Research on Soil Moisture Assimilation Based on Noah LSM in Hetao Irrigation District
Soil moisture is the key support to water resources management.It's meaningful for water resources management when obtaining available spatio-temporal continuous soil moisture.Hetao irrigation district is one of top three irrigation districts in China,in which there are no data-assimilation experiments to conduct in the aim of obtaining available spatio-temporal continuous soil moisture.This study uses observed point-scale soil moisture data on ground and region-scale soil moisture data by Remote Sensing to achieve modeling spatio-temporal continuous soil moisture in Hetao irrigation district based on Noah LSM and the Ensemble Kalman Filter(EnKF) algorithm.Then we analyzes and compares the results calculated by data-assimilation method and Noah model.Point-scale experiment shows results calculated by data-assimilation method and Noah model can both feedback the dramatic rainfall' influence and the former results are more close to ground observed soil moisture.Region-scale experiment illustrates that results calculated by Noah model represents worse spatial variability of soil moisture,which is obviously better showing by results calculated by data-assimilation method.Results calculated by data-assimilation method are more close to observed soil moisture by Remote Sensing.
soli moisturedata assimilationland surface process modelwater resources management in irrigation districtremote sensing
NETL
NSTL
万方数据
维普
