Browsing by Author "Boini Narsimlu"

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Appraisal of surface and groundwater of the subarnarekha river basin, Jharkhand, India: Using remote sensing, irrigation indices and statistical technique
(CRC Press, 2016) Sandeep Kumar Gautam; Abhay K. Singh; Jayant K. Tripathi; Sudhir Kumar Singh; Prashant K. Srivastava; Boini Narsimlu; Prafull Singh
Remote sensing and Geographic Information System (GIS) are very useful tools which could be used for synoptic representation of water quality of any area (Gupta and Srivastava 2010). Land use/land cover (LULC) changes quantification through satellite remote sensing is one of the major applications; it is important for assessing global environmental change processes, supports in making policies and optimizes the use of natural resources (Srivastava et al. 2012a). The LULC types, such as agricultural land and urban area associated with human activities, often affect both the surface andgroundwater quality. Hence monitoring spatial-temporal changes is essential to understand the driving factors that influence the water quality of an area (Merchant 1994; Wu and Segerson 1995; Srivastava et al. 2013). On the other hand, GIS is an important tool for spatial analysis and integration of spatial and non-spatial data to derive useful outputs (Singh et al. 2013a) and helps in decision making. It can be used for formulating a simple and robust water quality pollutionassessment tool for rapid information generation and broadcasting to water resources managers and the public (Vasanthavigar et al. 2010; Singh et al. 2012). © 2017 by Taylor & Francis Group.
SWAT Model calibration and uncertainty analysis for streamflow prediction of the Tons River Basin, India, using Sequential Uncertainty Fitting (SUFI-2) algorithm
(Springer Science and Business Media Deutschland GmbH, 2017) Nirmal Kumar; Sudhir Kumar Singh; Prashant K. Srivastava; Boini Narsimlu
Tons river basin has a great significance to states Madhya Pradesh and Uttar Pradesh in India, concerning water resources aspects and the ecological balances. A hydrological modeling approach was used to identify the sensitive hydrological parameters of the basin through Sequential Uncertainty Fitting (SUFI-2) technique. SUFI-2 was used for the calibration of SOIL WATER ASSESSMENT TOOL (SWAT) model. It was calibrated for period (1979–2000) including 3 years as warm up (1979–1982), subsequently model was validated on 11 years of datasets (2001–2011). The percentage of observation covered by the 95PPU (p-factor) and the average thickness of the 95PPU band divided by the standard deviation of the measured data (r-factor), were taken into an account for performance evaluation of model. In calibration and validation the p-factor and the r-factor was obtained as 0.54, 0.76 and 0.68, 0.56 respectively. The coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS) and RMSE-observations standard deviation ratio (RSR) have been used for goodness of fit between observation and final best simulation. The R2, NSE, PBIAS and RSR are 0.74, 0.73, −3.55 and 0.54 respectively during the calibration whereas in validation period values are 0.75, 0.69, 18.55 and 0.56 respectively. © 2017, Springer International Publishing Switzerland.