Application of WRF-Hydro modeling system in Chenhe Basin and comparison with Xin'anjiang model

Abstract

本文利用全球陆面数据同化系统与降雨观测数据，以陕西半湿润区陈河流域为研究对象，驱动WRF-Hydro模型，研究该模型的表现和适用性，并在结构、参数、输入输出和模拟结果方面与新安江模型对比.考虑到次表面层与实际包气带的区别，引入土层厚度乘子ZSOILFAC对前者进行等比缩放，发现其与新安江模型反推包气带的厚度有较好的一致性.研究表明：在陈河流域中WRF-Hydro计算步长须在建议值的基础上缩小；WRF-Hydro模型善于模拟洪水细节，新安江模型表现好且稳定；前者的径流深和洪峰合格率平于或略低于后者；在两个指标均合格的洪水中，前者平均均方根误差比后者小21.5%，但对于其他洪水，前者平均均方根误差比后者大56.2%；WRF-Hydro在洪水起涨时刻模拟较好，表现出其在中小流域应用的潜力.;The WRF-Hydro modeling system (WRF-Hydro model) was used for flood forecast in semi-humid small and medium catchment in China, proposed by the National Center for Atmospheric Research Center (NCAR) in 2013. The Global Land Data Assimilated System (GLDAS) and observed rainfall data are adopted to drive WRF-Hydro model in Chenhe Basin located in the south-central Shanxi Province. This study examine the practical features and applicability of the model, and also compare with Xin'anjiang (XAJ) model in structure, parameters, inputs & outputs and simulation results. Given the excessive time consume in model running, the stepwise approach for calibration is used for five main parameters in this study. The multiplier for subsurface layer thickness (ZSOILFAC) is introduced to modify this thickness to establish contact between subsurface layer and aeration zone to meet the actual situation of the basin, and the good agreement between subsurface layer modified by ZSOILFAC and the aeration thickness evaluated by XAJ model is achieved. The results show that the time step is supposed to be reduced from 6 s recommended by User's Guidance to 1 s when spatial resolution of routing grid is 100 m in Chenhe Basin. WRF-Hydro model is good at simulating the details of flood, while XAJ model performs well and stably. The qualified rates of runoff depth and flood peak for the former are equal or slightly inferior to those for the latter. The mean root mean square Error (RMSE) of the former is 21.5% less than that of the latter for the flood events with qualified runoff depth and flood peak; while mean RMSE of the former is 56.2% greater than that of the latter for others. WRF-Hydro model has good skills in simulating the start time of observed hydrograph and has promising potential for hydrological simulation, flood forecasting and water resources evaluation for small- and medium-sized catchments.