Calibration and Validation of SWAT Model by Using Hydrological Remote Sensing Observables in the Lake Chad Basin

Calibration and Validation of SWAT Model by Using Hydrological Remote Sensing Observables in the Lake Chad Basin

Bennour, Ali (Chinese Academy of Sciences; University of Chinese Academy of Sciences; Commissariat Regional au Development Agricole)
Jia, Li (Chinese Academy of Sciences)
Menenti, M. (TU Delft Optical and Laser Remote Sensing; Chinese Academy of Sciences)
Zheng, Chaolei (Chinese Academy of Sciences)
Zeng, Yelong (Chinese Academy of Sciences; University of Chinese Academy of Sciences)
Barnieh, Beatrice Asenso (Chinese Academy of Sciences; University of Energy and Natural Resources)
Jiang, Min (Chinese Academy of Sciences)

2022

Model calibration and validation are challenging in poorly gauged basins. We developed and applied a new approach to calibrate hydrological models using distributed geospatial remote sensing data. The Soil and Water Assessment Tool (SWAT) model was calibrated using only twelve months of remote sensing data on actual evapotranspiration (ETa) geospatially distributed in the 37 sub-basins of the Lake Chad Basin in Africa. Global sensitivity analysis was conducted to identify influential model parameters by applying the Sequential Uncertainty Fitting Algorithm–version 2 (SUFI-2), included in the SWAT-Calibration and Uncertainty Program (SWAT-CUP). This procedure is designed to deal with spatially variable parameters and estimates either multiplicative or additive corrections applicable to the entire model domain, which limits the number of unknowns while preserving spatial variability. The sensitivity analysis led us to identify fifteen influential parameters, which were selected for calibration. The optimized parameters gave the best model performance on the basis of the high Nash–Sutcliffe Efficiency (NSE), Kling–Gupta Efficiency (KGE), and determination coefficient (R²). Four sets of remote sensing ETa data products were applied in model calibration, i.e., ETMonitor, GLEAM, SSEBop, and WaPOR. Overall, the new approach of using remote sensing ETa for a limited period of time was robust and gave a very good performance, with R² > 0.9, NSE > 0.8, and KGE > 0.75 applying to the SWAT ETa vs. the ETMonitor ETa and GLEAM ETa. The ETMonitor ETa was finally adopted for further model applications. The calibrated SWAT model was then validated during 2010–2015 against remote sensing data on total water storage change (TWSC) with acceptable performance, i.e., R² = 0.57 and NSE = 0.55, and remote sensing soil moisture data with R² and NSE greater than 0.85.

African Sahel
ETMonitor evapotranspiration
hydrological modeling
hydrological remote sensing observables
limited calibration
SWAT model

http://resolver.tudelft.nl/uuid:d37d12bd-ad7c-4567-9c05-649f310a5806

https://doi.org/10.3390/rs14061511

2072-4292

Remote Sensing, 14 (6)

Institutional Repository

journal article

© 2022 Ali Bennour, Li Jia, M. Menenti, Chaolei Zheng, Yelong Zeng, Beatrice Asenso Barnieh, Min Jiang