Impact of rainfall input on simulation results of HSPF model in Qinglong River Watershed

Abstract:

In order to evaluate the impact of rainfall input on the simulation results of BASINs/HSPF model in Qinglong River Watershed and improve its simulation accuracy, 200 sets of rainfall simulation series were obtained using random modeling procedures such as trend component modeling, periodic component modeling, dependent random component modeling, and independent random modeling (white noise) procedures, as well as the Monte Carlo simulation method. The Nash-Sutcliffe efficiency coefficient (E_NS) was taken as the evaluation criterion of the model simulation, and the following conclusions were drawn: 1) Using trend component, periodic component, ARMA modeling, and normal random simulation to obtain rainfall stochastic simulation series is a suitable method for the quantification of randomness of rainfall input. 2) Under the condition of model parameter optimization, the variation range of E_NS value of HSPF simulation was [71.09%, 74.96%], and the fluctuation range was 3.87%, suggesting that the randomness of rainfall input had a significant impact on the HSPF simulation results. 3) When considering the annual daily rainfall extremes, the variation range of E_NS value was [75.35%, 78.81%], the fluctuation range was 3.46%, and the results were better than those of the stochastic simulation series which ignored the daily rainfall extremes. It revealed that the extremes of rainfall time series had a significant impact on HSPF simulation results. 4) With the increasing number of extremes considered in the simulated rainfall time series, the HSPF simulation results showed a downward trend, indicating that more attention should be paid to the impact of some critical extremes. 5) The uncertainty of rainfall input is a crucial source of the uncertainty of HSPF simulation results, so randomness and extremes of rainfall time series should be taken into consideration to improve the simulation effects of HSPF. This study provides reference for quantifying the impact of rainfall input on HSPF model simulation and optimizing rainfall scenarios for HSPF simulation.