Improving Flood Forecasting in Karnali River Basin of Nepal Using Rainfall-Runoff Model and Complementary Error Model

Abstract

Accuracy of flood forecast is important to take appropriate preparedness measures for saving lives and livelihoods of people residing in the floodplains. Predictions from flood forecasting models are usually uncertain which can be improved by complementing the hydrological model with an error model that can capture the information which the operational hydrological model lacks. This paper presents the application of this approach for improving daily flow forecasts for flood warning in Karnali River Basin of Nepal. A conceptual rainfall-runoff model, TUWmodel has been developed to model the rainfall-runoff processes and to predict the runoff at the outlet of the basin at Chisapani. The model has been calibrated for the period 2008-2011 with Nash-Sutcliffe Efficiency (NSE) 0.91 and percent bias (PBIAS) -0.7% and validated for the period 2012-2014 with NSE 0.88 and PBIAS -9.1% using observed temperature, precipitation and discharge data. A complementary ARIMA error model was developed from the error series for calibration set using automatic procedure and the predicted discharges were corrected using the error predictions from the error model. After error corrections, NSE and PBIAS were 0.95 and 0.1% respectively for calibration and 0.92 and 0.1% respectively for validation indicating significant improvements in the skill of forecasts.