different at different WTDs, as well as, were different for

116

various piezometer sampling depths in the soil profile. The NO3-N

concentrations generally decreased with increasing soil depth under all three

WTDs. These concentrations also decreased with time, significantly higher

NO3-N concentrations were observed during the early part of the growing

season. Heavy rainfalls during the early part of the growing season of 1993

perhaps caused NO3-N movement from the surface layer to the deeper depths

immediately after N application. Figure 4 compares the NO3-N concentrations at

different piezometer depths. Higher NO3-N concentrations were observed at the

1.2 m piezometer depths than at 1.8 and 2.4 m depths. These values ranged

from 31 to 2, 40.9 to 2.7, and 103 to 6.6 mg/L at the 1.2 m piezometer depth

under 0.2, 0.6, and 1.1 m WTDs, respectively. NO3-N concentrations ranged '

from 31 to 2.8, 32.2 to 3.1, and 30.6 to 3 mg/L at 1.8 m piezometer depth,

8.6 to 0.4, 17.8 to 0.1, and 27.5 to 1.4 mg/L at 2.4 m piezometer depth under

0.2, 0.6, and 1.1m WTDs, respectively. These results indicate that average

NO3-N concentrations were lower at the 0.2 m WTD than at 0.6 and 1.1 m

WTDs at all piezometer depths during 1992 and 1993 seasons.

NO3-N concentrations In suction tube water samples at the Ankeny site

Samples were taken at 0.9, 1.5, and 2.1 m suction tube depths in the

soil profile under 0.3, 0.6, and 0.9 m WTDs. The NO3-N concentration data as

a function of DAP and WTD are plotted in Figure 5 for subirrigation field at

117

Ankeny site during 1992 and 1993. The data presented in Figure 5 show that

the highest NO3-N concentrations of 6.4, 11, and 10.5 mg/L were observed in

the water samples collected at the 0.9 m soil depth. These concentrations

were observed on 38 DAP in 1992 and water table depths were under natural

conditions. The NO3-N concentrations significantly decreased after WTDs were

raised which shows the effect of water table depths on the movement of NO3-N

in the soil profile. Figure 5 shows that, the trends in NO3-N concentrations

were similar to those in piezometer water samples. The 0.3 m WTD showed

lower NO3-N concentrations as compared with 0.6 m and 0.9 m depths for all

suction tube sampling depths. Figure 5 also shows that NO3-N concentrations

decreased with increasing depth in the soil profile under all water table

treatments depths. NO3-N concentrations at the 0.9 m suction tube depth

ranged from 6.4 to 1.3, 11 to 4.4, and 10.5 to 4.6 mg/L for 0.3, 0.6, and 0.9

m WTDs, respectively. Also, similar trends were observed at the 1.5 and 2.1 m

suction tube depths. The NO3-N concentrations ranged from 6.4 to 0.2, 5.8 to

1, and 7.3 to 1.9 mg/L at the 1.5 m, and from 7.2 to 1.6, 6.2 to 1.5, and 7.1

to 0.1 mg/L at the 2.1 m suction tube depth in the soil profile for 0.3, 0.6, 0.9

m WTDs, respectively. Although, data in Figure 5 indicated an increase In NO3-

N concentrations at the 0.9 m suction tube depth on 168 DAP (at the end of

season) under all WTDs, but showed different responses with WTDs.

Figure 5 also shows the relationship between average NO3-N

118

concentrations at various suction tube depths as function of WTD and DAP for

subirrigation field at Ankeny during 1993. It can be seen in this figure that the

highest NO3-N concentrations of 19.6, 49.9 and 50 mg/L were observed on 48

DAP (2 days before WTD treatment began), at the 0.9 m suction tube depth,

for 0.3, 0.6, and 0.9 m WTDs, respectively. Heavy rainfalls in 1993 caused

leaching of residual and applied N fertilizer from surface layer to deeper depths,

therefore, higher amounts be anticipated. Also, WTD treatments were not

started at this point, which in turn, would have helped in reducing the

downward leaching of NO3-N. Although, rainfall continued throughout the

growing season, the NO3-N concentrations were affected by WTDs. The higher

NO3-N concentrations were observed at the 0.9 m WTD as compared with 0.3

and 0.6 m WTDs. The NO3-N concentrations for the rest of the growing season

(after WTD treatments were started) ranged between 3.3 to 0.5, 4.7 to 1.5,

and 6.3 to 3.5 mg/L at the 0.9 m suction tube depth for 0.3, 0.6, and 0,9 m

WTDs, respectively. NO3-N concentrations ranged from 1.7 to 0.4, 2.2 to 1.6,

and 3.4 to 2.6 mg/L at the 1.5 m suction tube depth, and from 1.4 to 0.3, 2.1

to 1.5, and 2.6 to 1.5 mg/L at the 2.1 m suction tube depth, under 0.3, 0.6,

0.9 m WTDs, respectively.

119

NO3-N concentrations in piezometer water samples at the Ames site

The data for Ames site were plotted differently than those at the Ankeny

site only to compare the trends of NO3-N concentration by depth and for each

sampling day as a function of WTD. This way a clear differences between WTD

treatments for any given sampling day could be monitored. The average NO3-N

concentrations as a function of WTD and piezometer depth for each sampling

DAP for the growing season of 1992 are plotted in Figure 6. The highest NO3-N

concentrations were observed In the water samples collected on 39 DAP at all

piezometer depths. Those ranged from 95.5 to 212, 21.6 to 125.7, and 7.2 to

54.8 mg/L at 1.2, 1.8, and 2.4 m piezometer depths, respectively, in the soil

profile. These samples were collected 10 days before the actual water table

treatments began. Figure 6 shows that NO3-N concentrations significantly

decreased after WTDs were raised. Those ranged from 18.1 to 1.4, 19.5 to

1.9, and 27.5 to 5.9 mg/L at the 1.2 piezometer depth after WTDs were raised

to 0.3, 0.6, 0.9 m, respectively. NO3-N concentrations ranged from 3.9 to 0.4,

7.7 to 2.5, and 25.4 to 4 mg/L at the 1.8 m piezometer depth, and ranged from

6.2 to 2.6, 19.3 to 21.1, and 19.5 to 3.1 mg/L at the 2.4 m piezometer depth

under 0.3, 0.6, and 0.9 m WTDs, respectively. Although, there was a

decreasing trend in average NO3-N concentrations in groundwater samples with

time, a slight increase in the NO3-N concentrations in groundwater samples

collected at the 1.8 and 2.4 m piezometer depths was observed at the end of

120

the season (on 169 DAP), under all three WTDs. However, at the 1.2 m

piezometer depth samples were not available for analysis, therefore, no definite

conclusion could be made for this piezometer depth for 169 DAP. Figure 6 also

compares the NO3-N concentrations in groundwater samples by depth under all

WTDs. The data show that the NO3-N concentrations decreased with increased

piezometer depth in the soil profile. The higher concentrations were observed in

the water samples collected at the 1.2 m piezometer depth as compared with

the 1.8 and 2.4 m piezometer depths.

The data on average NO3-N concentrations, for 1993, as a function of

WTD are presented in Figure 7. This figure shows distinct trend of decreasing

NOgrN concentrations in groundwater samples with time at all piezometer

depths during the growing season. The average concentrations decreased with

increased sampling depths, and 1.2 m piezometer depth, most of the time,

showed lower concentrations as compared to 1.8 and 2.4 m piezometer depths.

Figure 7 also shows that the highest NO3-N concentrations were observed at all

sampling depths on 48 DAP (2 days before water treatment began), and those

significantly decreased after water table treatments were initiated, which shows

the effects of water table depth practices. The average NO3-N concentrations

in groundwater at the 1.2 m piezometer depth decreased from 27.8 to 0.8,

20.8 to 2.6 and 53.6 to 3.9 mg/L under 0.3, 0.6, 0.9 m WTD, respectively.

Similarly, NO3-N concentrations decreased from 18.6 to 0.8, 18.9 to 1, and

121

38.3 to 3.9 mg/L at the 1.8 m piezometer depth, and decreased from 15.7 to

0.3, 12.6 to 0.6, and 34.1 to 1.8 mg/L at the 2.4 m piezometer depth under

0.3, 0.6, and 0.9 WTDs, respectively.

NO3-N concentrations in suction tube water samples at the Ames site

The average NO3-N concentration in groundwater at 0.3, 0.6, 0.9, 1.5,

and 2.1 m suction tube depth as a function of WTD, for 1992, in lysimeter plots

at the Ames site are presented in Figure 8. Figure shows that NO3-N

concentrations under the 0.3 m WTD were lower than those observed at 0.6

and 0.9 m WTDs, almost during the entire growing season. Comparison

between suction tube sampling depths shows that the NO3-N concentrations

decreased with the increased suction tube depth in the soil profile. These

concentrations decreased from 30.3 to 3.2 mg/L at the 0.3 m suction tube

depth with a WTD of 0.3 m, after water table was raised, and those decreased

from 63.8 to 6.7 mg/L, and from 115.3 to 5.1 mg/L with 0.6 and 0.9 m WTDs,

respectively, at the same suction tube depths. Similar trends in NO3-N

concentrations decrease at 0.6, 0.9, 1.5, and 2.1 m suction tube depths were

observed under all three water table depths. Regardless of suction tube

sampling depth, the NO3-N concentrations decreased with time under 0.3, 0.6,

0.9 m WTDs, and significant differences between WTD treatments were

observed. However, a slight increase in NO3-N concentrations at the end of

122

season on 169 DAP was observed at the 0.3 and 0.9 m suction tube sampling

depth under 0.6 and 0.9 m WTD.

The data on NO3-N concentration as a function of WTD and water

sampling depths in the soil profile for 1993 are shown In Figure 9. Figure

shows that NO3-N concentrations decreased with increasing suction tube

sampling depth, and also decreased with time. The highest NO3-N

concentration of 67.1, 95.5, 40.9 mg/L on 48 DAP were observed at 0.3, 0.6,

and 0.9 m suction tube depths, respectively, with 0.9 m WTD. However, those

under 0.3 m WTD were 21.6, 17.5, and 10.1 mg/L at 0.3, 0.6, and 0.9 suction

tube depths, respectively, and were 16, 5.1, 4.7 mg/L under 0.6 m WTD at

0.3, 0.6, and 0.9 m suction tube depths, respectively. Heavy rainfalls during

the early part of the growing season of 1993 caused leaching of residual and

applied N fertilizer from the surface layer to deeper depths, therefore, higher

amounts of NO3-N could be anticipated. The average NO3-N concentrations in

groundwater at all suction tube depths, after 48 DAP, were always less than 10

mg/L under all WTDs for the rest of the growing season.

The analysis of the data at both sites (Ankeny and Ames) shows that

NO3-N concentration were lower at the 0.3 m (shallow) WTD as compared to

0.6, 0.9, and 1.1 m (deep) WTDs. These results are in agreement with the

previous reports by Kalita and Kan war (1992). They found that nitrate

concentration were reduced by maintaining a shallow water table depths in the

123

range of 0.3 to 0.6 m. In the unsaturated zone of the soil profile NO3-N

concentration as high as 285 mg/L was observed, but the average NO3-N

concentrations in the groundwater never exceeded the 10 mg/L drinking water

standard. They hypothized that the reduction of NO3-N concentration at

shallow water table depths was possibly enhanced by increased denitrification.

In the saturated zone where air in the pore spaces may be replaced by water,

the bacterial reduction of NO3-N to nitrogen gas may have been greatly

enhanced. Myrold and Tiedje (1985) also stated that under saturated soil

conditions, the denitrification capacity could be significantly increased.

Distribution of NO3-N in the soil profile

Table 3 shows the effect of WTDs on average seasonal residual soil NO3-

N concentrations as a function of sampling depth in the soil profile at the

Ankeny and Ames sites. The table shows the NO3-N concentrations in the soil

profile on two sampling dates during the 1992 and 1993 seasons. In 1992,

higher NO3-N concentrations were observed at both sites in the soil samples

collected during the early part of the growing season. These soil samples were

collected on 34 DAP, therefore, higher concentrations due to cumulative NO3-N

(applied plus residual) could be anticipated. Data in this table show that NO3-N

concentrations to be seem concentrated in the upper 0,15 to 0.6 m of the soil

profile and that the NO3-N levels decreased with the increased soil depth under

124

all water table treatments. However, at the 0.9 m depth, NO3-N concentrations

were higher in comparison with those observed at 0.3 and 0.6 depths at the

Ames site. At the Ankeny site, similar trends were observed, the highest

concentrations were observed at the 1.1m WTD as compared to other four

WTDs. The soil samples collected at the time of harvest showed low values of

NO3-N concentrations with statistically significant differences in the amounts for

the different water table treatments.

In 1993, the samples were collected before N fertilizer application, and at

harvesting, therefore, the data in Table 3 reflect the average residual NO3-N

concentrations. The NO3-N concentrations were significantly reduced during

this year. Precipitation received in 1993 was sufficient to flush out some of the

cumulative NO3-N amounts into the drainage as well as into surface runoff

waters. However the higher NO3-N concentrations were concentrated in the

upper 0.3 m of soil depth under all WTDs. This trend decreased with increasing

soil depth. The top soil layer lost accumulated NO3-N which moved to deeper

depths in the soil profile. Although, low values of NO3-N concentrations were

observed at all sampling depths in 1993, the 0.9 m WTD depth gave

comparatively higher NO3-N levels than did other WTDs at the Ames site. An

opposite trend was observed at Ankeny site, and higher concentrations were

observed at 0.2 m WTD In comparison with other four WTDs. Data In Table 3

shows that NO3-N accumulated more in the upper soil profile (top 0.15 to 0.6 m

125

depth) and gradually decreased with depth. The trend of NO3-N concentrations

was influenced very much by climatic variations. A wet year (1993) gave lower

amounts of NO3-N under all WTDs implicating that more NO3-N was either

utilized by the plants or flushed out through the drainage or in surface runoff.

Figure 10 shows the best fit regression lines comparing residual NO3-N In

the soil profile under different WTD treatments at the Ankeny and Ames sites.

Regression equations and their R^ values are shown in this figure. Results

indicate that WTD treatments significantly affected the residual NO3-N

distribution in the soil profile at all sampling depths. The difference is quite

significant for the top 0.3 m depth and this difference gradually tends to

approach a constant value at greater depths. The best fit curves (Fig 10) show

that NO3-N levels in the soil profile exponentially decreased with increasing

sampling depth in the soil profile at both sites. The coefficient of correlation R^

ranged between 0.58 to 0.95 at the Ankeny site and it ranged between 0.88

and 0.97 for the Ames site under different WTDs.

Figure 11 shows the best fit regression lines comparing residual NO3-N in

the soil profile under different WTD treatments using pooled data observed at

the Ankeny and Ames sites. Regression equations and their R^ values are

shown in the figure. Results indicate that WTD treatments significantly affected

the residual NO3-N distribution in the soil profile at all sampling depths. The

difference is quite significant for the top 0.3 m depth and this difference

126

gradually tends to approach a constant value at greater depths. The best fit

curves (Fig 11) show that NO3-N levels in the soil profile exponentially

decreased with increasing sampling depth in the soil profile. The correlation

coefficient ranged between 0.79 to 0.98 with pooled data. These values

were very high as compared to those observed for the individual site.

Crop yield

Corn yields for 1992, and 1993 for the Ankeny and Ames sites are


from the plots under the 0.9 and 1.1 m depths, and the lowest yield was

obtained from the plots under the 0.2 m depth in 1992. In 1993, however, the

1.1 m depth gave the highest, and the 0.2 m depth gave the lowest yield. At

the 0.2 m depth crop yield was very poor in both years. High rainfalls caused

almost surface flooding conditions for a few days during 1992, and almost all

the time during the growing season of 1993, at the 0.2 m depth, which in turn




higher yields than did the 0.6 m depth for both years.



127



However, the means were significantly different between 0.2, 0.9, and 1.1m


between 0.3, 0.6, 0.9, and 1.1 m WTDs during 1993.






corn yields between two years were observed.







128

CONCLUSIONS

Field experiments were conducted to study the effects of water table

depths on groundwater quality. Average NO3-N concentrations in groundwater

as affected by different WTDs were measured in Iowa for two growing seasons

(1992 and 1993). Data for 1992 and 1993 were collected at two research

sites owned by the Iowa State University. These two research sites are located

near the Ankeny and Ames. This study resulted in the following conclusions:

1. The average NO3-N concentrations in groundwater were reduced by

maintaining WTDs between 0.3 to 0.6 m during the growing season. The

average concentrations in groundwater generally decreased with increased

depth and time during the growing seasons. The highest NO3-N concentrations

in groundwater were observed before the water table treatments were initiated.

However, NO3-N concentrations were significantly reduced after WTD

treatments started and in most cases these concentrations in groundwater were

less than 10 mg/L under 0.3 m WTD.

2. Generally decreasing trends in groundwater NO3-N concentrations with

increasing sampling depths under two sampling methods were consistent in

both study years at both experimental sites.

3. The residual soil NO3-N concentrations seem to be concentrated in the upper

0.15 to 0.6 m of the soil profile and the NO3-N levels decreased with the

129

increased soil depth under all water table treatments. However, at the 0.9 m

WTD, the NO3-N concentrations were higher as compared to those observed at

the 0.3 and 0.6 depths at the Ames site. At the Ankeny site, similar trends

were observed, the highest concentrations were observed at the 1.1m WTD as

compared to other four WTDs. The soil samples collected at the time of harvest

showed low values of NO3-N concentrations with statistically significant

differences in the amounts for the different water table treatments.

4. At the Ankeny site, the highest corn yield was obtained from the plots under

the 0.9 and 1.1m WTDs, and the lowest yield was obtained from the plots

under the 0.2 m WTD in 1992. In 1993, however, the 1.1 m WTD gave the

highest, and the 0.2 m WTD gave the lowest yield. At the 0.2 m depth crop

yield was very poor in both years at this site. At the Ames site, the highest

yield was obtained from the plots under a WTD of 0.9 m, and the lowest yield

was obtained from the plots under a WTD of 0.3 m during both study years.

5. Findings of this study show that, although, the 0.3 WTD is most suitable for

groundwater quality control, it is not appropriate if the highest crop yields are

desired. The best water table management practice for best crop yields and

groundwater quality control would be somewhere between 0.6 to 1.1 m WTD

for Iowa's Nicollet loam soils.


Depth Sand m %

Silt %

Clay %

pH Bulk density Mg m'3

Organic matter %


0.15 29.5 44.3 26.2 5.9 1.25 3.2

0.30 31.5 40.4 28.1 6.6 1.49 2.3

0.60 38.6 34.1 27.3 7.1 1.46 1.5

Nicollet loam soil at the Ames site"

0.15 31.3 43.6 25.1 7.3 1.20 4.3

0.30 31.2 42.8 26.0 6.7 1.30 4.0

0.60 27.7 42.2 30.1 6.9 1.35 2.9

^Charkhabi (1990); "Kanwar et al. (1988)

131

Table 2. Monthly rainfall (mm) at the Ames and Ankeny during 1992 and 1993

Ames Ankeny

Month 1992 1993 1992 1993

Jan 30.2 20.3 22.6 27.4

Feb 38.4 19.8 35.6 31.5

March 62.7 82.8 70.4 73.2

April 98.6 65.0 85.3 74.4

May 26.4 185.7 26.7 198.6

June 14.7 193.8 38.4 145.5

July 259.3 416.3 232.7 282.7

August 56.6 263.9 29.5 326.9

Sept 103.6 101.3 93.2 130.6

Oct 13.7 38.4 6.4 42.2

Nov 117.1 28.2 85.6 3.8

Dec 46.2 46.2

Total 867.7 1415.5 772.4 1336.8

132

Table 3. NOg-N (mg/L) distribution pattern in the soil profile under different water table treatnnents at the Ankeny and Ames sites.

Water Table Depth

Site Sampling Date

Ankeny 06-11-92

10-31-92

05-04-93

10-19-93

Ames 06-11-92

10-31-92

05-04-93

Depth 1.1 m m

0.15 23.36 0.30 72.41 0.60 18.36 0.90 7.60 1.20 6.71 1.50 5.04 0.15 0.19 0.30 28.83 0.60 18.08 0.90 3.21 1.20 1.72 1.50 0.25 0.15 16.63 0.30 7.15 0.60 3.63 0.90 1.06 1.20 0.89 1.50 0.97 0.15 0.86 0.30 0.73 0.60 0.31 0.90 0.46 1.20 0.91 1.50 0.95

0.15 0.30 0 . 6 0 0.90 1 . 2 0 1.50 0.15 0.30 0 . 6 0 0.90 1 . 2 0 1.50 0.15 0.30 0 . 6 0 0.90

0.9 0.6 m m

10.68 11.05 7.03 6.60 4.44 3.85 4.53 3.78 2.67 3.76 2.15 3.59 0.20 0.05 46.37 13.98 8.06 1.24 1.02 0.26 0.61 0.51 0.34 0.26 8.90 10.43 13.58 3.88 3.12 1.57 1.06 0.86 0.60 0.70 2.89 0.37 0.59 0.93 0.80 0.60 0.37 0.44 0.51 1.61 0.71 1.32 0.53 1.03

76.82 93.32 40.45 21.52 23.80 16.20 11.58 11.75 10.07 8.19

5.22 8.21 12.49 11.25 10.80 8.31 5.46 5.04 4.15 1.83 1.42 0.59 0.25 0.29 17.17 18.31 6.37 4.22 6.31 4.31 3.99 2.56

0.3 0.2 m m

8.18 8.39 4.62 2.81 2.61 1.72 1.94 1.34 1.99 1.59 1.86 2.23 0.67 0.05 8.92 7.02 0.72 0.89 0.30 0.39 0.20 0.34 0.24 0.15 14.50 9.10 2.81 2.35 1.37 1.23 0.82 0.69 0.45 0.54 0.05 0.63 0.78 1.27 0.54 0.78 0.61 2.31 0.98 2.00 0.71 1.55 0.77 1.26

31.90 27.35 15.78 15.31

7.82 6 .36 7.57 6.71 3.03 3.07 0.48 0.14 12.18 3.64 4.02 1.35

133

Table 3 (continued)

1.20 1.80 L .08 0.85 1.50 1.43 0, .94 0.46

10-19-93 0.15 0.33 0, .47 0.38 0.30 8.71 2, ,19 1.42 0.60 4.05 2, ,01 1.13 0.90 3.14 1. ,30 0.73 1.20 1.25 0. 68 0.53 1.50 0.50 0. 53 0.34

134

Table 4. Corn yield kg/ha as a function of water table depth at Ames and Ankeny sites for 1992 and 1993.

WTD, m Ames Ankeny

Year 1992

0.2

CO

CO

o

0.3 5216' 8400'

0.6 6970'" 8348'

0.9 8732" 9280'

1.1 9293'

Year 1993

0.2 3671'

0.3 4930' 5226'

0.6 7914" 5150'"

0.9 8860" 6960"'

1.1 7399"'


Iirigallon

S3 Corf ugalcd HmIk lump CacmOO) Cofiygatcd flailicTilt

PVCricBibU Lintr

Sump f ump

w en


i

136

City of Ames Main Water Supply Line

Water Meter Pit —

Hydrant ^3—Water Storage Tank Xy/ (1.3 m diameter,

1.6 m height)

L.

a 0

r" s at


0c-

T


Ô0

Co-

Co

I I

0 lo

•T"

0 lo

.1..

0 0

Mc.

1 I

•-1— Irrigation Lateral

• Water Meter

o,o

0.25 mm Plastic Barrier (1.2 m deep)

I 3 m .

9m

36 m

O Corrugated Plastic Sump ———0,25 mm PVC Flexible Liner

o o Observation Wells (1.7 m deep)

Figure 2. Layout of the experimental plots at the Ames site (after Kalita and Kanwar, 1992)

Reservoir

Irrigation Lines!

Drainage

Lines

Return

Drainage Pump

Figure 3 A schematic sketch of the dual-pipe subirrigation system at the Ankeny site (after Kalita and Kanwar, 1992)

35 30

25

20

IS

10

5

0

30

25

20

15

10

S

0

30

25

20

15

10

5

0

At 1.2 m depth from soil surfact

J J J J • WTD-0.2n<

Q WTD-0.6m

• WTD-1.1 m

jLi (1992)

At 1.8 m depth from sofl surf»c«

a J . 1

At 2.4 m depth from soil surface

<NS - no wxtcr sample availal

^ lÉ d d b TI

sample available for analysis)

38 54 82 112 140 168

Days after planting

E »

I -I " Z 10 S s

At 1.2 m depth from soi surface

• WTD-0.2m

IS WTD.0.6m • WTD-I.I m

I



J 68 88 116 144

Days after planting

4. Nitrate-N concentration in piezometer water samples at Ankeny site, 92, 93

14

12

10

8

6

4

2

0 14

12

10

8

6

4

2 0

14

12

10

S

6

4

2

0

At 0.9 m depth from sofl suf1«cc

At I.SmdtpttifromsoiisurfKC


• WT0-0.3m Q WTO-O.6m B WTD " 0.9 m

1 m

NS NS

38 54 82 112 140 168

Days after planting

14

12

10

8

! 2

0

14

E 12 c o 10

S 10

c 8 o 8

u c 6 o 6 o Z 4

o s

2

A z 0

14

12

10

6

4

2

0

49.9 SO

At 0.9 m depth from soil surf

Ax 1.5 m depth from soM surfj


(1993)

• WTD«0.3m

tS WTD-0.6m • WTD-O^m

68 88 116

Days after planting

5. Nitrate-N concentration in suction tube samples at Ankeny site, 92, 93 {NS - no water sample available for analysis)

DAP - 55

DAP - 61

E « 25 g

jL 20

'•20 1.80 2.40

Depth below soil surface, m

§ O 10

i : 25

20

15

10

5

0

• WTD»0.3m

E3 WTD-OGm

• WTD«0.9m

1

1.20 1.80 2.40


Fig. 6. Nitrate-N concentration in piezometer water samples at Ames site, 1992.

120

20

IS

10

S

0 120

20

IS

10

S

0

15

10

S

0

115.3

DAP « 55

DAP - 81

0.60 0.90 1.50


IS _ • WTD-0.3m

ES WTD-0.6m

10 - • WTD-0 j m

as

{"

L

à A A

J -iil -Bl Jh

0.60 0.90 1.50


7. Nitrate-N concentration in suction tube samples at Ames site, 1992 (NS - no water sample available for analysis)

I

O) E

i

1 1

48 DAP

WTD«0.3m 116 DAP

a a WTO«0.6m

WrD»0.9m

is 6

O *

S 2

144 DAP

to

Depth below soil surface, m Depth below soil surface, m

Figure 8. Nitrate-N concentration in piezometer water samples at Ames site, 1993

60

10

8

6

4

2

0

8

6

4

2

0

8

6

4

2

0

67.1 g

a^M .DH 409 a » iB

48 DAP

WTD-0.3m

IS WTD-0.6m

WTD-0.9m

0.30 0.60 0.90 1.50 2.10


i: 1.

1.

WTD-0.3fn

IS3 WTO-O.6m

WTD«0.9fn

iJi -ji ̂0.60 0.90 1.50 2.10


9. Nitrate-N concentration in suction tube samples at Ames site, 1993

144

NItrate-N, ppm (dry soil) 10 15

o- Ankeny site

WTD • 0.3 m

WTD - 0.3 m

• • I A • • I

WTD - 0.6 m

WTD • 0.9 m

NOy N - 04.49 MP I" 1.13 D)

NOy N • 03.67 MP

NO 3* N - 05.31 MP

(. 1.61 01

NOy N « 60.85 MP (• 3.84 0)

M * NOg. N - 38.24 MP

R:

0.91

0.63

Ames site

WTD - 0.3 m

M • ÛH • • I

WTD " 0.8 m

# « # # » # # «

NOj- N - 07.07 MP (• 2.12 01

NOg. N - 09.68 MP .(•2.11 Dl

NOg.N - 18.07 Mp' I-1.14 0)

0.97

Figure 10. Residual Nitrate-N pattern in the soil profile as a function of

water table depth at the Ankeny and Ames sites

Nitrate-N, ppm (dry soil basis)

10 20 30 25 0

0.2

0.4

0.6

0.8 1-1.1213 01 WTD = 0.2 m NO3-N = 04.16 exp 0.81

1 (-1.4855 01 NO 3. N = 10.77 exp*' 0.95 WTD = 0.3 m

I-1.5492 D) NO3-N = 14.60 up 0.88 WTD = 0.6 m

(. 1.8943 0) 0.98 NOy N = 25.96 exp ̂WTD = 03m

1.4 I- 2.0081 01 0.79 NO3- N = 24.81 exp'' WTD = 1.1 m

1.6

Figure 11. Residual nitrate-N distribution pattern as a function of sampling depth in the soil profile under different WTDs (using pooled data for two sites)

146

PAPER III. MOVEMENT OF PESTICIDES INTO SHALLOW GROUNDWATER

AS AFFECTED BY WATER TABLE MANAGEMENT

147

ABSTRACT

Field experiments were conducted at two research farms of Iowa State

University near Ames and Ankeny to evaluate the effects of water table depths

(WTD) practices on the movement of two surface applied herbicides, atrazine

and alachlor, into the groundwater. Data were collected by using piezometers

and suction tubes during the growing seasons of 1992 and 1993 at these

research farms, and average concentrations of atrazine and alachlor in

groundwater (as affected by different WTDs) were measured.

The average atrazine and alachlor concentrations in groundwater were

reduced by maintaining shallow WTDs between 0.3 to 0.6 m during the two

growing seasons. The average herbicide concentrations in groundwater

generally decreased with increased sampling depth and time. It was also

observed that alachlor concentrations were lower than those of atrazine under

similar WTD treatments. Alachlor was not detected in many samples, however,

atrazine was detected in almost all water samples. However, atrazine

concentrations were significantly reduced after WTD treatments started which

shows a positive influence of WTD practices in reducing pesticide

concentrations.

Regression analysis show that atrazine concentrations in the soil profile

linearly decreased with increased sampling depths under all WTD treatments.

148

However, atrazine concentrations were always higher under deep WTD

treatment, and those decreased for shallow WTDs, The best fit regression lines

for alachlor data show that alachlor concentration in the soil profile linearly

decreased with increased sampling depth in the soil profile under all WTD

treatments. Alachlor concentrations in most cases were higher under deep

WTD treatment, and those decreased under shallow WTDs.

Corn yields significantly increased as water-table depths increased from

0.2 to 1.1 m in 1992 and 1993 at the Ankeny site. A shallow water-table

depth of 0.2 to 0.3 m significantly reduced corn yield in the wet season of

1993 at this site. In the lysimeter plots at the Ames, crop yields were

maximum under a WTD of 0.9 m, whereas, in the subirrigation field, the highest

yields were observed at 1.1 m WTD. The yields were also affected by wet

conditions in 1993 at the Ankeny site, and were less than those observed

during 1992. However those were not affected by wet conditions at the Ames

site. Findings of this study show that, although, the 0.3 WTD is most suitable

for groundwater quality control, it is not ideal for obtaining the highest crop

yields. The best water table management practice for best crop yields and

groundwater quality would be somewhere between 0.6 to 1.1 m WTD for

Iowa's Nicollet loam soils of central Iowa.

149

INTRODUCTION

Modern agriculture is heavHy dependent on the use of agrichemicals,

particularly fertilizers and pesticides. For economic reasons, continued use of

pesticide and fertilizers is expected for the foreseeable future in U.S. agriculture

Willis et al., 1992). The greatest volume of pesticides used in agriculture is

accounted for by herbicide application in crop production (Leonard, 1990). As

of 1982, the pesticide usage in the Corn Belt States was nearly 300 million

kilograms, and 85 percent of this usage was in the Corn Belt States, such as,

Iowa, Illinois, Indiana, Ohio, and Michigan (Hallberg, 1986). A major concern is

that low concentrations of less soluble but widely used pesticides have been

detected in shallow aquifers under a wide range of agricultural and climatic

condition. In 1986 the Environmental Protection Agency (EPA) reported the

presence of 17 pesticides in groundwater in 23 states (Cohen et al., 1986).

However, during recent years, this figure has gone up, and the reported cases

increased to 77 pesticides in groundwater in 39 states (Williams et al., 1988).

Herbicide presence in surface and groundwater bodies has been

documented in the literature. Some of these studies reported on the following:

Lower Mississippi River (Pereira and Posted, 1990; Pereira et al., 1992); River

Basins of the Midwestern U.S. (Thurman et al., 1991); Little Vermilion River

(Mitchell et al., 1993), few other studies have reported the presence of

150

herbicide in groundwater systems (Bengtson et al., 1990, 1993); Southvwck et

al., 1990a, 1990b; Fausey et al., 1990; Kanwar, 1990; Kalita and Kanwar,

1989, 1990; and Kalita, 1992).

During the past decade numerous studies have been conducted to

characterize the fate and movement of applied pesticides and their impact on

surface and groundwater. This is of particular concern because groundwater is

the predominant source of domestic water in most rural areas in the United

States (National, 1985). It is estimated that 97% of the nation's rural

population relies on groundwater as its source of drinking water (Moody, 1990).

According to Ritter (1986), widely used herbicides such as atrazine,

alachlor, metolachlor, and cyanazine have been detected in groundwater

systems of several states. He further reported that atrazine and alachlor

together accounted for 25% of all pesticides sold in U.S. during 1982. Isensee

et al. (1988) reported that three corn production herbicides, atrazine [2-chloro-

4-(ethylamino)-6-(isopropylamino)-S-triazine], alachlor [2-chloro-2',6'-diethyl-N-

(methoxymethyl) acetanilide], and cyanazine [2-chloro-4-(cyano-1-methylamino)-

6-ethylamino-S-triazine], have been detected in groundwater in many states

because of their wide application. They found that atrazine concentration in

shallow groundwater was between 0.2 to 1.8 ppb and that of alachlor was 0.3

ppb. These concentrations were far below the health advisory limits for atrazine

(3 ywg/L) and alachlor (2 ywg/L). Mitchell et al. (1993) reported that atrazine

151

concentrations as high as 9.6 ppb were observed from the sub-surface tile flow

station outlets located in East Central Illinois. Alachlor and metolachlor were

also detected on 20 occasions, and trifluralin was detected on 19 occasions in

the tile flow.

Alachlor has been found to be less persistent than atrazine in soil profiles

(Buhler et al., 1993). In their tests of drain outflow, alachlor was found in only

2% of samples whereas atrazine was detected in 97% of the samples taken in a

6 year period. Alachlor has been detected in groundwater samples in Iowa,

Nebraska, Maryland, and Pennsylvania at residue levels of 0.1-10 //g/L (Cohen

et al., 1986). Alachlor concentration in groundwater as high as 16//g/L was

found in Iowa (Kelley et al., 1986). Libra et al. (1986) and Kelley et al. (1986)

reported that atrazine concentrations of 10 //g/L were detected in a karst aquifer

In Iowa. In a study, Smith et al. (1990) found that atrazine concentration in the

soil water at a depth of 0.61 m reached 350//g/L after 19 days of application.

They also reported that atrazine concentration as high as 90 //g/L was observed

in the shallow groundwater after 16 months of its application, however, alachlor

was not detected in the soil below the depth of 0.36 m, they hypothized that

apparently most of the alachlor had degraded during their experimental period.

Workman et al. (1993) presented atrazine and alachlor concentration data

from soil cores taken to a depth of 0.9 m and partitioned into the increments of

0.0-0.15, 0.15-0.3, 0.45-0.6, and 0.75-0.9 m, and observed that herbicide

152

remained in the top 0.15 m of the soil profile during their two year study period.

The chemicals had degraded for approximately two half-lives for atrazine and 3-

4 half-lives for alachlor. The computed rate constant, k, and half-life, was

0.02 days'^ and 35 days for atrazine, respectively. A rate constant of 0.04

days^ and half life of 17 days computed for alachlor. In addition, they reported

that chemical seem to adsorb to the clays and organic matter in the soil since

the residual level of atrazine remained relatively high during the winter (50-100

ppb).

While determining the leaching potential of atrazine in a sandy loam soil

in Southern Quebec Canada, Smith et al. (1992) found a large variation in

atrazine concentration in soil solution at various depths and in leachate. The

maximum levels in the leachate ranged from 0.0 to 11.2 /yg/L. Higher solution

concentrations in the top 5 cm were correlated with higher moisture contents,

suggesting desorption of atrazine with water. They further observed that the

Deisopropylatrazine, one of the metabolites of atrazine, was detected near the

soil surface but did not leach beyond the 15 cm depth.

In a study conducted in Denmark on leaching of atrazine into

groundwater, Folding (1992) found that atrazine leaching was significantly

affected by high water tables and only small quantities of atrazine were

observed in the upper groundwater zone. The samples were taken from the

upper 1.5 m ground water zone at three well drained levels. The atrazine

153

content was between 0.01 to 0.05 //g/L. The highest concentrations being

found at the top of groundwater table.

There is a scant literature on pesticide management with water table

management practices. However, recently these practices have received

attention as potential measure to reduce pollution hazards to groundwater

system. Few studies have shown that water table management (WTM)

practices that include controlled drainage, and controlled drainage-subirrigation

could reduce pesticide concentrations in shallow groundwater and improve crop

yield (Baker, 1980; Baker and Johnson, 1976; Bengtson et al., 1990, 1993;

Evans et al., 1989; Fausey et al., 1990; Kanwar, 1990; Kanwar et al., 1988;

Kalita and Kanwar, 1989, 1990; and Kalita, 1992).

Baker (1980) and Baker and Johnson (1976) found that the concentration

of most herbicides and insecticides were higher in surface runoff than in

subsurface drainage, but chemical that were not adsorbed, such as anionic

herbicides, usually had higher concentrations in the subsurface drainage.

Kladivko et al. (1991) determined field scale pesticide losses to subsurface

drainage on a low organic matter and (poorly structured) silt loam soil under

typical agricultural management practices. They observed small amounts of

carbofuran, atrazine, cyanazine, and alachlor in subsurface drain flow within 3

weeks of pesticide application. The annual carbofuran losses in subsurface

drain flow ranged from 0.8 to 14.1 g/ha, whereas, the losses of all other

154

pesticides were ^ 0.06% of the amount applied. Bengtson et al. (1990)

reported that atrazine and metolachlor losses were reduced by 55 and 51 %,

respectively, in the areas where subsurface drainage systems were used. They

concluded that subsurface drainage substantially reduced atrazine losses, and

about 2/3 of the losses occurred within 30 days after herbicide application.

They also found that atrazine concentrations were substantially greater than

EPA's advisory level for drinking water. In another study, Bengtson et al.

(1993) reported that subsurface drainage reduced alachlor and norflurazon

losses by 34 and 31%, respectively. They found alachlor and norflurazon

losses under nondrained fields were 48 and 59%, respectively. Based on their

findings, they concluded that subsurface drainage may offer a management tool

for decreasing pesticide input from non-point agricultural sources into aquatic

areas of the Lower Mississippi Valley.

In previous study conducted in Iowa, Kalita (1992) observed that under

different water table depths, pesticide concentrations were lower at shallow

water table depths, however, this trend increased with increasing water table

depth. Higher concentrations of atrazine and alachlor were observed at water

table depth of 0.9 m or deeper. Results of this and other studies have stressed

on the need of further research on the use of WTM practices to reduce

groundwater quality degradation caused through the use of pesticides.

Because of the growing concern over the herbicide use which may lead to

155

significant contamination of both surface and groundwaters, information on the

pollution potential from herbicides and possible ways to reduce or control non-

point pollution is of great importance. Thus, the objectives of this study were

to investigate the effects of WTM practices on the movement of herbicides into

shallow groundwaters. The specific objective of this study was to discuss the

effects of WTM practices on the movement of two surface applied herbicides,

atrazine and alachlor, to shallow groundwater during the growing seasons of

1992 and 1993.

156



Field studies were conducted during growing seasons of 1992 and 1993

on two research farms owned by Iowa State University. These research farms

are located near Ames and Ankeny. The soils at these sites are predominantly

Nicollet loam (Aquic Hapludolls) in the Clarion-Nicollet-Webster soil association.

Table 1 lists some of the physical properties of these soils at these two sites.

At the Ames site, nine field lysimeters (each 3 m wide and 6 m long)

were installed in 1986. A 0.2 m wide and 1.2 m deep trench around the

perimeter of each lysimeter was dug using a Ditch Witch trencher, and each

lysimeter was completely enclosed using a plastic barrier 0.25-mm-thick to

minimize any lateral subsurface water movement between lysimeters. A

corrugated, perforated plastic tube (100-mm diameter) was installed at the

bottom of the trench inside the plastic barrier. A 0.9 m wide ditch was dug to a

depth of 1.35 m with a back hoe to install a 1.5 m tall corrugated plastic pipe

(used as sump) at the corner of each lysimeter. The bottom of 1.5 m tall sump

was located 1.35 m below the soil surface, and the top of the sump was 0.15

m above the soil surface. The two ends of the perforated plastic tubes at right

angles to each other were inserted into the sump at a height of 0.15 m from the

bottom of the sump. In 1990, all lysimeters were enclosed with another 0.25-

157

mm-thick PVC (poly-vinyl-chloride) flexible liner to a depth of 1.7 m. Each liner

encased a square area (9 m X 9 m) with the 3 X 6 m original field lysimeter

located in the center of the enclosed area to ensure that subsurface water did

not move laterally between lysimeters to a depth of 1.7 m. A detailed






mm diameter PVC irrigation pipe. The layout of the experimental area for this

site is shown in Figure 2.

At the Ankeny site, a dual pipe subirrigation system was installed in 1988

on a 0.5-ha area with a significant natural ground slope of 2.5 percent. The

basic concept of the dual-pipe subirrigation system is illustrated in Figure 3.

Shallow irrigation pipes (51-mm diameter) were installed at a depth of 0.5 to

0.6 m parallel to and midway between drainage pipes, which were installed at a

depth of 1.2 m. Because of the natural ground slope along the length of the

field, water tables could be maintained at various depths below the soil surface

by controlling the subsurface drainage outflows and by supplying irrigation

water through the subirrigation pipes.

158



0.9 m in 1992 and 1993. Each water table treatment depth was replicated





corn roots to develop within 0.3 to 0.9 m soil profile. It took almost three days


1993 the record wet year, there was no problem in bringing the water tables

near the surface but water tables had to be lowered using a sump pump.

Observation wells (25-mm diameter and 1.2-m long PVC pipes) were installed in

the center of each lysimeter to monitor water levels.

At the Ankeny site, WTDs were maintained at 0.2, 0.3, 0.6, 0.9, and 1.1

m, respectively. However, the water table depths ranged from 0.05 to 1.2 m

during the growing season. A maximum water-table depth of 1.2 m was

observed at the highest elevation site (north boundary) of the field in the

beginning of the 1992 season. The minimum water table depth of 0.05 m was

observed at the lowest elevation site of the field twice during the growing

season of 1992, and most of the time during growing season of 1993 due to

heavy rainfall.

159

Each treatment location was divided into three subplots, where the


per each water table depth treatment along the row. Water table depths,

however, were maintained from 49 to 110 DAP in 1992 and from 50 to 98 DAP

in 1993. An elapsed period of about 50 days between planting and start of

subirrigation allowed corn roots to develop uniformly in this field to a depth of

0.2 to 1.1 m.

Groundwater sampling

Ground water samples were collected using suction tubes and

piezometers on monthly basis in 1992 and 1993 from both sites for pesticide

analysis. Solute suction tubes were made by coupling a 200-kPa porous

ceramic cup to the end of 38-mm diameter PVC pipe. The top ends of these

tubes were sealed with rubber stoppers. At the Ames site, suction tubes were

installed at the center of all nine lysimeters (three replications per treatment) at

0.3, 0.6, 0.9, 1.5, and 2.1 m depths to collect water samples. A vacuum

pump was used to create a vacuum in the solute suction tubes one day before

sample collection, and water samples were collected the following day.

Piezometers were made of 25-mm diameter PVC pipes by making perforations

at the lower end to be placed in the ground. The lower ends were sealed with

rubber stoppers. Piezometers were installed in each lysimeter plot at 1.2, 1.8,

160

and 2.4 m depth to collect ground water samples and to monitor piezometric

heads. The piezometers were pumped out one day before sampling if any water

was sitting in the piezometers and water samples were collected on the

following day. All water samples collected, were then preserved in a cold

chamber at 4 °C for analysis.

At the Ankeny site, solute suction tubes were installed at 0.9, 1.5, and

2.1 m depths at three locations (B, C, and D locations as shown in Figure 1)

with three replications at each location. Piezometers were also installed at three

locations (A, C, E locations as shown in Figure 1) at 1.2, 1.8, 2.4 m depths

with three replications per location. Similar procedures (those at Ames site)

were followed to collect water samples.

Herbicide extraction procedures

The 300 ml water sample plus 100 ml of methylene chloride [CHg CIg]

were placed in a separation funnel. This mixture was hand shaken for 2

minutes and the solvent was collected. This procedure was repeated 3

additional times using 50 ml of methylene chloride each time. The solvent was

then evaporated to dryness and the residues dissolved in approximately 10 ml

of methanol. The extract was stored at 4 °C for further analysis.

Analysis of herbicide: The extracts were analyzed using a Varian 3400 gas

chromatograph (fused-silica megabore DBS-column; TSD detector) equipped

161

with an integrator and an auto-sampler, in the water quality laboratory of

Agricultural and Biosystems Engineering Department. A very small portion of

the extract was injected into a tracer 560 GC with a N-P thermionic detector.

Operating conditions were: column oven at 160 °C, inlet at 245 °C, detector at

245"'C, Helium carrier gas at the rate of 18 cm^ min'\ Hydrogen reaction gas at

the rate of 3.5 cm^ min \ and air reaction gas at the rate of 100 cm^ min'\

Herbicides were separated using a 3% OV-1 column.

Planting, harvesting, and chemical management system

The corn genotype Pioneer 3379 was planted at both sites. In 1992,

seeds were planted on May 8, and were hand harvested on November 6 in the

lysimeter plots at Ames site, and were harvested using a combine at the

Ankeny site in 1992. In 1993, seeds were planted on May 21 at both sites,

and were hand harvested on October 21 in the lysimeter plots at Ames site, and

were harvested on October 31 using a combine at the Ankeny site. The plant

population was 67000 per ha with a row-to-row spacing of 0.75 m and seed-to-

seed distance of 0.2 m at each site. Urea nitrogen, phosphorus, and potassium

fertilizers were surface applied at planting time at both sites every year at the

rate of 200 kg-N ha \ 60 kg ha % and 40 kg ha'\ respectively. Herbicides

atrazine (C3H14CIN5) and alazhlor (trade name lasso, Ci^HgoCINOg) were applied

at the rate of 2.2 kg ha \ in both years at the Ankeny and Ames sites.

162

RESULTS AND DISCUSSION

Atrazlne concentrations in piezometer water samples at the Ames site

Atrazine concentrations as a function of WTD and piezometer sampling

depth for 1992 are plotted in Figure 4. At this site, WTDs were constantly

maintained at 0.3, 0.6, 0.9 m depths during the growing seasons of 1992 and

1993. Figure 4 shows that atrazine concentrations were lower at WTD of 0.3

m in comparison with WTDs of 0.6, and 0.9 m. Atrazine concentrations

generally decreased with time and increased with piezometer sampling depth.

Figure 4 shows that atrazine concentrations in groundwater samples at 1.2 m

were lower than at 1.8 and 2.4 m piezometer sampling depths with few

exceptions. At the 1.2 m sampling depth, concentrations in groundwater

ranged between 3.9 to 2.1, 5.2 to 1.2, and 18.3 to 5.4//g/L under 0.3, 0.6,

and 0.9 m WTD, respectively, during the growing season of 1992. Atrazine

concentrations at the 1.8 and 2.4 m piezometer sampling depths also showed,

on the average, an increasing trend with lowering WTD. Similarly, atrazine

concentrations ranged between 7.2 to 0.9, 9.7 to 1.4, and 33.9 to 0.6//g/L at

the 1.8 m depth, and ranged between 6.0 to 0.4, 8.6 to 1.1, and 14.5 to 2.1

)[yg/L at the 2.4 m depth under 0.3, 0.6, and 0.9 m WTDs, respectively.

However, the highest concentrations of 18.3, 33.9, and 14.5 //g/L were

observed under the 0.9 m WTD at 1.2, 1.8, and 2.4 m piezometer sampling

163

depth, respectively, on 55 DAP.

Atrazine concentrations in piezometer water samples for 1993 as a

function of WTD and DAP are presented in Figure 5. The figure shows a

distinct trend of decreasing concentrations with time and increasing piezometer

depth. Higher atrazine concentrations were observed at the 0.9 m WTD as

compared to those observed at the 0.3 and 0.6 m WTDs. At the 1.2 m depth,

most of the time, lower atrazine concentrations were observed as compared to

the 1.8 and 2.4 m piezometer sampling depths. Figure 5 also shows that the

highest atrazine concentrations of 128.8 and 626.1 yc/g/L were observed at the

1.8 and 2.4 m piezometer sampling depths under 0.9 m WTD on 48 DAP. This

might be the result of quick transport of atrazine due to excessive rain activity

in 1993. The average atrazine concentrations in groundwater at the 1.2 m

piezometer sampling depth ranged between 5.2 to 1.0, 7.0 to 1.8 and 8.6 to

0.8 yt/g/L under 0.3, 0.6, 0.9 m WTD, respectively. Similarly, concentrations

ranged between 11.6 to 0.7, 7.8 to 1.2, and 128.8 to 8.8 //g/L at the 1.8 m

piezometer depth, and those ranged between 4.5 to 1.5, 22.5 to 3.0, and

626.1 to 2.8ywg/L at the 2.4 piezometer depth under 0.3, 0.6, and 0.9 WTDs,

respectively.

164

Atrazine concentrations in suction tube water samples at tlie Ames site

Concentrations of atrazine in suction tube water samples in 1992 are

shown in Figure 6. Water samples were collected using suction tubes at 0.3,

0.6, 0.9, 1.5, and 2.1 m depths during the growing season, but no water

samples could be collected for analysis from 0.3, 0.6, and 0.9 m suction tube

depths on 39 DAP because of drier soil conditions. Also, very few samples

were available for analysis at those suction depths on 141 and 169 DAP. This

was due to unsaturated soil profile particularly when WTD was maintained at

0.6 and 0.9 m depths. Figure 6 shows that atrazine concentrations under the

0.3 m WTD were lower than those observed at the 0.6 and 0.9 m WTDs. The

highest atrazine concentration of 66.8 ywg/L on 39 DAP was observed at the 0.9

m WTD in comparison with 24.4//g/L at the 0.6 m WTD. Figure 6 also

compares the atrazine concentrations by sampling depth in the soil profile. The

atrazine concentrations were generally higher at shallow sampling depths as

compared to deep sampling depths in the soil profile under all WTDs with few

exceptions. These concentrations decreased from 4.9 to 1.9 //g/L at the 0.3 m

suction tube depth with a WTD of 0.3 m, after water table treatment was

started, and those decreased from 7.9 to 0.9 //g/L and from 26.2 to 3.8 //g/L

under 0.6 and 0.9 m WTDs, respectively, at the same suction tube depth.

Similar trends of decrease in atrazine concentrations under three WTDs were

observed at 0.6, 0.9, 1.5, and 2.1 m suction tube sampling depths.

165

The data on atrazine concentration as a function of WTD and water

sampling depths in the soil profile for 1993 are plotted in Figure 7. Figure 7

shows that atrazine concentrations decreased with increasing suction tube

sampling depth, and also decreased with time with few exceptions. The

highest atrazine concentrations of 19.9, 31.8, 60.3 //g/L on 48 DAP were

observed at 0.3, 0.6, and 0.9 m suction tube depths, respectively. These

concentrations were observed under 0.9 m WTD. However, those under 0.3 m

WTD were 20.9, 17.5, and 21.4 jt/g/L at 0.3, 0.6, and 0.9 suction tube depth,

respectively, and were 19.1, 2.8, 26.0yc/g/L under 0.6 m WTD at 0.3, 0.6, and

0.9 suction tube depths, respectively. The atrazine concentrations ranged

between 26.0 to 1.1, 23.7 to 0.7, and 60.3 to 2.6 ywg/L under 0.3, 0.6, and 0.9

m WTDs, respectively, during the growing season. The average atrazine

concentrations in groundwater at all suction tube depths, after 48 DAP, were

always less under all WTDs for the rest of the growing season. These results

show significant differences in atrazine concentrations between WTD

treatments, and reveal a positive influence of WTDs in reducing atrazine

concentrations in groundwater. Another noticeable observation was that, at the

Ames site, atrazine concentrations in suction tube water samples were higher

than those in piezometer water samples.

166

Atrazine concentrations in piezometer water samples at the Ankeny site

Atrazine concentrations in piezometer samples for the growing season of

1992 at the Ankeny site are presented in Figure 8. Water table depths were

maintained at 0.2, 0.6, and 1.1 m at this site. The average concentrations as a

function of DAP and WTD in the subirrigation field at Ankeny site show that the

atrazine concentrations in groundwater samples were different at different

WTDs during the growing season of 1992. The 0.2 m WTD showed lower

atrazine concentrations in comparison with those observed at the 0.6 and 1.1 m

WTDs. Atrazine concentration decreased with time under all WTDs. In the

early part of growing season of 1992, higher concentrations were observed at

1.2, 1.8, and 2.4 m piezometer depths than In the later part of the growing

season. The higher concentrations are associated with greater amounts of

atrazine available In the soil profile due to applied herbicide. Therefore, higher

atrazine concentrations could be anticipated. The highest atrazine concentration

o f 2 1 . 6 j u g / L w a s o b s e r v e d a t t h e 2 . 4 m p i e z o m e t e r d e p t h 5 4 D A P u n d e r 1 . 1 m

WTD treatment. With sublrrigatlon practice, atrazine concentrations in

groundwater decreased significantly. Figure 8 also compares the atrazine

concentrations at 1.2, 1.8, and 2.4 m piezometer water sampling depths, under

0.2, 0.6, and 1.1 m WTDs. Figure 8 shows that the atrazine concentrations

generally decreased with increased depth in the soil profile under all WTDs with

few exceptions. The atrazine concentrations decreased with time, however, at

167

all three piezometer sampling depths in the soil profile. At the 1.2 piezometer

depth, concentrations of atrazine in groundwater samples varied from 10.1 to

0.5, 13.6 to 1.9, and 19.6 to 1.1 yt/g/L for 0.2, 0.6, and 1.1 m WTDs,

respectively. Similarly, those varied from 8.8 to 0.5, 19.9 to 1.7, and 11 to 0.5

yug/L at the 1.8 m piezometer depth, and from 1.6 to 0.2, 1.4 to 0.2, and 21.6

to 2.1 //g/L at the 2.4 m piezometer depth for 0.2, 0.6, and 1.1 m WTDs,

respectively.

The average atrazine concentrations in piezometer water samples for

1993 as a function of WTD and DAP are plotted in Figure 9. Similar trends in

atrazine concentrations were observed in 1993 as compared to those observed

in 1992. However, the highest concentrations of 22.2, 21.3, 16.6 //g/L on 68

DAP were observed at 1.2, 1.8, and 2.4 m piezometer depths in the soil profile

under 1.1 m WTD. The atrazine concentrations were significantly reduced with

time. These results show a definite influence of WTD treatments on pesticide

concentrations in groundwater. The atrazine concentrations were different at

different WTDs, and were different for various piezometer sampling depths in

the soil profile. Data for 1993 also indicate that atrazine concentrations were

lower under 0.2 m WTD than at 0.6, and 1.1 m WTDs, and generally decreased

with increased sampling depth in the soil profile under all three WTDs. The

concentrations also decreased with time, significantly higher concentrations

were observed during the early part of the growing season. Heavy rainfalls

168

during the early part of the growing season of 1993 perhaps caused leaching of

applied herbicide from the surface layer to the deeper depths. Atrazine

concentrations ranged between 12.0 to 1.2, 8 to 1.8, and 22.2 to 10.9 ,ug/L at

the 1.2 m piezometer depth under 0.2, 0.6, and 1.1m WTDs, respectively.

Similarly, atrazine concentrations ranged between 8.5 to 2.8, 611.2 to 1.5, and

23 to 9.3 //g/L at the 1.8 m piezometer depth, 4.7 to 1.2, 6.7 to 5.8, and 16.6

to 1.9/yg/L at 2.4 m piezometer depth under 0.2, 0.6, and 1.1 m WTDs,

respectively. Comparison between atrazine concentrations at different

piezometer depths shows that greater amounts were observed at the 1.8 m

piezometer depths than those observed at 1.2 and 2.4 m piezometer depths.

Atrazine concentrations in suction tube water samples at the Aniceny site

Atrazine concentrations in groundwater samples collected from the

suction tubes during 1992 are shown in Figure 10. Figure shows that atrazine

concentrations ranged between 114.6 to 0.2, 14.4 to 1.2, and 36.2 to 0.2 //g/L

for 0.3, 0.6, and 0.9 m WTDs, respectively. The highest atrazine

concentrations of 114.5 /yg/L was observed at 0.9 m suction tube depth on 38

DAP. Those at 1.5, and 2.1 m suction tube depths were 22.7 and 9.9/yg/L,

respectively. However, the atrazine concentrations were significantly reduced

at the 0.9, 1.5, and 2.1 m suction tube depths under all WTDs after

subirrigation was started. The atrazine concentrations decreased with time and

169

increased suction tube depth. At the end of the growing season, atrazine

concentrations in groundwater samples decreased to 0.2, 0.8, and 0.7 //g/L at

0.9, 1.5, and 2.1 m soil depths, respectively. Water samples from suction tube

also showed higher atrazine concentrations at the 2.1 m soil depth than those

at 1.5 and 0.9 m soil depths towards the end of the growing season when

subirrigation was cut off.

The data on average atrazine concentration as a function of WTD and

suction tube depths in the soil profile for 1993 are illustrated in Figure 11.

Figure 11 shows that atrazine concentrations decreased with increasing suction

tube sampling depth and also decreased with time. The highest atrazine

concentrations of 36.4, 3.4, 1.4//g/L on 48 DAP were observed at 0.9, 1.5,

and 2.1 m suction tube depths, respectively, at 0.9 m WTD. However, those

under 0.3 m WTD were 2.7, 1.5, and 0.5 //g/L at 0.9, 1.5, and 2.1 suction tube

depths, respectively, and were 4.5, 0.5, and 10.2//g/L under 0.6 m WTD at

0.9, 1.5, and 2.1 suction tube depths, respectively. During the early part of the

growing season of 1993 greater atrazine concentrations were observed. Heavy

rainfall in the early part of the growing season caused leaching of applied

herbicides from surface layer to deeper depths, therefore, higher amounts could

be anticipated. It was observed that atrazine concentrations in groundwater

were significantly lower with 0.3 m WTD than with 0.6 and 0.9 m WTDs under

all sampling depths. However, almost similar trends in atrazine concentrations

170

were observed in piezometer and suction tube water.

Alachlor concentrations at the Ames site

The results of the alachlor concentrations in piezometer and suction tube

water samples for the two growing seasons (1992-93) are presented in Table 2.

Alachlor was not detected in many samples collected on different dates in 1992

and 1993. Table 2 shows only the dates when alachlor was detected in

groundwater samples during the two years. In 1992, alachlor was detected in

only ten piezometer water samples, and the results were inconsistent. It was

detected only in nine suction tube samples and the trends were similar to those

in piezometer samples. The highest concentration of 18.3 /yg/L was observed in

piezometer samples at 0.9 m WTD on 81 DAP. Alachlor has been found less

persistent than atrazine in soil profiles (Buhler et al., 1993). In their tests,

alachlor was found in only 2% of samples whereas atrazine was detected in

97% of the samples taken in a 6-year period. Nash (1988) reported that under

normal agricultural use conditions, 90% of alachlor was degraded within 30 to

100 days of application. Wu and Fox (1981) reported that the time for 90%

loss from the upper 0.3 m zone was 298 days for atrazine, and only 45 days for

alachlor. Their study shows that alachlor was detected 77 days after its

application with a concentration of 1.1 /yg/L at the 2.1 m soil depth.

In 1993, alachlor concentrations were detected at almost all sampling

171

depths in piezometer samples collected on 48, 68, 90, and 116 DAP. However,

those concentrations were not detected in many suction tube samples and

results were inconsistent. The highest concentrations were observed in

piezometer samples on 48 DAP. Alachlor concentration in piezometer samples

ranged between 58.4 to 1.2, 4.3 to 0.8, and 37.3 to 2.1 yug/L under 0.3, 0.6,

and 0.9 m WTDs, respectively. These concentrations were lower in 1992 than

in 1993. However a shallow WTD significantly reduced alachlor concentrations

at all depths.

Alachlor concentrations at the Ankeny site

Table 3 presents alachlor concentrations in piezometer and suction tube

water samples for the two growing seasons (1992-93) in the subirrigation field

at the Ankeny site. Similar trends in alachlor concentrations at this site were

observed. Alachlor concentrations were detected only on three occasions

during the growing season of 1992 in piezometer samples. Those were

d e t e c t e d o n 3 8 , 5 4 , a n d 8 2 D A P i n p i e z o m e t e r w a t e r s a m p l e s a t 0 . 6 a n d 1 . 1 m

WTDs. However, alachlor concentrations were not detected in any of the

suction tube water samples during the growing season of 1992. The highest

concentration of 1.2 //g/L was observed in piezometer samples collected on 54

DAP. In 1993, alachlor concentrations were detected in almost all suction tube

samples collected on 48 DAP under all three WTD treatments. The highest

172

concentration of 11.5, 6.7, and 3.1 /yg/L were observed at 0.9, 1.5, and 2.1 m

sampling depths under 0.9 m WTD. These concentrations were higher than

those observed at 0.3 and 0.6 m WTDs. However, alachlor concentrations

were detected only in two samples collected at 0.6 m WTD on 68 DAP. In

piezometer samples, alachlor concentrations were observed in about 50% of the

samples collected on four sampling dates (i.e. 48, 68, 88, and 116 DAP).

Atrazine and alachlor distribution pattern in the soil profile

Relative sampling depths from the soil surface in the soil profile versus

the atrazine and alachlor concentrations under different WTDs fit the respective

regression relations. The regression analysis was performed on the pooled data

collected at both sites during the two year study period. Equations of

regression lines and their respective R-square values for atrazine and alachlor

concentration as a function of sampling depth under different WTDs are given

below:

Regression equations using atrazine data

WTD — 0.2 m. Atra = 6.95 - 2.39 D R2 = 0.80

WTD = 0.3 m. Atra = 8.94 - 2.85 D R2 = 0.40

WTD = 0.6 m. Atra = 10.95 - 3.36 D R2 = 0.37

WTD = 0.9 m. Atra = 18.95 - 5.05 D R2 = 0.36

WTD — 1.1 m. Atra = 21.46 - 5.47 D R2 = 0.98

173

Regression equations using alachlor data

WTD = 0.2 m, Alac = 3.35 - 1.25 D R2 = 0.60

WTD = 0.3 m, Alac = 3.61 - 0.88 D R2 = 0.69

WTD = 0.6 m, Alac = 2.36 - 0.49 D R2 = 0.44

WTD = 0.9 m, Alac = 10.56 - 5.73 D R2 = 0.77

WTD = 1.1 m, Alac = 3.31 - 0.75 D R2 = 0.83

where WTD is water table depth, Atra is atrazine concentration in //g/L, D is

water sampling depth in the soil profile in m, and Alac is alachlor concentration

in //g/L. The respective best fit regression lines for atrazine data are shown in

Figure 12a. Figure 12a shows that atrazine concentration in the soil profile

linearly decreased with increased sampling depth in the soil profile under all

WTD treatments. However, atrazine concentrations were always higher under

deep WTD treatments, and those decreased for shallow WTDs. Figure 12b

shows best fit regression lines for alachlor data. Figure 12b shows that alachlor

concentration in the soil profile linearly decreased with increased sampling depth

in the soil profile under all WTD treatments. Alachlor concentrations in most

cases were higher under deep WTD treatments, and those decreased under

shallow WTDs. However, the differences between WTD treatments were not

clear in some cases.


on the entire data set to determine the differences between atrazine means

174

under five WTD treatments. The ANOVA results for atrazine are presented in

Table 4. The ANOVA results by water table treatment depth for atrazine show

that, regardless of sampling method and site, the means for 0.2, 0.3, 0.6, 0.9,

and 1.1 m depths were significantly different at the 0.05% probability level.

These results show a positive effect of WTD on the atrazine movement. The

ANOVA results by sampling depth are also presented in Table 4. Table 4 shows

that atrazine means were significantly different for the suction tube samples,

but, were not significantly different for the piezometer samples at both

experimental sites.


on the entire data set to determine the differences between alachlor means

under different WTD treatments. ANOVA results by WTD treatment show that,

alachlor means were not significantly different at the 0.05% probability level

with piezometer samples at both sites, whereas, those were significantly

different with suction tube samples. Almost, similar trends in alachlor means

were observed with ANOVA performed on alachlor data by sampling depth in

the soil profile.

Crop yield

Corn yields for 1992 and 1993 for the Ankeny and Ames sites are


175

from the plots under the 0.9 and 1.1m depths, and the lowest yield was

obtained from the plots under the 0.2 m depth in 1992. In 1993, however, 1.1

m depth gave the highest, and 0.2 m depth gave the lowest yield. At 0.2 m

depth crop yield was very poor in both years. High rainfalls caused almost

surface flooding conditions for a few days during 1992, and almost all the time

during the growing season of 1993, at the 0.2 m depth, which in turn




higher yields than did the 0.6 m depth for both years.





However, the means were significantly different between 0.2, 0.9, and 1.1 m


between 0.3, 0.6, 0.9, and 1.1 m WTDs during 1993.





176


corn yields between two years were observed.







177

CONCLUSIONS

Field experiments were conducted at two research farms of Iowa State

University near Ankeny and Ames to evaluate the effects of water table depth

(WTD) practices on the movement of two surface applied herbicides, atrazine

and alachlor into the groundwater. Data were collected by using piezometers

and suction tubes during the growing seasons of 1992 and 1993 at these

research farms, and average concentrations of atrazine and alachlor in

groundwater as affected by different water table depths (WTDs) were

measured. This study resulted in the following conclusion;

1. The average atrazine and alachlor concentrations in groundwater were

reduced by maintaining shallow WTDs between 0.3 to 0.6 m during the two

growing seasons. The average herbicide concentrations in groundwater

generally decreased with increased sampling depth and with time,

2. Alachlor was not detected in many samples and the results were

inconsistent, however, atrazine was detected in almost all water samples. The

highest atrazine concentrations in groundwater were mostly observed before the

water table treatments began. It was also observed that alachlor concentrations

were lower than those of atrazine under similar WTD treatments. However,

atrazine concentrations were significantly reduced after WTD treatments started

which shows a positive influence of WTM practices in reducing pesticide concentrations.

178

3. Regression analysis show that atrazine concentrations in the soil profile

linearly decreased with increased sampling depth in the soil profile all WTD

treatments. However, atrazine concentrations were always higher under deep

WTD treatment, and those decreased for shallow WTDs. The best fit regression

lines for alachlor data show that alachlor concentration in the soil profile linearly

decreased with increased soil depth under all WTD treatments. Alachlor

concentrations in most cases were higher under deep WTD treatment, and

those decreased under shallow WTDs. However, the differences between WTD

treatments were not clear in some cases.

4. Corn yields significantly increased as WTDs were lowered from 0.3 to 0.9 m

at the Ames site during both study years. At the Ankeny site, yields increased

as WTDs were lowered from 0.2 to 1.1 m. However, yields were not

significantly different between WTDs during 1992 but were significantly at the

0.05 probability level during 1993, and shallow water-table depths (0.2 and 0.3

m) significantly reduced corn yield due to excessive wet conditions.

5. These results indicate that pesticide concentrations in groundwater can be

significantly reduced while corn yield can be maintained at an optimum level by

adopting the right WTD. Therefore, appropriate use of WTD is recommended as

a best management practice for reducing pesticide residue movement into the

groundwater systems.


Depth Sand m %

Silt %

Clay %

PH Bulk density Mg m'3

Organic matter %


0.15 29.5 44.3 26.2 5.9 1.25 3.2

0.30 31.5 40.4 28.1 6.6 1.49 2.3

0.60 38.6 34.1 27.3 7.1 1.46 1.5

Nicollet loam soil at the Ames site"

0.15 31.3 43.6 25.1 7.3 1.20 4.3

0.30 31.2 42.8 26.0 6.7 1.30 4.0

0.60 27.7 42.2 30.1 6.9 1.35 2.9

®Charkhabi (1990); ''Kanwar et al. (1988)

Table 2. Aiachlor concentrations (//g/L) In suction tube and piezometer water samples at the Ames site In 1992 and 1993

Suction tube water samples Piezometer water samples

Sampling depth Sampling depth

DAP WTD. m 0.3m 0.6m 0.9m 1.5m 2.1m DAP WTD, m 1.2m 1.8m 2.4m

39 0.3 NS NS NS NS NS 39 0.3 ND ND NS 0.6 NS NS NS 4.6 18.2 0.6 ND ND 0.4 0.9 NS NS NS 7.2 ND 0.9 ND 7.4 3.2

55 0.3 ND ND 0.5 ND 1.2 55 0.3 ND ND ND 0.6 2.6 ND ND 1.3 ND 0.6 0.3 0.3 NS 0.9 ND ND ND ND ND 0.9 0.7 2.6 1.2

81 0.3 ND ND ND ND 0.8 81 0.3 ND ND ND 0.6 ND ND 1.0 ND ND 0.6 ND ND ND 0.9 ND 18.3 ND ND ND 0.9 ND ND 0.5

48 0.3 ND ND ND 2.0 ND 48 0.3 5.4 8.4 58.8 0.6 ND 1.6 1.8 0.8 ND 0.6 2.2 2.4 4.3 0.9 1.6 ND 3.8 1.2 ND 0.9 22.1 3.0 37.3

68 0.3 ND ND ND ND ND 68 0.3 3.9 9.4 2.9 0.6 1.7 ND 1.6 ND 0.5 0.6 3.7 4.3 1.1 0.9 ND ND ND 1.5 1.5 0.9 1.2 4.0 23.0

90 0.3 ND ND ND ND 4.8 90 0.3 1.6 2.6 1.2 0.6 ND 2.5 ND 0.8 0.4 0.6 1.4 0.9 1.2 0.9 ND ND ND 1.0 1.7 0.9 4.2 2.1 1.9

116 0.3 ND ND ND ND ND 116 0.3 1.2 2.0 1.7 0.6 ND ND ND 0.9 ND 0.6 ND 0.8 ND 0.9 ND ND ND 0.7 ND 0.9 1.1 ND 8.9

144 0.3 ND ND ND ND ND 144 0.3 ND 0.8 ND 0.6 ND ND ND 0.5 ND 0.6 ND ND ND 0.9 ND ND 2.0 0.9 ND 0.9 ND ND ND

Table 2. (continued)

Overall average 0.3 ND ND 0.5 2.0 2.3 0.3 3.0 4.6 16.2 0.6 2.2 2.1 1.5 1.5 6.4 0.6 1.9 1.7 1.8 0.9 1.6 18.3 2.9 2.1 1.6 0.9 5.9 3.8 10.9

DAP - days after planting; WTD - water-table depth; NS - no water sample available; ND - below detectable limit

182

Table 3. Alachlor concentrations (yt/g/L) in suction tube and piezometer water samples at the Ankeny site in 1992 and 1993



Year DAP WTD.m 0.9m 1.5m 2.1m DAP WTD,m 1.2m 1.8m 2.4m

1992 38 0.3 ND ND ND 38 0.2 ND ND ND 0.6 ND ND ND 0.6 ND ND ND 0.9 ND ND ND 1.1 ND ND 1.5

54 0.3 ND ND ND 0.2 ND ND ND 0.6 NS ND NS 0.6 ND 0.3 ND 0.9 NS NS ND 1.1 0.6 0.7 1.2

82 0.3 ND ND ND 0.2 ND ND ND 0.6 ND ND ND 0.6 ND ND ND 0.9 ND ND ND 1.1 ND ND 0.1

1993 48 0.3 2.4 0.9 ND 48 0.2 2.2 NS ND 0.6 1.7 2.2 4.1 0.6 ND 1.8 1.5 0.9 11.5 6.7 3.1 1.1 2.8 6.9 2.6

68 0.3 ND ND ND 68 0.2 ND 0.4 0.7 0.6 2.0 NS 0,4 0.6 6.4 ND ND 0.9 ND ND ND 1.1 1.1 0.9 0.7

88 0.6 0.4 ND ND 1.1 NS 0.4 1.1

116 0.2 ND 0.3 ND 0.6 0.4 ND ND

Overall averages 0.3 2.4 0.9 ND 0.2 2.2 0.4 0.7 0.6 1.9 2.2 2.3 0.6 3.4 1.0 1.5 0.9 11.5 6.7 3.1 1.1 1.5 2.2 1.4

DAP - days after planting; WTD - water table depth; NS - no water sample available; ND - below detectable limit

Table 4. Analysis of variance (ANOVA) on atrazine and alachlor i f jg/L) data as function of water table depth (WTD) and sampling depth using two years data.

ANOVA by sampling depth, m

Sampling mode Site 0.3 0.6 0.9 1.2 1.5 1.8 2.1 2.4 F Pr > F

Atrazine Suction tube Pi zometer Piezometer

both Ames Ankeny

8.4'" 10.7* 10.2* 8.4* 6.5*

5.6" 2.3' 4.3*" 6.9*

3.1" 4.3*

2.93 0.0220 2.96 0.0575 2.05 0.0575

Alachlor Suction tube Pi zometer Piezometer

both Ames Ankeny

1.9* i .r 1.3* 4.4*= 2.0*

1.5" 3.2" 1.5*

12.9' 1.2*

3.05 0.0377 2.01 0.1538 0.31 0.7391

ANOVA by WTD treatment, m

0.2 0.3 0.6 0.9 1.1 F Pr > F

Atrazine Suction tube Piezometer Piezometer

both Ames Ankeny 2.9*

4.5* 2.8*

5.3* 4.8*" 4.9"

10.4" 7.3"

10.3"

6.07 10.03 12.36

0.0028 0.0226 0.0001

Alachlor Suction tube Pi ezometer Pi ezometer

both Ames Ankeny 0.9*

1.6* 8.3*

2.4* 2.0* 1.6*

5.2" 9.2*

1.8*

2.60 1.34 0.11

0.0930 0.2780 0.8985

Mean followed by same letter in a row are not significantly different at 0.05% probability level

184

Table 5. Corn yield kg/ha as a function of water table depth at Ames and Ankeny sites for 1992 and 1993.

WTD, m Ames Ankeny

Year 1992

0.2 7033*

0.3 5216* 8400*

0.6 6970*" 8348*

0.9 8732" 9280*

1.1 9293*

Year 1993

0.2 3671*

0.3 4930* 5226*

0.6 7914" 5150*"

0.9 8860" 6960%

1.1 7399":


Iriigatlon

fMêlMtchaïutm

Gaidtn

Corrwgaltd Hailk Sump Mi un 00) Corrugalcd flatUciHt ItOunOO)

m I I PUilUlatficf I—I jo 25 mm iliuk) 12 ] FVCfltiiblilbMt

Sump f ump -


00 oi

186

City of Water Supply Line

Water Meter Pit

Hydrant


L.

0 0

s IS

Oo.

do T

Oo

Water Storage Tank (1.3 m diameter, 1.6 m height)


Oo

Oo

—!— Irrigation ! Lateral

jcU

• Water Meter

o,o • 0.25 mm Plastic Barrier (1.2 m deep)

, 3 m . 9m

36 m

O Corrugated Plastic Sump ———0.25 mm PVC Flexible Liner

o o Observation Wells (1.7 m deep)

Figure 2 . Layout of the experimental plots at the Ames site (after Kalita and Kanwar, 1992)

Reservoir Pump 2

Irrigation l.inesi__c— 'Locatio"

Drainage Lines

Return

Drainage Pump

Figure 3 A schematic sketch of the dual-pipe subirrigation system at the Ankeny site (after Kalita and Kanwar, 1992)

35

30

25

20

IS

10

S

0

30

25

20

IS

10

5

0

30

25

20

15

10

5

0

• WTO - 0.3 m

S WTO . 0.6 m

B WTO « 0.9 m

35

30 -

• WTO - 0 ̂m

Q WTD • 0.6 m

B WTD " 0.9 m

DAP - 55

1-2 1.8 2.4

Depth from the soil surface, m

S

I

J

'•2 1.8 2,4 •


jure 4. Atrazine concentrations in piezometer water samples at the Ames site in 1992 (NS - no water sample available for analysis)

189


Figure 5. Atrazine concentrations in piezometer water samples at the Ames site in 1993 (NS - no sample available)

70

30*

25

20

15

10

5

0

25

20

15

10

S

0

25

20

15

10

5

0

WTD • 0.3 m

WTD - 0.6 m

WTD - 0.9 m

DAP - 39

DAP . 81

0.60 0.90 1.50


I

I

I WTD . 0.3 m

j WTD • 0.6 m

I WTD • 0.9 m

a

1 s s

a 0.60 0.90 1.50


6. Atrazine concentrations in suction tube water samples at the Ames site in 1992 (NS - no water sample available for analysis; ND - below detectable level)

00

35 30 25 20

16

10

5 0

30 26

20

16

to

5 0

30

26

20

16

10

6

0

30

26

20

16

10

S

0

30

26

20

15 10

6

0

191

0,30 0 80 0.90 1.80 2.10


7. Atrazine concentrations in suction tube water samples at the Ames site in 1993 (NS - no sample available)

1.8


Figure 8. Atrazine concentrations in piezometer water samples at the Ankeny site in 1992

(NS - no water sample available for analysis)

2B

20

IB

10

S

0

20

IB

10

B

0

20

IB

10

B

0

20

IB

10

6

0

20

16

10

B

0

193

Wro • 0.2 m

BS WTO - 0.0 m

WTO - 1.1 m DAP - 48

DAP • 08

DAP • 60


e 9. Atrazine concentrations in piezometer water samples at the Ankeny site in 1993 (NS - no sample available)

6

5

4

3

2

1

0

6

5

4

3

2

1

0

6

5

4

3

2

1

0

DAP • 38

a

0.90 ISO 2.10


|: S 2

: <

• WTO - 0.3 m

• WID - 0.6 m

H WTO - 0.9 m

NS

OJO 1.60 2.10


jre 10. Atrazine concentrations in suction tube water samples at the Ankeny site in 1992 (NS - no water sample available for analysis)

195

).60

Depth from the soil surfece, m

Figure 11. Atrazine concentrations in suction tube water samples at the Aniceny site in 1993 (NS - no sample available)

196

25

WTD " 0.2 m

WTD - 0.3 20

WTD - 0.6 m

16 WTD " 0.9 m

WTD - 1.1 m

10

S

0 0 0.6 2.6 1 1.6 2

Sampling depth from the soil surface, m

Figure 12a. Atrazine pattern in the soil profile as a function of water table depth (using pooled data)

8

WTD - 0.2

7

WTD - 0.3 m

6 WTD - 0.6 m

6 WTD " 0.8 m

4 WTD - 1.1 m

3

2

1

0 2.5 0 0.5 1 1.5 2

Sampling depth from the soil surface, m

Figure 12b. Alachlor pattern in the soil profile as a function of water table depth (using pooled data)

197

OVERALL CONCLUSIONS

This study was conducted to investigate the effects of different water

table management practices on plant physiological parameters, crop yield,

and groundwater quality. Data for 1992 and 1993 were collected from field

experiments conducted at two sites near Ankeny and Ames. At the Ankeny

s i t e , t h e w a t e r t a b l e d e p t h s w e r e m a i n t a i n e d a t 0 . 2 , 0 . 3 , 0 . 6 , 0 . 9 , 1 . 1 m

depths on 0.5 ha subirrigation field, and were maintained at 0.3, 0.6, and

0.9 m depths in lysimeter plots at Ames site. Measurements on different

physiological parameters (photosynthesis rate, stomatal conductance,

transpiration rate, intercellular 00% (Ci),' and canopy temperatures) were

taken on biweekly basis using the leaf chamber techniques, and those on

chlorophyll were taken using a SPAD-502 chlorophyll meter. Water samples

for NO3-N and pesticide analysis were collected on monthly basis by using

suction tubes and piezometers installed at different depths in the soil profile.

This study resulted in the following conclusions:

Physiological parameters and WTDs

Analysis of the data show that photosynthesis rates, stomatal

conductances, transpiration rates. Ci, canopy temperatures, and chlorophyll

exhibited similar relation with various WTDs during the growing season. The

198

values of these parameters were significantly affected at the 0.2 and 1.1m

depths as compared to 0.3, 0.6, and 0.9 m depths. The 0.3 WTD had

higher values of these physiological parameters, and these values decreased

with lowering the WTDs. In 1993, a extremely wet year, the values of these

parameters were lower than those observed in 1992 under all WTD

treatments.

The statistical analysis of the data showed that means for

photosynthesis between WTDs for Ames site were significantly different at

the 0.05 probability level during both years, whereas, those were not

significant for 1993 at Ankeny site. However, the means for chlorophyll

readings between WTDs were significantly different at the 0.05 probability

level for both years. The stomatal conductances were not significant at the

0.05 probability level.

Relationship between different parameters were developed by fitting



1993, at both experimental sites. Results of these analyses reveal that leaf

chlorophyll could be used as a good predictor of photosynthesis rates

regardless of water table treatment depth. Also, a strong positive relation

between stomatal conductance and transpiration rates was observed. The

regression analysis revealed that the transpiration rates were highly

199

dependent on the stomatal behavior.

NO3-N concentrations in groundwater

The average NO3-N concentrations in groundwater were reduced by

maintaining WTDs between 0.3 to 0.6 m during the two growing seasons.

The average concentrations in groundwater generally decreased with

lowering the WTD and time during the growing season. The highest NO3-N

concentrations in groundwater were mostly observed before the water table

treatments began. However, NO3-N concentrations were significantly

reduced after WTD treatments started, and in most cases these

concentrations in groundwater were less than 10 mg/L under the 0.3 m

WTD. Generally decreasing trend of NO3-N concentration in groundwater

with increasing sampling depth under two sampling methods was consistent

in both study years at both experimental sites.

The residual soil NO3-N concentrations seem to be concentrated in the

upper 0.15 to 0.6 m of the soil profile and that the NO3-N levels decreased

with the increased soil depth under all water table treatments. However, at

the 0.9 m WTD, the NO3-N concentrations were higher in comparison with

those observed at the 0.3 and 0.6 depths at the Ames site. At the Ankeny

site, also similar trends were observed, the highest concentrations were

observed at the 1.1 m WTD as compared to other four WTDs. The soil

200

samples collected at the time of harvest showed low values of NO3-N

concentrations with statistically significant differences in the amounts for the

different water table treatments.

Pesticide concentrations in groundwater

The average atrazine and alachlor concentrations in groundwater were

higher at the 0.9 and 1.1m WTDs In comparison with those observed at

0.2, 0.3, and 0.6 m WTDs. The average herbicide concentrations in

groundwater generally decreased with increased sampling depth and time.

Alachlor was not detected in many samples, however, atrazine was detected

in almost all water samples. The highest atrazine concentrations in

groundwater were mostly observed before the water table treatments began.

It was also observed that alachlor concentrations were lower than those of

atrazine under similar WTD treatments. However, atrazine concentrations

were significantly reduced after WTD treatments started which shows a

positive Influence of WTD practices In reducing pesticide concentrations.

Regression analysis show that atrazine concentrations In the soil profile

linearly decreased with increased sampling depth in the soil profile under all

WTD treatments. However, atrazine concentrations were always higher

under deep WTD treatment, and those decreased for shallow WTDs. The

best fit regression lines for alachlor data show that alachlor concentration in

201

the soil profile linearly decreased with increased soil depth under all WTD

treatments. Alachlor concentrations in most cases were higher under deep

WTD treatment, and those decreased under shallow WTDs. However,

trends between WTDs were not clear in some cases.

Corn yield

Corn yields significantly increased as water-table depths were lowered

from 0.2 to 1.1 m in 1992 and 1993 at the Ankeny site. A shallow water-

table depth of 0.2 to 0.3 m significantly reduced corn yield in wet season of

1993 at this site. In the lysimeter plots at Ames, crop yields were maximum

under a WTD of 0.9 m, whereas, in the subirrigation field, the highest yields

were observed at 1.1 m WTD. At the Ankeny site, the yields were also

affected by wet conditions in 1993 and were less than those observed

during 1992. However, at the Ames site, no significant differences in yields

were observed between the two study years. Findings of this study show

that, although, the 0.3 WTD is most suitable for groundwater quality control,

but is not appropriate if the highest crop yields are desired. For the highest

crop yields a WTD between 0.6 to 1.1 m would be desired. Therefore, the

results of this study conclude that a WTD between 0.6 to 0.9 m would be

the best water table management practice for crop productivity and

groundwater quality control.

202

RECOMMENDATIONS FOR FUTURE WORK

This study reports the effects of different water table management

practices on plant physiological parameters and on the movement of applied

chemicals on the groundwater quality. The data on plant physiological

parameters show that results were not conclusive for dry and wet seasons.

Even though, the effects of water table depths were clear for the individual

year. Therefore, further study is needed to develop the nature of the

relationship under different climatic conditions. Results of this study,

however, showed a strong relationship between physiological parameters

regardless of water table depth and climatic conditions. Further studies on

leaf chlorophyll and photosynthesis should be continued to determine

usefulness of relationships determined under this study between these

parameters. Also, N status in leaves as well as in the soil profile should be

determined at the time of chlorophyll measurements. This would provide

instantaneous information about nutrient uptake by plants under any water

table treatment depth, and would also help in determining the exact amount

of chemicals needed for plants at that particular growth stage.

Results of this study indicate the usefulness of water table

management practices to improve crop production and enhance groundwater

quality. However, this study shows that a compromise between crop yield

and groundwater could be made by maintaining water tables between 0.6

203

and 0.9 m from soil surface. Such a water table depth would minimize

leaching of chemical concentration in groundwater while maintaining crop

yield at an optimum level. Therefore, further water-table management

e x p e r i m e n t s a r e s u g g e s t e d w i t h w a t e r t a b l e d e p t h s b e t w e e n 0 . 6 a n d 1 . 1 m

in order to determine the appropriate WTD.

Results on NO3-N show that since a major portion of the applied

chemical had leached to deeper depths within the first few weeks of their

application (especially during the wet year, 1993), therefore it is strongly

recommended water table depth treatments should be started from the

beginning of the growing season. This would help prevent a significant

portion of chemical from leaching to deeper depths at the beginning of the

growing season. Also, soil and water samples should be collected right from

the time of planting and chemical application for a thorough understanding of

water table management effects on chemical transport to shallow

groundwater.

204

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ACKNOWLEDGEMENTS

Foremost, I am extremely grateful to most beneficent Allah, the Almighty,

who bestowed me good health, strength, and courage in accomplishing my

academic goals. Above all, I believe in Allah's boundless love and grace that

have filled my soul with hope and happiness and have Inspired me to live

through difficult times of my life.

I also wish to express my heartfelt gratitude and sincere appreciation to

those whose contributions collectively were of immeasurable value in my

educational pursuits. First, I wish to extend profound thanks and sincere

appreciation to my major professor. Dr. Rameshwar S. Kanwar, for his superb

guidance, constructive suggestions, timely help, and heartfelt cooperation and

counseling which enabled me accomplishing the objective of this research in

professional and scholarly manner. My gratitude for him is forever.

I would like to extend special appreciation and thanks to Drs. Stewart W.

Melvin, Thomas S. Colvin, Thomas E. Fenton, and Theodore B. Baily for serving

as members on my graduate study committee and for their professional

assistance. I must also express gratitude to all my primary and secondary

school, college, and university teachers at Sindh, Pakistan, for instilling in me

values and ideas that inspire me every day.

My father (who passed away on December 8, 1993) was the constant

221

source of support and encouragement throughout my study period. His

support, encouragement, unreserved love, and sacrifices helped me to reach

this stage In my career. I express the deepest sense of appreciation to my

father's soul late Gul Muhammad and my mother's soul late Sultani Mirjat and

dedicate this piece of work to both of them.

Words can not express my feeling for my wife Sahibzadi, daughter Sahar,

and sons Khadim, Mukhtiar, and Zahid, who suffered from not having husband

and a father at home for long three and half years. Their devotion and sacrifice

have been unflinching. I owe them all my achievements. I also extend thanks

to my brothers, sisters, and other relatives especially my cousins and brother-in-

laws for their moral support and everything they did for me during this study

period.

My dear friends/brothers Mr. Alimuddin K. Brohi, Mr. Khadim Hussain

Mirjat, Mr. Muhammad Luqman Mirjat, Dr. Karam All Mirjat, Mr. Mir Khan

Mirjat, Mr. Ghulam Nabi Mirjat, Mr. All Gohar Mirjat, Mr. Muhammad Hayat

Nizamani, Mr. Hafeezullah Baluch, and several others who were extremely

helpful in many ways for which I am grateful to them.

My special thanks to Mr. Loren Shiers for analysis of soil and water

samples for my research. Thanks to Mr. Carl Pedarson for his extreme

cooperation and full assistance in carrying out the field work. The help of Mr.

Ashok Verma in collection of the field data is acknowledged.

222

Thanks to many of my friends and fellow graduate students in the

Department of Agricultural and Biosystems Engineering for their cooperation and

handy help during this study. I appreciate all the help and encouragement

received from Dr. Bherulal T. Devrajani during the course of this study.

Very special thanks are also expressed to Dr. Abdul Qadir Mughul and

Mr. Imam Bux Koondhar, Professors, Sindh Agriculture University Tandojam

Pakistan, for their keen interest in my professional development. Dr. Mughul's

timely help in many official and un-official matters back in Pakistan is

particularly acknowledged.

I extend my sincere thanks to Sindh Agriculture University Tandojam,

Government of Pakistan, and USAID for their financial support in sponsoring my

studies at Iowa State University without whose support I would have never

been able to achieve my career goals. As s scholarship recipient, I feel honored

and grateful. I recognize the valuable assistance from Department of

Agricultural and Biosystems Engineering, Graduate College, College of

Agriculture International Agriculture Program office, and office of the

International Students and Scholars, Iowa State University for providing me an

excellent educational environment and a pleasant stay in Ames, Iowa.

Last but not least, my gratitude extends to the villagers of Hayat Khan

Nizamani and Bahar Khan Mirjat for sharing part of their life with me. Their

sincere cooperation made this study possible.

223

APPENDIX: SUMMARIZED DATA ON PLANT PHYSIOLOGICAL

PARAMETERS NO3-N AND PESTICIDE

224

Table 1. Mean photosynthesis rate (// mole m'^ s'^) under different water table depths for Ankeny and Ames sites in 1992 and 1993

Water table depth, m

Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 29.8 29.7 28.0 28.6 28.3 1992 56 31.4 35.4 31.5 31.9 30.4

71 33.1 44.7 42.8 38.3 34.3 86 38.0 52.0 47.4 42.9 39.7 98 37.6 39.3 36.9 35.1 34.4 110 31.2 30.5 31.4 31.9 31.5 120 23.4 22.7 22.1 20.5 17.9 130 15.9 21.2 18.3 19.0 15.5

1993 40 21.9 23.7 24.2 24.3 21.1 56 20.9 29.9 28.5 22.1 22.3 71 22.6 32.1 30.1 29.8 23.7 86 34.0 42.0 40.6 38.6 35.6 98 26.7 30.6 29.4 28.5 25.4 110 15.8 18.4 19.9 17.5 16.3

Ames 40 29.6 28.5 29.9 1992 56 29.9 28.4 30.0

71 38.5 34.6 31.4 86 47.7 39.8 35.0 98 40.9 30.0 28.8 110 25.2 25.5 22.2 120 12.9 15.2 18.1 130 8.8 7.1 6.3

1993 40 23.4 23.8 23.1 56 30.1 30.7 27.8 71 35.6 31.3 29.5 86 39.0 34.6 30.2 98 23.5 22.9 24.1 110 12.1 11.9 10.1

DAP - Days after planting

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Table 2. Mean stomatal conductance (mole m'^ s'^) under different water table depths for Ankeny and Ames sites in 1992 and 1993


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 0.33 0.32 0.29 0.33 0.26 1992 56 0.50 0.67 0.62 0.52 0,46

71 0.58 0.83 0.72 0.65 0.60 86 0.60 0.94 0.76 0.70 0.63 98 0.62 0.74 0.71 0.66 0.63 110 0.47 0.66 0.63 0.61 0.56 120 0.45 0.47 0.46 0.45 0.42 130 0.41 0.37 0.43 0.45 0.40

1993 40 0.55 0.54 0.52 0.59 0.51 56 0.63 0.71 0.63 0.72 0.62 71 0.70 0.85 0.77 0.76 0.65 86 0.72 0.93 0.72 0.79 0.71 98 0.43 0.46 0.42 0.45 0,38 110 0.33 0.31 0.31 0.33 0.29

Ames 40 0.36 0.31 0.34 1992 56 0.61 0.56 0.51

71 0.69 0.63 0.60 86 0.77 0.72 0.66 98 0.68 0.69 0.67 110 0.45 0.44 0.41 120 0.34 0.33 0.28 130 0.29 0.26 0.23

1993 40 0.39 0.41 0.41 56 0.57 0.52 0.45 71 0.72 0.74 0.66 86 0.94 0.87 0.79 98 0.60 0.53 0.56 110 0.44 0.42 0.35


226

Table 3. Mean transpiration rate (mm/day) under different water table depths for Ankeny and Ames sites in 1992 and 1993


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 5.1 7.3 6.1 5.8 4.6 1992 56 7.4 10.8 8.3 8.6 4.7

71 9.0 14.6 12.0 13.1 10.0 86 13.9 22.8 16.2 16.3 12.7 98 10.1 13.5 11.1 10.4 10.0 110 5.1 8.7 7.2 6.9 4.6 120 4.9 6.0 5.5 5.8 3.8 130 2.5 4.4 4.2 4.1 2.9

1993 40 4.9 5.7 6.5 5.3 4.8 56 6.2 8.4 8.0 7.3 5.8 71 7.7 8.6 10.2 10.3 7.8 86 12.3 12.7 13.5 11.7 10.1 98 2.8 4.1 5.0 4.5 2.5 110 1,3 3.8 3.7. 4.1 1.2

Ames 40 5.2 4.9 4.4 1992 56 11.3 10.0 8.8

71 16.8 14.2 12.3 86 22.0 14.7 11.1 98 14.0 12.4 7.3 110 9.3 8.8 3.1 120 5.4 4.9 1.6 130 4.0 3.2 1.5

1993 40 5.7 4.7 5.5 56 10.8 8.2 6.9 71 14.8 11.2 10.6 86 15.1 13.6 11.2 98 11.5 9.9 8.8 110 2.1 2.0 2.1


227

Table 4. Mean Intercellular CO2 concentration (ppm) under different water table depths for Ankeny and Ames sites in 1992 and 1993


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 204.2 187.2 214.1 206.4 208.0 1992 56 211.4 228.3 224.9 220.0 214,5

71 246.1 265.8 252.8 243.4 237.7 86 242.8 255.0 249.8 238.0 233.1 98 221.5 246.4 244.3 238.3 229.2 110 185.8 227.5 211.7 207.7 207.2 120 209.1 231.8 221.9 223.4 225.6 130 206.2 204.3 205.8 206.3 204,9

1993 40 224.6 257.5 231.0 234.5 232.0 56 221.3 238.9 228.9 220.2 228.1 71 224.8 257.6 245.5 234.9 232.1 86 234.8 264.0 266.2 259.8 238.1 98 213.8 219.2 205.8 221.9 212.1 110 180.7 196.2 190.2 180.9 174.7

Ames 40 240.0 239.2 268.3 1992 56 333.2 269.7 341.1

71 303.3 314.2 310.6 86 356.6 339.3 350.2 98 282.9 242.3 201.4 110 280.6 265.1 232.4 120 290.1 281.2 274.8 130 241.8 234.3 229.0

1993 40 206.4 206.7 199.9 56 223.9 220.7 219.6 71 283.5 277.3 269.3 86 282.1 278.1 279.6 98 226.7 219.8 218.5 110 202.2 198.5 204.6


228

Table 5. Mean chlorophyll content (SPAD units) under different water table depths for Ankeny and Ames sites in 1992 and 1993

Site DAP


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 42.7 43.7 43.4 43.2 41.9 1992 56 43.3 50.2 50.1 48.7 46.2

71 48.5 53.7 51.4 50.5 49.7 86 50.9 55.3 53.8 52.5 50.3 98 46.7 53.6 50.4 50.7 45.7 no 39.7 46.7 44.2 42.9 39.3 120 36.2 36.8 35.4 34.3 33.7 130 35.8 36.5 35.0 34.0 33.3

1993 40 41.2 41.8 40.8 41.5 41.1 56 42.4 46.1 44.2 44.0 43.4 •71 39.4 47.7 46.7 43.7 42.3 86 43.4 51.6 51.2 50.9 44.8 98 38.8 51.9 48.7 51.7 42.8 110 30.3 45.7 41.3 41.9 33.2

Ames 40 41.7 43.4 43.2 1992 56 47.1 46.7 45.4

71 54.8 51.9 46.6 86 57.7 54.0 49.1 98 55.6 52.6 48.1 110 52.7 51.1 44.8 120 47.3 45.9 41.5 130 39.5 39.7 35.9

1993 40 39.5 41.4 37.8 56 44.8 44.7 38.9 71 50.9 49.2 42.6 86 53.3 50.1 40.1 98 46.3 41.0 37.3 110 41.3 37.7 34.4


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Table 6. Mean air temperature (°C) under different water table depths for Ankeny and Ames sites in 1992 and 1993

Site DAP


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 29.0 31.8 30.4 30.7 29.8 1992 56 26.8 30.3 28.5 29.1 27.8

71 31.2 31.4 31.5 32.1 31.5 86 27.9 28.6 29.6 29.0 28.3 98 33.3 31.3 31.6 30.9 30.9 110 31.5 28.5 29.8 28.9 30.3 120 27.5 28.0 27.1 28.6 27.2 130 26.7 23.9 27.8 25.8 27.0

1993 40 29.1 29.5 30.3 29.7 29.6 56 28.6 27.8 27.8 26.4 26.1 71 28.8 29.7 30.3 30.2 30.0 ' 86 31.3 31.6 31.5 29.6 30.9 98 26.2 25.7 25.5 25.7 25.8 110 21.0 21.8 21.6 24.0 23.8

Ames 40 29.5 29.7 29.9 1992 56 34.9 33.5 32.4

71 31.5 31.0 30.4 86 28.7 28.2 26.7 98 23.4 23.4 24.4 110 25.3 24.6 24.1 120 21.7 23.6 24.5 130 22.1 21.2 22.4

1993 40 28.4 29.0 28.4 56 31.9 31.6 31.6 71 29.7 29.4 29.1 86 31.9 31.7 31.2 98 21.2 22.7 23.2 110 16.9 17.3 17.3


230

Table 7. Mean leaf tennperature (°C) under different water table depths for Ankeny and Ames sites in 1992 and 1993

Site DAP


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 28.4 30.3 29.7 29.9 29.0 1992 56 26.2 28.7 27.5 28.0 27.2

71 31.1 30.7 31.1 31.6 31.2 86 27.9 28.1 29.5 28.8 28.1 98 33.6 31.0 31.5 30.7 31.2 110 31.9 28.7 29.9 29.3 30.5 120 28.0 28.2 27.3 28.8 27.4 130 27.2 24.1 27.7 25.9 27.1

1993 40 29.2 29.6 30.4 29.8 29.7 56 28.1 27.3 27.2 26.0 25.8 71 29.0 29.6 30.1 29.9 30.1 86 31.7 31.8 31.7 29.9 31.3 98 26.7 26.0 25.8 26.0 26.2 110 21.8 22.3 21.9 24.3 24.3

Ames 40 29.3 29.5 29.7 1992 56 33.3 32.5 31.7

71 30.6 30.4 30.0 86 28.1 27.7 26.7 98 22.9 23.0 24.5 110 25.0 24.3 24.3 120 21.4 23.4 24.8 130 21.9 21.1 22.8

1993 40 28.5 29.1 28.5 56 31.1 31.0 31.4 71 29.1 29.2 29.2 86 31.5 31.3 31.7 98 21.2 22.4 23.9 110 17.2 17.8 17.8


231

Table 8. Mean leaf-air temperature differentials (°C) under different water table depths for Ankeny and Ames sites in 1992 and 1993


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 -0.6 -1.4 -0.7 -0.8 -0.8 1992 56 -0.6 -1.6 -1.0 -1.1 -0.6

71 -0.1 -0.6 -0.5 -0.5 -0.3 86 0.1 -0.4 -0.2 -0.2 -0.2 98 0.3 -0.3 -0.1 -0.1 0.3 110 0.4 0.2 0.1 0.3 0.2 120 0.4 0.2 0.2 0.1 0.3 130 0.6 0.3 -0.1 0.1 0.1

1993 • 40 0.1 0.1 0.1 0.1 0.1 56 -0.5 -0.5 -0.5 -0.5 -0.3 71 0.2 -0.2 -0.2 -0.3 0.2 86 0.4 0.2 0.2 0.2 0.4 98 0.5 0.3 0.3 0.3 0.4 110 0.8 0.5 0.4 0.3 0.5

Ames 40 -0.2 -0.2 -0.2 1992 56 -1.6 -1.0 -0.7

71 -0.9 -0.7 -0.5 86 -0.6 -0.5 -0.0 98 -0.5 -0.4 0.1 110 -0.4 -0.4 0.1 120 -0.3 -0.3 0.3 130 -0.2 -0.1 0.4

1993 40 0.1 0.1 0.0 56 -0.8 -0.7 -0.2 71 -0.6 -0.2 0.2 86 -0.5 -0.4 0.5 98 -0.0 -0.3 0.7 110 0.3 0.5 0.5


232

Table 9. Mean plant height (cm) under different water table depths for Ankeny and Ames sites in 1992 and 1993

Site DAP


Site DAP 0.2 0.3 0.6 0.9 1.1

Ankeny 40 69.7 67.5 60.9 58.1 50.0 1992 56 137.9 126.2 133.8 146.5 134.3

71 186.3 179.2 187.1 203.5 184.6 86 246.3 249.7 247.7 255.3 252.7 98 249.7 255.3 250.7 259.3 253.7 110 249.7 255.3 250.7 259.3 253.7 120 249.7 255.3 250.7 259.3 253.7 130 249.7 255.3 250.7 259.3 253.7

1993 40 90.1 105.8 100.5 86.5 103.8 56 133.8 160.6 152.4 127.0 144.2 71 154.9 198.1 186.5 165.4 168.9 86 210.0 248.6 230.5 222.2 217.8 98 217.8 249.6 234.7 222.8 218.8 110 217.8 249.6 234.7 222.8 218.8

Ames 40 57.9 59.1 56.1 1992 56 112.0 115.4 111.8

71 168.0 175.7 165.7 86 234.3 236.0 233.3 98 242.3 241.0 236.7 110 242.3 241.0 236.7 120 242.3 241.0 236.7 130 242.3 241.0 236.7

1993 40 101.1 104.4 99.6 56 154.9 153.8 137.7 71 205.1 205.2 179.8 86 240.4 239.8 216.1 98 247.3 245.2 225.2 110 247.3 245.2 225.2


233

Table 10. NO3-N concentrations (mg/L) In piezometer water samples for 1992 and 1993



Year DAP WTD, m 1.2m 1.8m 2.4m DAP WTD, m 1.2m 1.8m 2.4m

1992 39

55

81

113

141

169

1993 48

68

90

116

144

0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9

0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9 0.3 0.6 0.9

95.5 21.6 7.2 38 0.2 9.4 7.5 2.5 NS 41.2 19.2 0.6 11.7 9.9 7.0

212.0 125.7 54.8 1.1 23.8 16.9 8,5 18.1 3.9 6.2 54 0.2 10.3 5.9 3.7 19.5 7.7 19.3 0.6 10.5 6,0 4,9 27.5 25.4 19.5 1.1 16.4 6.7 6.3 2.2 2.1 1.9 82 0.2 4.7 4,4 2.0 3.8 2.9 1.1 0.6 11.3 7.8 4,0 9.8 7.9 5.3 1.1 12.0 6,7 4.5 8.6 2.2 1.4 112 0.2 2.1 1.9 1,6 8.6 4.2 2.6 0.6 4.1 3.6 3.5 11.1 6.6 4.5 1.1 6.9 5.2 4.7 1.4 0,4 2.6 140 0.2 2.7 3.1 2.0 1.9 2.5 2.1 0.6 NS NS NS 5.9 4.0 3.1 1.1 4.9 5.5 3.3 NS 5.9 6.2 168 0.2 1.6 1.6 4.5 NS 5.1 4.9 0.6 4.5 5.1 3.3 NS 5.6 4.5 1.1 NS NS NS

27.8 18.6 15.7 48 0.2 31.0 31.0 8.6 20.8 18.9 12.6 0.6 40.9 32.2 17,8 53.6 38.3 34.1 1.1 103.0 30.6 27.5 12.3 7.3 3.9 68 0.2 9.7 5.2 2.2 5.0 2.8 3.2 0.6 13.3 8.3 3.5 29.5 17.2 3.4 1.1 24.0 9.0 8.2 3.8 2.4 1.7 88 0.2 5.8 4.5 1.0 3.6 2.3 1.1 0.6 6,7 5.8 5.5 8.7 6.1 3.2 1.1 11.7 7.1 4.5 1.6 2.2 1.7 116 0.2 3.4 2.8 0.4 1.0 2.0 2.2 0.6 5.9 4.2 1.9 3.9 3.3 3.0 1.1 8.8 8.4 3.5 0.8 0.8 0.3 144 0.2 2.0 NS 1.3 2.6 1.0 0.6 0.6 2.7 3.1 0,1 8.7 2.1 1.8 1.1 6.6 3.0 1.4

DAP - days after planting; WTD - water table depth; NS - no water sample available for analysis

Table 11. NO3-N concentrations (mg/L) in suction tube samples for 1992 and 1993


Suction tube depth Suction tube depth

DAP WTD, m 0.3 m 0.6 m 0.9 m 1.5 m 2.1 m DAP WTD, m 0.9 m 1.5 m 2.1 m

39 0.3 NS NS NS 0.0 14.3 38 0.3 6.4 6.4 3.9 0.6 NS NS NS 16.4 3.9 0.6 11.0 5.8 6.2 0.9 NS NS 120.9 4.1 5.3 0.9 10.5 7.3 7.1

55 0.3 30.3 22.0 22 .2 4.2 4.9 54 0.3 3.6 2.2 2.1 0.6 63.8 48.6 47.2 2.7 0.8 0.6 5.0 3.8 NS 0.9 115.3 108.0 92.8 14.3 3.7 0.9 6.8 2.6 1.9

81 0.3 9.1 6.7 3.5 3.3 0.8 82 0.3 2.6 2.6 2.4 0.6 11.8 10.0 10.8 2.3 1.8 0.6 6.4 3.4 2 .4 0.9 19.2 10.1 11.4 2.7 1.9 0.9 9.2 4.5 3.5

113 0.3 3.3 1.0 0.5 0.6 1.2 112 0.3 3.0 1.9 1.6 0.6 7.1 2 .6 1.9 1.7 1.7 0.6 4.4 3.3 1.8 0.9 7.1 4.6 4.3 0.7 0.8 0.9 4.6 4.1 2.7

141 0.3 3.2 1.4 NS 0.2 0.8 140 0.3 1.3 0.2 NS 0.6 5.1 1.2 2.3 3.4 2.1 0.6 NS NS NS 0.9 NS NS 4.0 3.4 1.5 0.9 5.3 1.9 0.1

169 0.3 NS NS NS 0.7 0.2 168 0.3 4.5 1.0 NS 0.6 6.7 NS 1.1 1.1 0.8 0.6 4.9 1.5 NS 0.9 10.4 NS 9.8 1.4 0.3 0.9 7.2 NS NS

48 0.3 16.0 5.1 4.7 1.4 0.8 48 0.3 19.6 3.3 0.9 0.6 21.6 17.5 10.1 2.5 1.6 0.6 49.9 4.2 1.2 0.9 67.1 95.5 40.9 1.0 3.2 0.9 50.0 11.5 1.5

68 0.3 3.6 3.5 3.2 1.3 1.0 68 0.3 2.5 1.5 1.4 0.6 5.1 3.7 4.0 2.8 1.6 0.6 2.8 1.6 1.5 0.9 7.2 6.6 6.2 3.3 3.2 0.9 3.5 2.6 2.1

90 0.3 3.2 1.4 1.8 1.6 0.3 88 0.3 0.5 0.4 0.6 0.6 4.5 1.9 1.3 1.5 0.7 0.6 2.6 1.7 1.6

1992

1993

Table 11 (continued)

116

144

0.9 0.3 0.6 0.9 0.3 0.6 0.9

6.8 1 . 8 5.0 5.1 1 .8 3.3 6.0

4.5 1.7 2.9 3.2 NS 3.1 3.5

2 . 1 1.4 1.1 2.4 1.2 1.4 2.3

2.8 1.1 0.7 1.5 0.5 0 .8 2 . 1

DAP - days after planting; WTD - water-table depth

0.4 0.1 0.5 1.6 0.4 0.8 2.0

116

144

0.9 0.3 0.6 0.9 0.3 0.6 0.9

3.7 3.3 4.7 5.9 1.3 1.5 6.3

3.4 1.7 2 . 1 2.5 0.9 2.2 2.4

2.5 0.4 1.0 2.1 0.3 2.1 2.6

M W Ol

Table 12. Atrazine concentrations i j j g /L ) in suction tube and piezometer water samples at the Ames site for 1992 and 1993

Suction tube water samples

Year

Sampling depth

Piezometer water samples

Sampling depth

DAP WTD. m 0.3m 0.6m 0.9m 1.5m 2.1m DAP WTD, m 1.2m 1.8m 2.4m

39 0.3 NS NS NS NS NS 39 0.3 1.8 7.2 0.4 0.6 NS NS NS 24.4 16.5 0.6 NS 9.7 8.6 0.9 NS NS NS 66.8 5.6 0.9 1.4 6.1 6.1

55 0.3 4.9 ND 8.7 18.2 2.9 55 0.3 ND 4.2 6.0 0.6 6.2 4.0 42.1 15.2 1.7 0.6 3.2 8.5 8.6 0.9 26.2 15.0 23.0 12.2 10.9 0.9. 18.3 33.9 14.5

81 0.3 5.5 7.1 11.2 6.3 3.7 81 0.3 3.9 2.1 2.4 0.6 7.9 25.0 10.0 4.8 3.1 0.6 5.2 3.4 4.1 0.9 6.3 26.0 12.4 7.6 3.2 0.9 7.2 5.0 4.4

113 0.3 1.1 ND 3.4 3.5 1.4 113 0.3 2.1 0.9 3.2 0.6 0.9 4.8 4.5 3.0 1.5 0.6 1.2 2.1 2.0 0.9 3.8 6.3 3.3 8.7 1.4 0.9 10.0 0.6 4.4

141 0.3 1.9 0.9 8.0 0.7 0.2 141 0.3 NS NS NS 0.6 NS NS NS 1.1 ND 0.6 NS 2.3 1.1 0.9 NS NS NS NS NS 0.9 5.4 1.3 3.9

169 0.3 NS NS NS NS 1.3 169 0.3 NS 1.2 3.3 0.6 2.4 3.2 0.9 1.1 NS 0.6 NS 1.4 2.8 0.9 NS NS NS 4.6 2.0 0.9 NS 4.5 2.4

48 0.3 19.1 2.8 26.0 9.1 12.2 48 0.3 1.0 0.7 1.5 0.6 20.9 17.5 21.4 8.1 5.6 0.6 1.8 1.2 22.5 0.9 19.9 31.8 60.3 14.8 10.9 0.9 0.8 128.8 626.1*

68 0.3 3.0 7031.8 18.5 4.5 7.2 68 0.3 1.7 1.5 2.9 0.6 4.8 13.6 20.1 2.2 6.0 0.6 7.0 3.3 11.7 0.9 9.8 13.5 33.3 18.7 9.0 0.9 8.0 29.8 20.1

1992

1993

Table 12 (continued)

90 0.3 3.3 NS 7.0 3.6 4.6 90 0.3 2.0 11.6 4.5 0.6 1.2 23.7 6.7 14.3 4.0 0.6 6.0 7.0 7.5 0.9 12.6 7.9 17.2 12.0 9.5 0.9 8.6 20.9 16.0

116 0.3 1.1 NS 2.9 3.9 2.5 116 0.3 5.2 5.7 3.2 0.6 0.9 18.2 8.3 13.1 2.8 0.6 6.5 7.8 5.1 0.9 7.8 17.8 4.3 9.6 3.0 0.9 8.4 14.9 8.9

144 0.3 NS NS NS 3.7 1.9 144 0.3 NS 2.7 NS 0.6 0.7 NS NS 7.8 2.8 0.6 NS 6.9 3.0 0.9 3.7 NS 11.0 7.5 2.6 0.9 NS 8.8 2.8

DAP - days after planting; WTD - water-table depth; NS - no water sample available for analysis; ND - non detectable level; * - outlier fo

w

238

Table 13. Atrazine concentrations (//g/L) Suction tube and piezometer water samples at the Ankeny site in 1992 and 1993


Year DAP WTD,

Sampling depth

DAP WTD.

Sampling depth

Year DAP WTD, m 0.9m 1.5m 2.1m DAP WTD. m 1.2m 1.8m 2.4m

1992 38 0.3 114.6 22.7 0.1 38 0.2 1.5 8.8 1.6 0.6 14.4 5.1 6.3 0.6 7.5 2.6 1.4 0.9 36.2 14.0 9.8 1.1 NS NS 17.5

54 0.3 5.9 NS 1.6 54 0.2 10.1 3.2 1.1 0.6 NS 6.6 NS 0.6 13.6 19.9 0.5 0.9 NS NS 5.0 1.1 19.6 11.0 21.6

82 0.3 1.6 2.0 0.4 82 0.2 2.4 1.2 0.5 0.6 NS 1.1 1.7 0.6 6.5 6.2 0.3 0.9 2.3 0.1 2.6 1.1 7.5 1.5 5.8

112 0.3 0.5 0.8 0.2 112 0.2 0.6 0.6 NS 0.6 4.9 0.9 1.2 0.6 1.9 1.7 0.3 0.9 2.1 1.7 0.2 1.1 5.6 1.6 2.1

140 0.3 0.3 NS 0.6 140 0.2 0.5 0.5 0.2 0.6 NS NS NS 0.6 NS NS 0.2 0.9 NS NS NS 1.1 1.1 0.5 NS

168 0.3 0.2 NS NS 168 0.2 NS 0.5 0.2 0.6 NS NS NS 0.6 NS 1.7 0.2 0.9 NS NS NS 1.1 NS NS NS

1993 48 0.3 2.7 1.5 0.5 48 0.2 12.0 NS 2.9 0.6 4.5 0.6 10.2 0.6 2.9 1.5 5.8 0.9 36.4 3.4 1.4 1.1 10.9 21.7 5.4

68 0.3 2.5 1.1 0.8 68 0.2 2.8 8.5 4.7 0.6 5.2 NS 1.5 0.6 5.2 611.2 5.9 0.9 30.5 3.1 2.6 1.1 22.2 21.3 16.6

88 0.3 NS 0.9 0.4 88 0.2 1.8 5.7 3.6 0.6 NS 2.7 0.6 0.6 8.0 7.2 6.4 0.9 1.9 16.4 0.5 1.1 Ns 23.0 4.1

116 0.3 1.0 0.9 0.6 116 0.2 1.2 3.0 1.2 0.6 1.3 NS 0.7 0.6 1.7 7.1 6.7 0.9 2.3 2.6 0.8 1.1 11.5 11.2 1.9

144 0.3 0.7 0.7 0.3 144 0.2 NS 2.8 NS 0.6 NS NS 0.4 0.6 3.9 5.2 NS 0.9 NS 0.7 NS 1.1 NS 9.3 2.0

DAP - days after planting; WTD - water table depth; NS - no water sample available for analysis

239

Table 14. Raw data on different plant physiological parameters at Ames and Ankeny sites for 1992 and 1993

Data for Ames site during 1992

DAP WTD REP PHO COND CHL CI T-Air T-Leaf

40

56

71

86


98

0.3 0.3 0.3 0 . 6 0 . 6 0.6 0.9 0.9 0.9 0.3 0.3 0.3 0 . 6 0.6 0 . 6 0.9 0.9 0.9 0.3 0.3 0.3 0.6 0 . 6 0 . 6 0.9 0.9 0.9 0.3 0.3 0.3 0.6 0.6 0.6 0.9 0.9 0.9 0.3 0.3 0.3 0 . 6 0 . 6

1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 1 2

29.7 30.1 29.1 31.4 26.7 27.6 34.2 25.2 30.3 26.5 32.0 31.1 27.8 23.9 33.6 27.6 31.2 31.3 39.1 37.3 39.1 34.6 32.5 36.7 26.2 32.3 35.6 47.8 47.8 47.4 37.4 39.3 42.8 39.4 31.9 33.8 39.3 40.8 42.8 28.5 34.1

0.44 0.38 0.27 0.46 0.31 0.39 0.32 0.41 0.21 0 .66 0.48 0.70 0.39 0 .62 0.66 0.46 0.49 0.57 0.60 0.67 0 . 8 0 0.71 0.58 0 .61 0.71 0.46 0.63 1.13 0 . 8 0 0.56 0.70 0.50 0.95 0 .62 0.51 0.84 0.73 0.67 0.65 0.76 0.69

46.9 38.4 39.7 40.4 43.8 46.2 41.9 43.2 44.6 48.9 44.6 47.9 44.6 46.1 49.5 44.4 43.7 48.0 54.3 55.2 54.9 54.5 50.2 50.9 47.9 46.0 45.8 57.9 56.1 59.0 53.6 54.5 53.9 46.1 48.3 53.0 56.2 55.0 55.7 51.7 55.5

249.0 234.7 236.3 237.1 254.9 225.4 257.7 276.3 271.0 367.4 254.7 377.4 249.4 270.5 289.1 403.3 326.0 294.1 296.5 317.9 295.4 323.7 316.3 302.6 300.3 314.6 316.9 366.0 356.1 347.7 339.4 338.1 340.6 341.9 364.6 344.2 306.2 326.1 216.5 213.6 314.2

29.4 29.5 29.6 29.9 29.8 29.4 29.7 29.7 30.2 36.3 35.5 34.7 34.3 33.3 32.8 33.8 32.7 30.7 29.6 30.4 31.3 31.3 31.1 30.7 30.9 31.4 32.1 25.7 27.5 27.8 28.3 28.4 27.2 29.0 29.3 27.7 24.8 24.3 24.1 23.3 23.4

29.0 28 .8 29.1 29.6 29.0 29.3 29.9 29.9 29.6 33.3 33.0 33.6 32.8 32.5 32.2 33.4 31.9 29.9 29.1 29.7 30.7 30.9 30.6 29.8 29.9 30.5 31.4 25.8 26.9 27.3 28 .1 27.3 27.8 27.9 2 8 . 2 27.2 24.5 23.8 23.7 23.0 22.9

240


0.6 3 27.3 0.63 50.6 199.2 23.9 23.0 0.9 1 31.2 0.76 41.9 153.7 23.5 23.4 0.9 2 27.8 0.55 47.2 232.2 23.5 23.1 0.9 3 27.3 0.68 55.2 218.2 23.1 22.6

110 0.3 1 25.2 0.46 53.5 276.3 24.8 24.8 0.3 2 23.7 0.54 53.5 276.1 24.4 24.1 0.3 3 26.6 0.34 51.2 289.5 23.5 23.1 0.6 1 24.6 0.61 51.2 259.8 24.3 24.2 0.6 2 25.6 0.43 52.1 264.5 25.2 24.6 0.6 3 26.2 0.30 50.0 271.1 24.5 24.0 0.9 1 21.6 0.34 39.3 230.7 25.0 25.0 0.9 2 24.0 0.55 45.1 243.5 25.7 25.5 0.9 3 21.0 0.33 50.2 223.1 25.3 24.4

120 0.3 1 7.8 0.30 49.5 308.4 21.0 20.5 0.3 2 11.8 0.33 48.0 276.4 21.7 21.2 0.3 3 19.0 0.39 44.5 285.6 22.5 22.4 0.6 1 14.8 0.35 47.4 274.6 23.8 23.4 0.6 2 15.8 0.39 47.5 288.0 23.9 23.6 0.6 3 15.1 0.23 42.8 280.9 23.3 23.1 0.9 1 17.4 0.27 39.2 252.2 24.3 24.9 0.9 2 16.9 0.28 42.2 279.9 24.7 24.9 0.9 3 20.0 0.30 43.1 292.4 24.9 24.5

130 0.3. 1 6.9 0.28 43.3 257.0 23.0 22.8 0.3 2 7.1 0.27 40.4 230.3 22.2 22.1 0.3 3 12.4 0.32 34.9 238.0 22.5 22.4 0.6 1 6.0 0.22 39.0 228.8 21.8 21.6 0.6 2 7.2 0.27 40.2 240.0 22.2 22.0 0.6 3 7.9 0.30 40.0 234.1 22.3 22.1 0.9 1 5.4 0.20 33.5 210.2 21.3 21.1 0.9 2 7.4 0.25 37.2 233.3 21.2 21.1 0.9 3 6.0 0.25 37.1 243.7 21.1 20.9

40

56


0.3 1 23.3 0.32 39.8 188.0 28.6 28.7 0 .3 2 20.3 0.42 42.8 211.0 29.0 29.1 0 .3 3 26.6 0.44 35.9 220.0 27.6 27.7 0 .6 1 21.9 0.51 40.2 209.6 29.0 29.2 0 ,6 2 25.7 0.34 41.7 195.5 29.2 29.2 0, .6 3 23.9 0.38 42.2 215.1 28.8 28.9 0, ,9 1 23.6 0.41 36.2 211.0 28.6 28,7 0, ,9 2 21.8 0.35 36.5 225.9 28.4 28.5 0, ,9 3 23.9 0.46 40.6 162.8 28.2 28.2 0, 3 1 30.9 0.64 42.6 215.7 32.4 31.8 0, 3 2 27.6 0.51 47.3 224.1 31.7 30.8 0. 3 3 31.7 0.55 44.5 231.8 31.5 30.8 0. 6 1 35.3 0.47 41.9 216.6 31.8 30.8 0. 6 2 27.0 0.57 44.8 230.7 31.5 31.1

241


47.2 214.9 31.6 31.0 37.4 220.0 31.7 31.4 35.3 213.9 31.1 30.9 44.0 224.8 32.0 31.8

71 0.3 1 35.3 0.66 49.5 273.6 29.4 28.8 52.7 292.5 29.9 29.2 50.6 284.4 29.8 29.2 49.6 273.9 29.5 29.4 46.6 279.4 29.4 29.4 51.6 278.7 29.3 28.9 41.9 267.5 29.7 29.7 41.1 278.5 28.9 29.0 44.9 262.0 28.7 29.0

86 0.3 1 41.2 0.95 52.9 309.2 31.8 31.2 54.2 284.4 31.6 31.0 53.0 252.6 32.4 32.3 45.3 289.0 31.7 31.9 51.1 276.6 31.5 30.9 54.0 268.7 31.9 31.2 38.4 283.8 31.6 31.8 38.4 285.5 31.1 31.7 43.6 269.6 30.9 31,6

98 0,3 1 24.2 0.59 49.5 227.9 20.8 21.0 48.1 248.0 21.7 21.8 43.4 204.1 21.2 20.9 36.2 213.8 22.9 22.6 39,2 223.0 22.8 22.7 47.6 222.6 22.3 21.9 33.2 221.3 23,3 24.0 40.3 226.3 23.2 23.8 38.3 207.9 23.1 23.9

110 0.3 1 9.9 0.51 42.4 200.4 16.5 16.8 41.4 198.4 16.5 17.0 40.1 207.8 17.7 17.7 36.2 195.3 17.5 17.8 35.8 207.0 17.6 17.8 41.0 193.2 16.9 17.7 31.2 198.3 17.9 18.4 36.9 209.1 17.0 17.5 35.0 206.2 17.1 17.5

40

0.6 3 29.9 0.53 0.9 1 25.9 0.52 0.9 2 25.8 0.45 0.9 3 31.7 0.38 0,3 1 35.3 0.66 0.3 2 33.8 0.63 0.3 3 37.8 0.87 0.6 1 32.7 0.76 0.6 2 31,3 0.86 0.6 3 29.9 0.61 0.9 1 26.6 0.59 0.9 2 28.8 0.70 0.9 3 33.1 0.70 0.3 1 41.2 0.95 0.3 2 35.8 0.87 0.3 3 40.1 1.37 0.6 1 35.9 1.03 0.6 2 32.0 0.84 0.6 3 35.8 1.03 0.9 1 29.1 0.73 0,9 2 30.1 0,81 0.9 3 31.5 0,83 0,3 1 24.2 0.59 0,3 2 24.0 0.59 0.3 3 22.4 0.63 0.6 1 20.7 0.49 0.6 2 22.1 0.51 0.6 3 25.7 0.60 0.9 1 21.3 0.45 0.9 2 22.8 0.65 0.9 3 28.1 0,56 0.3 1 9.9 0,51 0.3 2 15.7 0,48 0.3 3 10.8 0.34 0.6 1 8.9 0,39 0.6 2 14.0 0.47 0.6 3 12.9 0,41 0.9 1 6.7 0,34 0.9 2 8.7 0,33 0.9 3 14.7 0,38

Data for Ankeny site during 1992

0.2 1 30.3 0.29 43.4 201.7 29.3 28.6 0.2 2 29.5 0.37 44.0 196.7 29.1 28.4 0.2 3 29.7 0.34 40.8 214.1 28.7 28.2 0.3 1 28.9 0,30 41.2 191.5 32.6 31.3 0.3 2 31.5 0.40 42.0 181.6 31.6 30.0

242


0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2

28.6 0.27 26.0 0.34 29.3 0.23 28.6 0.30 28.8 0.37 32.0 0.35 25.0 0.28 25.6 0.29 31.7 0.24 27.4 0.25 31.0 0.46 31.2 0.59 31.9 0.46 35.1 0.64 37.4 0.72 33.6 0.66 30.8 0.57 32.2 0.71 31.6 0.58 31.6 0.61 33.1 0.47 31.1 0.48 30.0 0.55 28.2 0.49 32.9 0.35 32.7 0.69 34.2 0.54 32.4 0.50 43.8 0.80 43.5 0.89 46.8 0.78 47.4 0.69 40.7 0.64 40.3 0.83 32.7 0.74 43.9 0.73 38.3 0.48 37.7 0.44 36.8 0.60 28.4 0.76 41.5 0.48 35.5 0.55 36.9 0.76 52.7 1.10 48.7 0.74 54.5 0.96 44.1 0.94 51.4 0.67

47.8 188.6 43.2 206.9 44.0 217.1 43.0 218.2 41.6 199.9 43.8 200.1 44.3 219.2 42.4 202.7 41.3 216.2 42.0 205.1 47.8 196.0 46.2 218.2 35.8 219.9 52.0 224.7 48.8 230.4 49.9 229.8 49.2 220.1 52.2 228.3 49.1 226.2 50.8 223.5 50.7 220.0 44.7 216.5 47.7 207.7 45.9 212.0 45.1 223.7 47.8 235.4 48.0 261.7 49.7 241.3 55.5 255.1 51.3 274.0 54.3 268.2 49.6 263.9 52.7 232.2 52.0 262.3 50.8 258.0 50.8 237.9 50.0 234.2 50.2 226.5 51.1 250.4 47.7 236.3 52.0 233.8 48.5 263.0 52.3 231.6 55.0 245.5 55.1 253.8 55.8 265.6 56.2 258.9 53.7 247.7

31.2 29.7 30.7 29.9 30.3 29.6 30.2 29.5 30.7 30.1 30.6 29.5 30.9 30.2 29.9 29.2 29.7 28.6 29.9 29.2 27.3 26.4 26 .8 26 .1 26.3 26.0 31.0 29.4 30.1 28.4 29.8 28.3 28.8 27.8 28.5 27.4 28.4 27.5 28.8 27.9 29.1 27.7 29.5 28.4 27.8 27.1 27.7 27.3 28.0 27.1 31.1 31.0 31.3 31.1 31.1 31.0 31.8 31.0 31.4 30.9 31.0 30.2 31.2 30.9 31.4 31.0 31.9 31.3 32.3 31.8 32.3 31.6 31.7 31.2 31.8 31.5 31.7 31.2 31.1 31.0 28.4 28.4 28.0 28.1 27.2 27.3 28.8 28.3 28.6 28.2 28.3 27.9 29.8 29.4 29.9 29.6


0.6 3 46.8 0. 0.9 1 43.9 0. 0.9 2 39.1 0. 0.9 3 45.9 0. 1.1 1 38.0 0. 1.1 2 40.4 0. 1.1 3 40.6 0. 0.2 1 34.4 0. 0.2 2 38.4 0. 0.2 3 40.1 0. 0.3 1 41.9 0. 0.3 2 40.1 0. 0.3 3 36.0 0. 0.6 1 35.4 0. 0.6 2 37.0 0. 0.6 3 38.3 0. 0.9 1 33.3 0. 0.9 2 35.7 0. 0.9 3 36.4 0. 1.1 1 34.6 0. 1.1 2 35.1 0. 1.1 3 33.6 0. 0.2 1 28.5 0. 0.2 2 34.4 0. 0.2 3 30.8 0. 0.3 1 39.0 0. 0.3 2 25.2 0. 0.3 3 27.3 0. 0.6 1 27.7 0. 0.6 2 31.2 0. 0.6 3 35.4 0. 0.9 1 34.5 0. 0.9 2 29.7 0. 0.9 3 31.6 0. 1.1 1 28.4 0. 1.1 2 35.6 0. 1.1 3 30.6 0. 0.2 1 21.6 0. 0.2 2 19.5 0. 0.2 3 29.2 0. 0.3 1 23.5 0. 0.3 2 24.8 0. 0.3 3 19.7 0. 0.6 1 22.5 0. 0.6 2 22.6 0. 0.6 3 21.3 0. 0.9 1 18.6 0. 0.9 2 23.0 0.

51.5 242.7 29.2 29.4 54.9 249.0 28.8 29.0 52.3 237.0 28.9 28.5 50.3 227.9 29.4 28.9 49.1 242.0 28.3 28.2 52.0 236.3 28.4 28,2 49.8 221.1 28.2 27.9 46.6 205.9 32.3 32.6 46.2 229.1 33.4 33.5 47.2 229.6 34.1 34.6 54.0 227.2 30.8 30.4 53.0 253.9 31.4 31.1 53.6 258.1 31.6 31.5 50.3 258.3 31.5 31.3 49.0 266.1 31.6 31.4 51.8 208.6 31.7 31.7 50.2 226.0 30.9 30.8 50.3 252.7 30.6 30.4 51.8 236.4 31.G 31.0 49.4 237.3 31.0 31.2 43.8 221.6 30.9 31.3 43.9 228.7 30.9 31.1 41.4 162.2 31.0 31.4 40.7 145.2 31.7 31.9 37.0 249.9 31.7 32.3 48.5 209.8 27.7 27.8 46.2 256.2 29.1 29.2 45.6 216.5 28.6 29.1 45.8 219.2 29.2 29.3 44.0 201.6 30.3 30.5 43.0 214.2 29.9 30.0 43.6 203.6 29.1 29.3 43.9 201.0 28.9 29.0 41.1 218.4 28.8 29.4 42.3 211.5 30.8 31.0 40.8 216.7 29.9 30.0 34.8 193.4 30.1 30.4 38.3 208.6 27.2 27.6 35.9 200.7 27.5 28.0 34.4 218.0 27.9 28.3 38.8 206.1 27.9 28.0 35.3 281.7 27.9 28.1 36.5 207.6 28.1 28.4 36.6 220.3 27.4 27.6 35.2 214.9 26.8 27.1 34.4 230.5 27.1 27.2 34.9 216.1 28.5 28.5 35.1 231.3 28.5 28.6

68 57 86 68 46 63 80 69 61 55 78 75 70 74 62 77 64 63 72 62 67 60 30 20 90 59 71 67 72 54 63 64 58 61 66 56 46 47 46 42 52 48 41 56 39 42 47 43

244


0.9 3 20.0 0.46 32.9 222.8 28.9 29.1 130 1.1 1 17.3 0.47 33.9 231.7 27.3 27.6

1.1 2 17.9 0.47 32.6 229.3 27.3 27.4 1.1 3 18.6 0.33 34.5 215.9 26.9 27.3 0.2 1 8.8 0.44 37.9 208.4 27.2 28.2 0.2 2 23.4 0.45 35.5 213.5 26.0 26.'3 0.2 3 15.5 0.35 34.1 196.7 26.7 27.3 0.3 1 18.1 0.33 38.4 211.1 22.5 22.9 0.3 2 26.6 0.41 34.9 195.5 23.9 24.1 0.3 3 18.9 0.36 36.1 206.4 24.5 24.7 0.6 1 16.0 0.45 36.2 200.7 30.4 30.5 0.6 2 23.3 0.45 34.9 202.6 26.6 26.6 0.6 3 15.6 0.40 34.0 214.0 26.4 26.0 0.9 1 18.1 0.48 34.5 191.8 26.8 27.1 0.9 2 15.9 0.41 34.7 214.8 25.4 25.5 0.9 3 16.3 0.45 32.6 212.3 25.1 25.2 1.1 1 19.0 0.35 33.5 206.3 27.5 27.7 1.1 2 13.2 0.45 32.3 205.9 27.1 27.0 1.1 3 14.2 0.41 34.2 202.5 26.5 26.6


40 0.2 1 21.7 0.59 39.3 229.8 29.2 29.3 0.2 2 21.6 0.57 42.7 215.8 28.9 29.0 0.2 3 22.5 0.47 41.6 228.2 29.2 29.3 0.3 1 24.4 0.51 42.1 266.0 29.2 29.4 0.3 2 26.9 0.63 41.3 259.0 29.6 29.8 0.3 3 19.7 0.48 41.9 247.4 29.6 29.7 0.6 1 21.7 0.47 43.2 226.2 30.4 30.5 0.6 2 29.2 0.66 42.3 243.7 30.6 30.6 0.6 3 21.9 0.44 37.0 223.1 29.9 29.9 0.9 1 26.2 0.61 41.0 245.7 29.4 29.5 0.9 2 23.3 0.57 41.3 211.2 29.7 29.7 0.9 3 23.3 0.60 42.2 246.7 30.2 30.3 1.1 1 20.3 0.54 40.4 228.5 29.6 29.8 1.1 2 19.7 0.51 41.0 225.9 29.6 29.7 1.1 3 23.3 0.48 42.0 241.7 29.7 29.7

56 0.2 1 19.2 0.70 42.4 227.3 28.3 27.8 0.2 2 20.7 0.63 43.1 224.6 28.4 27.9 0.2 3 22.8 0.57 41.7 212.1 29.0 28.6 0.3 1 32.1 0.67 45.2 232.7 28.2 27.9 0.3 2 29.6 0.77 45.5 247.8 27.6 27.2 0.3 3 28.1 0.68 47.5 236.2 27.5 26.9 0.6 1 30.1 0.56 45.6 197.8 27.4 26.9 0.6 2 31.4 0.81 44.0 273.3 27.8 27.2 0.6 3 24.2 0.53 43.1 215.5 28.0 27.6 0.9 1 22.7 0.66 46.3 227.7 26.9 26.4 0.9 2 21.5 0.82 42.4 213.7 26.4 25.9

245


0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2 1.1 3 0.2 1 0.2 2 0.2 3 0.3 1 0.3 2 0.3 3 0.6 1 0.6 2 0.6 3 0.9 1 0.9 2 0.9 3 1.1 1 1.1 2

21.9 0.67 17.6 0.59 23.1 0.62 26.2 0.64 21.9 0.79 21.9 0.68 24.1 0.62 30.6 0.84 34.7 0.83 31.0 0.88 27.1 0.84 34.0 0.76 29.3 0.73 28.7 0.81 32.6 0.71 28.2 0.77 22.6 0.60 21.1 0.56 27.4 0.79 33.3 0.55 33.4 0.77 35.2 0.84 42.3 1.57 43.8 0.54 39.9 0.68 41.4 0.74 37.6 0.77 42.8 0.65 40.1 0.77 36.5 0.85 39.3 0.75 31.7 0.70 31.8 0.73 43.1 0.70 23.5 0.43 30.0 0.39 26.7 0.47 28.7 0.63 34.3 0.38 29.0 0.37 30.1 0.44 30.8 0.46 27.2 0.36 29.0 0.42 28.9 0.49 27.7 0.43 25.5 0.41 27.9 0.38

43.3 219.1 44.5 222.0 43.0 230.4 42.7 231.9 36.3 228.4 40.9 216.1 41.1 230.0 47.8 266.3 49.7 259.2 45.6 247.5 50.0 269.3 49.0 244.4 41.2 222.8 44.3 246.0 44.2 211.6 42.5 247.0 41.0 228.6 42.0 225.9 44.0 241.7 41.0 235.6 42.9 237.5 46.3 231.3 51.6 262.9 51.6 274.8 51.5 254.3 52.4 289.6 55.0 225.6 46.2 283.2 50.2 269.4 51.7 267.7 50.9 242.2 45.2 241.6 39.5 240.9 49.8 231.8 36.7 220.7 39.0 160.6 40.7 260.1 53.0 223.7 53.2 203.8 49.4 230.1 51.7 221.7 51.6 178.1 42.9 217.4 50.4 249.0 52.0 208.7 52.6 208.1 41.8 217.6 38.8 223.0

26.1 25.7 25.9 25.7 26.2 25.8 26.1 25.8 28.6 28.9 28.8 28.9 29.0 29.3 29.7 29.4 29.8 29.6 29.8 29.7 30.3 30.1 30.8 30.5 29.9 29.7 29.9 29.7 30.0 29.7 30.6 30.3 29.9 30.1 29.9 30.0 30.0 30.2 31.3 31.7 31.2 31.7 31.4 31.7 32.1 32.4 30.7 30.8 32.0 32.3 31.1 31.3 31.4 31.6 31.9 32.2 29.2 29.4 29.5 29.8 30.2 30.4 31.1 31.5 30.9 31.3 30.7 31.1 24.9 25.5 25.5 25.9 28 .1 28 .6 25.3 25.6 25.9 26.3 25.8 26.1 25.8 26.1 25.3 25.6 25.5 25.7 25.4 25.7 2 6 . 0 2 6 . 2 25.8 26.1 25.8 26.3 26.0 26.4

246


1.1 3 22.9 0.34 47.9 195.8 25.5 25.9 110 0.2 1 15.9 0.34 32.4 172.3 20.8 21.4

0.2 2 14.5 0.28 31.0 180.1 21.0 22.1 0.2 3 17.1 0.37 27.4 189.6 21.1 21.9 0.3 1 15.9 0.33 47.2 192.5 21.6 21.6 0.3 2 20.2 0.28 44.3 179.0 22.0 22 .8 0.3 3 18.9 0.31 45.7 217.2 21.7 22.5 0.6 1 18.5 0.33 48.2 210.9 22.7 23.0 0.6 2 22.0 0.33 43.7 156.6 20.9 21 .3 0.6 3 19.2 0.27 31.9 203.1 21.1 21.5 0.9 1 17.4 0.34 41.1 189.8 23.0 23.4 0.9 2 20.0 0.34 40.5 174.7 24 .7 25.0 0.9 3 15.3 0.30 44.2 178.3 24.2 24.5 1.1 1 16.8 0.30 34.2 204.3 24.0 24.6 1.1 2 16.1 0.29 29.0 160.7 23 .3 23.8 1.1 3 15.9 0.27 36.4 159.1 24.0 24.6

DAP - days after planting; WTD - water table depth; REP -replications; PHO - photosynthesis; COND - stomatal conductance; CHL - chlorophyll; CI - intercellular carbon dioxide; T-Air -crop canopy air temperature; T-Leaf - leaf temperature

247

Table 15. NO3-N concentrations (mg/L) in suction tube and piezometer water samples at Ames and Ankeny site for 1992 and 1993

Suction tube depth Piezometer depth

DAP WTD REP 0.3 0.6 0.9 1.5 2.1 WTD 1.2 1.8 2.4 m m m m m m m m m m


4.1 6.4 0.9 NS 40.3 10.2 NS 5.1 212.6 165.2 61.7 NS 4.4 NS 171.4 92.4 5.3 6.0 0.6 NS 22.1 0.2 17.3 4.2 NS 53.5 14.5 26.6 1.5 NS 48.0 43.0 NS NS 0.3 113.9 Ns 6.2 NS 14.3 77.2 21.6 9.1 NS NS NS NS 6.2

55 0.9 1 NS 219.1 38.4 4.1 3.5 0.9 22.7 14.1 11.1 2.2 2.6 34.0 27.3 23.5 36.7 5.1 26.0 34.7 24.0 2.4 1.4 0.6 21.9 4.7 18.0 7.8 3.0 34.7 4.9 19.7 •2.4 0.4 2.0 13.4 20.2 0.2 0.0 0.3 5.6 5.3 4.8 0.5 1.4 35.0 4.5 9.6 7.5 0.8 13.7 1.8 4.2

81 0.9 1 0.8 19.7 2.0 4.5 3.1 0.9 7.4 8.8 3.1 3.2 1.6 12.5 7.9 3.1 0.3 1.0 9.5 6.9 9.7 0.5 4.2 0.6 1.6 1.5 2.3 5.0 0.7 9.3 6.2 0.1 1.3 0.6 0.6 1.0 0.8 0.4 0.4 0.3 0.1 0.8 0.2 2.1 0.0 6.2 1.6 2.6 7.5 2.0 0.3 3.9 2.8

113 0.9 1 2.2 5.0 4.3 0.6 0.8 0.9 ND 6.7 4.2 NS NS 18.3 8.5 4.5 0.9 NS 4.0 4.7 5.0 0.8 1.7 0.6 1.9 2.5 3.9 3.2 NS 17.5 6.6 2.9 0.9 NS 6.3 3.6 1.0 0.0 1.5 0.3 9.0 3.3 0.5 0.2 2.0 11.9 2.4 2.9 1.0 0.2 5.0 1.1 0.9 4.3 1.0 0,9 5.7 5.0 4.0 3.2 1.2 8.0 4.5 2.7 2.8 2.4 3.9 2.5 2.7 0.5 3.7 0.6 3.5 2.0 1.7

0,9 1 NS NS 123,2 2 NS NS 118,6 3 NS NS NS

0.6 1 NS NS NS 2 NS NS NS 3 NS NS NS

0.3 1 NS NS NS 2 NS NS NS 3 NS NS NS

0.9 1 NS 219.1 38.4 2 NS 68,9 NS 3 115.3 36,0 147.3

0.6 1 17.0 0.7 ND 2 70.5 61.8 48.9 3 3.6 3.4 17.6

0.3 1 117.1 48.2 52.6 2 50.4 NS 35.1 3 23.9 48.9 54.0

0.9 1 0.8 19.7 2.0 2 17.1 7,1 18.6 3 39.6 3,4 13.6

0.6 1 0.0 1,1 2.3 2 28.6 19,4 25.8 3 6.6 9,5 4.3

0.3 1 3.9 5.4 1.2 2 0.8 9.0 0.6 3 22.7 5.9 8,8

0.9 1 2.2 5.0 4,3 2 0.6 3.8 NS 3 18.4 4.9 NS

0.6 1 0.9 4.3 NS 2 14.9 3.1 1,0 3 5.7 0.4 2,7

0.3 1 0.2 NS 0,9 2 8.6 1.7 NS 3 1.1 0,3 0,1

0,9 1 NS NS 1,7 2 NS NS 0,5 3 NS NS 9.9

0,6 1 ND 0,5 NS

248


2 7.5 1.7 3.8 1.9 2.3 1.7 1.6 4.6 3 2.7 1.3 0.7 7.9 0.4 0.4 3.9 0.2

0.3 1 0.6 1.3 NS 0.2 0.9 0.3 NS 0.3 0.9 2 3.2 1.2 NS ND 0.7 1.4 0.5 4.3 3 5.8 1.9 ND ND ND ND 0.3 2.5

0.9 1 10.5 NS 10.4 1.4 0.3 0.9 NS 6.1 3.4 2 NS NS 9.2 0.3 0.2 NS 7.5 5.0 3 NS NS NS 2.5 0.3 NS 3.2 5.1

0.6 1 2.8 NS NS NS NS 0.6 NS 3.0 2.5 2 10.7 NS 1.0 2.1 1.2 NS 7.0 5.2 3 NS NS 1.2 0.1 0.4 NS 5.2 7.0

0.3 1 NS NS NS NS 0.1 0.3 NS 0.8 0.3 2 NS NS NS NS 0.3 NS 11.5 4.3 3 NS NS NS 0.7 NS NS 5.3 8.1


48 0.9 1 63.6 92.6 7.8 1.5 4.5 0.9 12.0 17.0 5.9

68

90

2 93.9 109.6 109.8 1.6 1.2 3 43.9 84.3 5.0 0.1 4.0

114.1 14.6 5.0 34.9 83.4 91.2

0.6 1 42.4 34.0 5.4 0.8 3.5 0.6 16.2 4.1 3.5 2 0.9 18.3 13.4 3.3 0.7 20.4 20.9 0.2

3.5 0.7 25.7 35.0 34.1 1.1 0.0 0.3 11.7 7.1 27.2 3.1 1.5 36.8 3.9 8.1 0.2 0.7 35.0 45.6 7.9 1.4 5.4 0.9 8.8 6.9 4.4 4.9 1.8 63.4 9.1 3.4 3.8 2.4 16.4 35.7 2.4 1.1 1.9 0.6 2.4 3,1 4.8 3.2 1.7 4.6 2.6 4.3 4.1 1.1 8.0 2.6 0.5 1.1 0.6 0.3 4.2 14.7 2.5 2.4 0.6 18.1 3.5 1.3 0.3 1.7 14.7 3.7 7.9 5.0 NS 0.9 6.5 6.4 3.8 1.4 NS 14.6 2.1 1.8 1.9 0.4 5.0 9.6 4.2 1.3 0.2 0.6 3.5 2.2 1.2 1.5 0.2 1.7 2.5 1.1 2.1 0.6 5.5 2.3 1.1 1.2 0.0 0.3 0.6 4.8 2.2 1.9 0.3 4.6 0.9 1.0 NS 1.7 6.1 1.5 1.8 2.3 0.3 0.9 3.5 4.0 2.8 0.8 2.4 3.5 1.2 3.5 2.2 2.2 4.9 4.6 3.3 0.7 0.0 0.6 1.0 1.9 2.3

3 NS 0.2 11.5 0.3 1 7.2 2.8 7.6

2 30.7 5.3 5.5 3 10.0 7.2 1.0

0.9 1 7.5 9.7 3.8 2 7.2 4.3 5.5 3 6.8 5.8 9.4

0.6 1 2.0 2.7 1.9 2 4.2 4.2 5.5 3 9.1 4.2 4.7

0.3 1 3.6 6.3 3.8 2 3.7 2.5 2.5 3 3.5 1.5 3.2

0.9 1 4.1 2.5 0.9 2 9.5 6.0 3.4 3 NS 5.0 2.0

0.6 1 0.7 1.4 2.1 2 1.8 1.2 1.8 3 7.1 1.6 1.4

0.3 1 3.2 3.2 1.8 2 4.1 1.5 0.5 3 6.2 0.9 1.4

0.9 1 NS NS 4.2 2 5.1 5.7 1.3 3 NS 0.7 1.6

0.6 1 4.6 2.1 NS


249

54

82

2 4.8 2.2 2.1 0.4 0.2 2.3 3.3 3 5.5 4.3 1.1 1.1 1.4 1.1 1.9 0.9

0 .3 1 2.4 0.7 1.0 1.4 0.1 0.3 1.0 4.0 3.1 2 2.1 1.5 1.6 1.9 0.1 1.2 1.6 0.3 3 0.9 2.8 1.6 ND NS 2.6 0.9 1.9

0 .9 1 NS NS NS 3.7 0.7 0.9 19.5 2.5 • 0.7 2 10.1 5.6 1.1 1.2 1.9 3.1 1.7 3.3 3 2.0 1.4 3.6 1.3 3.5 3.5 NS 1.4

0, ,6 1 NS NS 0.7 0.5 0.7 0.6 NS 0.9 0.6 2 0.2 NS 1.8 1.2 0.8 2.8 1.4 0.2 3 6.4 3,1 1.8 0.6 NS NS 0.8 1.0

0, 3 1 1.0 NS 1.5 NS 0.1 0.3 0.8 0.6 0.5 2 1.6 NS 2.0 NS 0.5 NS 0.5 0.2 3 2.7 NS ND 0.5 0.8 NS 1.3 0.1

38

112 0


0.9 1 0.0 NS NS 1.1 34.5 8.6 3.6 2 7.7 1.0 6.7 NS 7.6 1.5 3 13.2 7.3 7.5 13.1 6.4 NS

0.6 1 3.7 6.2 NS 0.6 19.5 13.8 12.6 2 4.6 5.5 4.5 5.8 6.7 7.0 3 24.6 5.8 7.9 9.6 9.1 5.9

0.3 1 11.8 10.2 6.0 0.2 7.5 NS 2.6 2 0.9 2.5 1.8 7.5 5.4 3.2 3 NS NS ND 13.1 28.5 15.3

0.9 1 0.0 2.6 ND 1.1 8.4 11.0 3.5 2 6.7 NS 1.9 7.2 5.3 3.5 3 6.9 NS 0.2 15.2 1.4 4.2

0.6 1 3.8 3.1 NS 0.6 8.6 7.5 4.8 2 5.0 3.1 NS 12.4 5.9 5.3 3 6.3 5.3 NS NS 4.6 4.6

0.3 1 3.8 ND 0.6 0.2 19.2 1.9 11.0 2 1.2 0.4 2.0 13.6 6.2 1.1 3 5.9 2.2 2.2 159.5 12.0 6.9

0.9 1 7.5 1.2 0.5 1.1 10.4 2.3 2.8 2 10.9 5.6 3.5 2.1 4.1 0.8 3 0.1 6.7 0.1 23.5 13.7 2.5

0.6 1 4.4 3.9 1.7 10.1 9.7 1.3 2 8.6 2.4 2.4 0.6 14.8 7.1 3.8 3 6.1 3.9 3.2 9.0 6.7 6.9

0.3 1 2.5 1.9 ND 5.5 5.9 4.5 2 1.6 0.9 0.4 0.2 4.5 3.2 5.2 3 3.7 5.0 4.3 4.0 4.1 3.7

0.9 1 NS ND 3.6 1.1 8.3 5.1 0.6 2 4.1 NS 2.1 7.5 3.7 6.8 3 5.0 4.1 2.3 4.9 6.7 6.7

250


0 .6 1 1.0 3.5 0.0 0.6 4.4 3.6 1.4 2 6.1 2.5 1.8 4.9 3.7 4.0 3 6.0 4.0 ND 3.1 3.6 5.0

0.3 1 4.2 1.0 ND 0.2 0.8 0.9 3.0 2 1.7 1.2 1.5 3.0 0.7 1.0 3 0.3 3 .5 1.7 2.4 4.0 • 1.0

140 0.9 1 5.4 0.4 0.1 1.1 6.8 6.7 0.6 2 4.9 3.4 NS 5 .9 5.3 3.4 3 5.6 NS NS 2.1 4.4 5.9

0.6 1 NS NS NS 0.6 NS NS NS 2 NS NS NS NS NS NS 3 NS NS NS NS NS NS

0.3 1 1.3 0 .2 ND 0.2 2.0 1.8 NS 2 NS NS NS NS 3.2 0.9 3 NS NS NS 2.1 4.5 4.5

168 0.9 1 3.2 ND NS 1.1 NS NS NS 2 11.2 0.9 NS NS NS NS 3 7.1 1.1 NS NS NS NS

0.6 1 1.4 1.6 NS 0.6 6.0 5.8 0 .6 2 8.5 1.4 NS 4.0 4.8 3.4 3 0.6 0.3 NS 3 .4 4.6 6.0

0.3 1 4.7 ND NS 0.2 1.6 0.8 7 .2 2 4.5 NS NS NS 1.9 3.3 3 4.5 ND NS NS 2.0 3.1


48 0.9 1 35.7 1.2 0.6 1.1 90 .0 36.9 9 .3 2 35.7 29.6 2.2 61.2 38.6 7.4 3 78.7 3.9 0.8 157.7 16.2 9 .2

0.6 1 43.8 4.7 0.6 0.6 11.9 42 .9 16.8 2 39.4 3.9 0.3 50.3 36 .6 35.9

0.3 1 22 .5 7.0 1.1 0.2 4.7 22 .9 5.4 2 22 .7 2.0 0.8 44.7 36 .2 NS 3 13.7 0.9 ND 17.3 34.0 49.6

68 0.9 1 NS 0.2 1.9 1.1 42 .3 1.6 13.6 2 5 .0 5 .8 2 .2 23 .5 19.5 6.0 3 5.4 1.8 ND 6.3 5.8 5.1

0.6 1 NS 1.8 1.5 0.6 13.2 11.4 8 .2 2 2.4 2.0 1.5 13.2 5.2 0.5 3 6.0 0.1 ND 13.4 1.8 2.0

0.3 1 0.0 0.5 0.4 0.2 9.1 7.5 0.7 2 4.5 2.5 0.5 1.3 3.0 4.2 3 0.5 ND 3.4 18.8 4.9 1.8

88 0.9 1 NS ND 2.3 1.1 3.5 2.2 10.3 2 1.0 8.6 2.6 14 .2 11.2 2 .5 3 66.4 3.9 3 .6 60.6 17.0 0.8

251


3 6.5 1.6 0.4 17.5 7.8 0.7 0.6 1 3.7 1.0 1.0 8.8 8.1 NS

2 1.0 3.4 3.8 0.6 4.7 5.5 2.8 3 3.2 0.7 0.1 0.4 3.7 8.2

0.3 1 1.0 NS ND 5.7 9.5 1.7 2 0.2 ND 0.5 0.2 5.9 2.8 • 1.2 3 0.4 0.4 0.7 0.1 1.4 0.2

116 0.9 1 3.2 0.4 2.3 1.1 1.3 2.5 2.0 2 6.0 6.0 1.2 14.2 8.5 1.5 3 8.4 1.2 2.7 11.1 14.3 6.9

0.6 1 0.7 1.8 0.8 0.6 10.3 7.7 NS 2 1.8 NS 2.1 4.2 2.0 2.8 3 11.7 2.4 0.1 3.3 3.1 1.0

0.3 1 1.8 NS 0.2 0.2 3.6 2.4 NS 2 7.3 3.5 0.3 5.3 2.5 NS 3 0.8 ND 0.7 1.4 3.5 0.4

144 0.9 1 NS 0.1 3.8 1.1 1.6 1.7 0.7 2 6.3 4.7 3.6 11.4 1.3 2.3 3 NS NS 0.5 6.6 6.0 1.3

0.6 1 NS 0.1 0.5 0.6 5.1 5.9 NS 2 1.5 2.2 2.2 1.5 2.4 0.1 3 NS 0.1 3.5 1.7 0.9 0.1

0.3 1 NS 0.8 ND 0.2 5.2 NS NS 2 1.9 1.8 ND 0.1 NS NS 3 0.7 0.2 0.3 0.7 NS 1.3

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