It is often necessary to estimate extreme events at sites where little or no hydrometric data are available. In such cases, one may use a regional estimation procedure, utilizing data available from other stations in the same hydrologic region. In general, a regional flood frequency procedure consists of two steps, delineation of hydrologically homogeneous regions and regional estimation. This paper focuses on the development of a regional flood frequency procedure based on canonical correlation analysis (CCA) and its application to data from a northern Canadian basin in which floods are dominated by spring snowmelt. This CCA-based procedure allows the joint regional estimation of spring flood peaks and volumes. The CCA method allows the determination of pairs of canonical variables such that the correlation between the canonical variables of one pair is maximized and between the variables of different pairs is equal to zero. Therefore, it is possible to infer hydrological canonical variables, knowing the physiographical-meteorological canonical variables. The methodology developed was applied to the St. Maurice River basin system, which is operated by Hydro-Quebec and characterized by the relatively low precision of flow data available. Results show that the proposed method allows for a significant reduction in the 100-year spring flood and volume quantile estimation bias and mean square error. The study also shows that, in 60% of cases, the method that was previously used overestimates quantile values, which leads to an overdesign of retention structures.
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