Srinivas and Naik, J Hydrogeol Hydrol Eng 2017, 6:2 DOI: 10.4172/2325-9647.1000153 Journal of Hydrogeology & Hydrologic Engineering Research Article a SciTechnol journal and drinking. Hence, it is an essential task to simulate and optimize Hydrological Modeling of Musi the utilization of water resources within the technical and economic framework [1]. River Basin, India and Sensitive Soil and Water Assessment Tool (SWAT) is a physically based Parameterization of Stream distributed parameter model which have been developed to predict runoff, erosion, sediment and nutrient transport from agricultural Flow Using SWAT CUP watersheds under different management practices [1]. SWAT is freely available which is linked to a GIS system (Arc-view) through Srinivas G* and Gopal M Naik an interface that makes data processing and visualization easy. SWAT model has been developing for almost 30 years now and that it has Abstract undergone numerous modifications and adaptations [2]. Sub surface flow will be an important parameter for the wet land due to lateral The Hydrological modeling System is designed to simulate the flow can decrease system flashiness in urban areas [3]. The equation rainfall-runoff processes of watershed systems. In this paper, a for lateral flow is derived from a series of input parameters like continuous simulation based hydrological model is developed through a distributed hydrological modeling approach for the hill slope, soil porosity, field capacity, hydraulic conductivity Musi river basin, India using space inputs, soil type and slopes. and volume of soil water [4]. The curve number method with a The basin is geographically located between 17° 58’ N to 16° 38’ physically based water balance yielding the same or more accurate N latitude and 77° 46’E to 79° 48’ E longitude. The hydrologic results [5,6]. The model can simulate long periods, up to several modeling approach includes rainfall-runoff modeling; sensitivity years, operating with a daily time step. SWAT requires soils data, analysis has been carried out using through SWAT CUP Sequential land use/management information and elevation data to drive Uncertainty domain parameter fitting (SUFI-2) algorithm for most flows and direct sub-basin routing. SWAT lumps the parameters sensitive parameterization of stream flow. Digital Elevation Model into Hydrological Response Units (HRU) and storm runoff for (DEM) generated from Indian Remote Sensing Satellite Cartosat-1 each HRU is predicted with the CN equation. SWAT is most of 30m resolution, land use/land cover derived from the Indian versatile model. SWAT has been widely used in various regions Remote Sensing Satellite (IRS-P6) AWiFS data, and soil textural data obtained from National Bureau of Soil Sciences and Land Use and climatic conditions on daily, monthly and annual basis [7] Planning (NBSS&LUP) of the study area are used in the modeling. and for the watershed of various sizes and scales [8]. SWAT has The model is calibrated for the years 2010 and 2011 and validated been successfully used for simulating runoff, sediment yield and for 2013 by observed data. Performance of the calibration and water quality of small watersheds for Indian conditions [9,10]. validation results evaluated using Nash-Sutcliffe Coefficient (NSE), Land use/Land cover is a very important parameter in hydrological Percentage of deviation measures (Pbias) and RMSE-observations modeling. SWAT used to predict the monthly stream flow and Standard deviation Ratio (RSR). The obtained results indicated quantification of uncertainty of Nagwa watershed in Eastern India that the observed and simulated discharge were not significantly [11]. SWAT 2005 applied to test the performance for prediction of different at 95% level of confidence (95PPU). After considering the uncertainties during model inputs and sensitive parameterization stream flow in the lake Tana basin [12]. Evaluated the differences the model gave good correlation during daily simulation results and and similarities between uncertainty techniques and compared very good correlation for monthly time series. five uncertainty analysis as SUFI-2,GLUE, Parasol, a Bayesian framework implemented using Markov chain Monte Carlo and Keywords Importance Sampling technique in SWAT application to Chaohe Hydrological modeling; Runoff; Musi River; Sensitivity analysis; basin in China [13]. SWAT cup The application of SWAT model and its parameterization using SUFI-2 (SWAT CUP) under GIS platform provides advance option Introduction in hydrological modeling and control environment between large Water is one of the most valuable resources. It plays a vital role, amount data sets during parameter sensitivity analysis [14]. The long not only in agriculture but also in industry, navigation and production time- series real data of rainfall, discharge were available on Musi of energy. River basins are a useful for the management of water River basin at Damaracherla gauge station and these were applied to resources are shared by more than one country. During monsoon simulate the model parameters and calibrate stream flow correlation months, large quantities of water flow as runoff. The distribution of between simulated and observed. rainfall over a year is uneven and therefore during non-monsoon Study area months sufficient water is not available especially for agriculture The Musi river basin extends over a geographical area of about 11,270 sq. km. Musi River is a tributary of the Krishna River in Telangana state in India. Musi River is flowing through the Hyderabad *Corresponding author: Srinivas G, Department of Civil Engineering, University College of Engineering (Autonomous), Osmania University, Hyderabad, Telangana city and joins the Krishna River at Vadapally in Nalgonda district State, India, Tel: 9989228382; E-mail: [email protected], [email protected] Telangana State after passing through a distance of about 240 km. The ° ° ° Received: August 28, 2017 Accepted: September 12, 2017 Published: basin is bounded by 170 58’ N to 160 38’ N latitude and 770 46’E to September 19, 2017 790° 48’E longitude. All articles published in Journal of Hydrogeology & Hydrologic Engineering are the property of SciTechnol, and is protected by International Publisher of Science, copyright laws. Copyright © 2017, SciTechnol, All Rights Reserved. Technology and Medicine Citation: Srinivas G, Naik GM (2017) Hydrological Modeling of Musi River Basin, India and Sensitive Parameterization of Stream Flow Using SWAT CUP. J Hydrogeol Hydrol Eng 6:2. doi: 10.4172/2325-9647.1000153 Materials and Methods the rainfall depth for the day (mm), S is retention parameter (mm). Run-off will occur when Rday > 0.2S. Data used The retention parameter varies spatially due to changes in soil, Land use/Land cover map was obtained from Resource sat IRS-P6 land use, management and slope and temporally due to changes in Advanced Wide Field Sensor data of 56 m resolution. The Land use/ soil water content. The retention parameter is defined as Land cover of the basin is shown in Figure 1. The image corresponds 1000 to the 2013 year and consists of major followed by Buildup Plantation S =25.4 − 10 (2) /orchard Evergreen forest, Scrub/Deg forest Other wasteland CN scrubland water bodies and crop areas like Cotton, Wheat, Rice, Where, CN is the curve number for the day Maize, Soybean, Jowar, Coconut and Ragi etc., A soil textural map of the study area at the 1:250,000 scales were SWAT model set up obtained from the National Bureau of Soil Sciences and Land-Use The SWAT model requires input parameters including a digital Planning of India. The soils are classified based on the soil textural elevation model for contour and slope, climate, soil characteristics information. In the Musi river basin most of the soil covered with and land cover [16-18] (Figure 4). Additional information about clayey, clayey skeletal, loamy, loamy skeletal. water infrastructure and land management practices can also be Digital Elevation Model (DEM) of Musi river basin with 30 incorporated. The first step in model construction is the delineation of m resolution. DEM is the main input for topographic parameter the watershed and its associated sub-basins and reaches. As a physically extraction like various slopes of various channels and sub basins. The based model, SWAT derives topography, contour and slope from a CARTO Digital Elevation Model (DEM) as per Figure 2 generated digital elevation model used to divide the basin into sub-watersheds. from Indian Remote Sensing Satellite Cartosat-1 of 30 m resolution. Once the DEM is added, the model then uses the contours and The Figure 3 indicates slope map of Musi river basin with a ground watershed slope, calculated during the delineation, to determine flow profile slope ranges from 0 to 90°. Daily rainfall of entire Musi river direction and accumulation. Once flow direction and accumulation basin was extracted from these grids and fed into model. Discharge have been established, the model generates a stream network in data of Damarcherla station in the Musi river basin was collected which each individual reach drains a sub basin, all of which drain from the Central Water Commission (CWC) and used for model into a major reach. Each reach has a node or outlet. The modeller then calibration and validation. Discharge data of 2010 and 2011 were selects a node that corresponds to the outlet at which the discharge used for model calibration and 2013 data was used for validation of the model. All the spatial datasets are re-sampled to 56 m resolution. Methodology The model is process based, computationally efficient, and capable of continuous simulation over long time periods. Major model components include weather, hydrology, soil temperature and properties, plant growth, nutrients, pesticides, bacteria and pathogens, and land management. 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, topographical, and soil characteristics. The HRUs are represented as a percentage of the sub watershed area and may not be contiguous or spatially identified within a SWAT simulation.