Impacts of Climate Change under the Threat of Global Warming for an Agricultural Watershed of the Kangsabati River

The effects of global warming on India vary from the submergence of low-lying islands and coastal lands to the melting of glaciers in the Indian Himalayas, threatening the volumetric flow rate of many of the most important rivers of India and South Asia. In India, such effects are projected to impact millions of lives. As a result of ongoing climate change, the climate of India has become increasingly volatile over the past several decades; this trend is expected to continue. Climate change is one of the most important global environmental challenges, with implications for food production, water supply, health, energy, etc. Addressing climate change requires a good scientific understanding as well as coordinated action at national and global level. The climate change issue is part of the larger challenge of sustainable development. As a result, climate policies can be more effective when consistently embedded within broader strategies designed to make national and regional development paths more sustainable. The impact of climate variability and change, climate policy responses, and associated socio-economic development will affect the ability of countries to achieve sustainable development goals. A very well calibrated Soil and Water Assessment Tool (R = 0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the Kangsabati River watershed in Bankura district of West Bengal, India, in order to evaluate projected parameters for agricultural activities. Evapotranspiration, Transmission Losses, Potential Evapotranspiration and Lateral Flow to reach are evaluated from the years 2041-2050 in order to generate a picture for sustainable development of the river basin and its inhabitants. India has a significant stake in scientific advancement as well as an international understanding to promote mitigation and adaptation. This requires improved scientific understanding, capacity building, networking and broad consultation processes. This paper is a commitment towards the planning, management and development of the water resources of the Kangsabati River by presenting detailed future scenarios of the Kangsabati river basin, Khatra sub basin, over the mentioned time period. India’s economy and societal infrastructures are finely tuned to the remarkable stability of the Indian monsoon, with the consequence that vulnerability to small changes in monsoon rainfall is very high. In 2002 the monsoon rains failed during July, causing profound loss of agricultural production with a drop of over 3% in India’s GDP. Neither the prolonged break in the monsoon nor the seasonal rainfall deficit was predicted. While the general features of monsoon variability and change are fairly well-documented, the causal mechanisms and the role of regional ecosystems in modulating the changes are still not clear. Current climate models are very poor at modelling the Asian monsoon: this is a challenging and critical region where the ocean, atmosphere, land surface and mountains all Sujana Dhar is DST Fast Track Young Scientist and Asis Mazumdar is Director, School of Water Resources Engineering, Jadavpur University, Kolkata 700032 (Email: [email protected]) interact. The impact of climate change on regional ecosystems is likewise unknown. The potential for the monsoon to become more volatile has major implications for India itself and for economies worldwide. Knowledge of future variability of the monsoon system, particularly in the context of global climate change, is of great concern for regional water and food security. The major findings of this paper were that of all the chosen projected parameters, transmission losses, soil water content, potential evapotranspiration, evapotranspiration and lateral flow to reach, display an increasing trend over the time period of years 20412050. Keywords—Change, future water availability scenario, modeling, SWAT, global warming, sustainability. I. STUDY AREA Fig. 1 Kangsabati River in Bankura, West Bengal, India Bankura the western-most district of West Bengal (Fig. 1) may be described having the most varied physiographic features. The district can be geologically divided in three categories according to the height of a total land area of 384496 hectares. High Hilly Region / Hard rock area region consists of Khatra and Ranibandh covering 176915 hec. Most of these parts don't have the irrigation facility and full of grits. Uneven Lands / Hard rock ring area lands are also gritty but when irrigated covers 150611 hec. The drought prone area shares the area of 118370 hec., the hilly area stretches over a Impacts of Climate Change under the Threat of Global Warming for an Agricultural Watershed of the Kangsabati River Sujana Dhar and Asis Mazumdar World Academy of Science, Engineering and Technology International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering Vol:3, No:3, 2009 136 International Scholarly and Scientific Research & Innovation 3(3) 2009 scholar.waset.org/1999.1/1204 In te rn at io na l S ci en ce I nd ex , A gr ic ul tu ra l a nd B io sy st em s E ng in ee ri ng V ol :3 , N o: 3, 2 00 9 w as et .o rg /P ub lic at io n/ 12 04 part of 21432 hec. and 12676 hec. suffers as flood prone. According to soil texture, 60207 hec. is Clay area, 81944 hec. is loamy-clay area and the rest is described as sandy-clay area. Fig. 2 Land use map of Raipur watershed of Kangsabati River, Bankura in West Bengal, India The drainage of the district is mainly controlled by Damodar, the Dwarakeswar and the Kangsabati river (Fig 1) along with their network of tributaries. They have in general south easterly flow. The Kangsabati or the Kasai is the third largest river in the district, which rises in the hilly terrain of Jhalda block in the adjoining district of Purulia and enters Bankura district in Khatra block. Therefore it flows south easterly for a distance of about 56 Km. Across the southern part of the district and enters Midnapur district at the south east corner. All the rivers are seasonal, hence the district is drought prone. II. RESEARCH METHODOLOGY Several maps like watershed and sub watershed boundaries, drainage networks, land use/cover and soil texture are required besides rainfall and other hydrological data. Various parameters of SWAT model such as stream length, average slope length, drainage density, erosion control practice factor (P), soil erodability factor (K), available water holding capacity, bulk density, and saturated hydraulic conductivity have been computed using cartography generated topographical maps or thematic cartographic maps. The model requires average main channel depth and width for determining the losses from each sub watershed. Table I displays the different sets of data used with their sources. The Raipur sub basin of the Kangsabati River in the Bankura region of West Bengal was chosen for the futuristic study. Fig. 3 Drainage and watershed map A. Model Selection In recent years a number of conceptual watershed models have been developed to assess the impacts of changes in land use, land cover, management practices, or climatic conditions on water resources and water quality at watershed scales. Examples of continuous watershed simulation models reported in the literature include CREAMS (a field scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems, SWBM (the Spatial Water Budget Model, HSPF (Hydrologie Simulation Program), SWAT (Soil and Water Assessment Tool [1], PRMS (Precipitation Runoff Modeling System, and IRMB (the Integrated Runoff ModelTABLE I DETAILS OF VARIOUS DATA SETS USED IN THE PRESENT STUDY Type of Data Source of Data Survey of India Topographical sheet Survey of India Thematic Maps: Soils, Slope National Bureau of Soil Survey and Land Use Planning Agricultural Report All India Soil and Land Use Survey PS Maps Directorate of Land Use and Land Records DPMS Series National Thematic Mapping Organization World Academy of Science, Engineering and Technology International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering Vol:3, No:3, 2009 137 International Scholarly and Scientific Research & Innovation 3(3) 2009 scholar.waset.org/1999.1/1204 In te rn at io na l S ci en ce I nd ex , A gr ic ul tu ra l a nd B io sy st em s E ng in ee ri ng V ol :3 , N o: 3, 2 00 9 w as et .o rg /P ub lic at io n/ 12 04 F.Bultot). These models generally operate on a daily time step, are computationally efficient, and often lump many detailed processes that occur over short time steps into simplifying approximations [2]. The most appropriate model for this scale of watershed and for long-term analysis is the Soil and Water Assessment Tool (SWAT Version 2000). SWAT, a semi-distributed watershed model developed by the United State Department of Agriculture (USDA), has been applied throughout the United States [2], [3]. The equations in SWAT focuses on a soil water balance. SWAT simulates the water balance, along with plant growth, sediment erosion and transport, nutrient dynamics, and pesticides. The model permits the incorporation of management practices on the land surface, including fertilizer application, livestock grazing, and harvesting operations. There are hundreds of parameters in SWAT. Some of these parameters vary by subbasin, land use, or soil type, which increases the number of parameters substantially. B. SWAT Model The hydrologic components of the model have been previously validated for several watersheds [3]-[5]. Brief descriptions of some of the key model components are provided here; more detailed descriptions of the model components can be found in [3]. For modeling purposes in SWAT, a watershed is partitioned into a number of subbasins. Each subbasin delineated within the model is simulated as a homogeneous area in terms of climatic forcing, but with additional subdivisions within each subbasin to represent different soils and land use types. Each of these individual land use areas is referred to as a hydrologic response unit, or HRU [2] and is assumed to be spatially uniform in terms of soil, land use, topographic, and climatic data. A daily water budget is computed for each HRU based on precipitation, runoff, ET, percolation, and return flow from subsurface and ground water flow. Subdivision of a watershed into HRUs allows the model to reflect differences in ET for various crops and soils, using the Priestly-Taylor [6], Penman-Monteith [7], or Hargreaves methods. The SCS runoff curve number is used to estimate surface runoff from daily precipitation, with curve number values based on soil type, land use, and land management conditions [8]. The curve number is also adjusted on a daily basis according to moisture conditions in the watershed [1]. For each subbasin delineated in SWAT, the ground water flow contribution to total streamflow is simulated by creating shallow aquifer storage [1]. Percolation from the bottom of the root zone is recharge to the shallow aquifer. A recession constant is used to lag flow from the aquifer to the stream [1]. Water routing through the channel network delineated by SWAT is performed by using either the variable storage coefficient method or the Muskingum river routing method [9]. SWAT is a river basin or watershed scale model developed by the USDA Agricultural Research Service (ARS). SWAT was developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds with varying soils, land use and management conditions over long periods of time. SWAT is a continuous time model operating on daily time step. The subbasin components of SWAT can be placed into eight major divisions--hydrology, weather, sedimentation, soil temperature, crop growth, nutrients, pesticides, and agricultural management Hydrology Surface runoff, Percolation, Lateral Subsurface Flow, Groundwater Flow, Evapotranspiration, Snow melt and Transmission Losses Weather Precipitation, Air Temperature, Solar Radiation, Wind Speed and Relative humidity. Sedimentation Sediment Yield. Soil temperature Daily average soil temperature is simulated at the center of each soil layer for use in hydrology and residue decay. Crop growth Nutrients Nitrogen and Phosphorus Pesticides Gleams technology for simulating pesticide transport by runoff, percolate, soil evaporation and sediment was added to SWAT. Agricultural Management Tillage and residue management and Irrigation. Routing component Channel flood routing, Channel sediment routing, Channel nutrient and pesticide routing, Reservoir Routing, Reservoir water balance and routing, Reservoir sediment routing, Reservoir nutrient and pesticides. In Fig 4 illustrates the schematic basin of Kangsabati River Catchment of SWAT model which was used for this study. Fig. 4 Schematic representation of Kangsabati River with sub basins by the SWAT model III. RESULTS AND DISCUSSIONS A. Calibration Results for the Khatra Sub Basin of the Kangsabati River Located in Bankura District of West Bengal The calibration has been performed using flow calibration hydrographs for eye inspection and also flow correlation in order to statistically represent the accuracy of the model over the Easter Indian river basin. Fig. 5 and Fig. 6 show the flow calibration and flow correlation results for the HEC HMS model over the Khatra sub basin of the Kangsabati River. The value of the coefficient of determination R obtained was very nearly 1.0. World Academy of Science, Engineering and Technology International Journal of Biological, Biomolecular, Agricultural, Food and Biotechnological Engineering Vol:3, No:3, 2009 138 International Scholarly and Scientific Research & Innovation 3(3) 2009 scholar.waset.org/1999.1/1204 In te rn at io na l S ci en ce I nd ex , A gr ic ul tu ra l a nd B io sy st em s E ng in ee ri ng V ol :3 , N o: 3, 2 00 9 w as et .o rg /P ub lic at io n/ 12 04 Flow Calibration for 2001 over Khatra 0 0.001 0.002 0.003 0.004 0.005 0.006 0.007 0.008 jan ua ry ma rch ma y jul y se pte mb er no ve mb er Month Fl ow in c m s inflow outflow Fig. 5 Flow calibration for the year 2001 over Khatra Sub basin of the Kangsabati River in Bankura district. Flow correlation at Khatra in 2001