Abstract
AbstractDrought indicators are used as triggers for action and so are the foundation of drought monitoring and early warning. The computation of drought indicators like the standardized precipitation index (SPI) and standardized streamflow index (SSI) require a statistical probability distribution to be fitted to the observed data. Both precipitation and streamflow have a lower bound at zero, and their empirical distributions tend to have positive skewness. For deriving the SPI, the Gamma distribution has therefore often been a natural choice. The concept of the SSI is newer and there is no consensus regarding distribution. In the present study, twelve different probability distributions are fitted to streamflow and catchment average precipitation for four durations (1, 3, 6, and 12 months), for 121 catchments throughout the UK. The more flexible three‐ and four‐parameter distributions generally do not have a lower bound at zero, and hence may attach some probability to values below zero. As a result, there is a censoring of the possible values of the calculated SPIs and SSIs. This can be avoided by using one of the bounded distributions, such as the reasonably flexible three‐parameter Tweedie distribution, which has a lower bound (and potentially mass) at zero. The Tweedie distribution has only recently been applied to precipitation data, and only for a few sites. We find it fits both precipitation and streamflow data nearly as well as the best of the traditionally used three‐parameter distributions, and should improve the accuracy of drought indices used for monitoring and early warning.
Highlights
It is widely written that drought is a complex phenomenon that is notoriously hard to define
The proportion of occurrences for which the normal distribution cannot be rejected at the 5% significance level (p-value 5 0.05) by the Shapiro-Wilk test is shown for all four aggregation durations separately, as well as for all the durations lumped together
Drought indicators can be used as triggers for action and declaration of drought, and form the foundation of drought monitoring and early warning
Summary
It is widely written that drought is a complex phenomenon that is notoriously hard to define. Indicators provide crucial information to support the recognition of drought onset and termination, and duration, as well as the relative severity and rarity of events. They are used as triggers for action and communication (or declaration of drought) and so are the foundation of drought monitoring and early warning. Copes poorly with outliers in the data Thicker tails than the GEV, and less prone to abrupt upper/lower bounds This is advantageous when extrapolating, using distribution parameters fitted for a fixed standard period, such as for a realtime monitoring and early warning system Has fewer occurrences of distributions fitted with mass below zero (F(0)>0) than the Generalized Logistic and the GEV.
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