dc.description.abstract |
In the subject of water resources management, the accuracy of the flood routing model is critical. The output hydrograph provides vital information for the decision support system at the chosen location as a consequence of hydraulic simulations. The Rainfall-Runoff Inundation Model (RRI) is a two-dimensional model based on Saint-Venant equations that was created under the auspices of UNESCO by The International Centre for Water Hazard and Risk Management (ICHARM) Japan. In this study, the RRI model has been calibrated for the flood routing using different flood scenarios in River Jhelum, one of the largest river in Pakistan. In the case of ungauged or sparsely gauged catchments, the approach used in the study can be a valuable opportunity. To examine the efficiency of model, we used observed precipitation data as well as considered the Zero rainfall data to check the impact of precipitation during hydraulic routing. The model's calibration and validation were performed using observed flood data. With the help of sensitivity analysis, the most influential model parameters were identified, which formed the basis of the accurate calibration. Parameter sensitivity test is mandatory to evaluate simulation uncertainty and model response on different parameter values.
It was concluded that both the Coefficients of River Depth (Cd) and River Width (Cw) are the most influential and interactive parameters during low floods. Output hydrograph was not sensitive to Manning’s roughness coefficient during the low flood scenarios. Other four parameters (River Threshold, Soil porosity, Soil water depth and Wetting front suction) were screened out for the calibration process because they showed neither influence at the output hydrograph nor interaction among other parameters.
The Coefficient of Determination (0.89), Index of Agreement (0.93), Nash-Sutcliff Efficiency (0.78) and Pearson's Correlation Coefficient were used at the Mangla gauging station on the River Jhelum to establish good agreement between simulated and observed stream flood (0.91). |
en_US |