A probabilistic view of Hershfield's method for estimating probable maximum precipitation

Koutsoyiannis, D., A probabilistic view of Hershfield's method for estimating probable maximum precipitation, Water Resources Research, 35 (4), 1313–1322, 1999.



A simple alternative formulation of Hershfield's statistical method for estimating probable maximum precipitation (PMP) is proposed. Specifically, it is shown that the published Hershfield data do not support the hypothesis that there exists a PMP as a physical upper limit, and therefore a purely probabilistic treatment of the data is more consistent. In addition, using the same data set, it is shown that Hershfield's estimate of PMP may be obtained using the generalized extreme value (GEV) distribution with shape parameter given as a specified linear function of the average value of annual maximum precipitation series and for return period of about 60,000 years. This formulation substitutes completely the standard empirical nomograph that is used for the application of the method. The application of the method can be improved when long series of local rainfall data are available that support an accurate estimation of the shape parameter of the GEV distribution.

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Our works referenced by this work:

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Our works that reference this work:

1. Koutsoyiannis, D., Statistics of extremes and estimation of extreme rainfall, 1, Theoretical investigation, Hydrological Sciences Journal, 49 (4), 575–590, 2004.
2. Koutsoyiannis, D., Statistics of extremes and estimation of extreme rainfall, 2, Empirical investigation of long rainfall records, Hydrological Sciences Journal, 49 (4), 591–610, 2004.
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7. Papalexiou, S.M., D. Koutsoyiannis, and C. Makropoulos, How extreme is extreme? An assessment of daily rainfall distribution tails, Hydrology and Earth System Sciences, 17, 851–862, 2013.

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Tagged under: Course bibliography: Hydrometeorology, Determinism vs. stochasticity, Extremes, Rainfall models