4.7 Article

An Experimental Study on Evapotranspiration Data Assimilation Based on the Hydrological Model

Journal

WATER RESOURCES MANAGEMENT
Volume 30, Issue 14, Pages 5263-5279

Publisher

SPRINGER
DOI: 10.1007/s11269-016-1485-5

Keywords

Evapotranspiration; Remote sensing; Hydrological model; Ensemble Kalman filter; Data assimilation

Funding

  1. Natural Science Foundation of China [41401042, 41271003, 41371043]
  2. Anhui Provincial Natural Science Foundation [1508085QD69]
  3. China Postdoctoral Science Foundation [2014M550823]
  4. National Key Basic Research Program of China (973 Program) [2015CB452701]

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The accurate estimation of watershed evapotranspiration (ET) has been a research hotspot in the field of hydrology and water resources for a long time. This study aims to develop a new comprehensive method integrating the advantages of the hydrological model and remote sensing data for improving the daily ET processes simulation. For the purpose, a data assimilation (DA) approach was established on the basis of a physical-based hydrological model, Distributed Time Variant Gain Model (DTVGM). Due to the calculation of ET by using soil moisture recurrence relations in distributed hydrology model, ET was expressed by state variables, in combine with the remote sensing data of ET through a two-layer model, by using ensemble Kalman filter (EnKF) for ET assimilation and constructed a ET assimilation system based on DTVGM, obtained more accurate continuous time series values of ET. Applied in Beijing Shahe River Basin, the DA approach made the simulation shift towards the remote sensing results. According to the verification based on the measurement data of the flux station, the mean absolute percentage error of the DA-based ET was reduced from 25.8 to 8.2 % in No. 1 hydrological unit. The DA approach improved the ET simulation accuracy of hydrological model, and provides a new effective method for daily ET estimation.

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