Hydrology, Hydraulics and Water Resources Engineering
4
Scopus Publications
Scopus Publications
Multi-spatial resolution rainfall-runoff modelling—a case study of sabari river basin, india Vimal Chandra Sharma, Satish Kumar Regonda Water Switzerland, 2021 One of the challenges in rainfall-runoff modeling is the identification of an appropriate model spatial resolution that allows streamflow estimation at customized locations of the river basin. In lumped modeling, spatial resolution is not an issue as spatial variability is not accounted for, whereas in distributed modeling grid or cell resolution can be related to spatial resolution but its application is limited because of its large data requirements. Streamflow estimation at the data-poor customized locations is not possible in lumped modeling, whereas it is challenging in distributed modeling. In this context, semi-distributed modeling offers a solution including model resolution and estimation of streamflow at customized locations of a river basins with less data requirements. In this study, the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model is employed in semi-distribution mode on river basins of six different spatial resolutions. The model was calibrated and validated for fifteen and three selected flood events, respectively, of three types, i.e., single peak (SP), double peak (DP)- and multiple peaks (MP) at six different spatial resolution of the Sabari River Basin (SRB), a sub-basin of the Godavari basin, India. Calibrated parameters were analyzed to understand hydrologic parameter variability in the context of spatial resolution and flood event aspects. Streamflow hydrographs were developed, and various verification metrics and model scores were calculated for reference- and calibration- scenarios. During the calibration phase, the median of correlation coefficient and NSE for all 15 events of all six configurations was 0.90 and 0.69, respectively. The estimated streamflow hydrographs from six configurations suggest the model’s ability to simulate the processes efficiently. Parameters obtained from the calibration phase were used to generate an ensemble of streamflow at multiple locations including basin outlet as part of the validation. The estimated ensemble of streamflows appeared to be realistic, and both single-valued and ensemble verification metrics indicated the model’s good performance. The results suggested better performance of lumped modeling followed by the semi-distributed modeling with a finer spatial resolution. Thus, the study demonstrates a method that can be applied for real-time streamflow forecast at interior locations of a basin, which are not necessarily data rich.
Two-dimensional flood inundation modeling in the godavari river basin, India—insights on model output uncertainty Vimal Chandra Sharma, Satish Kumar Regonda Water Switzerland, 2021 Most flood inundation models do not come with an uncertainty analysis component chiefly because of the complexity associated with model calibration. Additionally, the fact that the models are both data- and compute-intensive, and since uncertainty results from multiple sources, adds another layer of complexity for model use. In the present study, flood inundation modeling was performed in the Godavari River Basin using the Hydrologic Engineering Center—River Analysis System 2D (HEC-RAS 2D) model. The model simulations were generated for six different scenarios that resulted from combinations of different geometric, hydraulic and hydrologic conditions. Thus, the resulted simulations account for multiple sources of uncertainty. The SRTM-30 m and MERIT-90 m Digital elevation Model (DEM), two sets of Manning’s roughness coefficient (Manning’s n) and observed and estimated boundary conditions, were used to reflect geometric, hydraulic and hydrologic uncertainties, respectively. The HEC-RAS 2D model ran in an unsteady state mode for the abovementioned six scenarios for the selected three flood events that were observed in three different years, i.e., 1986, 2005 and 2015. The water surface elevation (H) was compared in all scenarios as well as with the observed values at selected locations. In addition, ‘H’ values were analyzed for two different structures of the computational model. The average correlation coefficient (r) between the observed and simulated H values is greater than 0.85, and the highest r, i.e., 0.95, was observed for the combination of MERIT-90 m DEM and optimized (obtained via trial and error) Manning’s n. The analysis shows uncertainty in the river geometry information, and the results highlight the varying role of geometric, hydraulic and hydrologic conditions in the water surface elevation estimates. In addition to the role of the abovementioned, the study recommends a systematic model calibration and river junction modeling to understand the hydrodynamics upstream and downstream of the junction.
Evaluation of an instantaneous dryness index-based calibration-free continuous hydrological model in India Swagat Patnaik, Vimal Chandra Sharma, Basudev Biswal Hydrology Research, 2019 Traditional continuous hydrological models have a large number of free parameters whose values need to be determined through calibration, and thus their applicability is limited to gauged basins. For prediction in ungauged catchments, hydrologists generally follow regionalization methods to develop region-specific calibration-free continuous models. An alternative attempt was made recently to develop a calibration-free model by proposing an empirically derived universal ‘decay function’ that enables definition of instantaneous dryness index as a function of antecedent rainfall and solar energy. The model was earlier tested in the USA, and its performance was found to be comparable to that shown by regionalization-based models. Here, we test the instantaneous dryness index-based calibration-free model considering data from 108 Indian catchments. The medians of coefficient of determination (R2), Nash–Sutcliffe efficiency (NSE) and Kling–Gupta efficiency (KGE) values for the study catchments, respectively, are 0.50, 0.38 and 0.40. Furthermore, the model's performance significantly improved upon Box–Cox transformation (RBC2, NSEBC and KGEBC, respectively, are 0.70, 0.52 and 0.57), suggesting that the model predicts discharge quite well except during flood periods. Overall, our results suggest the model can be used as an alternative platform for predicting discharge in ungauged catchments in the USA and peninsular India, if not in every part of the world.
Experimental flood early warning system in parts of Beas Basin using integration of weather forecasting, hydrological and hydrodynamic models P. R. Dhote, P. K. Thakur, S. P. Aggarwal, V. C. Sharma, V. Garg, B. R. Nikam, A. Chouksey International Archives of the Photogrammetry Remote Sensing and Spatial Information Sciences ISPRS Archives, 2018 The flood early warning for any country is very important due to possible saving of human life, minimizing economic losses and devising mitigation strategies. The present work highlights the experimental flood early warning study in parts of Beas Basin, India for the monsoon season of 2015. The entire flood early warning was done in three parts. In first part, rainfall forecast for every three days in double nested Weather Research and Forecasting (WRF) domain (9 km for outer domain and 3 km for inner domain) was done for North Western Himalaya NWH using National Centres for Environmental Prediction (NCEP) Global Forecasting System (GFS) 0.25 degree data as initialization state. Rainfall forecast was validated using Indian Meteorological Department (IMD) data, the simulation accuracy of WRF in rainfall prediction above 100 mm is about 60%. Rainfall induced flood event of August 05–08, 2015 in Sone River (tributary of Beas River) Basin, near Dharampur, Mandi district of Himachal Pradesh caused very high damages. This event was picked three days in advance by WRF model based rainfall forecast. In second part, mean rainfall at sub-basin scale for hydrological model (HEC-HMS) was estimated from forecasted rainfall at every three hours in netcdf format using python script and flood hydrographs were generated. In third part, flood inundation map was generated using Hydrodynamic (HD) model (MIKE 11) with flood hydrographs as boundary condition to see the probable areas of inundation.
