Comparison of Calibration Strategies for Daily Streamflow Simulations in Semi-Arid Basins

Khaoula Ait Naceur (), El Mahdi El Khalki (), Abdessamad Hadri (), Oumar Jaffar (), Luca Brocca (), Mohamed Elmehdi Saidi (), Yves Tramblay () and Abdelghani Chehbouni ()
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Khaoula Ait Naceur: Mohammed VI Polytechnic University (UM6P)
El Mahdi El Khalki: Mohammed VI Polytechnic University (UM6P)
Abdessamad Hadri: Mohammed VI Polytechnic University (UM6P)
Oumar Jaffar: Mohammed VI Polytechnic University (UM6P)
Luca Brocca: National Research Council
Mohamed Elmehdi Saidi: Cadi Ayyad University
Yves Tramblay: Espace-Dev (Univ. Montpellier, IRD)
Abdelghani Chehbouni: Mohammed VI Polytechnic University (UM6P)

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2025, vol. 39, issue 3, No 7, 1089-1105

Abstract: Abstract Hydrological modeling is a crucial tool for water resources management. It becomes more important in data-scarce regions like Morocco. Therefore, accurate parameter tuning of models used in this region is vital for reliable predictions. Traditionally, the Nelder-Mead Simplex Algorithm has been used to calibrate the GR4J and MISDc models. However, this study aims to enhance the calibration process by employing Particle Swarm Optimization (PSO), Nelder-Mead Simplex Algorithm (FMIN), Simulated Annealing (SA), and Genetic Algorithm (GA) for daily streamflow forecasts across 26 basins. A sensitivity analysis of their parameters was performed, along with the use of various calibration scenarios. In addition, a snow module was used in the mountainous basins. The research reveals significant sensitivity of the GR4J groundwater exchange coefficient and MISDc parameters related to soil, drainage, and snow dynamics. FMIN and PSO proved to be the most efficient, and the MISDc model outperformed GR4J. The choice of splitting scenario proved critical, and the lower model performance was attributed to discrepancies between calibration and validation periods in terms of runoff coefficients, precipitation-runoff correlations, and the distribution of dry and wet years. Integrating a snow module in both models enhanced their performance in larger basins.

Keywords: Hydrological Modeling; Morocco; GR4J; MISDc; Optimization Algorithms; Parameter Sensitivity (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11269-024-04007-3

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