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流域水文模型是研究水文规律和模拟水文过程的主要工具,而流域气候和下垫面条件的变化给径流的准确模拟带来了新的挑战。以渭河华县水文站以上流域为例,采用智能优化算法(SCE-UA)对HyMOD模型首先进行参数优选,并针对传统“捆绑率定”策略模拟效果不佳的实际情况,将集合卡尔曼滤波(EnKF)数据同化方法分别应用于HyMOD模型的状态变量更新、参数更新及状态—参数的同时更新,并在渭河流域近50年的日径流模拟中进行了效果检验。结果表明,状态—参数的双EnKF策略获得了最满意的效果,模拟精度比传统模型率定方法有显著提升。
Watershed hydrological models are the main tools for studying hydrological laws and simulating hydrological processes. Changes in basin climate and underlying surface conditions have brought new challenges to accurate simulation of runoff. Taking the watershed above Huaxian hydrological station in Weihe River as an example, the HyMOD model is first optimized by using intelligent optimization algorithm (SCE-UA). In order to solve the problem that the traditional “bundling rate” strategy is ineffective, The EnKF data assimilation method is applied to update the state variables, update the parameters and update the state-parameters of the HyMOD model respectively. The validation of the results is performed in the daily runoff simulation of the Weihe River basin in the past 50 years. The results show that the state-parameter double EnKF strategy achieves the most satisfactory results, and the simulation accuracy is significantly improved compared with the traditional model.