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A review on evapotranspiration data assimilation based on hydrological models
Dong Q. Q.; Zhan, C. S.; Wang, H. X.; Wang, F. Y.; Zhu, M. C.
Source PublicationJournal of Geographical Sciences
2016
Volume26
Issue2
Pages230-242
Keywordevapotranspiration data assimilation hydrological model non-state variable northwest china heihe river water streamflow catchment parameters filter states
AbstractAccurate estimation of evapotranspiration (ET), especially at the regional scale, is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper, a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET, being a non-state variable, to construct data assimilation relationships are elaborated upon, with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this, a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model (DTVGM), and the ET-soil humidity nonlinear time response relationship of this model. Moreover, the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states, and may be referenced for accurate estimation of regional evapotranspiration.
Indexed BySCI
Language英语
ISSN1009-637X
DOI10.1007/s11442-016-1265-4
Citation statistics
Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/42915
Collection历年回溯文献
Recommended Citation
GB/T 7714
Dong Q. Q.,Zhan, C. S.,Wang, H. X.,et al. A review on evapotranspiration data assimilation based on hydrological models. 2016.
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