太阳成8722(中国)有限公司-GREEN NO.1

标题：Improving the estimation of hydrological states in the SWAT model via the ensemble Kalman smoother: Synthetic experiments for the Heihe River Basin in northwest China作者：Lei, Fangni; Huang, Chunlin; Shen, Huanfeng; Li, Xin

来源出版物：ADVANCES IN WATER RESOURCES 卷：67 页：32-45 DOI：10.1016/j.advwatres.2014.02.008 出版年：MAY 2014

摘要：Data assimilation as a method to predict variables, reduce uncertainties and explicitly handle various sources of uncertainties has recently received widespread attention and has been utilized to combine in situ and remotely sensed measurements with hydrological models. However, factors that significantly influence the capability of data assimilation still need testing and verifying. In this paper, synthetic surface soil moisture data are assimilated into the Soil and Water Assessment Tool (SWAT) model to evaluate their impact on other hydrological variables via the ensemble Kalman smoother (EnKS), using data from the Heihe River Basin, northwest China. The results show that the assimilation of surface soil moisture can moderately improve estimates of deep layer soil moisture, surface runoff and lateral flow, which reduces the negative influences of erroneous forcing and inaccurate parameters. The effects of the spatially heterogeneous input data (land cover and soil type) on the performance of the data assimilation technique are noteworthy. Moreover, the approaches including inflation and localization are specifically diagnosed to further extend the capability of the EnKS.

入藏号：WOS:000333980300003

文献类型：Article

语种：English

作者关键词：Soil moisture, SWAT, Data assimilation, Heterogeneity, EnKS

扩展关键词：LAND DATA ASSIMILATION; SURFACE SOIL-MOISTURE; SEQUENTIAL DATA ASSIMILATION; DATA RESOLUTION; FILTER; UNCERTAINTY; STREAMFLOW; PERFORMANCE; CALIBRATION; SYSTEM

通讯作者地址：Huang, Chunlin; Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Gansu, Peoples R China.

电子邮件地址：huangcl@lzb.ac.cn; shenhf@whu.edu.cn

地址：

[Lei, Fangni; Shen, Huanfeng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China.

[Lei, Fangni; Huang, Chunlin; Li, Xin]Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Lanzhou 730000, Gansu, Peoples R China.

研究方向：Water Resources

ISSN：0309-1708