摘要
基于可变下渗能力水文模型(Variable Infiltration Capacity,VIC)和集合卡尔曼滤波(Ensemble Kalman Filter,EnKF)算法发展了一种土壤表层水分的数据同化方案,并在新疆维吾尔自治区的森林、高盖草和低盖草3种植被覆盖类型地区进行试验。在同化过程中,有强降水存在时,3种植被覆盖类型的同化值均比实际测量值高;降水较少时,高盖草和低盖草两种类型的同化值比实际测量值略低,而在森林地区,同化值比实际测量值略高。总体上,该同化方案得到的结果比VIC模拟得到的结果更接近于实际测量值,取得较好同化效果。
Soil moisture is not only an important part of water resource, but also one of the most important factors of the land e- cosystem. Accurate soil moisture is significant in environmental science field. This paper presents a soil water data assimilation scheme which based on Variable Infiltration Capacity （VIC） and the Ensemble Kalman Filter （EnKF）. The scheme was experi- mented on three land cover types, which are forestry, high cover grass land and low cover grass land, in the Xinjiang Uygur Au- tonomous Region. During the assimilation process, when heavy rain, the estimated value of new scheme was larger than field sur- veys. However, when little rain, the estimated value was less than the field survey in high cover grass land and low cover grass land, but larger than field survey in forestry. In general, the experiment results showed that the estimated values of soil moisture by this new scheme were more close to field surveys than the simulated values of VIC, which showed that the proposed soil moisture assimilation scheme based on VIC and EnKF has a preferable result.
出处
《地理与地理信息科学》
CSCD
北大核心
2013年第1期91-95,共5页
Geography and Geo-Information Science
