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Technical Session V

DECISION SUPPORT TOOLS FOR NATURAL RESOURCE MANAGEMENT

GIS DESIGN AND DATABASE DEVELOPMENT

Hugh W. Calkins
Department of Geography
University at Buffalo
Amherst, NY 14261, USA

ABSTRACT

GIS design is the short term for identifying the process of planning, designing and implementing a GIS. Also included under the umbrella of this term are the necessary plan for maintenance of both the GIS and the database accompanying it. This paper presents an overview of the current practice of GIS design emphasizing the structure of the process, the documentation requirements and the verification and validation needed with each step in the process. The GIS design process begins with a needs assessment and continues through all steps required before the GIS becomes operational. While the GIS design process is aimed at creating documentation and plans, it also should assist in the management of the GIS development project. This paper continues by describing the linkage between the needs assessment and database design stages of the GIS design process and management tools for controlling scheduling and the GIS costs. Commonly available management tools provide support for schedule and cost control. The entire GIS design process, including the management tools, are linked together so changes can be evaluated and revised schedules and cost estimates prepared.

INTEGRATED WATER RESOURCES MANAGEMENT-THE NEED FOR "HARD" AND "SOFT" SYSTEM TOOLS.

Ian R Calder
Centre for Land Use and Water Resources Research
University of Newcastle upon Tyne, UK

ABSTRACT

Chapter 8 of Agenda 21 states that “Prevailing systems for decision-making in many countries tend to separate economic, social and environmental factors at the policy, planning and management levels. ” Whilst progress has been made since the Earth Summit in 1992 in developing “hard system” tools to assist land and water resource decision makers balance competing demands for water resources, conservation and production economics it appears that less progress has been made in developing tools which take account of the social factors. The paper briefly reviews examples of “hard system” tools, the NELUP and Waterware decision support systems and discusses the need also to develop “soft system” tools which facilitate participatory approaches, incorporate indigenous knowledge and, in conjunction with the “hard system” tools, are able to predict the social or “livelihoods” impacts of land use decision making.

Integrated Water Resources Management is now perceived as the philosophy or process underlying the management of water resources. Unlike earlier quests for the development of a tightly defined “Water Resources Master Plan” there is increasing recognition that Integrated Water Resources Management is more likely to be achieved if it is structured as an incremental, evolving iterative process. Integrated Water Resources Management needs to accommodate means of obtaining progressive commitments from stakeholders to new developments and initiatives. There is a need for technological, or “hard”, methodologies to be blended and tempered with “soft” methods that can deal with the human dimension.

Tools are being developed in both the hard mould which captures all our recent advances in information technology and the physical and environmental sciences and in the soft mould which contains our new appreciation of the complexity and importance of the human players in unstructured real world systems; systems where tensions and conflicts abound and where the linkages between different interest groups are ill defined.

These “hard “ and “soft” system tools are with us today. The challenge for us is to decide if they can be linked together usefully to assist the quest for sustainable development and, some would argue, sustainable societies, and how best this can be done. Partly this is a technological problem but perhaps more fundamentally the problem lies in bringing together researchers and practitioners from the diverse biophysical sciences and socio-economics disciplines. Paradoxically, one of the most significant outputs from the task of developing these “soft” and “hard” system linkages is that of providing a focus for discussion which may assist in “building bridges” between the disciplines and providing a structured environment for systematically analysing the linkages between our land and water resources and the impacts on society.
The paper takes forward the arguments discussed in the book “The Blue Revolution” published by Earthscan.

MULTICRITERIA METHODS AND DYNAMIC MODELLING FOR LOCAL PLANNING

J Sai baba , Novaline Jacob, ASV Lakshmi and PVSSP Prasada Raju
Advanced Data Processing Research Institute
Department of Space, Govt. of India
Manovikas Nagar post, Secunderabad, 500009, INDIA

ABSTRACT

The development of an area happens due to complex interactions among its constituents viz., natural resources, social, physical, human and financial aspects. Sustainable development of the area should first make the best use of its resources and then engage and trade with other economies. Spatial decision problems like sustainable development involve a large set of feasible alternatives and multiple conflicting evaluation criteria. Multicriteria based methods based on multiattribute decision making, collaborative decision making etc. provide a number of techniques useful in spatial modeling applications. Most of the commercial GIS software packages do not offer analytical modeling capabilities required in complex spatial planning process. This paper in its first part describes a general purpose software called DecisionSpace developed using the Arc Macro Language of Arc/info GIS. It provides a decision support environment by tightly integrating the multicriteria methods viz., Analytical Hierarchy Process(AHP), Factor of Importance, Compromise programming, Fuzzy logic with the Arc/Info GIS software. The different modules of the package viz. Project creation, Expert module, User module are briefly explained. Applications of DecisionSpace for some local planning tasks like Water Harvesting Structure siting are also provided.

The second aspect discussed in the paper deals with the integration of dynamic modeling methods with a GIS. Local development can be conceived as a self –organizing system in which natural constraints and institutional controls such as land use policies influence the way in which local decision making processes produce macroscopic developmental patterns. Cellular automata based self-organizing systems have proved to be attractive in dynamic simulations for a number of reasons. Cellular automata based approach provides a means to simulate the different land use scenarios that may result from different land use policies. The increasing availability of higher spatial resolution remotely sensed imagery provides temporal information from which time series analysis can provide stochastic representation of landscape transformations. The contemporary GIS packages are deficient in providing built in dynamic modeling capabilities. Applications of Cellular automata and other dynamic modeling methods are discussed in the second part of the paper. Dynamic simulation methods and multicriteria methods when integrated with GIS facilitate planners to generate growth scenarios and evaluate alternate scenarios.

ADVANCES IN WATERSHED MODELING AND MANAGEMENT USING GIS

R. Jayakrishnana, R. Srinivasanb, M. Di Luzioc, C. Santhid, J. G. Arnolde

a)GIS Specialist, b)Associate Professor, c)Post-doctoral Research Associate,
d)Post-doctoral Research Associate, Blackland Research and Extension Center,
Texas A&M University System, 720 East Blackland Road, Temple, Texas, 76502,
USA.
eHydraulic Engineer, USDA-Agricultural Research Service, 808 East Blackland
Road, Temple, Texas, 76502, USA.

ABSTRACT

Water resources management and hydrologic modeling studies are intrinsically related to the spatial processes of the hydrologic cycle. Development of spatial data bases together with Geographic Information Systems (GIS) lead to tremendous progress in detailed spatially distributed analysis of hydrologic and water resources systems. Integrated use of
digital spatial data and computer-based models enable the water resources professionals to study the water resources systems efficiently, with significant savings in time and cost. It also facilitates analysis of the impact of different watershed management scenarios on water yield and quality. This paper describes some recent developments in the application of GIS for water resources management, assessment, flood analysis, and water quality management in the United States with practical applications. This opens the door for future enhancements and challenges in the GIS and water resource management decision support system such as real time prediction of water quantity and quality, short and long term forecasting of water availability and integration of surface and groundwater linkages.

A REMOTE SENSING-GEOGRAPHIC INFORMATION SYSTEM COMPATIBLE SURFACE RAINFALL RUNOFF MODEL FOR REGIONAL LEVEL PLANNING

Dhrubajyoti Sen
Department of Civil Engineering
IIT Kharagpur, INDIA

ABSTRACT

The application of a physically based surface-runoff model is demonstrated for regional level water resource system planning. The model takes as input the effective rainfall over a catchment and produces discharge and depth hydrographs at critical points within the catchment. Essentially a distributed model, it may easily be integrated to remotely sensed (RS) or geographic information system (GIS) database for obtaining the various parameters required for the model to run. The overland and channel flows are modelled using the kinematic wave approximation of fluid flow and are solved by the finite difference method. An interactive graphical user interface (GUI) has been developed for handling the database for the model and it may run on a personal computer without much memory requirement. Regional level planners may find the model useful for such activities like design of flood protection works, erosion control measures, etc.

EVOLVING A DSS INTEGRATING USLE AND GIS FOR SOIL CONSERVATION PLANNING IN SEMI ARID WATERSHEDS OF ATTAPPADY VALLEY

Gopakumar R and James E J
CWRDM, Kozhikode – 673571, INDIA

ABSTRACT

A decision support system (DSS) provides a representation of the complex system under study in the form of an integral model. A DSS has many advantages that are helpful to a decision maker like:

* It assists in exploring decision space with numerous possible measures, as well as multiple, possibly conflicting objectives

* Adaptable to changing needs and environments of the problems studied

Soil water erosion is a serious environmental problem affecting large areas of the agricultural landscape in our country. The problem of soil erosion varies largely depending upon climate, topology, soil and landuse etc. To control soil erosion, sound land management practices are to be adopted. Various methodical approaches can be applied to the problem of modelling the spatial patterns of soil erosion. Universal Soil Loss Equation (USDA, 1978) is a popular prediction model to estimate long-term average annual sheet and rill erosion. The factors of Universal Soil Loss Equation (USLE) are geographic in nature, and therefore they can be referenced to a particular location. Under the NRDMS project on Hydrology of Small Watersheds, a study has been carried out to develop a decision support system for soil conservation planning in the watersheds of Attappady valley of Kerala by integrating USLE model and GIS.

Study Area

The Payakkara watershed is located between 11o 2' and 11o 6' N latitude and 76o 35' and 76o 40' E longitude in Agali Panchayat of Attappady block in Kerala State. The annual rainfall recorded within the watershed of 23.2 km2 area varies spatially from 1800 mm to 2500 mm. The watershed has a complex topography and the altitude varies between 500-950m above the mean sea level. The soils in this area are classified under six soil series. A major portion of the watershed is classified as wasteland.

Universal Soil Loss Equation (USLE)

The USLE is developed as method to predict average annual soil loss from sheet and rill erosion. USLE is given by;

Soil loss, A = R*K*L*S*C*P tons/ha

Where;

R - Rainfall erosivity factor which is the product of two characteristics; Kinetic energy
(E) and maximum 30 minutes intensity (I30).

K - Soil erodibility factor which depends on the texture class of the soil.

L - Slope length factor

S - Slope gradient factor

C - Cropping management factor which includes the interrelated effects of cover, crop
sequence, productivity level and rainfall distribution

P - Erosion control practice factor accounts for the effect of mechanical erosion control
measures on soil loss.

Data availability and Derivation of USLE variables in GIS

For modelling soil erosion, digital maps have been derived in ILWIS for each of the USLE variables, using the available data and maps on rainfall, soils, landuse and topography. Rainfall erosivity factors (R) are calculated using the continuous storm records and by spatial interpolation, rainfall erosivity map of the watershed is derived. Soil erodability values (K) are selected from tables (ARS, 1975) for the soil series in the study area. By using the soil map and the attribute information of K factor, soil erodability map has been prepared. By spatial interpolation of the digitized contour map, a digital elevation model and slope map is prepared. By using the slope map, maps of slope length factor and slope gradient factor have been prepared.

For cropping management factor C, a map has been prepared by using the landuse map and the C factors selected from tables (ARS, 1975; Wischmeier, 1974). The baseline condition of the watershed has been assumed to be an untreated in terms of mechanical control measures.

Modelling soil erosion under alternate land management scenarios

The different landuse categories in the study area are : agricultural plantations (AP), annuals (AN) evergreen/semi evergreen (EG), degraded forest (DF), deciduous open (DE), land with or without scrub (SC) and permanent fallow (PF). Using the DSS, soil erosion has been modelled under different scenarios considering alternate erosion control practices for the different land categories. As an example, in Scenario-1, the entire watershed is assumed to have no mechanical treatments whereas Scenario-2 includes a package of proposed treatment measures for the watershed.

Comparison of the modelling results of different scenarios will provide information on the effect of watershed treatment packages on changing the soil erosion pattern. Statistical summary of the classified average annual soil erosion for two scenarios are given in Table 1. The spatial distribution of soil erosion for Scenario_2 presents an improved picture compared to Scenario_1.

Table 1. Statistical summary of soil erosion for two scenarios

Class Erosion, (t/ha/yr)Upper limit Scenario_1 Scenario_2
Area (sq.km.) Area % Area (sq.km.) Area %
1 25 13.73 59.18 14.22 61.32
2 50 3.88 16.75 3.73 16.09
3 100 1.15 4.96 0.99 4.26
4 200 0.98 4.21 0.82 3.52
5 500 2.39 10.30 2.37 10.20
6 1000 0.80 3.44 0.80 3.44
7 4000 0.27 1.16 0.27 1.16
Total Area 23.20
Erosion, t/ha/yr (weighted av.) 114.60 112.64

Conclusion

This study demonstrates the utility of a DSS integrating USLE and GIS to facilitate soil conservation planning of watersheds in Attappady valley. Using the system, the soil erosion potential within the Payakkara watershed was modelled and the results presented as georeferenced maps. Data used to generate the USLE variables included digitized topographic, landuse and soil maps, and tabular precipitation data.

The DSS is useful to model and map the soil erosion for alternate landuse scenarios that includes implementation of soil conservation practices. The GIS part of the system allows the user to place queries on the maps for location specific information needed for decision support in land management for which results will be available in map form. The ability for predictive modelling given the scenarios demonstrates the robustness of the DSS, and its utility as a soil conservation planning tool.

References

1. CWRDM (1997). Ecorestoration Plan. Attappady Wasteland Comprehensive Environmental Conservation Project. Volume 1 . CWRDM Kozhikode
2. ITC (1998). ILWIS Users Manual. International Institute for Aerospace Survey and Earth Sciences, Enschede
3. Kent J and Bubenzer G D (1989). Soil Loss Estimation. Soil Erosion. John Wiley and Sons. Chichester
4. Pennsylvania Department of Environmental Protection (1996). Soil Erosion and Sedimentation Control Manual for Agriculture. Bureau of Land and Water Conservation. Harrisburg.
5. Wischmeier W H and Smith D D (1978). Predicting Rainfall Erosion Losses : a Guide to Conservation Planning. Agriculture Handbook. No. 537. US Department of Agriculture Washington D.C.

INTEGRATION OF A LINEAR PROGRAMMING TOOL WITH SPATIAL DECISION SUPPORT SYSTEM FOR ALLOCATION AND IMPACT ASSESSMENT OF OPTIMUM SOIL CONSERVATION STRATEGIES IN NAGWAN WATERSHED IN HAZARIBAGH DISTRICT OF JHARKHAND, INDIA

Ravinder Kaur *and Debapriya Dutta #
* Division of Environmental Sciences, Indian Agricultural Research Institute, New Delhi-110 012
# Department of Science & Technology, New Mehrauli Road, New Delhi

ABSTRACT

Monitoring and management of non-point source pollutants like sediments in run-off from large watersheds is technically difficult, complex and time consuming because different parts of the watershed, exposed to different agricultural systems, do not yield sediment/ run-off at similar rate and the available resources with the government are not adequate to treat the entire area immediately. It is therefore necessary to locate critical source areas, which have greater potential to yield sediment. Once the problem areas are identified, a variety of techniques can be used to minimize the impact of agriculture and other activities on environment. These practices are generally area specific and thus general guidelines are not feasible. The cost effectiveness of the practices also varies significantly from site to site. Evaluating alternative management practices through experiments at a site is generally not feasible. To identify non- point source pollution problem areas within watershed and to calculate the effectiveness of hypothetical solutions, model and decision support system are of great use. A decision support system is any computer system, hardware or software designed to support decision-makers interactively in thinking about and making decisions about relatively unstructured and complex environmental problems. It has three major components: an user interface, a database and a model. The user interface component helps in presenting and receiving information from a user and the data base component manages data required for the running of different types of models / methods embedded in the model base for simulating changes in the objects and attributes. For planning purposes, this ability to dynamically change information, forecast and perform sensitivity analysis is essential.

Keeping this in view, an attempt has been made through this study to integrate a Spatial Decision Support System (SDSS) with a linear programming tool for proposing and analyzing the impact of alternative soil conservation strategies on the sediment yields from the total and the SDSS based high priority areas within the test watershed of Nagwan in Hazaribagh district of Jharkhand, India. The SDSS used in this study comprised of digital maps on contour, soil and landuse themes and database files; Soil and water assessment Tool (SWAT) hydrological model and its interface with ARC-VIEW GIS package. Since different areas in a watershed are dominated by land use and soil properties different enough to impact its hydrology, therefore , for modeling purposes, the test watershed was first partitioned into a number of sub-watersheds by rasterisation and the input information for each sub-watershed was organized into weather, land cover, soil and management, groundwater and main channel or reach categories for homogeneous hydrological response units (HRUs) within a sub-watershed. By partitioning the watershed into sub-watersheds, the user is able to relate different areas of the watershed to one another. This sub watershed-level input information was used by the hydrologic model component of the SDSS for simulating their impact on total soil loss and run-off from the test watershed for simulation period (1981-92). Besides this, information on soil erosion by each HRU in a sub-watershed, along with the other input details on crop production, cost of cultivation, resource limitation and social preferences for crops, was used for suggesting an optimum soil conservation practice plan for the whole watershed through a Linear Programming (LP) resource optimization algorithm. The above algorithm for the test watershed (with 15 sub-basins and 44 HRUs), was formulated with the practice factor (P) of the USLE equation as the decision variable. Technical coefficients on per ha basis such as soil loss/ ha/ HRU etc., were also evaluated for the formulation of the objective function and the constraints of the above algorithm. The objective of the proposed LP algorithm was minimization of the sum of product of soil loss (in tonnes) and P – factor per HRU subject to 15 soil loss – constraints (one per sub-basin). The optimum solution of this algorithm was the following conservation practice plan for the proposed watershed (Fig. 1). In the above conservation plan, a P-factor ranging between 0.52-0.55 referred to contour bunding practice while a P-factor ranging between 0.31-0.33 indicated sowing along contours. The earlier practice was suggested for areas under paddy cultivation and the latter practice was suggested for the areas under maize cultivation. Forested areas were not put under any conservation practice and this was indicated by a P-factor value of 1.0. Incorporation of these conservation practices within each HRU of the test watershed resulted into the following total sediment yields from the test watershed for the (1981-92) simulation period (Fig. 1). It could be observed from these results that the above conservation practice plan for the test watershed could lead to about 44.52% reduction in the total sediment yield from the watershed. In other words, it could bring down the total sediment yield of the watershed from about 26 t/ha to just 14 t/ha. Since the proposed watershed comprises of very deep soils (> 150 cm) therefore for such a watershed soil loss tolerance value was fixed at 11.4 t/ha as per the soil loss tolerance-lookup table of Macormack and Young (1981). It could thus be observed that the optimized conservation practice plan suggested by the proposed LP model can help in bringing down the total sediment yield of the proposed watershed quite close to its soil loss tolerance value.

However, the above plan suggested the implementation of some or the other conservation practice in majority of the cropped areas within the watershed. Since central and state cost sharing funds for such activities are limited therefore the need of the time is to prioritize the implemenntation of these conservation strategies in only those areas of the watershed which can lead to maximum soil loss reductions with minimum of fund utilization. For this, three conservation practice-prioritization criteria were designed and their impact on the total sediment yield reductions was analyzed. These prioritization criteria so formulated were as follows:

1. Allocation of LP optimized conservation practices in only those areas where soil loss is greater than 40 t/ha ,

2. Allocation of LP optimized conservation practices in only those areas which have area greater than 500 ha, and

3. Allocation of LP optimized conservation practices in only those areas which have soil loss greater than 40 t/ha and area greater than 500 ha .

It could be noticed from the results that prioritization criteria No. 1 could lead to lowest reductions (11. 82 %) in the observed/ actual sediment yields of the test watershed. This was followed by the prioritization criteria No. 3 (18.6%) & No. 2 (22.32%). Although total watershed scale sediment yield values simulated with the conservation plan No.2 seemed to be lower than those obtained with the plan No.3, yet prioritization criteria No. 3 was found to be more feasible and acceptable. This was because conservation plan No.2, covering about 50 % area of the total watershed, could lead to about same reduction in the observed sediment yield of the test watershed as obtained by the conservation plan No. 3, imposed on just 25 % area of the total watershed.

Thus, this study could lucidly demonstrate the application/use of such integrated LP-SDSS systems for proposing optimum soil conservation measures for target problem areas and for analyzing their impact on the sediment yields from any test watershed.

References

1. Macormack, D.E. and Young, K.K. (1981) Technical and societal implications of soil loss tolerance. In Morgan, RPC (Ed.), Soil Conservation: Problems and Prospects. John Wiley & Sons, Chichester: 365-376.

GROUNDWATER MODELLING OF UNCONFINED AQUIFER SYSTEM OF CRYSTALLINE AREA - A CSAE STYDY IN LAPSIYA WATERSHED, HAZARIBAGH, INDIA

Ashok Kumar
Earth Resource Division
Remote Sensing Application Centre
IGSC- Planetarium, Patna - 800 001

ABSTRACT

In the India considerably large geographical area comes under crystalline area. Groundwater occurrence and its management are the major task before the scientists and planner. These area experiences acute crisis of groundwater for drinking water and irrigation. In these areas due unconfined nature of aquifer system, the storage and retrieval of groundwater is major task before the scientists. The weathered materials are the principal aquifer system and ground water occurs under water table condition. Several attempts have been made through computer modeling in alluvial plain of India but less stress has been made for the modeling of the aquifer in hard rock area.

In present study, modeling exercise has been attempted in Lapasiya watershed, Hazaribagh, India. It has helped in understanding the behavior of unconfined aquifer system with various varying input parameters. The outcome of the model helped in identifying suitable area for groundwater augmentation on the long term. The present model also helped in optimization of rate of new wells. The model has simulated up to a level to the near real field condition. The present modeling exercise and its results has given enough scope for taking up such types exercise in other parts of hard rock of India. There is still possibility for further refinement of various parameters. The present modeling exercise is a part of UNDP training programme and it may not been treated as final.

Objective of Modeling in present case study

1. The first objective of model was to simulate the condition similar to aquifer behaviors with time. The water table or equi-potential surface remains near to the surface after the monsoon; water table starts falling down from Nov. onwards and reaches maximum depth in the month of May/ June. After onset of monsoon, water table comes up.
2. To budget the groundwater resources
3. Find out the suitable area for bore well development and optimization of pumping rate and duration. In study area, 20 deep bore well have been identified through geo-hydrological and geophysical survey. But it sustainability could not be determined on long term basis.
4. To determine the sensitivity of the model the various input parameters i.e. recharge/ evapo-transpiration, hydraulic conductivity. So more stresses should be given in collection of field data.

STUDY AREA

The Lapasiya watershed is a part of Upper Hazaribagh plateau and forms the 500-600 (above m.s.l.) meters erosion surface. On the whole the plain is undulating with some minor ridges interrupting the level nature topography. The area may be termed as buried pediplain. The cover material is formed by coarse alluvium in the immediate valley of streams while rest of the pediplain has a gravely ferruginous soil. The porosity of soil does not permit wetting of the topsoil and the water rapidly percolates to the lower horizons. The present study area is a part of upper Hazribagh plateau. The watershed has total areal extent of 85 sq. km. Area on average receives 1322.41 mm of rainfall.

SOFTWARE USED - Visual MODFLOW 2.8

Visual MODFLOW is a computer program based on USGS MODLOW code with pre and post processor. It simulates three-dimensional ground-water flow through a porous medium by using a finite-difference method. Groundwater flow within the aquifer is simulated using a block-centered finite-difference approach. Flow associated with external stresses, such as wells, areal recharge, evapo-transpiration, drains, and streams, can also is simulated. The finite-difference equations can be solved using different solvers.

RESULTS

Model output has indicated that a place where basement depth is more, failure well is less. The largest water body in the watershed “charwa dam” effects on the surrounding ground water movement has been noticed. It has been observed that the up stream drainage area of the dam drains the groundwater to the dam. But much lateral control on groundwater movement has been noticed. The flow lines are coming to the dam area and it is moving towards down streamside.

The volumetric calculation of total available utilizable groundwater within aquifer has been made using output generated in the steady state. Total volume is 230.050x106 m3. The model simulation has indicated that this type of aquifer can be pumped with slow rate (most appropriately at the rate of 100 m3/day) due to high draw down. Similarly, well can not be pumped for long duration at one stretch.

In the entire watershed putting huge number of dug wells can augment groundwater and shallow tube wells energized with 2 H.P. pumps. In middle portion and mid-north-east corner of the watershed, we can pump the water even at high rate i.e. up to 200 m3/day. Because simulation results are stable. This area gets ground water recharge from the upper reaches of watershed and recharge guided by the main river channel.

Flow Budget from the model output

Results of flow budget indicate that an amount of 9712.80 m3 per day has been pumped on the 1st Jan. from the 18702-m3 available effective storage of the aquifer. After end of 31st Jan., all the pumping wells are not able to pump more than 4361.5 m3 per day. This indicates that some of wells have gone dry. Total storage available in the system also comes down to 7843.50 m3. The result indicates decrease in pumping volume till the month of June-July. The in out to the system is also decreases till the month of June-July. After start of monsoon i.e. June- July, situation reversed after increase in recharge to the system. Inspection of draw down of the individual pumping wells indicated that radius of influence wells are very limited and rarely interfering the other wells. Further wells are going dry only where depth of basement is shallow and pumping rate is high. It has been found that 50 m3/day upping rate is optimum. Even in some places, groundwater may be pumped with the rate of 100 m3/day - 200 m3/day

CONCLUSIONS

The modeling exercise of unconfined aquifer system of hard rock area in Indian condition is possible and model can be simulated to near real field condition. Based on present modeling exercise following points emerged out

* Model accuracy very much dependent aquifer geometry.

* Modeling is a complex exercise; lot of discussion with experts and consultation is required.

Groundwater modeling of unconfined aquifer system can provide solution for estimating the available groundwater resource, optimizing the pumping rate and identifying suitable locations/ area where there will less adverse effects on the aquifer system in long duration pumping. The pumping rate of pumps can be optimised in the upper reaches to check groundwater seepage in the drainage channel. The modeling exercise has given better understanding of the aquifer behavior with change in different input parameter.

ACKNOWLEDGEMENT

Groundwater modeling of Lapasiya watershed, Siwane sub-basin, Hazaribagh, India was part of UNDP-DST training programme on GIS based Groundwater Modeling at Centre for Groundwater Studies, CSIRO, Wembley, Western Australia. Author is thankful to Dr. Chris Barber, Director, CGS, Western Australia, Dr. Kumar A. Narayan, Principal Research Officer; Dr. Ramsis Salama, Research Group Leader; Mr. Tonny Barr and Dr. Raiyast Ali, Scientists, Land and Water, CSIRO, Wembley, Western Australia, and Dr. Prabhakar Clement, Centre for Water Research, University of Western Australia, Perth, Australia for providing the training in the Visual MODFLOW and GMS package of groundwater modeling.

ROLE OF VILLAGE TANKS IN MEETING THE DOMESTIC AND CROP WATER REQUIREMENTS - A CASE STUDY FOR RAIPUR DISTRICT USING GIS TOOLS

A.S.R.A.S. Sastri*, V.P.Singh**, G.V. Prasad* and Diwakar Naidu*
*Indira Gandhi Agricultural University, Raipur (Chhattisgarh)
** International Rice Research Institute, Los Banos, Philippines

ABSTRACT

In Chhattisgarh state, situated in Eastern India, there are three distinct agroclimatic egions viz., I) Chhattisgarh Plains, II) Bastar Plateau and III) Northern Hills. Rice is the main crop grown in kharif season. Only 20 per cent area is under irrigation and the rest of the 80 per cent area is under rainfed conditions. The irrigation is through canals but tank irrigation as a life-saving irrigation for rice crop is also an age-old practice. These village tanks in Chhattisgarh play a very important role in meeting the domestic as well as irrigation water requirements. Almost every village in the state has at least two tanks to meet the water needs of the villages.

The number of tanks in the 7 undivided districts (at present there are16 districts) of the state is as follows:

S.No. District No. Tanks Irrigated area ('000 Ha)

1. Raipur 12,737 2.3
2. Durg 2,156 8.7
3. Rajnadgaon 187 6.1
4. Bilaspur 15,681 16.3
5. Bastar 138 1.3
6. Surguja 2,368 2.5
7. Raigarh 6,138 2.5

These tanks, which exist since several hundred years play a vital role for meeting the water needs both domestic and irrigation purposes. The tank water is used as life-saving irrigation to rice crop when the monsoon rains withdraw and rice crop attains flower stage in October.

However, since last few decades these tanks are not well maintained and hence, the irrigation efficiency of these tanks decreased. Also, as there are some changes in rainfall pattern with increasing drought conditions, the run-off water into these tanks has also been decreased.

Analysis of the water availability to these tanks was carried out using storage index (SI) at different blocks in Raipur district in different years like excess, normal and deficit years . The SI represents the run-off water into these tanks. The analysis revealed that the SI values ranged between 62.9 to 89.3 per cent of the normal rainfall in excess rainfall years and from 24.2 to 40.2 per cent of the normal rainfall during normal rainfall years. However, during deficit rainfall years, the SI values are usually between zero to 10.5 of the normal rainfall in different blocks. This indicates that during drought period, the tank water is seldom-useful even for life saving irrigation.

Using the GIS tools, the spatial analysis on the number and irrigated area of these tanks has been analyzed. Superimposing these two maps, the efficiency of the tanks in different areas has also been analyzed. Regarding the density it has been observed that in Raipur district eastern most parts, covering the Saraipali and parts of Bilaigarh and Basna blocks, have the highest tank density (greater than 140 per 100 Sq.Km) and Kurud, Dhamtari and parts of Magarlod blocks have least density ( less than 80 per 100 Sq.Km). In Mahasamund, Pithora, Kasdol, Bagbahara, chhura, Deobhog, Simga, Tilda and parts of Bhatapara and Arang blocks the tank density is medium (110 to 140 per 100 Sq.Km).

Regarding irrigated area it is also highest in those parts where the tank density is highest. It ranged between 24 to 36 per cent of the total irrigated area. In Saraipali block, it is the highest with greater than 36 per cent of the total irrigated area.

For assessing the irrigation efficiency of these tanks, these two maps are superimposed on each other. It has been observed that There are some villages in a few blocks where the irrigation efficiency is quite high. But there are also a few villages in the western part of the district viz. Dharsiwa, Simga and Bhatapara blocks, where the efficiency is low (Medium number with low irrigated area).

This implies that priority must be given in these low tank efficiency villages for taking suitable measures for improving the tank water use efficiency. In southern part of the district, the number of tanks is very low and the area is low. Hence, for increasing the rice productivity in these areas water-harvesting practices should be developed either through farm ponds or village ponds or through other methods like stop dams and check dams.

Also, with proper management of these tanks efforts can be made to increasing the cropping intensity in the district. Otherwise, it is a mono-cropped area with rice as predominant crop. For this purpose, GIS tools can be used to work out the possible areas for double cropping considering the soils, water availability periods etc.

THE SENMAP – A G.I.S. BASED MODEL FOR ENERGY BUDGETING AND PLANNING OF CROP PRODUCTION

B.S. Panesar*, R.C. Fluck@, S.S. Mann* and P.K. Gupta*
* School of Energy Studies for Agriculture,
Punjab Agricultural University, Ludhiana – 141 004, INDIA
@ Former Professor, Department of Agricultural and Biological Engineering,
University of Florida, Gainesville, U.S.A.

ABSTRACT

Energy – one of the limiting factors of production of agricultural systems – is required during all stages of crop cultivation, i.e., pre-growth stage, different stages of plant growth, and harvest, handling and processing of the harvest. Assessment and timely supply of correct quantities of energy during different stages of crop cultivation to a spatially variable agricultural system are a challenge. Further, planning of energy demands for increased crop production and productivity needs attention from planners point of view who are to generate viable plans for feeding the ever-increasing population of India.

The Spatial Energy Model for Agricultural Production (SENMAP) was developed to assess and plan spatial energy requirements of crop cultivation. It consists of several component models such as nutrient requirements model, crop water requirements model, and spatial energy requirements model for water application, soil-working tools, harvesting-threshing operations and other operations like nutrient application, plant protection, and bund making to budget/plan energy and resource requirements. The component models are integrated using GIS. A large number of GIS and other databases drive this model. The model has seven different sections on modifying soil, implement, crop and irrigation database; defining plan; determining intensities of energy and resources; evaluating plans; and acquiring model output in the form of tables and maps. If coupled with economics and goal programming models, the model can be used for strategy evaluation also. The model has been validated for Punjab state. Results of model indicate that four highly intensive energy requiring districts are Kapurthala, Ludhiana, Jalandhar and Ferozepore for diesel; Kapurthala, Ludhiana, Jalandhar and Gurdaspore for electricity; Kapurthala, Ludhiana, Bathinda and Amritsar for water; and Ludhiana, Kapurthala, Sangrur and Jallandhar for total energy. Therefore, these districts should be the target of energy and resource conservation efforts.