Articles | Volume 28, issue 5
https://doi.org/10.5194/hess-28-1127-2024
https://doi.org/10.5194/hess-28-1127-2024
Research article
 | 
06 Mar 2024
Research article |  | 06 Mar 2024

On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow

Dipti Tiwari, Mélanie Trudel, and Robert Leconte

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Cited articles

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Abaza, M., Anctil, F., Fortin, V., and Turcotte, R.: Exploration of sequential streamflow assimilation in snow dominated watersheds, Adv. Water Resour., 86, 414–424, 2015. a
Adeyeri, O., Laux, P., Arnault, J., Lawin, A., and Kunstmann, H.: Conceptual hydrological model calibration using multi-objective optimization techniques over the transboundary Komadugu-Yobe basin, Lake Chad Area, West Africa, Journal of Hydrology: Regional Studies, 27, 100655, https://doi.org/10.1016/j.ejrh.2019.100655, 2020. a
Ala-Aho, P., Autio, A., Bhattacharjee, J., Isokangas, E., Kujala, K., Marttila, H., Menberu, M., Meriö, L. J., Postila, H., Rauhala, A., and Ronkanen, A. K.: What conditions favor the influence of seasonally frozen ground on hydrological partitioning? A systematic review, Environ. Res. Lett., 16, 043008, https://doi.org/10.1088/1748-9326/abe82c, 2021. a
Asadzadeh, M. and Tolson, B.: Pareto archived dynamically dimensioned search with hypervolume-based selection for multi-objective optimization, Eng. Optimiz., 45, 1489–1509, 2013. a, b
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Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
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