Identification of Possible Incoming Runoff using Different Combinations of Extreme Rainfall Events in a Semi-arid Context: Banas River, Bisalpur Dam Catchment

Abstract

ABSTRACT Event-based hydrologic models are very useful to predict peak flow and flood volume, particularly in semi-arid regions. In HEC-HMS software methods selected for loss, transformation, routing and base flow were soil conservation service (SCS) curve number (CN), SCS unit hydrograph (UH), Muskingum and recession, respectively. A total of six extreme events from the year 2011 to 2019 were selected, out of which four were used for calibration, one each for validation and application. The developed model can identify the peak discharge and flood volume satisfactorily at 2-hour intervals. During validation performance statistical viz. percent difference in runoff volume (DV%), percent difference in peak flow (DP%), Nash Sutcliffe Efficiency (NSE), percent bias (%BIAS), coefficient of determination (R2) and ratio of the root mean square error to the standard deviation (RSR) were −3.68, −25.93, 0.52, 3.52, 0.53 and 0.69, respectively. The sensitivity analysis revealed that the CN is the highest sensitive parameter followed by the storage time constant (K), which affects the peak discharge. Whereas, for flood volume, CN is the highest sensitive parameter followed by the recession constant (Rc). The relative sensitivity of CN for peak flow and flood volume were 2.11 and 1.73, respectively. Out of center maximum rainfall (CeMR) and cumulative maximum rainfall (CuMR) distribution, CeMR distribution has given higher peak discharge for all rainfall duration. The rainfall characteristics of the 2016 flood event suggest a hypothetical 9-day rainfall duration can be considered. The 9-day event with CeMR gives 70.64% higher discharge as compared to the observed peak discharge during the 2016 flood.