A New Concept to Calibrate and Evaluate a Hydrological Model Based on Functional Data Analysis.

Larabi, Samah; St-Hilaire, André et Chebana, Fateh ORCID: https://orcid.org/0000-0002-3329-8179 (2018). A New Concept to Calibrate and Evaluate a Hydrological Model Based on Functional Data Analysis. Journal of Water Management Modeling , vol. 26 . C442. DOI: 10.14796/JWMM.C442.

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Résumé

Performance measures are widely used in hydrological modeling to provide objective evaluation of the match between simulated and observed system output (i.e. discharge). Each performance measure emphasises a particular aspect of a hydrograph, and the use of a particular performance measure on a specific metric typically means discounting one aspect at the expense of another (e.g. high flows vs low flows). This is mainly because most performance measures reflect the adequacy of simulations using one calculated value based on residuals between daily or hourly series of simulated and observed streamflows. However, it would be more practical to conserve the temporal flow variability of the entire annual hydrograph than to focus merely on flood peaks, for instance. Functional data analysis is a mathematical tool that allows the comparison of such data. In this paper, a methodology for model calibration and evaluation that considers an annual hydrograph as a single observation instead of 365 daily observations, based on functional data analysis, is proposed. The model is evaluated on its ability to reproduce the same shape and variability as the observed hydrographs. The functional statistics, defined for each time step, are used to construct the objective function for model calibration as well as for further model evaluation. A case study is presented to evaluate the hydrological CEQUEAU model on the Lac St-Jean drainage basin. The concept that we describe is general and can be used with any calibration scheme or model evaluation.

Type de document:	Article
Mots-clés libres:	modélisation; hydrologie;
Centre:	Centre Eau Terre Environnement
Date de dépôt:	11 nov. 2020 14:42
Dernière modification:	15 févr. 2022 14:12
URI:	https://espace.inrs.ca/id/eprint/9553

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