Evaluation of Multi- and Many-Objective Optimization Techniques to Improve the Performance of a Hydrologic Model Using Evapotranspiration Remote-Sensing Data
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 4
Abstract
In this study, we explore the use of different multi- and many-objective calibration approaches in hydrological modeling when considering both observed streamflow and remotely sensed actual evapotranspiration (ETa). Eight remotely sensed ETa and an Ensemble products were used in a watershed in Michigan. Regarding the calibration process, the Unified-Non-dominated Sorting Genetic Algorithm III was integrated with the soil and water assessment tool (SWAT). The first nine calibrations used a multi-objective approach with two variables, one being streamflow and the other being a remotely sensed ETa products/Ensemble. The tenth calibration was a many-objective calibration with nine objective functions that represented observed streamflow and all eight of the remotely sensed evapotranspiration datasets. Results showed that the multi-objective calibrations were able to successfully calibrate both streamflow and ETa. However, the highest model performances were achieved using the Ensemble ETa product. Meanwhile, the required computational time for the many-objective calibration is significantly higher than the multi-objective calibration. In addition, the overall performance of many-objective method can be improved by considering weighting factors and constraining the search space.
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Data Availability Statement
All data generated or used during the study are available from the corresponding author by request. This includes the generated data by SWAT models and the ones used to develop the SWAT model.
Acknowledgments
The authors thank Dr. Martha C. Anderson from USDA-ARS Hydrology and Remote Sensing Laboratory in Beltsville, MD, and Dr. Christopher R. Hain from NASA Marshall Space Flight Center at Huntsville, AL, for their help in providing the ALEXI data. This work is supported by the USDA National Institute of Food and Agriculture, Hatch project MICL02359.
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Journal of Hydrologic Engineering
Volume 25 • Issue 4 • April 2020
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©2020 American Society of Civil Engineers.
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Received: Jun 11, 2019
Accepted: Oct 11, 2019
Published online: Feb 13, 2020
Published in print: Apr 1, 2020
Discussion open until: Jul 13, 2020
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