Abstract

A comparison of different probability distribution models for describing the flow-duration-frequency behaviour of annual minima flow events in British rivers is reported. Twenty-five catchments were included in the study, each having stable and natural flow records of at least 30 years in length. Time series of annual minima D-day average flows were derived for each record using durations ( D) of 1, 7, 30, 60, 90, and 365 days and used to construct low flow frequency curves. In each case the Gringorten plotting position formula was used to determine probabilities (of non-exceedance). Four distribution types—Generalised Extreme Value (GEV), Generalised Logistic (GL), Pearson Type-3 (PE3) and Generalised Pareto (GP)—were used to model the probability distribution function for each site. L-moments were used to parameterise individual models, whilst goodness-of-fit tests were used to assess their match to the sample data. The study showed that where short durations (i.e. 60 days or less) were considered, high storage catchments tended to be best represented by GL and GEV distribution models whilst low storage catchments were best described by PE3 or GEV models. However, these models produced reasonable results only within a limited range (e.g. models for high storage catchments did not produce sensible estimates of return periods where the prescribed flow was less than 10% of the mean flow). For annual minima series derived using long duration flow averages (e.g. more than 90 days), GP and GEV models were generally more applicable. The study suggests that longer duration minima do not conform to the same distribution types as short durations, and that catchment properties can influence the type of distribution selected.

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