Evaluating Multi-objective Optimization Algorithms to Improve Hydrological Models Using Remote-Sensing Data of Actual Evapotranspiration Values in Karun’s Drainage Basin

Abstract

To enhance basin management and make the most of available water resources, it is essential to determine the real evapotranspiration in drainage basins. The SWAT hydrological model and the SEBAL algorithm for remote sensing are two well-known techniques that deal with this. Initially, the evapotranspiration values of the Karun drainage basin were obtained in three different years—2015, 2019 and 2022—during normal, wet, and dry conditions using the calibrated SWAT model and multi-objective optimization algorithms of BOA and HBA based on the SEBAL algorithm and run-off. Six hydrometric stations were used to calibrate and verify the SWAT model, respectively, for the years 2006–2016 and 2017–2020. The goals of this study included the analysis of applying the multi-objective method to calibrate the SWAT model instead of the traditional method and the assessment of identifying model parameters.