Simulating hydrological response of a monsoon dominated reservoir catchment and command with heterogeneous cropping patt
- PDF / 2,591,796 Bytes
- 16 Pages / 595.276 x 790.866 pts Page_size
- 120 Downloads / 207 Views
Ó Indian Academy of Sciences (0123456789().,-volV)(0123456 789().,-volV)
Simulating hydrological response of a monsoon dominated reservoir catchment and command with heterogeneous cropping pattern using VIC model MINOTSHING MAZA1,2, ANKUR SRIVASTAVA1,3, DEEPAK SINGH BISHT1,4,* , NARENDRA SINGH RAGHUWANSHI1,5, ARNAB BANDYOPADHYAY2, CHANDRANATH CHATTERJEE1 and ADITI BHADRA2 1 Agricultural 2
and Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur, India. Department of Agricultural Engineering, North Eastern Regional Institute of Science and Technology, Itanagar, India. 3 Department of Civil Engineering, University of Newcastle, Callaghan, NSW 2308, Australia. 4 National Institute of Hydrology, Western Himalayan Regional Centre, Jammu 180 003, India. 5 Maulana Azad National Institute of Technology, Bhopal, India. *Corresponding author. e-mail: [email protected] MS received 3 July 2019; revised 22 June 2020; accepted 5 July 2020
Present study assesses the eAect of Bner land-use classiBcation in simulating the rainfall-runoA response of Kangsabati reservoir catchment (3,627 km2) and command (7,112 km2) by considering cropland heterogeneity in variable inBltration capacity (VIC) model. High resolution LISS-IV satellite imageries were used for the land-use classiBcation. Global sensitivity analysis was performed using VIC-ASSIST to identify the most and least inCuential parameters based on the sensitivity index of elementary eAects. 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 classiBcation resulted in the reduction in streamCow 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 simulating the peak Cows; hence, highlighting the importance of detailed land-use classiBcation 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 streamCow with routed reservoir spillage using Hydrologic Engineering Center-River Analysis System (HEC-RAS) model. StreamCow updation employing HEC-RAS at Mohanpur improved the modelling eDciency (Nash–SutcliAe eDciency (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 streamCow in the monsoon dominated Kangsabati reservoir catchment and command. Keywords. VIC; HEC-RAS; VIC-ASSI
Data Loading...
