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On the Evaluation of Both Spatial and Temporal Performance of Distributed Hydrological Models Using Remote Sensing Products.

Authors :
Nguyen, Tam V.
Uniyal, Bhumika
Tran, Dang An
Pham, Thi Bich Thuc
Source :
Remote Sensing. May2022, Vol. 14 Issue 9, p1959-1959. 13p.
Publication Year :
2022

Abstract

Evaluating the spatial and temporal model performance of distributed hydrological models is necessary to ensure that the simulated spatial and temporal patterns are meaningful. In recent years, spatial and temporal remote sensing data have been increasingly used for model performance evaluation. Previous studies, however, have focused on either the temporal or spatial model performance evaluation. In addition, temporal (or spatial) model performance evaluation is often conducted in a spatially (or temporally) lumped approach. Here, we evaluated (1) the temporal model performance evaluation in a spatially distributed approach (spatiotemporal) and (2) the spatial model performance in a temporally distributed approach (temporospatial). We further demonstrated that both spatiotemporal and temporospatial model performance evaluations are necessary since they provide different aspects of the model performance. For this, a case study was developed using the Soil and Water Assessment Tool (SWAT) for the Upper Baitarani catchment in India, and the spatiotemporal and temporospatial model performance was evaluated against three different remotely based actual evapotranspiration (ETa) products (MOD16 A2, SSEBop, and TerraClimate). The results showed that an increase in the spatiotemporal model performance would not necessarily lead to an increase in the temporospatial model performance and vice versa, depending on the evaluation statistics. Overall, this study has highlighted the necessity of a joint spatiotemporal and temporospatial model performance evaluation to understand/improve spatial and temporal model behavior/performance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20724292
Volume :
14
Issue :
9
Database :
Academic Search Index
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
156874297
Full Text :
https://doi.org/10.3390/rs14091959