Geospatial and hydrological modeling to assess hydropower potential zones and site location over rainfall dependent Inland catchment

The increasing demand for energy, especially from renewable and sustainable resources, encourages the development of small hydropower plants (SHPs). Earlier hydropower studies were time consuming and less effective due to maximum involvement of the ground based and handheld surveys. This study aimed to present a new multi-criteria approach for harnessing hydropower through establishing small hydropower projects (SHPs) (≤25 MW) instead of large hydropower projects. The multi-criteria approach is based on an integration of advance raster/grid based preparation of geospatial data layers, hydrological modeling and weighted sum overlay analysis. The hydrological data simulation and parameterization were done in SWAT (soil and water assessment tool) model by utilizing 17 years long duration real time hydro-meteorological data sets. For this reason, we selected an Inland based Hamp river catchment, which is a part of Mahanadi river basin of India. The outcomes of this study allow spotting identification of four hydropower potential zones and 10 suitable sites location for SHPs along the stream network by characterizing whole catchment into different sub-catchments. Slope, soil, landuse/landcover (LULC), ET (evapotranspiration), water yield, and rainfall were identified as most important variables for hydropower assessment.

[1]  Tv Ramachandra,et al.  Spatial Decision Support System for Assessing Micro, Mini and Small Hydel Potential , 2004 .

[2]  Arun K. Saraf,et al.  Assessment of Snowmelt Runoff Using Remote Sensing and Effect of Climate Change on Runoff , 2010 .

[3]  Jin-Hee Lee,et al.  Site location analysis for small hydropower using geo-spatial information system , 2010 .

[4]  Debendra Chandra Baruah,et al.  Assessment of hydropower potential using GIS and hydrological modeling technique in Kopili River basin in Assam (India) , 2010 .

[5]  J. R. Sharma,et al.  Hydrological stream flow modelling on Tungabhadra catchment : parameterization and uncertainty analysis using SWAT CUP , 2013 .

[6]  Baldassare Bacchi,et al.  Modelling the statistical dependence of rainfall event variables through copula functions , 2011 .

[7]  Stephen J. Carver,et al.  Integrating multi-criteria evaluation with geographical information systems , 1991, Int. J. Geogr. Inf. Sci..

[8]  Xing-guo Yang,et al.  A Mathematical Model for Forecasting the Dam-Break Flood Routing Process of a Landslide Dam , 2012 .

[9]  Mohamed Nour El Din,et al.  APPLICATION OF THE OVERLAY WEIGHTED MODEL AND BOOLEAN LOGIC TO DETERMINE THE BEST LOCATIONS FOR ARTIFICIAL RECHARGE OF GROUNDWATER , 2011 .

[10]  D. Hannah,et al.  Flow regime characteristics of Himalayan river basins in Nepal , 2002 .

[11]  A. Dégre,et al.  Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium , 2011 .

[13]  K. Abbaspour,et al.  Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT , 2007 .

[14]  P. G. Diwakar,et al.  Kedarnath flash floods: a hydrological and hydraulic simulation study , 2014 .

[15]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .

[16]  M. Balistrocchi,et al.  Modelling the statistical dependence of rainfall event variables by a trivariate copula function , 2011 .