www.cafetinnova.org ISSN 0974-5904, Volume 10, No. 01 DOI:10.21276/ijee.2017.10.0120 February 2017, P.P.126-130 Received: July 12, 2016; Accepted: November 27, 2016; Published: February 28, 2017 International Journal of Earth Sciences and Engineering, 10(01), 126-130, 2017, DOI:10.21276/ijee.2017.10.0120 Copyright ©2017 CAFET-INNOVA TECHNICAL SOCIETY. All rights reserved. Estimation of Water Yield under Various Climate Scenarios at a River Basin Scale in the Manimala River, Kerala, India VENKATESH B, CHANDRAMOHAN T, JOSE M K, PURANDARA B K AND VARADARAJU S Regional Centre, National Institute of Hydrology, Hanuman Nagar, Belagavi, Karnataka, INDIA College of Fisheries, Hoize Bazar, Mangalore, Karnataka, INDIA Email: bvenki30@yahoo.com, cmohant@yahoo.com, mathewkjose@gmail.com, purandarabk@yahoo.com, svraju1103@rediffmail.com Abstract: In the present study, a distributed hydrological model namely soil water analysis tool (SWAT) has been employed for Manimala River Basin in Kerala, India. The entire basin has been divided into 7 major sub- basin to predict the water balance components and their variability under changing climatic conditions. The calibration of the model using the observed data indicated the model parameters such as SOL_AWC, ESCO, GW_REVAP and CN are the sensitive parameters. The estimates of water balance component at basin and sub- basin level show that irrespective of land covers, the runoff generation is as high as 47% (runoff coefficient Q/P) and groundwater recharge is 36%. The estimate of ET is comparatively low. Keywords: Water Yield, Climate Change, GCM, SWAT, Manimala 1. Introduction The Intergovernmental Panel on Climate Change (IPCC) states that the availability and distribution of freshwater resources will be greatly affected by climate change and the vulnerability to water scarcity that populations currently experience could increase [8]. Studies relating climate change and hydrology are becoming prevalent [10], but few published studies focus on changes in groundwater and the population dependent upon it. The IPCC calls for expanded research on local impacts of climate change and finer-resolution assessments of changes in surface and groundwater systems. Climate change continues, and with it our ability to predict changes is refined, but there is a need to develop simple tools that empower water resource managers to use the predictions to better understand and manage water sources. Complex models that generate outputs on continental scales are of little use for decision makers who are trying to allocate resources to alleviate local water scarcity. Rather, decision makers require readily applicable tools that can use climate predictions to accurately forecast local hydrologic changes. Water balance models have been used to accurately simulate historical basin discharges [11], forecast changes in discharges based on climate changes [4], [1], [6], and are relatively straightforward to apply. Thus, water balance models could be an empowering tool for water resource managers to prepare for and mitigate the effects of regional climate change on their local hydrologic resources. There are a number of integrated physically based distributed models. Among them, researchers have identified SWAT as the most promising and computationally efficient. Hence, in this study, an attempt has been made to identify the most sensitive parameters, calibrate, validate the SWAT model and to determine the important hydrologic components of a river basin with focus on water conservation and management. 2. SWAT Rainfall-Runoff Model The SWAT model is a long-term, continuous simulation watershed model. It operates on a daily time step and is designed to predict the impact of management on water, sediment, and agricultural chemical yields. The model is physically based, computationally efficient, and capable of simulating a high level of spatial detail by allowing the division of watersheds into smaller sub watersheds. SWAT models water flow, sediment transport, crop/vegetation growth, and nutrient cycling [7]. The model allows users to model watersheds with less monitoring data and to assess predictive scenarios using alternative input data such as climate, land-use practices, and land cover on water movement, nutrient cycling, water quality, and other outputs. Major model components include weather, hydrology, soil temperature, plant growth, nutrients, pesticides, and land management. Several model components have been previously validated for a variety of watersheds. In SWAT, a watershed is divided into multiple sub watersheds, which are then further subdivided into Hydrologic Response Units (HRUs) that consist of homogeneous land use, management, and soil characteristics. The HRUs represent percentages of the sub watershed area and are not identified spatially within a SWAT simulation. The water balance of each HRU in the watershed is represented by four storage volumes: rain, soil profile (0–2 meters), shallow aquifer (typically 2–20 meters), and deep aquifer