Development of an Evapotranspiration Data Assimilation Technique for Streamflow Estimates: A Case Study in a Semi-Arid Region

Ying Zhang, Ling Zhang, Jinliang Hou, Juan Gu and Chunlin Huang
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Ying Zhang: Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Ling Zhang: Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Jinliang Hou: Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
Juan Gu: College of Earth Environmental Sciences, Lanzhou University, Lanzhou 730000, China
Chunlin Huang: Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China

Sustainability, 2017, vol. 9, issue 10, 1-21

Abstract: Streamflow estimates are substantially important as fresh water shortages increase in arid and semi-arid regions where evapotranspiration (ET) is a significant contribution to the water balance. In this regard, evapotranspiration data can be assimilated into a distributed hydrological model (SWAT, Soil and Water Assessment Tool) for improving streamflow estimates. The SWAT model has been widely used for streamflow estimations, but the applications combining SWAT and ET products were rare. Thus, this study aims to develop a SWAT-based evapotranspiration data assimilation system. In particular, SWAT is gridded at Hydrologic Response Unit (HRU) level to incorporate gridded ET products acquired from the remote sensing-based ETMonitor model. In the modeling case, Gridded SWAT (GSWAT) shows a good agreement of streamflow modeling with the original SWAT. Such a scant margin between them is due to the modeling domain mismatch caused by different HRU delineations. In the ET assimilation case, we carry out a synthetic data experiment to illustrate the state augmentation Direct Insertion (DI) method and a real data experiment for the upper Heihe River Basin. The results demonstrate the benefits of the ET assimilation for improving hydrologic processes representations. In the future, more remotely sensed data can be assimilated into the data assimilation system to provide more reliable hydrological predictions.

Keywords: evapotranspiration; streamflow; data assimilation; SWAT; semi-arid (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
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