基于状态变量初值修正的洪水预报方法研究

Study on the Flood Forecasting Method Based on the Initial State Variable Correction

针对现有状态变量初值修正方法的不足,提出了一种基于状态变量初值修正的洪水预报方法(ISVC方法)。该方法以洪水起涨阶段平稳期的预报与实测流量过程间的残差为目标函数,采用粒子群优化算法对状态变量初值进行修正,利用修正后的状态变量初值开展洪水预报。将ISVC方法与新安江模型结合,采用赛塘流域进行了检验。结果表明,ISVC方法切实有效,能提高预报精度。ISVC方法具有一定的独立性、较强的适用性、一定的实用性等特点,具有一定的推广应用价值。

Aiming at that the current artifical correction lacking of standard regulation,this paper proposed a flood forecasting method based on an initial state variable correction.It took the residual between the forecasting and measured flow during the stable period in the initial stage of flood as the objective function,and applied the particle swarm optimization algorithm to correct the initial state variables,which was used to forecast flood.The ISVC method was verified with the combination of Xin'anjiang model in the Saitang watershed.The results show that the ISVC method is effective in improving the precision of the flood forecasting.