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Abstract

Critical-duration hydrologic events are those that determine the design flood storage capacity of a water storage facility or tailings storage facility (TSF). The critical duration is affected by the flood recovery period (the time required to drain down the facility between floods). For TSFs without an emergency spillway—a common operating condition—the critical duration is typically long, often encompassing a wet season, an extended period of wet weather, snowmelt, and/or multiple storms in quick succession. Methods for estimating probable maximum precipitation (PMP), such as the storm-area method, are limited to individual storm events, which typically last several days or less. The Hershfield method, originally developed for durations of 1 day or less, is sometimes applied to longer-duration events due to a lack of alternatives, but it can significantly overestimate PMPs. Therefore, there is a need for a method to estimate long-duration (e.g., ≥10-day) PMP-like events for the design of high-consequence, operating TSFs. The proposed method involves an Extreme Value Analysis (EVA) that utilizes an assumed PMP annual exceedance probability (AEP), estimates of mean and standard deviation derived from statistics at a local station, and skew estimates based on data from a larger regional dataset. This probabilistic method aligns with the vision outlined by the National Academy of Sciences for the future of PMP estimates. In this paper, the method is applied to 1-day and 30-day durations for climate stations in Juneau and Kamloops, utilizing ERA5 climate reanalysis and NASA’s Daymet data to estimate regional skew. The results align well with Hershfield and storm-area PMP estimates for 1-day durations. For 30-day durations, estimates from the proposed method are less than half of those from the Hershfield method because, while the proposed method captures the general trend of decreasing skew in annual maximum series at longer durations, the Hershfield method maintains a relatively constant skew.