GEOLOGICAL CONTROLS ON SEASONAL-POOL HYDROPERIOD IN A KARST...

GEOLOGICAL CONTROLS ON SEASONAL-POOL HYDROPERIOD IN AKARST SETTING

Michael A. O’Driscoll1 and Richard R. Parizek2

1Department of Geological Sciences

East Carolina University

Greenville, North Carolina, USA 27858

E-mail: [email protected]

2Department of Geosciences

The Pennsylvania State University

University Park, Pennsylvania, USA 16802

Abstract: Shallow depressions found in karst terrains may contain temporary (vernal) pools that are

inundated seasonally in response to changes in meteorological conditions. The hydrogeology of 16 pools

(0.06–0.4 ha) was studied in an Appalachian karst valley in central Pennsylvania, USA. The objective was to

determine the effect of the geologic substrate on pool hydroperiod. Meteorological, geophysical, and

hydrogeological data collected from November 1997–August 1999 and from January 2002–January 2004

suggested that hydroperiod was primarily controlled by meteorological conditions (total annual

precipitation) and surficial aquifer geology. Multiple regression models were found to predict most of the

spatial variability of pool hydroperiod with the following variables: thickness of the surficial sandy aquifer;

sediment electrical resistivity; and annual precipitation. It might be expected that hydroperiod would be

longer for clay pools than sandy pools because clay sediments can act as a seal to perch shallow ground-

water and surface-water. Our data revealed the opposite to be true. Sandy residual sediments helped capture

infiltration and direct this water along perched ground-water lenses or sheets to seasonal pools. This resulted

in annual hydroperiods that were 115 days longer for sandy pools when compared to clay pools. The results

suggest that the geologic substrate can be a major control on the duration of hydroperiod.

Key Words: isolated wetlands, karst pans, perched ground-water, vernal pools, wetland/ground-water

interactions

INTRODUCTION

The recent US Supreme Court ruling (Rapanos vs

United States, June 2006) and the current legal

status of federal protection of isolated wetlands calls

for an improved scientific understanding of isolated

wetland hydrology (Leibowitz et al. 2008). Seasonal

or ‘‘vernal’’ pools are ‘‘…temporary or semi-

permanent pools occurring in shallow depressions

that typically fill in the spring or fall and may dry

during summer or in drought years’’ (Calhoun and

DeMaynadier 2008). Seasonal pools are generally

isolated but intermittent surface-water connections

may occur.

Pool hydroperiod is the number of days per year

that the aquatic phase occurs. Hydroperiod is an

important control on pool ecology because it

influences invertebrate/ vertebrate species richness,

community composition, predator abundance, and

fire occurrence (Brooks 2000, Mitsch and Gosselink

2000). Specialized organisms that utilize seasonal

pools are able to survive the extreme changes in local

hydrology (Zedler 2003, Colburn 2004) and for this

reason pool habitats support numerous federally

listed threatened and endangered plant and animal

species (Tiner 2003). Pool hydroperiod has a major

influence on amphibian populations. In Rhode

Island, USA it was found that successful reproduc-

tion of most pond-breeding amphibians required

hydroperiods of 4–9 months with pool inundation

occurring from March–August (Paton and Crouch

2002).

Precipitation and evapotranspiration are the

major controls on seasonal-pool hydroperiod, but

ground-water inputs and losses may also be

important (Leibowitz and Brooks 2008). Ground-

water fluxes are controlled by the permeability of the

surrounding aquifer, geomorphology/topography,

and meteorological conditions (Winter and La-

Baugh 2003, Rheinhardt and Hollands 2008). Local,

intermediate, and regional scale ground-water flow-

paths can feed seasonal pools. Pools nourished by

larger-scale flowpaths are less likely to be affected by

recent weather patterns and are more likely to have

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WETLANDS, Vol. 28, No. 4, December 2008, pp. 1004–1017’ 2008, The Society of Wetland Scientists

1004

longer hydroperiods (Winter and LaBaugh 2003).

Geomorphic variables found to be related to

hydroperiod include pool depth and volume, and

possibly pool area. Larger pools tend to remain wet

longer (Brooks and Hayashi 2002, Skidds and Golet

2005).

Several studies have documented geologic con-

trols on seasonal-pool hydrology, mainly focused in

the Central Valley, CA and the glaciated northeast-

ern US. In the Central Valley, CA vernal pools were

found to be fed by a shallow ground-water system

perched on top of low-permeability sediments

(Rains et al. 2006). In these settings, Rains et al.

(2008) found that although vernal pools may appear

similar, differences in their underlying geology(hardpan vs. clay-rich soils) can result in large

differences in ground-water inputs and surface-water

geochemistry. In contrast, in central Massachusetts,

Grant (2005) used a GIS approach to map the

presence of potential seasonal pools and found that

pools were more likely to be found in more

permeable glacial deposits than in till/bedrock

settings. Rheinhardt and Hollands (2008) recently

reviewed the importance of glacial geology and

topography on seasonal-pool occurrence in the

Northeast. In a recent review of seasonal pool

hydrology, Brooks (2005) suggested that the distri-

bution of pools is controlled by: 1) an impermeable

sediment or bedrock layer near the surface, 2) the

presence of small topographic depressions, and 3)

meteorological conditions.

In a previous study, we documented a large range

of annual hydroperiod (33–192 days) for a series of17 seasonal pools in central Pennsylvania located

within several hundred meters of each other in a

karst setting (O’Driscoll and Parizek 2003). Meteo-

rological conditions, vegetative cover, and topogra-

phy were very similar across the chain of wetlands. It

was hypothesized that subsurface geology controlled

the variability in hydroperiod across the site. The

current study was designed to determine the effect of

the geologic substrate on seasonal-pool hydroper-

iod.

STUDY AREA

The study site occupied 22 hectares at thePennsylvania State Gamelands 176 in Spring Creek

Watershed, Centre County, Pennsylvania (77u549000

N, 40u509000 W) in a karst-underdrained valley in

the Appalachian region of central Pennsylvania,

USA (Figure 1a). The research site at the Game-

lands was located several hundred meters down-

gradient of a Pennsylvania State University waste-

water irrigation site and is comprised of crop fields

(60%), woodlands (35%), and wetlands (5%).

Wetlands were typically surrounded by mixed

deciduous forest. Previous studies revealed that

irrigation wastewater does not migrate to the

wetlands (O’Driscoll 2000, O’Driscoll and Parizek

2003).

The predominant geological formation underlying

the research area is the Gatesburg Formation

(Cambrian), which consists of dolomites, sandy

dolomites, and thin sandstones (Carrucio 1963).


Figure 1. a) Site map including geology and location ;of

study site in the Spring Creek Watershed, Centre County,

PA. b) The topography of the southwest corner of State

Gamelands 176 site, including the location of piezometer

nests, staff gages, vernal pools, and the transect A-A’. U

indicates an uncased piezometer nest. Topographic

contour elevations are in meters above sea level. Contour

interval is 1 meter. The soil contact from the Centre

County Soil Survey (Braker 1981) is overlain.

O’Driscoll & Parizek, GEOLOGIC CONTROLS ON SEASONAL-POOL HYDROPERIOD 1005

The Upper Sandy Member of the Gatesburg

Formation underlying the southern portion of the

site is approximately 150 m thick and consists of

alternating sandstones and dolomites that weather

to sandy loam residual soils (Butts and Moore 1936,

Braker 1981). The Mines Dolomite Member of the

Gatesburg Formation occurs stratigraphically above

the Upper Sandy Member, is approximately 70 m

thick, and underlies the area to the north of the

chain of wetlands. The Mines Dolomite Member

consists of coarse-grained dolomite, weathering to

clay-rich residual soils. Overall, the bedrock in the

area is covered by a thick mantle of residual soils,

ranging in depth from , 10 to 50 m. In a previous

study of this chain of seasonal pools, the perched

and regional ground-water system was mapped and

the catchment draining to seasonal-pool wetlands

was delineated. Direct precipitation and shallowperched ground-water fed these pools and the

perched ground-water system was influenced by

geologic controls including the presence of a tear

fault, permeability contrasts of residual soils, and

organic clay seals underlying pools (O’Driscoll 2000,

O’Driscoll and Parizek 2003).

METHODS

To determine the influence of the meteorological

and geological controls on hydroperiod, a field and

modeling approach was used. Hydrological moni-

toring was conducted to determine hydroperiod,

hydraulic head, and to characterize the ground-

water system. Geological and geophysical analyseswere performed to characterize the soil/aquifer

properties. Statistical models were developed to

evaluate the effects of meteorological and geological

conditions on pool hydroperiod.

Hydrologic Monitoring

In the fall of 1997, 124 nested piezometers were

installed at 31 locations throughout the site, with

each location containing a cluster of four piezom-

eters, one each at depths of 1.5, 3.0, 6.1, and 9.1 m

(Figure 1b). Piezometers consisted of 2.54-cm-diam-

eter PVC pipe with a 61-cm-long screened section

with a slot width of 1 mm located at the bottom of

the pipe. Boreholes for the piezometers were drilledwith a hollow-stem auger mounted on an all-terrain

vehicle. A sand pack was added to cover the

screened interval, and then a bentonite sealing layer

was added to prevent construction-related, vertical

hydraulic connection among piezometers in the

same nest. Piezometers were vented to the atmo-

sphere and developed by purging with a peristaltic

pump. Seventeen staff gages were installed in

wetland depressions to measure surface-water ele-

vations (Figure 1b). Pool 16 extends outside of the

study property and straddles the Gamelands prop-

erty line. The largest pond, Toftrees Pond (Pool 15),

is impounded and used to store irrigation water for a

neighboring golf course. In the current study, we

focused on the 16 remaining undisturbed pools.

Staff gage and piezometer location and elevation

were surveyed with a laser theodolite and added to

the topographic base map. Topographic data were

surveyed to create a 0.3048 m contour interval map

to allow direct comparison between surface-water

and ground-water head data.

Surface-water and ground-water levels were mea-

sured at the site during two intervals from Novem-

ber 1997 to August 1999 and from January 2002–

January 2004 at a bi-weekly interval during periods

when pools were inundated (monthly interval when

pools were dry from August 1998–January 1999)

with a one-time sampling during April 2004 during

an extreme wet period. Surface-water levels were

measured at staff gages installed in pools and

ground-water levels were measured in piezometers

using an electrical water-level meter. The first year of

complete surface and ground-water level sampling

was from August 1998–1999. Pools were all dry

from August 1998 until January 1999 during

drought conditions and completely dried up again

in August of 1999. The remaining two periods were

from January 2002–2003 and January 2003–2004.

Over the 3 year-long study periods, pools were

inundated for a total of 65 sampling visits. During

these visits 646 surface-water level measurements

were collected. Hydroperiod was estimated from

surface-water data collected during field visits by

considering the initial inundation to be the first

sampling date when water was present and the end

of the hydroperiod was considered to be the last

sampling date when water was present. The hydro-

period estimation error should be less than a month

for each year. Based on more frequent site visits

early in the study bi-weekly sampling was deemed

adequate because it generally took pools more than

several weeks to dry up after filling.

Total annual precipitation data from 1899–2006,

daily air temperature, and daily precipitation data

for the period of study were obtained from the

Pennsylvania State University weather station,

located approximately 4 km from the site (Pennsyl-

vania State Climatologist 2007; http://climate.met.

psu.edu/). Potential evapotranspiration (PET) esti-

mates for the period of study were based on the

Blaney-Criddle equation, PET (mm) 5 kp (0.46T +8.13). The consumptive coefficient is k, T is air


1006 WETLANDS, Volume 28, No. 4, 2008

temperature (degrees-C), and p is the percentage of

total daytime hours for the period of interest of total

daytime hours of the year (4,380 daytime hours/yr).

Daily air temperature and sunlight hours were

averaged for monthly periods to estimate the

monthly PET. The consumptive coefficients were

0.85 for the growing season (April–August), 0.45 for

the dormant season, and 0.65 for the transition

months, March and September (Xu and Singh

2002). In a previous study, Xu and Singh (2001)

found the Blaney-Criddle method to be more

accurate than six other temperature–based potential

evapotranspiration estimation techniques with a

maximum deviation from monthly pan evaporation

of , 25%.

However, this approach may overestimate actual

evapotranspiration if plants are water stressed. At our

site, the location of the wetlands in a topographic low,

the presence of a perched ground-water system, and

the presence of surface-water would tend to reduce

the likelihood of water limitation. A comparison

between PET estimates for this study (mean estimate

of 82% of annual precipitation) and past studies of the

Spring Creek Watershed based on water budgets

(43%–70% of annual precipitation) suggests that PET

values may overestimate actual evapotranspiration on

an annual basis (Giddings 1974, O’Driscoll 2004). For

the purposes of this study, we used PET data in a

limited way, to show time periods throughout the year

when water deficits were likely.

Geologic and Geophysical Characterization of Soils

and Residual Sediment

Continuous split-spoon sediment samples

(3.81 cm diameter) were collected at 30 of the 31

drilling locations to depths of 10 m. These sediment

borings were logged and classified in the lab.

Detailed logs are provided in O’Driscoll (2000).

Sediments were correlated based on texture, distinct

stratigraphic layers, abundance of rock fragments,

type of rock fragments, Munsell color, gleying, and

other criteria. Recovery of sediment cores was not

100%; 250 m of residual sediment core was logged

out of a potential 300 m.

Electrical resistivity surveys were conducted at the

site during the late fall–early winter of 1998 andrepeated during the late spring–early summer of 1999

to determine the subsurface sediment distribution

and the depth and extent of clay or sand lenses. Direct

current was injected into the subsurface by electrodes

that contacted the surficial sediments and additional

electrodes were used to measure the voltage between

two points. The greater the resistance to electrical

current flow at depth, the higher the apparent

resistivity (apparent resistivity refers to the composite

resistivity of numerous geologic layers to a certain

depth in the subsurface) of the underlying materials

(Burger 1992). Computer simulations are used to

create a model of the resistivity of subsurface units

that matches the measured surficial voltage measure-

ments. This method can help differentiate between

buried clay and sand sediments because they conduct

electricity differently. Clay and silt-rich sediments

have low apparent resistivities (10 s–100 s) (good

conductors), whereas sandy sediments have greater

apparent resistivity values (100 s–1000 s) (poor

conductors) (Burger 1992).

A common survey approach is to locate two

potential electrodes (to measure voltage) centered

above the point of interest at a fixed distance apart

(known as a-spacing) and locate two current

electrodes (one on each side of the potential

electrodes to inject current) the same distance from

the potential electrodes. This electrode geometry is

known as the Wenner array, and when a-spacing is

increased the depth of current penetration, and

hence the depth of subsurface imaging, increases. A

‘‘depth sounding’’ is performed when a-spacing is

systematically increased, the apparent resistivity

measurements represent a greater slice of the

subsurface and an electrical sample of earth

materials at depth is collected (Burger 1992).

Resistivity data were collected using an IP-Plus

resistivity meter (EDA Instruments, Inc.). Twenty-

five depth soundings were performed at the site, with

surface measurement points spaced approximately

95 m apart. In some areas, it was necessary to

deviate from this spacing to avoid surface-water or

hedgerows. Apparent resistivity was estimated at

each surface point for a series of 10 logarithmically

spaced a-spacings of 1, 1.47, 2.15, 3.16, 4.64, 6.81,

10.00, 14.68, 21.54, and 31.62 m (Burger 1992). Each

a-spacing represented a different depth of sediment

(10 resistivity measurements were collected at each

surface point and 250 total resistivity measurements

for the entire study site).

Computations performed using field data and

ERModel (Burger 1992) indicated that sediments at

depths of up to 10 m were characterized during

surveys with a-spacings of 31.62 m and for a-

spacings of 6.81 m earth resistivity values would

image depths of approximately 2.2 m in the

subsurface. The resistivity surveys imaged sediment

electrical resistivity at sufficient depths to character-

ize the perched aquifer system feeding the pools at

the site. Hydraulic head data from this and previous

studies showed that ground-water feeding pools was

always coming from depths of less than 9 m

(O’Driscoll 2000, O’Driscoll and Parizek 2003).



Resistivity data for the 6.81 m and 31.62 m a-

spacing surveys were used to generate resistivity

maps and contoured using the kriging approach with

Surfer contouring software (Golden Software; http://

www.goldensoftware.com/). Resistivity measure-

ments collected at these a-spacings were chosen for

contour maps because they provide insight into the

framework of the shallow aquifer system adjacent to

and underlying the pools. The 6.81 m and 31.62 m a-

spacings represent the shallow (2 m deep) sediments

adjacent to pools and the deeper sediments (10 m)

underlying the entire site, respectively.

Depth soundings were used to image a vertical

section of the subsurface. Greater a-spacing resulted

in a deeper subsurface investigation. The voltage

and current were measured 100 times at each survey

point and then an average voltage and current

reading was given for each surface measurement

point, specific to the a-spacing. These measurements

were then used to calculate the apparent resistivity

of subsurface materials below that surface point for

each particular a-spacing using the following equa-

tion for the Wenner array, r 5 2paV/I, where r is

apparent resistivity (ohm-m), p is 3.14159, V is

voltage measured (volts), I is current injected into

the subsurface (amps), and a is the a-spacing (m), or

distance between electrodes.

Statistical Analysis of Variables Affecting

Pool Hydroperiod

Eight geological/geophysical variables were eval-

uated to determine their relationship to pool

hydroperiod. These variables included sandy aquifer

thickness, pool depth, pool area, pool volume, soil

infiltration rate (obtained from the Centre County

Soil Survey), electrical resistivity at 6.81 m a-

spacing, electrical resistivity at 31.62 m a-spacing,

and pool topographic catchment area (m2). All

variables were log transformed and compared to

pool hydroperiod (mean of 3 year-long study

periods). The least squares estimation method was

performed to obtain Pearson correlation coefficients

to measure the strength of linear relationships

between the variables and hydroperiod. Following

these analyses, best subsets regression was per-

formed on the variables and hydroperiod to find

the best-fitting regression models for the specified

predictor variables (Minitab, Version 15). To

develop a general model that used the geologic

variables (Geologic Model) to predict hydroperiod

across the site, the variables were used to predict

mean hydroperiod at the 16 pool locations (n 5 16).

To develop a general model that used the geologic

variables and took into account the changing

meteorological conditions for the three separate

years of study (Geologic and Meteorologic Model)

the geologic variables for each pool and the total

precipitation and hydroperiod for each given year-

long study period were used (n 5 48). The frequency

distribution of annual rainfall (% exceedance) over

the period of 1899–2006 was estimated using an

empirical cumulative distribution function.

RESULTS

Temporal Variability in Seasonal-pool Hydroperiod

and Water Level

The three year-long periods studied had a range of

81–131 cm annual precipitation. The long-term

mean annual precipitation for State College is

98.3 cm (1899–2006) with a standard deviation of

14.7 cm. The 1998–1999 study year occurred during

drought conditions (81 cm) and the remaining two

study years experienced average to above average

precipitation (2002-104 cm and 2003-131 cm). Dur-

ing the driest sampling year (1998–1999) the mean

hydroperiod for the 16 pools was 112 days. At the

other extreme, during 2003, the mean hydroperiod

was 248 days. The mean annual pool hydroperiod

had a positive relationship with the magnitude of

annual rainfall (Figure 2a). Pool water levels peaked

in spring (April) and during late fall-early winter

(December). Precipitation excess (precipitation-po-

tential evapotranspiration (PET) affected pool water

levels, but in complex ways related to seasonal

variability in precipitation-PET and the timing of

the shallow ground-water response (Figure 2b).

Precipitation generally was greatest during summer

months, but summer was the period of peak PET so

water deficits were common. The drawdown of pool

levels during the growing season corresponded with

the period when there was a water deficit, resulting

in lowest pool levels commonly occurring in August

and September. On average, the month with the

lowest water levels and the occurrence of the greatest

number of dry pools was September; during this

month over 80% of the pools were dry for the three

one-year periods (Figure 2c). Conversely, April was

the month when pool levels were greatest and pools

had the lowest likelihood of being dry. During April

sampling dates only 9% of the pools sampled were

dry. There was a large degree in variability of drying

across the pool sites. The wettest pool (16) was dry

for 4.6% of the sampling dates. The driest pool (17)

was dry for 74% of the sampling dates (n 5 65).

These differences can be attributed to the contrast-

ing geological conditions across the site that will be

discussed next.



Geological and Meteorological Controls on Pool

Water Level and Hydroperiod

Electrical Earth Resistivity and Sediment Distribu-

tion. Electrical resistivity depth soundings, verified

by sediment cores, suggested three general types of

sediment distribution at the site: 1) thick sand

deposits (. 5 m); 2) thick clay and/or silt-rich

deposits (. 5 m); and 3) a thin surficial sand aquifer

underlain by clay at 2–4 m depth. Thick sand

deposits are common in the southern portion of

the site; depth sounding #1 (Figure 3a) shows an

apparent resistivity curve in this region indicative of

sandy soils to depths of 10 m. Thick clay and/or silt

deposits are common in the northern portion of the

site; depth sounding #10 (Figure 3a) shows a clay-

type apparent resistivity curve in this region.

Sediments in this northern portion of the site

consisted of silt, clay, and clay loam sediments from

the surface to at least 9 m depth. The thin surficial

sand aquifer underlain by clay at 2–4 m depth in

proximity of the ponds is evident in depth sounding

#5 located near pool 14 (Figure 3a). Here the

resistivity values for the a-spacings up to 3.16 m are

representative of sandy sediments, but as the survey

includes deeper sediments at greater a-spacings the

apparent resistivity declines to values of approxi-

mately 200 ohm-m, suggesting a clay-layer at depths

of 3 m or more. Sand layers exist beneath many of

the ponds and these aquifers may act as preferential

pathways for shallow perched ground-water to

nourish wetlands. In addition, cores taken in pools

revealed a 1–2 m thick organic clay layer underlying

pool depressions.

Apparent resistivity values at depth sounding

locations varied from 120–1425 ohm-m across the

site and were related to sediment distribution. Sandy

sediments had resistivity values greater than

500 ohm-m and silt or clay-rich sediments had

resistivity values less than 500 ohm-m. For the

6.81 m a-spacing survey a general pattern existed

across the site; higher apparent resistivity values


Figure 3. a) Depth soundings for three representative

sites. Apparent resistivity versus a-spacing curves for

settings with sand (depth sounding 1: DS-1), clay (depth

sounding 10: DS-10) and sand underlain by clay (depth

sounding 5: DS-5). Greater a-spacing indicates greater

sediment depth. b) Apparent resistivity map for the

6.81 m a-spacing survey. Units are in ohm-m. Wetland

pools, locations of three representative depth =soundings,

and the soil contact from the Centre County Soil Survey

(Braker 1981) are overlain.Figure 2. a) Annual rainfall vs. hydroperiod for the three

year-long sampling periods. b) Mean monthly variations

in mean pool depth (m- on right y-axis), PET, precipita-

tion, and precipitation excess (cm) for the entire study

period. c) Mean percentage of pools (n 5 16) that were

dry for a< given month for all of the three year-long

sampling periods.


were confined to the sandy southern corner of the

site and a low resistivity area (clay/silt rich

sediments) extended from the southern edge of the

wetlands area to the entire northern limits of the site

(Figure 3b). A lobe of higher resistivity materialswas apparent in the wetland area around pools 8, 9,

13, and 14. This trend represents a shallow sandy

aquifer that is present in the wetland region. The

sandy surficial aquifers are approximately 1–7 m

thick and extend from 1–7 m below grade and are

nearly always underlain by silt or clay-rich sediments

or at least have inclusions of silt or clay-rich

sediments. Resistivity data from 31.62 m a-spacingsurveys revealed similar patterns to those collected

at 6.81 m a-spacing.

Pool Classification by Sediment Type. On Figur-

es 1b, 3b, and 4 the contact between the Huble-rsburg silt loam and Morrison sandy loam has been

overlain from the Centre County Soil Survey

(Braker 1981). The resistivity surveys and sediment

cores collected during the current study suggest that

the sandy loam-silt/clay loam contact in this area

differs from the soil survey map, likely due to the

spacing of soil sampling locations used to generate

the original soils map. The 6.81 m a-spacingresistivity map and the sediment core data (upper

2 m) from 30 logs were used to more accurately map

the contact between silt/clay loam and sandy loam

soils (Figure 4). This approach is based on 55 data

points (30 cores at piezometer nests and 25 depth

soundings) per 22 ha or 2.5 data points/ha. The

contact line is a manual approximation based on

shallow sediment core data and on resistivity data inareas where no cores were taken. In most cases the

contact followed the resistivity contours. In a few

locations the contact slightly deviated from the

resistivity data because sediment cores nearby

indicated a local change in soil type.

This approach resulted in a classification of pools

into two groups: 1) sandy and 2) clay/silt pools (for

simplicity the latter will be referred to as clay pools).

Clay pools typically had adjacent apparent resistiv-

ity values of less than 500 ohm-m and were located

on the northern side of the site. Sandy pools had

apparent resistivity values of . 500 ohm-m and

were located in the southern portion of the site.

Seven sandy pools (pools 2, 8, 9, 10, 13, 14, and 16)

and nine clay pools (pools 1, 3, 4, 5, 6, 7, 11, 12, and

17) were mapped.

Controls on Pool Hydroperiod. Pool hydroperiod

was related to pool type (Figures 4 and 5). Sandy

pools remained wet longer than clay pools as

indicated by mean hydroperiod for the duration of


Figure 4. Updated soils map and mean annual hydro-

period for the three years of study. The dashed line shows

the sand-silt/clay loam contact overlain from the Centre

County Soil Survey (Braker 1981) map and the solid line

shows the sand-silt/clay loam contact inferred from

sediment logs and resistivity data. Sandy loam soils are

shaded gray and silt/clay loam soils are in white. Numbers

are mean hydroperiod (days).

Figure 5. a) Box and whisker plot of mean clay pool

versus mean sandy pool hydroperiod. Mean is for >the 3

year-long study periods. Box indicates the range from 25th

to 75th percentile and mid line is the median. b) Percentage

of sampling dates when a given pool was wet over the 3–

year long sampling periods versus pool depth (n 5 65).

Black circles indicate pools that were present in clay-rich

sediments and white circles indicate pools that were

present in sandy sediments.


the study (Figure 5a) and the percentage of sam-

pling dates when pools were wet (Figure 5b). In

addition, deeper pools tended to be inundated more

frequently. A Mann-Whitney comparison of hydro-

period for sandy pools versus clay pools revealed

that hydroperiods were significantly (p , 0.05)

shorter for clay pools by approximately 115 days.

Of the variables analyzed, all but catchment area

were significantly (p , 0.05) correlated with hydro-

period based on Pearson correlation tests (Table 1).

The strongest relationships existed between log

hydroperiod and log sand thickness, log depth,

and log resistivity (6.81 m a-spacing) (Table 1).

Pools adjacent to thick sandy surficial aquifers

tended to have longer hydroperiods than those that

were not connected to sandy aquifers. Pools

surrounded by greater resistivity sediments (sandier)

tended to have longer hydroperiods. The infiltration

rate of soils surrounding the pools also was related

to the duration of hydroperiod. Sandy soils with

greater infiltration rates correlated with pools with

longer hydroperiods. In addition, pool morphology

had a relationship with hydroperiod; deeper and

larger pools tended to remain inundated for longer

periods.

Models for Predicting Hydroperiod. A best subsets

regression analysis revealed several regression equa-

tions that could predict pool hydroperiod (Table 1).

A multiple regression model (Geologic Model)

including sand thickness and earth resistivity values

(31.62 m a-spacing) could predict 86% of the

variability in mean annual (log) hydroperiod for

the pools (Table 1 and Figure 6) suggesting the


Table 1. Correlations and regression equations for (log) hydroperiod. SE indicates the standard error. Bold correlation

coefficients and p-values indicate significant results at p , 0.05.

Parameter Pearson’s Corr. Coefficient p-value

log sand thickness (m) 0.906 0.000

log depth (m) 0.796 0.000

log resistivity (6.81 m) 0.734 0.001

log volume (m3) 0.702 0.002

log infiltration rate (cm/hr) 0.651 0.006

log resistivity (31.62 m) 0.637 0.008

log area (m2) 0.531 0.034

log catchment area (m2) 0.337 0.202

Equation Adjusted R2 SE (Predictor) p-value

log hydroperiod 5 2.30 + 0.142 log sand thickness (m) 0.81 0.018 0.000

log hydroperiod 5 2.19 + 0.912 log depth (m) 0.61 0.19 0.000

log hydroperiod 5 0.663 + 0.581 log resistivity ( 6.81 m) (ohm-m) 0.51 0.14 0.001

log hydroperiod 5 1.44 + 0.302 log volume (m3) 0.46 0.082 0.002

log hydroperiod 5 1.89 + 0.503 log infiltration (cm/hr) 0.38 0.16 0.001

log hydroperiod 5 0.807 + 0.524 log resistivity (31.62 m) (ohm-m) 0.36 0.17 0.008

log hydroperiod 5 1.35 + 0.302 log area (m2) 0.23 0.13 0.034

log hydroperiod 5 1.71 + 0.123 log sand thickness (m) + 0.216 log

resistivity (31.62 m) (ohm-m)

0.86 0.018 0.000

0.09 0.036

hydroperiod 5 2355 + 43.1 log sand thickness (m) + 102 log resistivity

(31.62 m) (ohm-m) + 2.73 precipitation (cm)

0.80 6.04 0.000

31.67 0.002

0.302 0.000

Figure 6. A comparison of predicted and measured

mean annual hydroperiod for each specific pool. The

Geologic multivariate model used log sand aquifer

thickness and log apparent resistivity (at 31.62 m a-

spacing) to predict mean annual log hydroperiod for each

site (n 5 16). The Geologic and Meteorologic multivariate

model used log sand aquifer thickness, log apparent

resistivity (at 31.62 m a-spacing), and precipitation to

predict mean annual hydroperiod for each site for each

given year (1999, 2002, and 2003) (n 5 48).


importance of geologic controls on pool hydroper-

iod. With this model, the greatest discrepancy

between predicted and measured mean annual

hydroperiod at a specific pool was 58 days (pool

5) and the mean difference between predicted and

actual hydroperiod (absolute value) was 21 days.

An additional multivariate model (Geologic and

Meteorologic Model) was developed that accounted

for the annual variability in hydroperiod due to

variations in annual precipitation for the three years

of study. This multivariate model could predict 80%

of the variability in annual hydroperiod for a

specific pool (Table 1 and Figure 6). For this model

the mean difference between predicted and actual

hydroperiod (absolute value) was 32 days. Two

outliers occurred in 2002 (Figure 6). At pool 5, the

model predicted 191 days but the actual hydroperiod

was 289 days. At pool 8, the model predicted 198

days for 2002 but the actual hydroperiod was

measured at 48 days. For the remaining years the

model predicted the hydroperiod at these pools

relatively well (between 3%–17% for pool 5 and

17%–29% for pool 8). Overall, these data suggest

that geologic substrate and precipitation are major

controls on pool hydroperiod in this setting.

To evaluate hydroperiod response across a range

of meteorological conditions the Geologic and

Meteorologic Model, including annual precipitation,

sand thickness, and resistivity, was used to approx-

imate hydroperiod for sandy and clay pools for the

long-term record of annual precipitation for the

State College area (1899–2006). The probability

distribution for precipitation was used to predict the

occurrence of mean hydroperiod over the last

century for all pools, clay pools, and sandy pools

(Figure 7). The model revealed that for similar

meteorological conditions clay pools were much

more likely to remain dry. For mean pool hydro-

period to be at least four months (conditions

favorable for amphibian reproduction; Paton and

Crouch 2002) at least 86 cm of precipitation is

needed. This is likely to occur for at least 80% of

years. However, clay pools as a group would only

have hydroperiods greater than four months for the

wettest 40% of years, requiring at least 102 cm of

annual precipitation.

The spatial distribution of pools with hydroper-

iods greater than four months for extreme wet (5%

exceedance 2123 cm annual precipitation), median

(50% exceedance 298 cm annual precipitation), and

extreme dry (95% exceedance 274 cm annual

precipitation) conditions are presented in Figure 8.

It is only during extreme wet conditions, which

occur infrequently, that clay pools would have

hydroperiods greater than 4 months. For example,

all clay pools have hydroperiods greater than 120

days for the 5% exceedance, which requires 123 cm

of annual precipitation (Figure 8a). For 50% of the

years all sandy pools should have hydroperiods

suitable for amphibian reproduction (. 4 months),

but most clay pools would have hydroperiods

shorter than 4 months and presumably less than

ideal conditions for amphibian reproduction (Fig-

ure 8b). For 95% of the years at least 6 pools should

have hydroperiods longer than 4 months, 5 of these

pools are in the sandy region (Figure 8c). These data

suggest that over time, sandy pools would be more

likely sites for amphibian reproduction.

Ground-water Response of Clay versus Sandy

Pools. Nested ground-water head and surface-

water elevation data were compared between a

sandy pool (MW 7, pool 10) and a clay pool (MW

15, pool 11) (Figure 9) for the period of September

2002–2003. These pools were selected because they

had both staff gages and piezometer nests located

within the pools and sediment cores showed that

they were screened in predominantly clay-rich (pool

11) and sandy (pool 10) sediments. Over this period,

the clay pool had a hydroperiod of 111 days and the

sandy pool had a hydroperiod of 234 days. During

the same period, the clay pool was inundated during

three periods, whereas the sandy pool remained

inundated for most of the year. The 9 m deep

ground-water head measurements at both pool sites


Figure 7. The probability of exceedance for precipitation

and the corresponding modeled mean hydroperiod for a

given year indicated for clay pools, sand pools, and all

pools (mean) based on the long-term (1899–2006)

distribution of annual precipitation. Four months is

shown to represent the minimum duration of hydroperiod

suitable for amphibian reproduction (Paton and Crouch

2002). For mean pool hydroperiod to be at least four

months at least 86 cm of precipitation is needed.


were always below the pool bottom elevation,

indicating that ground-water feeding these pools

must come from depths shallower than 9 m (Figur-

es 9a and 9b). For the sandy pool, there was a

period from March–September 2003 when ground-

water heads at 6 m (and shallower depths) were

sufficient to provide enough energy to transport

ground-water from these depths to the pool bottom

(Figure 9a). The deeper sandy aquifer surrounding

this pool (Figure 10) provided ground-water to

nourish the pool during periods of low rainfall and

high evapotranspiration. For the clay pool, the 6 m

deep ground-water head was never great enough to

supply ground-water to the elevation of the pool

bottom and 3 m deep ground-water only had

sufficient head to feed the pool on two sampling

dates for the period (Figure 9b). This pool was

rarely inundated because it was fed by very shallow

perched ground-water (, 3 m deep) and direct

precipitation.

These data suggest that the presence or absence of

the surficial sandy aquifer is a major control on

ground-water inputs and hence hydroperiod of these

seasonal pools. However, site observations suggest

that if sandy layers are very thick (. 7 m) and do

not contain clay aquitards, then closed depressions

will drain too quickly to form seasonal pools.

Evidence for this exists in the sandy southern

portion of the site. In this area, piezometer nest 8

was completely dry at all depths (up to 9 m deep) for


Figure 9. a) Ground-water and surface-water head

distribution for September 2002–2003 for Pool 10 (sand).

b) Ground-water and surface-water head distribution @for

September 2002–2003 for Pool 11 (clay). c) Daily

precipitation for the period of September 2002–2003.

Figure 8. Three different scenarios of hydroperiod

distribution based on corresponding precipitation distri-

bution: a) the 5% exceedance? (123 cm annual precipita-

tion); b) the 50% exceedance (98 cm of annual precipita-

tion); and c) the 95% exceedance (74 cm of annual

precipitation). In-filled (black) pools indicate pools that

were inundated for more than 4-months/year (pool areas

are not scaled to the actual volume of water predicted).

The numerical values adjacent to the specific pools

indicate the duration (days) that the pool would

contain water.


91% of the sampling dates. Sand was approximately

9 m thick at this coring location and major clay

units were absent from the core. Depressions and

swales in this sandy area did not typically hold water

for any extended period.

DISCUSSION

Differences in hydroperiod across the site were

attributed to the underlying geology and morphol-

ogy of wetland depressions. The hydroperiod

duration was positively correlated with thickness of

the surficial sandy aquifer. Two model outliers,

pools 5 (underpredicted) and 8 (overpredicted), in

2002 suggest that pool 5 may have a greater

connection to ground-water and pool 8 may have

less of a connection to the adjacent aquifer than

indicated by the model. Discrepancies between

model hydroperiod predictions and actual hydro-

period estimates may be related to local variability

in runoff generation, ground-water inputs, and/or

surface-water losses.

When the sand aquifer was thick and located

adjacent to a pool, the hydroperiod was longer when

compared to pools located in silt/clay-rich sedi-

ments. However, it is important to mention that

where the sandy aquifer was not underlain by a clay

or silt confining unit (in the extreme southern

portion of the site) the permeability of the sandy

residual sediments was too large to allow for the

formation of pools in depressions and ground-water

wells remained dry for most sampling dates even at

depths of 9.1 m. These data suggest that shallow

confining units are important controls on the

presence of seasonal pools.

Shallow sandy aquifer thickness was related to

hydroperiod because of its influence on the magni-

tude of ground-water inputs to the pools. Sandy

perched aquifers provide perched ground-water to

pools from deeper sediments and also from larger

catchment areas. Sandy aquifers adjacent to pools

were of limited extent and were typically perched on

top of clay/silt-rich sediment confining layers at

depths of 1–7 m at the site. There was limited

storage in these aquifers and variable degrees of

connection to the pools. The ground-water flux to

the pools was from shallow depths and responded to

seasonal variations in meteorological conditions.

Our results are in agreement with the conclusions of

Brooks (2005) and Rains et al. (2008) that seasonal/

vernal pools are generally not fed by deep ground-

water. In this setting, ground-water source was 6 m

or less.

Geophysical surveys and core collection for

subsurface geological characterization are costly,

time consuming, labor intensive, and may be

prohibited in sensitive wetland areas. Hence, de-

tailed geological and geophysical data are not

broadly available for seasonal pool sites. It would

be advantageous to be able to predict hydroperiod

using readily available, mapped data, such as soils

and topographic data. Infiltration rate data suggest

this may be possible; there was a positive relation-

ship between mean hydroperiod and soil infiltration

rate/soil type. For this study, the infiltration rates

were based on literature values for the appropriate

soil type from the Centre County Soil Survey and

may not adequately represent the local variability in

soil characteristics adjacent to the pools. Using

surficial soil data to infer hydroperiod requires

caution in these settings because the formation of

residual soils reflects the variability in the compo-

sition of the parent material and in some cases the

sandy residual sediments are buried by several

meters of clay or silt-rich sediments. Therefore, the

surficial sediments mask the underlying aquifer

materials. Conversely, soils data do not typically

provide information on the presence or absence of

confining units below the soil profile; a key factor

influencing the formation of perched ground-water

systems important to seasonal-pool formation. For

these reasons, sediment sampling or geophysical

surveying may be needed to characterize the

distribution of shallow, sandy, aquifer systems. This

is evident when looking at the mean hydroperiod for

pool 6 (Figures 1b and 4). Based on surficial

sediment data this pool is classified as a clay/silt-

rich pool, however adjacent to the pool there is a

buried sandy aquifer greater than 1 m thick and this

is the likely reason for this pool having a mean

hydroperiod of 260 days, one of the longest mean

hydroperiods observed.


Figure 10. Cross-section A-A’ (location presented in

Figure 1b) showing residual sediment distribution below

and adjacent to pools 10 and 11. Note the thick sandy

loam aquifer adjacent to Pool 10 that is absent from Pool

11. Numbers at the land surface represent piezometer nests.


Other surficial indicators of hydroperiod included

pool depth and pool area which were positively

related to hydroperiod duration. Many of the

variables that were compared with hydroperiod are

interrelated and interact in complex ways. In

addition, subsurface sediments are highly variable

in folded and faulted karst settings. These factors

make it difficult to completely isolate the importance

of one particular variable. For example, electrical

resistivity measurements are influenced to some

extent by every other variable. The relationship

between hydroperiod, sediment texture, and thick-

ness is complicated by the depth-hydroperiod

relationship. Sandy pools tended to be deeper and

larger, which can also influence the length of

hydroperiod. The occurrence of deeper pools in

areas of thicker sands suggests that the Upper Sandy

Member of the Gatesburg Formation may be more

prone to dissolution and collapse than the adjacent

Mines Dolomite Member. Differential subsidence

through time during the weathering process together

with variable abundance of insoluble minerals

within the carbonate source rock adds to the

complexity of soil sequences at our site and very

likely in other carbonate terrains.

In addition to the surficial aquifer distribution,

another important geologic control on the presence

and duration of seasonal pools in this setting is the

presence of a tear fault underlying the site (Fig-

ure 1a). Uneven westward movement of bedrock

units during development of the Birmingham thrust

fault (located due west of the site) has resulted in the

development of a tear fault that trends NW-SE

through the site and underlying the area that

contains the wetland pools. This fault was mapped

by Carrucio (1963) and extends for more than 16 km

to the southeast of the Birmingham thrust fault

(Clark 1965, Parizek et al. 1967). The tear fault

mapped through this site is likely responsible for the

topographic low region, or trough, trending NW–SE

through the site and underlying the pools. Residual

soils in this general area exceed 16 m in thickness

based upon a number of test borings used to

characterize the region. The slopes on both sides of

this trough collect water and distribute it to the pond

area; hence, the tear fault can be considered a major

control on the location of these wetland ponds. The

series of pools and their trend and location in a linear

series in the trough suggest a geologic control on

their origin. Uneven dissolution of carbonate rocks is

also enhanced by systematic joint sets that cross the

tear fault zone at an oblique angle. A number of

pools tend to be elongate parallel to this joint trend.

In previous studies at the site, recharge areas for

the individual pools were delineated based on

hydraulic head data and the entire recharge area of

the pools was found to span 2–8 ha, with typical

ground-water flowpath lengths to pools of less than

150 m. Water chemistry, hydraulic head, and

surface-water level data all suggested ground-water

inputs were derived from local shallow perched

aquifer systems. A deep well at the site (. 30 m

deep), approximately 200 m northwest of piezome-

ter nest 28, had ground-water levels greater than

30 m below the surface. These data confirm the

pools are part of a perched local ground-water flow

system (O’Driscoll 2000, O’Driscoll and Parizek

2003). Subsurface geology affects the degree of

perching and the nature of local ground-water

flowpaths to pools. Pools that were better connected

to the sandy perched aquifer system remained wetfor longer periods.

Karst watersheds exhibit a wide range of surface-

water-ground-water interactions related to hetero-

geneous hydraulic properties and bedrock dissolu-

tion processes (White 1988). In karst watersheds

with thin sediment deposits overlying bedrock,

seasonal pool wetlands are less likely to occur

because vertical seepage through permeable bedrock

is common. In temperate karst areas, with thick

residual sediment deposits and the presence of closed

depressions, seasonal pools are more likely, partic-

ularly if permeable sediments are underlain by

shallow low permeability sediments that can support

perched ground-water systems. The results of this

study should be applicable in karst and other

settings where local perched ground-water flow

systems are the predominant ground-water source

to pools, but not in settings where regional ground-water inputs have a substantial influence on the

hydroperiod.

CONCLUSIONS

The relationship between surficial and/or shallow

sand aquifer thickness, electrical resistivity, and

hydroperiod suggests that geophysical surveys may

help improve the understanding of geologic controls

on seasonal-pool hydrology in this and other

settings. It may be possible to utilize remote sensing

approaches (sensu Meng et al. 2006) to gather

similar data that would help better explain the

spatial variability in hydroperiod and the geologiccontrols on seasonal-pool location, occurrence, and

water level variability.

At first glance, one might have expected the

hydroperiod to be longer for clay pools than sand

pools in this karst setting, i.e., the need for a seal to

perch shallow ground-water and surface-water. The

opposite was shown to be true. Sandy residual soil



helped capture infiltration and directed this water

along perched ground-water lenses or sheets to

nearby seasonal pools. When sandy sediments were

not underlain by any type of confining unit in the

southern portion of the site, the sediments were too

well drained to allow for the formation of seasonal

pools. These results suggest that sandy surficial

aquifers can help prolong seasonal-pool hydroper-

iods but that they require a subsurface confining

layer to slow vertical seepage from the pools.

The observed differences in hydroperiod based

on subsurface geological conditions suggests that

geologic controls and the importance of perched

ground-water inputs will have an important effect

on a seasonal pool’s response to climate and/or

land-use change. In this karst setting, clay pools

may be more vulnerable to climate change due to

their shorter hydroperiods and greater sensitivity to

recent weather conditions. Sandy pools will show

more subdued responses due to the buffering effect

of shallow perched ground-water inputs. However,

land-use changes that affect recharge to or dis-

charge from surficial aquifer systems may have

greater effects on sandy pools and their hydroper-

iods than on clay pools. Overall, the observed

influence of subsurface geology on pool hydroper-

iod suggests that spatial variations in subsurface

geology may relate to spatial variations in pool

ecology.

ACKNOWLEDGMENTS

The authors greatly appreciate a helpful review by

Rick Rheinhardt and the comments provided by

several anonymous reviewers and the Associate

Editor. This paper is a result of research performed

at Pennsylvania State Gameland # 176; the authors

thank the PA Game Commission for access to the

site. We owe special appreciation to the Pennsylva-

nia State University Office of Physical Plant who

provided financial support for drilling, construction,

materials, and manpower to set up the monitoring

network. They also contracted for the detailed

topographic survey of a 1 ft. contour interval and

accurate survey of piezometer and staff gage

elevation critical to this investigation. In particular,

Bill Shaw and Lou Brown provided technical

assistance and water chemistry analyses; John

Gaudlip provided wage support, materials, maps

and technical information; and Frank Raymond

drafted the site topographic map. The authors also

appreciate the assistance of graduate students who

assisted with fieldwork: Tyrone Rooney and Garth

Lewellyn.

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Manuscript received 7 April 2008; accepted 22 July 2008.



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