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分别利用分布式时变增益水文模型(DTVGM)和分布式耗水过程模型(DEPM)对延河流域延安水文站以上区域进行水文过程模拟,并应用拓展卡尔曼滤波(EKF)算法对2个模型的绿水(实际蒸散发)模拟结果进行同化处理,从而优化了研究区的绿水量并得出绿水的空间分布规律。结果表明:在整个模拟期,DTVGM的月尺度效率系数(NSCE)达到了0.83,水量平衡相对误差为-1.97%,模型能够较好地模拟研究区的水文过程;DEPM的水量平衡相对误差为-1.81%,能较好地模拟流域的水量平衡;DTVGM和DEPM模拟的流域2010年平均绿水量分别为378.52 mm和375.55 mm,空间分布格局相似。与站点观测值比较,DTVGM和DEPM模拟绿水的NSCE分别是0.76和0.59,DEPM的结果具有更多的空间变化信息。同化结果表明EKF算法能综合优化2个模型的模拟结果,同化后DTVGM模拟研究区的平均绿水量为376.34 mm,NSCE为0.78;同化后研究区绿水标准差为40.37mm,比同化前增加了7.79 mm,绿水空间分布体现了更多的空间变化信息,同时,空间分布时格局也更加合理。
Hydrological processes were simulated above the Yan’an Hydrographic Station in the Yanhe River Basin using DTVGM and DEPM, respectively. EKF (Extended Kalman Filter) (Actual evapotranspiration) simulated results were assimilated to optimize the study area of green water and draw the spatial distribution of green water law. The results show that the monthly mean efficiency coefficient (NSCE) of DTVGM reaches 0.83 and the relative error of water balance is -1.97%. The model can simulate the hydrological process well in the study area. The relative error of water balance of DEPM is - 1.81%, which can better simulate the water balance in the basin. The average green water volume of DTVGM and DEPM in 2010 is 378.52 mm and 375.55 mm, respectively. The spatial distribution pattern is similar. Compared with the observed values of the stations, the NSCE of DTVGM and DEPM simulated green water are 0.76 and 0.59 respectively, and the results of DEPM have more spatial variation information. The assimilation results show that the EKF algorithm can comprehensively optimize the simulation results of two models. The average green water volume of the assimilated DTVGM simulation study area is 376.34 mm and the NSCE is 0.78. The standard deviation of green water in the assimilated study area is 40.37 mm, 7.79 mm, the spatial distribution of green water reflects more spatial change information, and the spatial distribution is more reasonable.