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The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction

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Title The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction
 
Creator Kunnath-Poovakka, A.
 
Contributor Ryu, Dongryeol
renzullo, Luigi
George, Biju Alummoottil
 
Subject streamflow calibration remotely sensed (rs) data
 
Description Calibration of spatially distributed hydrologic models is frequently limited by the availability of ground observations. Remotely sensed (RS) hydrologic information provides an alternative source of observations to inform models and extend modelling capability beyond the limits of ground observations. This study examines the capability of RS evapotranspiration (ET) and soil moisture (SM) in calibrating a hydrologic model and its efficacy to improve streamflow predictions. SM retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily ET estimates from the CSIRO MODIS ReScaled potential ET (CMRSET) are used to calibrate a simplified Australian Water Resource Assessment – Landscape model (AWRA-L) for a selection of parameters. The Shuffled Complex Evolution Uncertainty Algorithm (SCE-UA) is employed for parameter estimation at eleven catchments in eastern Australia. A subset of parameters for calibration is selected based on the variance-based Sobol’ sensitivity analysis. The efficacy of 15 objective functions for calibration is assessed based on streamflow predictions relative to control cases, and relative merits of each are discussed. Synthetic experiments were conducted to examine the effect of bias in RS ET observations on calibration. The objective function containing the root mean square deviation (RMSD) of ET result in best streamflow pre- dictions and the efficacy is superior for catchments with medium to high average runoff. Synthetic experiments revealed that accurate ET product can improve the streamflow predictions in catchments with low average runoff.
 
Date 2016-02-18
2017-02-23T13:10:48Z
2017-02-23T13:10:48Z
 
Type Journal Article
 
Identifier https://mel.cgiar.org/reporting/download/hash/m50a6YHT
A. Kunnath-Poovakka, Dongryeol Ryu, Luigi renzullo, Biju Alummoottil George. (18/2/2016). The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction. Journal of Hydrology, 535, pp. 509-524.
https://hdl.handle.net/20.500.11766/5907
Open access
 
Language en
 
Rights CC-BY-NC-4.0
 
Format PDF
 
Publisher Elsevier
 
Source Journal of Hydrology;535,(2016) Pagination 509,524