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Title: | Simulating hydrological response of a monsoon dominated reservoir catchment and command with heterogeneous cropping pattern using VIC model |
Authors: | Maza, Minotshing Srivastava, Ankur Bisht, Deepak Singh Raghuwanshi, N. S. Bandyopadhyay, Arnab Chatterjee, Chandranath |
Keywords: | VIC HEC-RAS VIC-ASSIST Reservoir Routing |
Issue Date: | 2020 |
Publisher: | Springer |
Citation: | Journal of earth System Science (2020)129:200 |
Abstract: | Present study assesses the effect of finer land-use classification in simulating the rainfall-runoff response of Kangsabati reservoir catchment (3,627 km2) and command (7,112 km2) by considering cropland heterogeneity in variable infiltration capacity (VIC) model. High resolution LISS-IV satellite imageries were used for the land-use classification. Global sensitivity analysis was performed using VIC-ASSIST to identify the most and least influential parameters based on the sensitivity index of elementary effects. A fully distributed calibration approach was employed using 16 (detailed) and 8 (lumped) vegetation classes. Low Cows during lean periods were over-estimated and peak Cows were under-estimated by both the model setups at Kangsabati reservoir site. Detailed land-use classification resulted in the reduction in streamflow over-estimation (Percent Bias (PBIAS) from 20.99 to 14.41 during calibration and from –22.83 to –7.17 during validation) at daily time step.It further demonstrates the improvement in sim- ulating the peak Cows; hence, highlighting the importance of detailed land-use classification for vegetation parameterization in VIC model setup. River discharge regulation at Kangsabati reservoir resulted in poor model performance at Mohanpur, downstream site of Kangsabati reservoir. Therefore, calibration for Mohanpur was performed after updating the VIC simulated streamflow with routed reservoir spillage using Hydrologic Engineering Center-River Analysis System (HEC-RAS) model. Streamflow updation employing HEC-RAS at Mohanpur improved the modelling efficiency (Nash–Sutcliffe efficiency (NSE) from 0.50 to 0.65 during calibration and from 0.55 to 0.67 during validation) and reduced bias (PBIAS from 6.25 to –2.23 during calibration and from 15.06 to 7.40 during validation) considerably for daily Cows. Model performance with reasonable accuracy was achieved at both the calibration locations which demonstrates the potential applicability of VIC model to predict stream flow in the monsoon dominated Kangsabati reservoir catchment and command. |
URI: | http://117.252.14.250:8080/jspui/handle/123456789/6522 |
Appears in Collections: | Research papers in International Journals |
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