WATER RESOURCES DEVELOPMENT ROLE OF REMOTE SENSING AND GEOGRAPHICAL INFORMATION SYSTEM ABSTRACT INTRODUCTION

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1 WATER RESOURCES DEVELOPMENT ROLE OF REMOTE SENSING AND GEOGRAPHICAL INFORMATION SYSTEM K.H.V. Durga Rao 1, V. Venkateswara Rao 2, and P.S. Roy 3 1 Water Resources Division, National Remote Sensing Agency, Department of Space, Govt. of India, Balanagar, Hyderabad Phone: , E mail: durgarao_khv@nrsa.gov.in 2 Geo-engineering Department, College of Engineering, Andhra University, Visakhapatnam 3 Deputy Director, RS&GIS AA, NRSA, Balanagar, Hyderabad, Ph: psr@nrsa.gov.in ABSTRACT Availability of water varies spatially and temporally. Idea of damming the rivers facing lot of objections from the environmentalists. In this context, developing water resources by constructing small water conservation structures is gaining momentum in recent years. In the present study, a user interactive Spatial Decision Support System (SDSS) has been developed for identifying suitable sites for water resources development. Basic guidelines provided by the Integrated Mission for Sustainable Development (IMSD) and the technical guidelines suggested by the Indian National Committee on Hydrology (INCOH) for identifying suitable sites for water harvesting structures have been used in the knowledgebase of the developed SDSS. Dehradun and its environs have been taken up as a study area to identify suitable sites for water harvesting structures using the developed SDSS. Various resource and thematic maps such as landuse / landcover, soil textural, topographic slopes, etc. have been prepared using remote sensing and GIS techniques. These layers have been fed into the developed SDSS and analysed using the decision rules. Sites for water harvesting structures such as check dams, farm ponds, groundwater recharge, etc. have been identified in the study area. INTRODUCTION In many parts of the world, rapid population growth, urbanisation, and industrialisation have increased the demand for water. Over exploitation of groundwater has resulted in depletion of water table. Water scarcity eventually hinders the agriculture production and productivity. A large part of agriculture is still under rain-fed condition in many countries. Severe drought conditions prevail where the rainfall is scant. Rainwater harvesting is one of the best solutions for water resources development and to augment the ever-growing demands. The remarkable developments in space technology during the last two decades have firmly established their immense potential in various applications of water resources and its development. Integration of remote sensing and GIS techniques provide reliable, accurate and an update database on land and water resources, which is a pre requisite for identifying runoff potential zones and suitable sites for water harvesting. Determination of potential sites for water harvesting requires basic knowledge of the rainfall regime characteristics, a detailed evaluation of surface topography, soil characteristics, geomorphological, and landuse/landcover in space and time too. Analysis of huge database for identifying suitable sites for water harvesting structures using set of criteria by conventional methods is time consuming and cost ineffective (Durga Rao, 2004). Harvested water can be used for variety of purposes when the common sources such as; streams, springs or wells fall. In addition to supplying drinking water for people, live stock and wild life; water-harvesting systems can provide supplemental water for growing food and fibre crops (Verma, et al., 1995). Water harvesting can be done at domestic and society levels. At domestic level it is a common practice to harvest rainwater from house roofs, hill-rock surfaces and store it in tanks or to recharge the groundwater. Durga Rao and Bhaumic (2003) has developed a spatial expert support system for identifying suitable zones for water harvesting structures such as check dams, farm ponds, etc. they have demonstrated the capabilities of remote sensing and GIS tools in water resources development projects. Jeykumar (2001), Hannah (2001), and Adhityan (2001)

2 discussed the methodology of roof water harvesting and its use. At society level, water harvesting can be done in larger level to meet the local irrigation and drinking water demands for some extent by constructing check dams, farm ponds, percolation tanks etc. Durga Rao, et al. (2001) demonstrated the role of remote sensing and geographical information system (GIS) in selecting suitable sites for water harvesting structures. Raju (2001) has proposed an innovative design of some water harvesting structures such as check dams and percolation tanks. Varma, et al. (1995) and IMSD (1995) suggested some guidelines for identifying suitable sites for water harvesting structures. Raman and Mohan (2000) have demonstrated the various applications of non-spatial expert systems in water resources management including drought management, flood management, and urban water supply management. Reitsma (1996), has highlighted the necessity to look beyond the usual role of decision support system as analytical tool for assisting operational management of water resources system. The focus of the research by the aforementioned investigations has mostly been on developing and validating a Spatial Decision Support System (SESS) to identify suitable sites for water harvesting structures. In this kind of system an end user can interact directly, can input data, can analyse, and can query to get the results that suits the user s area and requirements. The proposed SDSS is very flexible and user friendly. In absence of any GIS layer that requires for running the developed SDSS model, user can ignore that particular layer by inactivating the concerned graphical routine program without disturbing the remaining model to run successfully. HYDROLOGICAL DESCRIPTION OF THE STUDY AREA The study area is the Dehradun City and its environs, Uttaranchal State, India. Song River, which is a sub-watershed of the river Ganges, flows in the eastern part of the city. Tones, which is a sub-watershed of River Yamuna flows in the western part of the city. These two are main sources of water supply for irrigation and drinking for the Dehradun city and its environs. Dehradun is the main city in the Doon valley; its population is increasing rapidly due to migration of people from the surrounding areas besides the tourist population. As Dehradun got the state capital status recently, the rate of population growth may be more in near future. Demand for domestic water requirements is increasing with growing population and rising living standards besides the existing irrigation demand. Even though the average annual rainfall is large (2300mm per year), runoff resulting from the rainfall drains out very fast due to steep slopes resulting the water scarcity during the summer season (Durga Rao, 2004). The water levels in tube-wells near the city have declined during the last decade (Shaktawat, 1984), indicating that drafts exceed the recharge. As such there is no surface water reservoir available in the study area, 80% of drinking water requirements are met from the groundwater resources and the remaining is met by taping canal water. The spatial and temporal scarcities of the water resources have raised the serious concern in the water resource planners. Due to water shortages during the dry period, waterharvesting concept is gaining its momentum. DECISION RULES Technical guidelines suggested by IMSD (1995) and, INCOH (1995) for selecting suitable sites for conserving water depends on many variables like slope, landuse, soils, drainage, runoff potential, proximity to utility points, etc. these guidelines are very well tested and implemented in India under IMSD (Integrated Mission for Sustainable Development) project. Hence, these guidelines are used as knowledgebase in the developed SDSS. The decision rules used in the present study for identifying suitable zones for water harvesting structures are discussed below. Check Dams: Check dams are very popular type of water harvesting structures and have greater importance since it has got a complimentary benefit of controlling soil erosion also. In general, they are constructed at lower order streams (up to third order), the slope of the terrain should be flat to gentle so as to retain maximum quantity of water with less height of check dam. They are 2

3 proposed where water table fluctuations are very high and the stream is influent and or internally effluent. To have an economical design, the catchment area should be more than 25ha. The soils should be less to medium permeable to allow some recharge to the downstream side of the dam if necessary. It should be located nearer to agricultural and settlement areas to convey the harvested water. Farm Ponds: Farm ponds are made either by constructing an embankment across a watercourse or by excavating a pit or the combination of both. Normally, such structures are provided within individual farms. Farm ponds are generally created by excavating pits in areas having flat topography, low soil permeability and should be free from any faults. Preferably these ponds should be nearer to agricultural areas. Water Harvesting Bundhis: Bundhis (local name in India) are almost similar to the minor irrigation tanks except that they do not have extensive canal system and their command area is limited to the fields of downstream. They should not be located in very heavy soils or impervious strata, which may hinder groundwater recharge. There should be an adequate good cultivated land in the downstream of bundhi to reap the benefits of the water stored. Slopes of the area should be less to moderate. Nala Bunds and Percolation Tanks: Nala bunds and percolation tanks are structures constructed across or nearer to nalas (streams) for checking velocity of runoff, increasing water percolation, increasing soil moisture regime and to hold the silt flow. The feasibility of site for locating percolation tanks and nala bunds depends upon technical and economic considerations such as, the sites should be selected in a relatively flatter nala reach, the slope of the nala should preferably not be more than 2 percent. As far as possible, the catchment area of the percolation tank should not be less than 40 ha., there should be proper site for construction of emergency spillway by the side of the nala bund. The soils should have adequate permeability and good fracture development to facilitate potential groundwater recharge. Groundwater Recharge Structures: these types of structures are constructed for the purpose of enhancing the groundwater potential of the area under consideration. Groundwater recharge can be done by flooding the suitable areas or by constructing infiltration wells. In case of infiltration wells, water has to be diverted from the streams by unlined canals to felicitate more recharge. These structures are generally constructed on active aquifer and on scrub or barren land. Slope of the area should not be more than 5% and soil should be highly permeable. Sufficient land area should be available for constructing these structures. METHODOLOGY The determination of potential sites for rainwater harvesting structures requires a basic knowledge of the rainfall regime characteristics, a detailed evaluation of surface topography, surface soil properties and land use in space and time too. Once spatial decision is identified, the data can be manipulated and analysed to obtain information about the decision problem in hand. From the earlier studies and the above-cited literature, different possible constraints were identified for selecting suitable sites for water harvesting. With this view in mind various thematic maps have been prepared for their integration in Geographical Information System (GIS) environment as main inputs in the developed spatial decision support system and discussed below. Digital Elevation Model (DEM): Digital Elevation Model is the input for preparing the slopes at each and every pixel. Different slopes are suitable for different type of water harvesting structures, for example, check dams cannot be constructed at steeper slopes as the thrust on check dam will be more and capacity of storage will be less in steeper slopes for a given height of a check dam. DEM has been prepared using the topographic information of the study area. DEM 3

4 has been used as input in the developed spatial decision support system, which internally computes the slope in percent at each pixel for further GIS analysis. Drainage Network: The availability of the total quantity of surface water is proportional to the drainage order and some particular structure are suitable at a particular drainage order only for example, check dams should be constructed at lower order streams (preferably up to third order streams) (IMSD, 1995). The drainages digitised from satellite data and topo-maps have been ranked as per its order, higher the rank indicates more suitable. In identifying sites for check dams and nala bunds streams up to third order have been considered in the analysis. Landuse / Landcover Map: Landuse is one of the main constraints in selecting suitable sites for water harvesting structures, and it is the main representative factor for identifying runoff potential zones as well. Landuse map has been prepared using Landsat 5 TM satellite digital data of September 97 by applying different image processing and supervised classification algorithms coupled with ground truth data. Landuse classes like built-up area, forest are classified as unsuitable for locating water-harvesting structures. All landuse classes are ranked according to its suitability for locating water harvesting structures. Landuse with higher rank is more suitable. Soil Textural / Infiltration: Soils are the another important input parameter in this kind of study, the infiltration rate of the soil decides the type of structure to be located and the surface runoff potential also depends on the soil texture of the area. Soil textural map has been obtained from the Soils Division of Indian Institute of Remote Sensing, Dehradun. As different soils suit different type of water harvesting structures, weights have been given for each soil as per the structure under consideration. Lineament: Lineaments are favourable for some type of structures and unfavourable for others. As the lineaments in the study area are present at deeper depths and will not have any influence on small-scale water harvesting structures, this layer has been ignored in the present analysis. However, provision has been made in the developed SDSS that an end user can input the lineament layer for considering in the analysis in case of other areas. Proximity to Utility Points: It is an important criteria that the proposed water harvesting structures should be nearer to the utility points like irrigation and drinking water supply schemes because, the cost of conveyance of harvested water should be economical. A distance map has been created around the agricultural and settlement areas that are extracted from the main landuse map. Higher the rank indicates nearer to the utility point and more suitable. Runoff Potential: To augment the suggested water harvesting structures, a runoff potential map has been created in the GIS environment using Thronthwaite and Mather model. Runoff map has been further classified into three classes as low, medium and high. Very low runoff areas that fall mainly in forest areas are classified as unsuitable. Runoff potential zones are ranked as per the runoff availability, higher the rank indicates high runoff zone. Based on the expert opinions, and from the previous studies proper weights have been given for each layer. However, provision has been made in the developed SDSS to change the weights by decision makers as per the site conditions and requirements. The SDSS: Identifying suitable sites for different water harvesting structures is a multi-objective and multicriteria problem. Here objectives are identifying sites for check dams, farm ponds etc. Criteria are decision rules and variables are slopes, landuse, drainage, water potential etc. The developed SDSS has three modules. The first module is hypothesis in which user can define the objective function. The second module is rules in which decision rules were fed; choice is given to the user to change decision rules if required. In the third module user can feed the data (variables) required directly. In absence of any variable user can ignore that variable, in the same way user can add any new variable if required in the analysis. Graphical User Interfaces of the SDSS have 4

5 been developed using ERDAS GIS environment as platform. Interface developed for defining decision rules is shown in the figure 1. Fig.1 Graphical User Interface for Decision Rules All the required input layers that have been prepared in GIS environment have been fed into the developed SDSS and suitable zones were identified for locating water-harvesting structures by running the developed SDSS. The earlier mentioned decision rules have been used in the knowledgebase of the developed SDSS. RESULTS AND DISCUSSIONS Landuse map prepared using satellite remote sensing data is shown in the figure 2. From the landuse/landcover map it can be inferred that area occupied by forest is 493 sq.km which is 62.8% of the total study area and not suitable for locating water harvesting structures. Area occupied by agricultural land, settlements, barren, scrubs, riverbed are 74.1, 42.4, 21, 130.8, and 22.5 sq. km. respectively. Slope map prepared from DEM indicates that more than 50% of the area comes under steep to very steep category, which is not suitable for locating any water harvesting structures. Terrain slopes in the study area are shown in the figure 3. From the soil textural map it can be found that, the major soil textural association in the study area are coarse loam, fine loam and loamy skeletal. Loamy skeltel and coarse loam are more suitable for groundwater recharge. The maximum order of the drain in the study area is 6, up to third order drains were considered for locating check dams particularly. From the geomorphology map it can be noticed that one major fault exists along the Song river and other some minor faults exists in other locations. However, these faults were not considered in the analysis as those are located at deeper stratum. From the water balance studies it can be found that annual runoff available in various sub-watersheds of the study area varies from 450 mm to 1000mm and it is sufficient to augment the water harvesting structures. In the proximity analysis up to 500m distance from 5

6 settlements and agricultural areas has been considers as suitable. Initial cost benefit analysis has to be done to know the exact proximity distance. Landuse Fig. 2 Landuse/landcover Map Slope Class 0-1% 1-3% 3-5% 5-10% 10-15% 15-35% >35% Fig. 3 Classified Slope Map The developed SDSS has flexibility that, an end user in this field can input their data, can query, can interact and can analyse to identify suitable sites for water harvesting structures. In absence of any GIS input to the model, the user can inactivate the graphical routine of the model and can run with out any difficulty. Suitable sites for the check dams, farm ponds, percolation 6

7 tanks, water-harvesting bundhis have been identified in the study area using the developed spatial decision support system as shown in figure 4. As there is more potential for groundwater recharge in this area, concerned authorities should focus on constructing groundwater recharge structures. Some farm ponds may be constructed in the western side and upstream eastern side of the study area. With the help of the developed SDSS a user can avoid the laborious work involved in the conventional methods and can generate different scenarios that suits his area. Hopefully, the knowledge base will last indefinitely and can suitably be modified as and when required on the basis of some other expert knowledge if found more judicious in this present context. Water Harvesting Structures Fig. 4 Suitable Zones for Water Harvesting Structures Acknowledgements: The authors express sincere gratitude to the Director, NRSA for the support and cooperation given during the project. The first author acknowledges the cooperation provided by Shri G. Behera, GD, WR & O G, NRSA and Shri. V. Bhanumurthy, HDWRD, NRSA. Meteorological data support provided by CWC, Dehradun; CSWCR&TI, Dehradun is sincerely acknowledged. References Adhityan, A., (2001). The Singapore System: Urban Water Harvesting, Making Water Everybody s Business, edited by Anil Agarval, Sunita Narain and Indira Khurana, Centre for Science and Environment, New Delhi, pp Andriole, S. J., (1989). Handbook of Decision Support Systems, Tab Publishers, Blue Ridge Summit, Penn. 7

8 Carver, S.J., (1991). Integrating Multicriteria evaluation with geographic information systems, International Journal of Geographical Information systems 5(3), pp Durga Rao, K.H.V., M.K.Bhaumik (2003). Spatial Expert Support System in Locating Suitable Sites for Water Harvesting Structures, -A Case Study of Song watershed in Dehradun, International Journal of Geocarto, pp Durga Rao, K.H.V., (2004). Spatial Decision Support System for Water Resources Management, PhD thesis, Andhra University, Visakhapatnam. Durga Rao, K.H.V., Hari Prasad, V., and Roy, P.S. (2001). A Suitable Site: Geographic Information Systems and Remote Sensing Technology, Making Water Everybody s Business, edited by Anil Agarval, Sunita Narain and Indira Khurana, Centre for Science and Environment, New Delhi, pp Hannah Buttner., (2001). Learning the value of the raindrop, Making Water Everybody s Business, edited by Anil Agarval, Sunita Narain and Indira Khurana, Centre for Science and Environment, New Delhi, pp IMSD, (1995). Integrated Mission for Sustainable Development technical guidelines, National Remote Sensing Agency, Department of Space, Govt. of India. Jacek Malczewski, (1999). GIS and Multicriteria Decision analysis, John Wiley & Sons, Inc. Publications, New York. Jeyakumar, R., (2001). Quenching Chennai s Thrist, Making Water Everybody s Business, edited by Anil Agarval, Sunita Narain and Indira Khurana, Centre for Science and Environment, New Delhi, pp Loucks, D. P., and J. R. da Costa, eds. (1991). Decision Support Systems: Water Resources Planning, NATO ASI Series, Springer-Verlag, Berlin, Germany. Raju, K.C.B., (2001). Innovating Recharge Designs: Groundwater Recharge Structures, Making Water Everybody s Business, edited by Anil Agarval, Sunita Narain and Indira Khurana, Centre for Science and Environment, New Delhi, pp Raman, H. and Mohan, S., (2000). Application of Expert Systems in Water Resources Management. State of art report, National Institute of Hydrology, Roorkee, India. Thronthwaite, C.W. and Mather, J.R. (1957). Instructions and tables for computing potential evapotranspiration and water balance, Laboratory of climatology, Publication No. 10,Centerton,NJ. UNESCO, (2000). Water use in the world: present situation / future needs, Verma, H.N. and Tiwari, K.N. (1995). Current status and prospectus of rain water harvesting, Indian National Committee on Hydrology, National Institute of Hydrology, India. 8