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ISSN 0974-5904, Volume 09, No. 04
August 2016, P.P.1506-1515
Assessment of Hydrological Response under Climate Change scenarios-A Case Study of Sina Catchment, India NAGRAJ S P ATIL1, THAPA A2 AND DHUNGANA S 1 1
Department of Water and Land Management, Visvesvaraya Technological University, Karnataka-590018, India 2 International Centre for Integrated Mountain Development (ICIMOD)-Khumaltar, Lalitpur, Nepal Email:
[email protected],
[email protected]
Abstract: This study presents a comprehensive modeling environment of Soil and Water Assessment Tool (SWAT), hydrological model. Sequential Uncertainty Fitting Program (SUFI-2) in SWAT-Calibration and Uncertainty Programs (SWAT-CUP) was used for automatic calibration. To examine this framework, a study on annual water balance components including precipitation, evapotranspiration and water yield as well as simulating stream flow in the Sina Catchment was conducted. Hydrological Simulations were conducted for Base Line, A2 and B2 scenarios using PRECIS HadRM3 data. Model performance was evaluated using several statistical parameters, such as the Nash–Sutcliffe coefficient and the normalized objective function. For calibration (1981-85), R2 was obtained as 0.92 and for validation (1986-1990) it was 0.76. Similarly, NSE during calibration was 0.88 and during validation was obtained as 0.76. Calibration and validation results showed good agreement between simulated and observed data. The overall investigation carried out during this study indicates that the simulated Sina catchment is very sensitive to climatic variations. Precipitation trend is decreasing in A2 as compared to Base Line with slight overall increase whereas in B2 precipitation is increasing significantly. While only little changes can be observed in the rate of evapotranspiration, water yield is increasing drastically. The study of the discharge for a thirty year period under climate change scenarios showed that there was an increase in river discharge in future scenarios. Compared to the Base Line scenario (19611990), A2 and B2 scenarios (2071-2100) have much higher minimum and maximum annual discharges. Keywords: Climate change, Water Balance Component, SWAT Model, PRECIS, Flow analysis, SWAT-CUP 1. Introduction Environmental modelling is an effective tool for technically visualizing any sustainable developmental projects. Feasibility of any project requires modelling at its initial stage. Prediction of surface runoff is one of the most useful hydrological capabilities of a Hydrological Modelling. The prediction may be used to assess or predict aspects of flooding, aid in reservoir operation, or be used in the prediction of the transport of water born contamination (Jain 1996) [1]. This study will implicate Geographical Information System (GIS) and hydrological modelling tools, namely, Soil and Water Assessment Tool (SWAT) (Arnold et al. 1998) [2], to various scenarios of climate change. The study estimates the potential impacts of climate change on various water balance components and on discharge in a typical catchment in Bhima Basin, namely Sina Catchment in India. Studies on assessing the impacts of climate change on hydrological response have been conducted on regional as well as local scales. Acosta et al. (2014) [3]evaluated vulnerability to climate change in Lerma-Chapla basin, Mexico and stipulated decrease in surface run-off by 29% in the northern part which also is the cause of frequent droughts. Narsimlu et al. (2013) [4]concluded that the average annual
streamflow may increase considerably in future midcentury period and significantly for end-century period along with the increase in both surface runoff and base flow Upper Sind River Basin in the central part of India. The study also indicates that the average annual streamflow in the monsoon season would increase for mid-century and end-century by 16.4 % and 93.5 %, respectively, and lower streamflow conditions would occur during the off-season in future due to climate change. Thus water balance of the Upper Sind River basin would alter substantially due to the projected climate change, which in turn would affect the availability of water resources and streamflow patterns in future. Obuobie et al. (2008) [5]showed that there will be seasonally varying increase in precipitation rates resulting in increase in run-off in White Volta River Basin in West Africa. Both calibration and validation was done on a monthly and daily by comparing the discharge values which gave a satisfactory result. 1.1 Study Area The Sina River originates near the city of Ahemdanagar. It has two chief sources: one near Jamgaon about 20 kms. west of the town of Ahemdanagar and the other near Jeur about 16 kms to its north-east. For about, a distance of 55 kms roughly, the river forms boundary
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Assessment of Hydrological Response under Climate Change scenariosA Case Study of Sina Catchment, India between Ahemdanagar and Beed districts on the two sides. On the right, it receives the water from Mahekri, and ultimately joins the Bhima River on the Karnataka State border. It has earth filled Sina dam near Karjat in Ahemdanagar district.
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temperature. In winter while the maximum temperature in all parts varies between 30oC and 35oC, the minimum shows the significant variations. The elevation of Sina Catchment, as computed in SWAT Model run, lies between 411metres and 964metres. The mean elevation is 570.4 metres. As per the assessment of LULC (2005-06), major part of the basin (75.86%) is covered with agricultural area, 10% by forest, 7% by Wasteland and around 4% by water bodies, also shown in Figure 3(b). Sina Catchment is mostly covered by vertisols, covering almost 80% of the catchment area. Cambisols cover 15.85% of the total area. Phaeozems and luvisols cover a very small portion which accounts to 3.69% and 0.78% respectively. 2. Materials and Method For hydrological modelling, Soil and Water Assessment Tool (SWAT) was adopted after several literature surveys which showed that this is the most practically applicable modelling tool for this particular study. Hydrological Model Run is not complete without proper Sensitivity Analysis, Calibration and Validation. Therefore, SWAT-CUP has been used for the calibration and validation.
Figure 1: Relative Location of Study Area: Sina Catchment in Krishna Basin, South West India that forms a part of Upper Bhima basin in the Krishna river basin (Figure 1). Sina river is one of the seven major tributaries of the Krishna River. It covers an area of 11,858 sq kms. (11.858 lakh ha). It extends from 74°29’0.1” to 76°5’48.8” E Longitude and from 17°21’53.1” to 19° 15’ 18.8” N Latitude. The catchment is situated in the state of Maharashtra covering four districts namely Ahmednagar, Solapur, Bid and Osmanabad. Ahmednagar covers an area of 3843 sq kms contributing to the largest area of the catchment which amounts to 32.4 %. Similarly, Solapur covers an area of 3513 sq kms which is 29.6 % of the catchment. 2714 sq kms of Bid lies in Sina Catchment amounting to 22.9 % of the total catchment area and Osmanabad covers an area of 1788 sq kms contributing to 15 % of the catchment area. The Sina Catchment has a tropical climate. The climate is dominated by the southwest monsoon, which provides almost all the precipitation throughout the basin. Four distinct seasons occur in the basin throughout the year which includes: The cold weather, the hot weather, the south- Rainfall pattern in the Sina Catchment is spatially defined due to favorable geographic location. The highly elevated area near western margin of the basin acts as a natural barrier to the south-west Indian monsoon wind and causes heavy rainfall in surrounding area. The western area of the basin being closer to sea, is less continental and presents a comparatively low annual range of
It is always better to assess the present and predict the future for the feasibility of any project. Hence, to take all the scenarios into consideration, climate change scenario analysis has been done. PRECIS model results have been used for this purpose. It not only takes into account of the present context but also makes projections for futuristic scenarios. Figure 2 shows the work flow diagram for the current assessment.
Figure 2: Work Flow Diagram
International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 04, August, 2016, pp. 1506-1515
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N AGRAJ S P ATIL, T HAPA A AND DHUNGANA S
2.1 PRECIS Regional Climate Model The climate projections adopted for this assessment are based on PRECIS (Providing Regional Climates for Impact Studies) developed by the Hadley Centre of the UK Meteorological Office. The PRECIS RCM is based on the atmospheric components of the HadCM3 climate model (Gordon et al. 2000) [6]. It is extensively described by Jones et al. (2004) [7]. Compared to the GCM which are usually available at a coarser resolution of 250km X 250km, PRECIS RCM is more realistic at a regional level as it has a finer resolution of 50km X 50km. The extracted data for Base Line, A2 and B2 scenarios has been used as an input to SWAT Model and various analyses has been carried out.
90m x 90m gridded data was downloaded from Shuttle Radar Topography Mission (SRTM), USGS to delineate the boundary of the watershed and analyze the drainage patterns of the land surface terrain as shown in Figure 3 (a). The land use map of the study area has been obtained from Land Cover/Land Use of 1km grid cell size from University of Maryland as shown in Figure 3 (b). Soil Map used is the FAO Digital Soil Map of the world having scale of 1:5,000,000.
2.2 SWAT Model Soil and Water Assessment Tool (SWAT) is a continuous, physically based, long-term, semidistributed model developed with the joint efforts of USDA Agricultural Research Service and Texas University. SWAT runs on a daily time step and is suitable for both short and long-term predictions. Spatial detailing is constructively maintained as processing is done based on large number of watersheds and hydrological response units based on various input data. A single watershed is divided into large number of sub-watersheds to account for spatial differences in soils, land use, crops, topography, and channel morphology and weather conditions. The subwatershed is further sub-divided into Hydrologic Response Units (HRUs) based on the basis of homogenous land use, soil types and topography. Hydrological components, sediment yield and nutrient cycles are first simulated for each HRU individually and then aggregated for the sub-basin to give the final output. Also we can incorporate various water and land management practices like the on-stream and offstream effects of tanks, reservoirs and the check dams in SWAT.
Figure 3: (a) Digital Elevation Model and Figure 3 (b) LULC Map Similarly, non-spatial data like temperature, precipitation, relative humidity data, solar radiation data, wind speed of base line (1971-2005), at point location was acquired. Weather data used is high resolution (1° Lat x 1° Long) daily gridded temperature data set for the period 1971-2005 and high resolution (0.5° x 0.5° Lat/Long) gridded daily rainfall data for the period 1971-2005 over Indian region developed by national Climate Centre IMD Pune, India. Non-Spatial Data like requisite weather data were obtained from Indian Meteorological Department, Pune, India for a period of 35 years (1971 to 2005) and then soil and weather data was incorporated in the model.
The major components of SWAT include weather, surface runoff, evapotranspiration, percolation, transmission losses, return flow, irrigation water transfer, pond and reservoir storage, crop growth, erosion, nutrients, pesticides, groundwater flow, land management and channel routing. Model outputs include all water balance components (surface runoff, evaporation, lateral flow, recharge, percolation, discharge etc.), water quality parameters (nitrate, phosphate, sulphate, ammonia etc.) and sediment yield, at the level of each HRU or sub- basin and are available at daily, monthly or annual time steps. 2.3 SWAT Model Inputs SWAT model run requires two types of data sets: Spatial and Non-Spatial Data Sets. The spatial input data layers required to run the model include digital elevation model (DEM), land use data and soil data. A
Figure 4: Location Map of Weather and Gauge Stations
International Journal of Earth Sciences and Engineering ISSN 0974-5904, Vol. 09, No. 04, August, 2016, pp. 1506-1515
Assessment of Hydrological Response under Climate Change scenariosA Case Study of Sina Catchment, India Finally, the observed daily streamflow data at the outlet (Wadakbal gauge station) of the watershed (Figure 4) from 1971 to 2005 was obtained from Water Resources Information System (WRIS) of India.Ver.4.0 (http://www.indiawris.nrsc.gov.in/wris.html) 2.4 Model Set up and Execution SWAT generates the stream network, identifies the outlet points for a given threshold value, delineates the main watershed and sub-watersheds within it by processing the Digital Elevation Model (DEM). In this particular assessment, 29 sub-basins were created, is shown in Figure 5. This process is followed by overlaying of LULC and soil grid maps based on which the study area is further divided into smaller units known as Hydrological Response Units (HRUs). In this study, 270 HRUs have been taken into consideration by taking all land uses and soil occupying 10% or more of the sub-basins into account. Areas of minor land use and soil type (
