Physiographical space-based kriging for regional flood frequency estimation at ungauged sites.

Chokmani, Karem et Ouarda, Taha B. M. J. (2004). Physiographical space-based kriging for regional flood frequency estimation at ungauged sites. Water Resources Research , vol. 40 , nº 12. W12514. DOI: 10.1029/2003WR002983.

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Résumé

A physiographical space‐based kriging method is proposed for regional flood frequency estimation. The methodology relies on the construction of a continuous physiographical space using physiographical and meteorological characteristics of gauging stations and the use of multivariate analysis techniques. Two multivariate analysis methods were tested: canonical correlation analysis (CCA) and principal components analysis. Ordinary kriging, a geostatistical technique, was then used to interpolate flow quantiles through the physiographical space. Data from 151 gauging stations across the southern part of the province of Quebec, Canada, were used to illustrate this approach. In order to evaluate the performance of the proposed method, two validation techniques, cross validation and split‐sample validation, were applied to estimate flood quantiles corresponding to the 10, 50, and 100 year return periods. Results of the proposed method were compared to those produced by a traditional regional estimation method using the canonical correlation analysis. The proposed method yielded satisfactory results. It allowed, for instance, for estimating the 10 year return period specific flow with a coefficient of determination of up to 0.78. However, this performance decreases with the increase in the quantile return period. Results also showed that the proposed method works better when the physiographical space is defined using canonical correlation analysis. It is shown that kriging in the CCA physiographical space yields results as precise as the traditional estimation method, with a fraction of the effort and the computation time.

Type de document:	Article
Mots-clés libres:	regional flood estimation; kriging; canonical correlation analysis; principal components analysis; frequency analysis; streamflow
Centre:	Centre Eau Terre Environnement
Date de dépôt:	28 nov. 2019 19:28
Dernière modification:	28 nov. 2019 19:28
URI:	https://espace.inrs.ca/id/eprint/9477

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