Land Capability Classification for Agro-economic … Dam...Journal of Agricultural Engineering and...

Journal of Agricultural Engineering and Biotechnology Nov. 2014, Vol. 2 Iss. 4, PP. 63-75

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DOI: 10.18005/JAEB0204002

Land Capability Classification for Agro-economic

Evaluation of Mahadayi Dam, Karnataka, India Prashant R. Thawale*, R. Karthik, Surbhi Jore, Sanjeev K. Singh, Asha Juwarkar

CSIR- National Environmental Engineering Research Institute

Nehru Marg, Nagpur, Maharashtra, 440020, India

[email protected]*

Abstract-This paper examines the socio-economic impact of proposed dam on cropland productivity of Mahadayi project, Karnataka,

India. Systematic appraisal of dam and their designing by categories of classes on the basis of physical and chemical characteristics

of soil has been done in favour of development of agronomic conditions for the study of proposed dam sites in Karnataka. The study

is aimed at the effective utilization of land according to their classes. Documentation on the land capability classification is a versatile

component in formulation effective land use planning before the construction of dam. Thus an attempt was made to evaluate

dominantly occurring soils on four class’s viz. soil depth, soil texture, soil drainage and soil erosion. The study was focused on the

evaluation of economics of crop production based on agro climatic condition of the study area and existing cropping pattern. This

study is important as it explores how an input of water and nutrient would respond under variable climatic conditions. In addition,

interactions of water supplies with fertilizer rates at optimizing these resources need have been investigated. This paper identifies

key challenges and solutions for carrying out project-level economic analysis of adaptation to climate change, both stand-alone and

integrated into broader development projects. Very few projects addressing adaptation thus far have been subject to in-depth and

rigorous economic analysis for a variety of reasons, including a lack of guidance on how to deal with assessments of the impacts of

climate change, as well as with estimating costs and benefits of adaptation under uncertainty. Our focus is on the agricultural sector,

where the impacts of climate change have the potential to disrupt the livelihoods of rural populations in many regions and where

adaptation must be given urgent consideration. Nevertheless, some of the approaches discussed are suitable to projects in other

sectors.

Key words- Socio-Economic; Dam; Agronomic Condition; Land Capability Classification; Catchment Area; Crop Productivity; Land

Suitability Maps

I. INTRODUCTION

Dam projects generate a vast array of economic impacts both in the region where they are located, and at inter-regional,

national and even global levels. These impacts are generally evaluated in terms of additional output of agricultural

commodities, hydropower, navigation, fishing, tourism, recreation, prevention of droughts and reduction in flood damages [1].

Dams have been promoted as an important means of meeting perceived needs for water and energy and as long-term, strategic

investments, which have many additional benefits. Some of these additional benefits are typical of all large public

infrastructure projects, while others are unique to dams and specific to particular projects [2, 3]. The economics of adaptation

(in agriculture) has become a hot topic over the past few years, since the adverse impacts of climate change are raising

important concerns about the future livelihoods of many people around the world. In the very near term, vulnerable

communities will need to accelerate adaptation in order to mitigate the additional burdens of climate change. This is especially

important in the context of agriculture, given the critical role of that sector in the livelihoods of populations throughout the

developing world [4]. At the same time, investments in adaptation compete with other development priorities. Economic

evaluation of adaptation options can provide decision makers with important information for evaluating alternative uses of

scarce resources (land and water), as well as on when and how to make adaptation investments. In this paper, adaptation

projects are activities undertaken to ameliorate anticipated or actual losses in output and/or increases in cost of agricultural

production as a consequence of climate change. Our particular emphasis here is on anticipatory adaptation, though the same

basic concepts can also be applied to coping measures taken after adverse impacts are realized. For e.g.: A Weather-based

Farming Model for Communities (WFMC) and AdaptCap - Chinnakaramedu: Rain Water Storage Facilities, in India [5, 6].

Land evaluation for different uses also considered [7]. Unfortunately, very few adaptation projects or project components thus

far have been subject to in-depth and rigorous economic analysis that would contribute to weighing these trade-offs. This paper

identifies key challenges and solutions for carrying out economic analyses of adaptation projects and adaptation components

within broader development projects. While our focus is on the agricultural sector, we also highlight some general approaches

that are suitable to projects in other sectors as well.

Today, in developing countries, domestic demand for food crops is largely met. This success could not have been achieved

without the investment in irrigation in the last half century. India, one of the principal inputs to food production in south Asia,

irrigated agriculture continues to play a critical role in achieving food security, poverty alleviation and improving the quality of

life [8]. Methodology for monitoring and evaluation of integrated land and water development for river basin management has

been adapted from [9]. Guidelines on local framework for planning and project benefit monitoring and evaluation in Monila,

Philippines [10]. Importance of monitoring and evaluation of agro-economic benefits and project impact has been described by

http://cigrasp.pik-potsdam.de/adaptations/a-weather-based-farming-model-for-communities-wfmc

http://cigrasp.pik-potsdam.de/adaptations/a-weather-based-farming-model-for-communities-wfmc

http://cigrasp.pik-potsdam.de/adaptations/adaptcap-chinnakaramedu-rain-water-storage-facilities


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DOI: 10.18005/JAEB0204002

[11]. Irrigation is the largest public investment in many countries in the developing world [8]. Policy makers need to consider

economics for site identification along with dam structures, hydrology and hydraulics of irrigation to evaluate how

productively land and water resources are being used for agriculture, and to make more informed strategic decisions regarding

irrigation and food production.

Monitoring and agro-economic evaluation of irrigation projects plays an important role in the future due to water scarcity.

The process is complex, since a large number of regular, specific tasks must be performed, both concurrently and sequentially,

and coordinated by a variety of professionals with available time and resource constraints.

The paper points out the need for land capability classification (LCC) of a water resource project, concerning the functional

requirements and provides a realistic framework for carrying it out. For LCC evaluation to succeed, irrigation managers need

to develop a new evaluative mindset that enables them to appraise their projects performance, reflect for describes the

approach in economic evaluation and cost benefits analysis with respect to agricultural products of which is supposed to be

built on the Mahadayi river, Karnataka, mainly for irrigation purposes.

II. METHODOLOGY

A. Study Area

The proposed Mahadayi Hydroelectric Project (MHEP) envisages construction of dams across the Mahadayi River, four

diversion dams on tributaries, an underground power house and two dam site power houses along with land capability

classification. The Mahadayi, one of the west flowing rivers in Karnataka, takes its birth at an elevation of 914.40 m above

MSL in Khanapur taluka in Jamboti ghat 10 km north-east of Sonasagar in Belgaum district. The river basin lies between

latitudes 25015'24" N and 15042'00"E and 74023'54"E. The Mahadayi River is joined by three tributaries, in Karnataka viz. Bali

nadi, Kotni nadi and Bhendura nadi[12]. The catchment area of the Mahadayi basin is 375.11 km. in Karnataka. Study area

belongs to medium hot semi arid region with mostly lateritic soil developed from basalts. The silt content of the soil varies

from 4.9 to 13.0 percent. The soils having moderate water holding capacity ranges from 16.8 to 28.2 percent. The soils are

acidic in reaction and the pH varies from 5.7 to 6.5.

1) Climate:

The area comes under Deccan plateau and it is subjected to tropical climate. Broadly, the year can be divided into three

seasons, viz. winter, summer and monsoon. The climate is dry with large variation in temperatures ranging from 12oC in winter

to 42oC during summer seasons. The winter season occurs from November to February, while December and January are the

coldest months. The summer season extends from March to June. During this season, the maximum temperatures are recorded

during the month of May. The precipitation in this area is mainly due to southwest monsoon with a medium rainfall zone of

600 to 1000 mm and the weighted average rainfall being about 750 mm, which is more or less, assured but its distribution has

shown erratic trend. The monsoon precipitation, which commences generally in the last week of June, continues till end of

September, with occasional spell of post monsoon showers during October. Out of the total rainfall, about 94% of the

precipitations occur during June to October. During June to September the percentage of relative humidity is high which is of

the order of 88% in month of August.

2) Soil Type and Soil Quality of Command Area:

The physical properties of soil denote that soils of the area are clayey in texture with very high amount of clay followed by

silt and sand contents. The clay content of soils varies from 48.3 to 74.5 percent. The soils have medium to good water holding

capacity and the maximum water holding capacity ranges from 53.9 to 86.4%. The available water for plants ranges between

31.44 and 44.65%. The hydraulic conductivity of the soils varies from 7.5x10-5 to 8.9x10-4 cm/sec, in command area. The

porosity of the soils varies from 56.9 to 75.9% in command area. The bulk density of the soils varies from 1.19 to 1.49 g/cc.

Chemical analysis of the soils in the study area reveals that the soils are slightly to moderately alkaline with pH varying

between 7.6 and 8.5. The electrical conductivity of the soils of command area varied from 0.40 to 1.80 mS/cm. No salinity was

observed and all kinds of crops can be grown without any toxicity. The availability of nitrogen in the soil was medium;

however, the soils were very rich in phosphorus and potassium. The metals present in the soils were within the limits and with

no toxic potential. The soil has a very high adsorption capacity. The exchangeable sodium percentage in the soil indicates that

the soil has a good permeability. The organic carbon in soil was found to be varying between low and medium.

B. Agricultural Returns in the Existing Scenario

In order to review the agricultural returns due to the executions of the new dam project, it is required to compare the

existing value of agricultural produces with respect to the value of agricultural produces in the area, after the execution of the

project. The crop use, the existing prices of agricultural commodities and current average agricultural yield of each crop

cultivated in the region were collected from the concern authorities. The values of unirrigated produce per ha in the area was

estimated as:


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DOI: 10.18005/JAEB0204002

VYAP .. (1)

Where,

AP s value of agricultural produces in for the crop i per hectare (Rs. /ha.)

Y is the average yield of crop i in the present scenario (unirrigated) in quintals/ha.

V is the current value of agricultural products of crop i in Rs. /quintals.

The gross benefits due to agricultural production for crop per ha (as per NAFED) was estimated considering the deduction

in farmhouse practices and the revenues generated by fodder and farmyard manure. The deduction in farmhouse practices was

considered as 10% of the value of agricultural produce of the crop. The fodder yielding crops cultivated in the area were jowar,

groundnut and wheat and the fodder receipts were estimated as 15%, 10% and 10% (based on prevailing market price) of the

value of agricultural produces after deduction of the farmhouse practices. In the region, the sowing, ploughing and all

intercultural operations are done using animal power i.e. bull, which yields to farmyard manure. Therefore, farmyard manure

receipts were considered in the gross benefits as 3% of the value of agricultural produces after deduction of the farmhouse

practices. Thus, the gross benefits were estimated as:

FYFRDAPG )( (2)

Where,

G is the gross benefits due to agricultural practices for the crop i per ha in Rs.

D is the cost of farmhouse practices for the crop i per ha in Rs.

FR is the value of fodder receipts for the crop i per ha in Rs.

FY is the value of farmyard manure/ dung receipts for the crop i per ha in Rs.

In order to estimate the expenditure in agricultural production, the parameters considered were cost of seeds, pesticides,

fodder, fertilizer and manure, labor charges, implement charges, irrigation and interest in working capital. All the cost incurred

was calculated using Krishi diary by Dr. PDKV, Akola (2014) [13]. The cost of the seeds per hectare was estimated as:

SrScS . (3)

Where,

S is the cost of the seeds per ha. for crop i in Rs.

Sc is the cost of the seeds per kg. for crop i in Rs.

Sr is the seed rate for crop i in kg/ha.

Estimation of the cost of fertilizers applied was based on the nutrient required for the each crop in area in terms of NPK i.e.

Nitrogen (N), Phosphorus (P) and Potassium (K). The amount different fertilizer required by each crop was estimated based on

NPK contents of the fertilizers and the NPK requirement of the crops. For example, the nutrient requirement of Hybrid Jowar

is N = 80 kg/ha and P = 40 kg/ha. Applying 200 kg of Sufala (20 -20 - 0), which contains 20% N, 20% P and 0% K will

substitute the nutrient requirements by 40 kg of N and 40 kg of P. The balance 40 kg of N requirements is accomplished by

applying 87 kg of Urea (46 – 0 – 0). The economic considerations and fertilizers available in the region were taken into

account to estimate the fertilizer requirement. The value of the fertilizer and manure application per ha for a crop was

estimated as:

t

j

jj CWF

1

. (4)

Where,

F is the total cost of fertilizer and manure application per ha for crop i.

t is the number of types of fertilizers/manures applied for crop i.

Wj is the weight of fertilizer/manure j (in quintals for fertilizers/ cartload for manures/ kg for groundnut cakes) to be

applied to crop i

Cj is the cost of fertilizer/manure j (in quintals for fertilizers/ cartload for manures/ kg for groundnut cakes) to be applied to

crop i


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DOI: 10.18005/JAEB0204002

The fodder expenditure of the farm animals, implement charges and labor charges were considered as 10%, 3% and 20% of

the gross benefits respectively. The interest on capital was considered as 13% per annum on the sum of all the expenditures for

the duration of crops. The expenditure due to agricultural practices for each crop was estimated as:

IIrPLFeFSE Im (5)

Where,

E is the expenditure in due to cultivation of the crop i per ha in Rs.

Fe is the fodder expenditure per ha. for crop i in Rs.

Im is the implement charge per ha. for crop i in Rs.

L is the labor charges per ha. for crop i in Rs.

P is the cost of pesticides per ha. for crop i in Rs.

Ir is the irrigation charges per ha. for crop i in Rs.

I is the interest on working capital per ha. for crop i in Rs.

The net return per ha for each crops were computed as

E)(GN (6)

Where,

N is the net returns due to agricultural practices for crop i in Rs.

In order to standardize the computations involved to derive the cost benefits, initially the costs were calculated considering

1000 ha. The net returns due to agricultural practices for 1000 Ha in the unirrigated area was estimated as:

10

1cN.P x

n

i

NR

(7)

Where,

NR is the net returns due to agricultural practices for 1000 Ha in the unirrigated area in Rs.

Pc is the percentage of area under crop i

The net returns due to agricultural practices in the unirrigated area were estimated as:

1000

).( IADACAQASANRNRui

(8)

Where,

SA is the proposed submergence area in ha.

QA is the proposed quarry area in ha.

CA proposed colony area in ha.

DA is the proposed dam site area in ha.

IA is the proposed irrigable area in ha.

C. Agricultural Returns After Execution of Project (Irrigated)

1) Cropping Pattern Design and Project Formulation:

Within a few years of project completion, actual cropping patterns usually differ considerably from the originally

conceived pattern [8]. Nevertheless, economic feasibility and the design of an irrigation system requires assumptions at least

as to the class of crops to be grown in each season, and economic and financial analyses (farm budgets) require assumptions

that are more specific. A projected ropping pattern needs to be designed considering the various parameters involved. These

include the advent of a new type of crop in the area, balancing between seasonal water supply and demand, change in price

structure of agricultural commodities and inputs, and the expected agricultural returns. Considering these aspects, a proposed

cropping pattern was designed based on the climatic and the soil characteristics of the area, taking into consideration the local

cultural and eating habit


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DOI: 10.18005/JAEB0204002

D. Total Water Requirement for crops

In order to estimate the water demand of each proposed crop, the most important parameter is the potential

evapotranspiration (PET) of the crops in the area. The PET is often predicted based on climatic data. To compute the PET, the

reference evapotranspiration (ETo*) i.e. the PET of grass/alfalfa needs to be estimated. The modified Penman equation

(Doorenbos et. al., 1975) was used to estimate ETo* and is expressed as

(mm/day) termcaerodynami (mm/day)termradiation

)e-W).f(u).(e-(1 W.RETo* dan

(9)

Where,

ETo* is the reference evapotranspiration [mm day-1] that needs to be adjusted/corrected for the day/night time weather

conditions.

W is the values of weighing factor for the effect of radiation on reference crop evapotranspiration at different temperatures

and altitudes

Rn is the net radiation [mm day-1]

(1 – W) is the values of weighing factor for the effect of wind and humidity on reference crop evapotranspiration at

different temperatures and altitudes

f(u) is a wind related function

ea is the saturation vapor pressure [m bar]

ed is the actual vapor pressure [m bar]

The formula can be classified on two terms i.e. radiation terms (Solar Radiation) and aerodynamic terms (Wind related

parameters). The parameters in formula need to be derived based on the available meteorological data (IMD) (i.e. temperature,

wind speed, and relative humidity and sunshine hours) and geographical parameters (i.e. latitude and altitude) of the place. The

data from the nearest meteorological station at Buldana were considered for the purpose[14].

1) Radiation Terms:

The values of W and Rn were derived using the meteorological data and geographical parameters. The weighing factor W is

estimated as:

(10)

Where,

is the slope vapor pressure curve [kPaoC-1] i.e. the rate of change of the saturation vapor pressure with temperature.

γ is psychrometric constant [kPa oC-1]

The Slope Vapor Pressure Curve was derived using the formula [15, 16] taking into account the temperature of the place.

The psychrometric constant (γ) is derived by considering altitude and temperature of the place. [17-19].

Rn is derived by

nlnsn RRR (11)

Where, Rnl is the net longwave radiation [mm day-1] and Rns is the net incoming shortwave solar radiation [mm day-1]. The

net incoming short wave solar radiation Rns is estimated considering reflection coefficient as 0.25 and using the available

parameters like latitude, month of the year, sunlight hours [20-26]. Rnl is computed as:

(12)

Where,

f(t) is the correction for temperature on long wave radiation

f(ed) is the correction for vapor pressure on long wave radiation

is the correction for the ratio of actual and maximum bright sunshine hours on long wave radiation [W m-2]

f(t), f(ed) and were estimated as:

)/(W

)(ed).f(ff(t).RNn

nl

)f(Nn

)f(Nn


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DOI: 10.18005/JAEB0204002

(13)

(14)

(15)

Where,

σ is the Stefan-Boltzman constant = 5.6698 x10-8 [W m-2K-4]

K is the air temperature [oK]

ed is the actual vapour pressure [m bar]

n is the actual hours of bright sunshine [hrs]

N is the maximum possible duration of bright sunshine [hrs]

2) Radiation Terms:

The values of f (u) ea and ed were derived using the meteorological data. The saturation vapor pressure was estimated by

(16)

Where,

RH is the relative humidity [%] and ea, the saturation vapor pressure [m bar] is estimated from air temperature [15].

f(u) was estimated as:

(17)

Where, u2 is the wind speed at height of 2 meter [km hr-1]. Since, wind speed was not recorded at 2 meter; corrections were

made on wind speed based on factors given by Doorenbos et al. (1977)[20]. The monthly ET* were adjusted/corrected for the

day/night time weather conditions to obtain corrected reference monthly evapotranspiration ET (Doorenbos et al., 1977)[20]

considering monthly daytime average wind speed (m/s), monthly day and night ratio of wind speed and monthly relative

humidity (%). The monthly crop factors of each crop were estimated based on FAO methods (Doorenbos et al. 1977)[20]. The

crop factors (CF) of each crop were multiplied with monthly ET to obtain the crop evapotranspiration ETC of each crop for the

corresponding month. The effective rainfall (ERF) was estimated based on USDA methodology [27]based on monthly rainfall

and consumptive use. The monthly water requirement (WR) was estimated as

ERFETWR c {If WR <0 then WR=0} (18)

Where,

WR is the monthly water requirement of crop i for month k

ETc is the evapotranspiration of crop i for month k

ERF is the effective rainfall for month k

The irrigation scheduling was done on fortnightly basis. The irrigation requirement for fortnightly basis was estimated, if

the period of crop cultivation begins at second fortnight or extends up to first fortnight. The estimation of fortnightly WR is

similar to monthly WR (eqn. 18) except for fortnightly values of ETc and ERF. The first and second fortnightly values of ETc

and ERF were obtained from sliding scale method. The monthly net water requirement NWR of the crops is the same as WR

except the last fortnightly irrigation has been curtailed.

The total water requirement TWR in mm was estimated per 1000 Ha was estimated as:

10..

1 1

xPNWRIETWR c

n

i

d

k

(19)

Where,

K4

f(t)

01.0e444.34.0edf d

N

n9.1.0

N

nf

100

RHeead

)100

u1(27.0f(u)

2


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IE is the irrigation efficiency

NWR is the net water requirement for crop i for the month k

d is the number of calendar months of cultivation for crop i

The irrigation efficiency was considered as 50% considering evaporation from canals and dam, conveyance and seepage

losses. Based on NWR obtained above the water requirement of total area in million cum was estimated.

E. Economic Considerations

The change in price structures is a crucial and sensitive parameter that is often unpredictable. Several external parameters

govern the prices of agricultural commodities, which include:

1. Production of the crops or some alternate crops in the area, in the state, or in the country.

2. The government policies regarding import and export of agricultural commodities.

3. The purchasing power of consumers.

4. The cost of the agricultural inputs and the government policies regarding agricultural subsidies.

5. The shift or changes in consumer habits.

On the other hand, the cost of agricultural inputs is influenced by various factors:

1. The cost of fertilizers, in India is dependent on government policies like subsidy and import regulations and cost of raw

materials.

2. Estimating requirement of pesticides for crop protection is more complex and unpredictable as new pesticides are being

launched and the use of existing pesticides being restricted or banned due to environment and health concerns.

3. The labor charges are dependent on the migration of labors and the industrialization.

Considering the complexity and the unpredictability, the prices of the agricultural commodities and the prices of

agricultural inputs after execution of the project were considered as the current prices. The estimation of the value of irrigated

produces were estimated in the similar fashion than that of the current trend except in equation 7, the values of SA, QA, CA

and DA were considered as zero as these areas would not be cultivable and the irrigation cost which was not considered as the

area was not irrigated. The irrigation requirement of various crops (bajra, groundnut, wheat and jowar etc) estimated above

were reviewed to identify the calendar months in which irrigation is required. The irrigation charges of a crop are the sum of

the monthly charges of the month in which irrigation is required. [28]

III. RESULTS AND DISCUSSIONS

A. Land Use Pattern

For collection of baseline data on land environment 18 villages that fall in the command area in Khanapur taluka of

Belgaun district, Karnataka were identified and surveyed. The land use pattern in different villages is given in Table-1. The

catchment area of about 1033.5 ha (4.07%) of the total land is under agriculture of which 147.07 ha (0.38%) is irrigated and

866.4 ha (3.49%) is unirrigated. The main source of irrigation is either well, perennial nalas or river. About 21250 ha (83.77%)

area is under forest. The main forest products are teak salwood, bamboo, firewood and Mahera. The area under culturable and

unculturable wasteland is 2656 ha and 427.6 ha respectively. The present land use in Mahadayi River is shown in Fig. 1. Soils

in the project area are mostly lateritic and occur on gently undulating to hilly topography. Physical properties of soils of

different villages in the study area are given in Table-2. Moreover, the soils are chemically different in characteristics, which

are shown in Table 3.

The cultivated land in the area is divided into two main categories; (i) Paddy lands and (ii) land under other crops including

horticulture crops. Further the paddy land in the area is of three types; viz. Khazan land (saline soil), Ker land (sodic soil) and

morad land (lateritic soil). The important crops grown in command area are rice, ragi, pulses, coconut, groundnut, vegetables

and fruits. The main crops are grown in all villages in the study area are cereals-paddy, wheat, jowar; pulses- moong, gram;

oilseeds- sesamum, soybean; cashcrops-sugarcane and banana.


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Fig. 1 The present land use in Mahadayi River

TABLE 1 LAND USE PATTERN IN THE COMMAND AREA, KARNATAKA

Sl.

No.

Name of the

Village

Total area

(Ha)

Land Use Pattern, Hectares

Forest Agriculture Wastelands

Irrigated Unirrigated Culturable Unculturable

1. Kapoli K.G. 1171.67 784.67 10.02 202.75 137.26 36.97

2. Kapoli K.C. 755.22 612.25 - 49.00 83.74 10.23

3. Kirvale 999.46 848.02 4.86 57.45 62.99 26.14

4. Deogaon 666.55 612.34 - 11.41 23.31 19.49

5. Holade 1252.55 1149.49 2.23 14.27 55.24 31.32

6. Gawali 5309.61 4397.25 3.17 57.26 758.24 93.89

7. Jamagaon 1481.30 1373.62 33.36 22.24 48.95 3.13

8. Pastoli 692.62 626.69 22.36 15.32 14.56 13.49

9. Kongale 1249.89 1151.41 18.34 14.29 52.20 13.65

10. Merase 1987.04 1647.41 26.47 109.33 177.09 26.74

11. Kabanali 927.17 825.34 8.20 14.49 61.15 17.89

12. Mugawade 1153.94 982.75 1.21 59.11 90.77 20.10

13. Chapoli 889.50 646.62 - 26.39 200.09 16.40

14. Amagaon 3410.26 3090.86 - 22.93 241.59 54.88

15. Kanjale 316.28 146.59 13.89 37.39 108.82 9.59

16. Kavale 533.26 - - 21.58 498.32 13.36

17. Jamboti 296.22 187.50 2.93 71.00 29.58 5.21

18 Chikkle 2275.15 2167.81 - 80.11 12.14 15.09

Total 25367.69 21250.62 147.04 886.42 2656.04 427.57

Source: Census Report (2001)

B. Land Capability Classification of Soil

The land capability of 15 dominant soil units have been grouped into six land capability classes suitable for agriculture,

forest, pasture, recreation and rehabilitation (Fig. 2). In the region of 1000m good to marginally good land covers on area of

9198 ha while land suitable for forestry and other purposes is spread over 2897 ha further, in evaluating 10000m area (not

shown) it was observed that about 66 percent of land is suitable for agriculture while remaining 34 percent area is classification

as suitable for forest and other purposes.


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Fig. 2 Land capability classes

Land capability classification has been done on the basis of four criteria:

Soil depth, soil texture, and soil drainage and soil erosion.

Soil depth: About 48 percent of the area (24,511 ha) in the study region has soil of very shallow to moderately deep soil (75

to 100 cm depth) is spread on 5,293 ha (10:34 percent) while deep soil is found over 12,685 ha (24.8%). Very deep soils cover

an area of about 8,650 ha (16.9%). Soils of different depth are shown in Fig. 3.

Fig. 3 Soil depth

Soil Texture: The predominant soil texture in clay-to-clay loom and covering 27,056 ha area (52.9%). Followed by sandy

loom and sandy clay loom (14670 ha).

Soil drainage: In the region of 10000m width along the river about 30% of the soils are excessively drained and covers an

area of 15,411 ha and well-drained soil are spread on 14013 ha (27.4%). Poorly drained soils are confined to only 195 ha

(1.6%) and well-drained soil is spread over 3250ha.

Soil Erosion: In the study zone of 1000m long the river course slight to moderate erosion problem confined to over

10307ha. While several erosion covers 1788 ha.

1) Existing Crop Use Pattern:

The existing cropping pattern based on the average of the four years (2008-09 to 201-12). Cotton (cash crop) is the major

crop grown in this region (41.9%) followed by jowar (20.1%), which is the main cereal crop. The other cereal crops include

bajra and wheat. Tur, udid and gram are the pulses cultivated in this area. The oilseeds grown in this area are groundnut

sesamum and sunflower. Rice is the main serial crop and covers a large area; to a small extent millets are also grown. Cash

crops like cashew nut, coconut, bitternut, sugarcane and fruit crops viz. pineapple banana and mango are the major crops in

this region. The cropping pattern in the zone within the width 10,000 m on both sides along the river Mahadayi is shown in Fig.


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DOI: 10.18005/JAEB0204002

2. The rice crop covers an area 25% in a 10,000 m wide band while the narrow band (1000 m width) is spread over 43% area.

Cashew alone is grown on 77,776 ha (38.5%) while cashew- coconut mix plantation covers an area over 29544 ha in the region

2) Proposed cropping pattern:

The proposed cropping pattern is designed for two seasons kharif (rainy season) and rabi (winter season). It is proposed to

irrigate 65 and 80% of the area during kharif and rabi season respectively. 45% of the kharif crops are proposed to rainfed with

draught varieties or rainfall will take care of the irrigation requirements, including groundnut (20% of area), oilseeds(15%) and

sugarcane (10%). The irrigated rabi crops includes wheat (20% of area), oilseeds(15%), pulses (15%), soybean(10%). Two

seasons crops like coconut, banana and pulses are propsed to be cultivated and irrigated during both the kharif and rabi seasons,

which constitute 25% of the area.

3) Fertilizer Requirements and Costs:

The cost of fertilizers and their NPK contents is shown in Table 2. The nutrient requirements cost of fertilizers and manures

per hectare for existing and proposed crops are depicted in Table 3. The unit fertilizer and manure cost for turmeric was the

highest (Rs.17, 100.00) and lowest for groundnut (Rs.548.00).

TABLE 2 NPK CONTENTS AND PRICES OF FERTILIZERS FOR THE YEAR 2000–01 IN THE STUDY AREA.

Sr. No Fertilizers NPK Contents

Prices in Rs. /100 kg N P K

1 Urea 46 0 0 476.00

2 Single Super Phosphate (SSP) 0 16 0 300.00

3 Sufala1 20 20 0 660.00

4 Sufala2 19 19 19 660.00

5 Farmyard Manure/Compost 150.00

6 Groundnut Cakes 800.00

Per cartload

Source: Fertilizer Corporation of India

TABLE 3 NUTRIENT REQUIREMENTS, COST OF FERTILIZERS AND MANURES PER HECTARE FOR EXISTING AND PROPOSED CROPS (RS. /HA)

Crop

Organic Manure

Requirements Fertilizer

Requirements per ha.

in Kgs. Manure

cost Rs.

Name of

the

Fertilizer

Rate of

Applicat-

ion kg/ha

Fertili-

zer Cost

(Rs./ha)

Fertilizer &

Manure

Cost

(Rs./ha)

FarmYard

Manure

(cartload)

Ground-

nut Cakes

(Kg) N P K

Hy. Jowar 10 80 40 0 1500.00 Sufala1 200 1320.00

Urea 87 414.12 3234.00

Bajra 10 60 20 0 1500.00 Sufala1 100 660.00

Urea 87 414.12 2574.00

Tur 10 25 50 0 1500.00 Sufala1 125 825.00

SSP 157 471.00 2796.00

Mung & Udit 10 20 40 0 1500.00 Sufala1 100 660.00

SSP 125 375.00 2535.00

Groundnut - 16.5 16.5 0 - Sufala1 83 547.80 548.00

Sunflower - 40 60 0 - Sufala1 200 1320.00

SSP 125 375.00 1695.00

Sesamum 25 25 0 - Sufala1 125 825.00 825.00

Soybean - 30 75 30 - Sufala2 158 1042.80

SSP 282 846.00 1889.00

Cotton 12 30 15 0 1800.00 Sufala1 75 495.00

Urea 33 157.08 2452.00

Wheat 5 40 20 0 750.00 Sufala1 100 660.00

Urea 44 209.44 1619.00

Gram

(unirrigated) - 25 40 0 - Sufala1 125 825.00

SSP 94 282.00 1107.00


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DOI: 10.18005/JAEB0204002

LS Cotton 20 100 50 50 3000.00 Sufala2 263 1735.80

Urea 110 523.60 5259.00

Gram

(irrigated) - 25 50 0 - Sufala1 125 825.00

SSP 157 471.00 1296.00

Chilies - 150 50 50 - Sufala2 263 1735.80

Urea 218 1037.68 2773.00

Tomatoes 125 0 0 Urea 272 1294.72 1295.00

Turmeric 50 1200.00 17100.00 17100.00

Sunflower

(Hybrid) - 80 60 0 - Sufala1 300 1980.00

Urea 44 209.44 2189.00

Cauliflower - 100 50 0 - Sufala1 250 1650.00

Urea 109 518.84 2169.00

Source: Dr. PDKV Handbook, 2014

TABLE 4 CROP WISE EXPENDITURE PER HECTARE FOR EXISTING UNIRRIGATED CROPS IN THE COMMAND AREA OF JDP (USING COST OF CULTIVATION)

Sl. No. Crop

Duration

of Crops

in Days

Seed Cost

per ha in

Rs

Fertilizer

and

manure

cost in Rs.

Fodder

Expenses

Implement

Charges in

Rs.

Labour

Charges in

Rs.

Cost of

pesticides In

Rs.

Irrigation

Charges in

Rs.

Interest in

Working

Capital in Rs.

Total

Expenses in

Rs.

1 Hy.Jowar 120 320.00 3234.00 619.31 185.79 1238.62 466.50 0.00 259.18 6323.40

2 Hy. Bajra 105 120.00 2574.00 369.78 110.93 739.57 337.50 0.00 159.01 4410.79

3 Tur 170 2250.00 2796.00 1683.65 505.10 3367.31 277.50 0.00 658.74 11538.30

4 Mung 70 600.00 2535.00 1032.77 309.83 2065.55 277.50 0.00 170.05 6990.70

5 Udid 70 600.00 2535.00 541.35 162.40 1082.69 277.50 0.00 129.62 5328.56

6 Groundnut 120 1800.00 548.00 815.89 244.77 1631.78 435.00 0.00 234.02 5709.46

7 Sunflower 100 1750.00 1695.00 1155.43 346.63 2310.86 396.00 0.00 272.61 7926.52

8 Sesamum (Til) 90 200.00 825.00 948.64 284.59 1897.28 105.00 0.00 136.57 4397.08

9 Soybean 110 1125.00 1889.00 780.11 234.03 1560.21 366.00 0.00 233.28 6187.63

10 Ordinary

Cotton 180 225.00 2452.00 1156.38 346.91 2312.76 996.00 0.00 480.12 7969.17

11 Wheat 120 1375.00 1619.00 706.80 212.04 1413.60 892.50 0.00 265.80 6484.74

12 Gram 105 1250.00 1107.00 1061.41 318.42 2122.82 390.00 0.00 233.72 6483.37

TABLE 5 WATER REQUIREMENT OF VARIOUS CROPS IN THE STUDY AREA

Serial No. Crops Total water

requirement

Net water Requirement

in 1000 ha

Two seasonal crops

1. Coconut 343.20 0.3432

2. Banana 270.12 0.2161

3. Pulses 416.37 0.0833

Kharif Crops

4. Groundnut 23.03 0.0230

5. Hy-jower 51.50 0.1030

6. Sugarcane 43.74 .0437

Rabi Crops

7. Wheat 241.02 0.3615

8. Moong 196.33 0.2945

9. Soybean 206.70 0.3514

10. Sunflower 197.58 0.0593


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DOI: 10.18005/JAEB0204002

4) Proposed Cropping Pattern:

The proposed cropping pattern is designed for two seasons kharif (rainy season) and rabi (winter season). It is proposed to

irrigate 60% and 80% of the area during kharif and rabi season respectively. 40% of the kharif crops are proposed to rainfed

with draught varieties or rainfall will take care of the irrigation requirements, which includes groundnut (20% of area), pulses

(20%) and sheshum (10%). And 20% of land will remain uncultivated during rabi season. The irrigated kharif season crops

include hybrid jowar (20% of area), sunflower (10%) and tomatoes (10%). The irrigated rabi crops includes oilseeds (20% of

area), wheat (15%), gram (15%) and tomatoes (10%). Two seasons crops like cotton (10% of area), chillies (8%) and turmeric

(2%) are proposed to be cultivated and irrigated during kharif and rabi season, which constitutes 20% of the area.

The monthly reference evapotranspiration of the study area is depicted in Table 4. The ET was the highest during May

(291.67 mm) followed by April (250.78 mm) and the lowest during December and November (125.58 mm and 128.63 mm

respectively).

5) Irrigation Requirement and Costs:

The total water requirement for the irrigated area is depicted in Table 5. The total water requirement for 1000 ha and

command area are 4.32 and 330.59 million cum respectively. The evapotranspiration for rabi crop gram was the lowest (256.56

mm) and the two seasonal crop Turmeric was the highest (784.56 mm). In the proposed cropping pattern the total water

requirement (considering irrigation efficiency) of wheat was 55.31 million cum, the highest and the lowest was sunflower

(3.52 million cum).

The estimated irrigation charges of various crops are shown in Table 8. The charges for irrigating cotton were the highest

(Rs. 735.00) followed by turmeric and rabi crops (Rs. 660.00). The cost of irrigating kharif crops was the lowest (Rs. 240.00).

IV. CONCLUSIONS

The distributional impact of dams on the productivity of cropland was examined. Satellite data have been used to study the

upstream and downstream benefits on catchment areas. The GIS database we used is made of layers of information. Each layer

is made of many entries to which alphanumerical data are connected. Dams can relatively reduce water scarcity; further can

lead to enlargement of catchment areas and eventually leads to high yield. Speaking of irrigation and agriculture, dams have

been clearly useful for downstream catchment areas thus enabling better crop productivity. A comprehensive assessment of the

total benefits and costs clearly necessitates a credible quantitative analysis. The objective of irrigation projects is to increase

agricultural production and consequently to improve the economic and social well-being of the rural population. However,

changing land use patterns may have other impacts on social and economic structure of the project area. The study implies that

water development sector and any evaluation of the net development contribution to a social system such as an irrigation

system requires a social analysis for ensuring effective, efficient and significant development impact on policy and projects.

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