Rainfall intensity–duration–frequency relationships derived from large partial duration series

SummaryA procedure is proposed for basing intensity–duration–frequency (IDF) curves on partial duration series (PDS) which are substantially larger than those commonly used for this purpose. The PDS are derived from event maxima series (EMS), composed of the maximum average intensities, over a given duration, determined for all rainfall events recorded at a station. The generalized Pareto distribution (GP) is fitted to many PDS nested within the EMS and the goodness-of-fit is determined by the Anderson–Darling test. The best fitted distribution is selected for predicting intensities associated with the given duration and with a number of recurrence intervals. This procedure was repeated for eleven rainfall durations, from 5 to 240 min, at four stations of the Israel Meteorological Service. For comparison, the GP and the generalized extreme value (GEV) distributions were fitted to annual maxima series (AMS) and the Gumbel and lognormal distributions were fitted to the PDS and to the AMS at these stations.In almost all cases, the GP distribution well fits to ranges of PDS within an EMS, while in a few cases the best fit is fair only. Another result is that the GP distribution does not fit to AMS and to EMS. The GEV distribution well fits to most AMS, and fairly fits to the others. The Gumbel and the lognormal distributions well fit to most of the AMS and to a very few PDS. In most cases of good fits of different distributions, the predicted values by the different distributions are not much different from one another. This indicates the importance of good fit of the distribution and of the power of the AD test used for determining it. In most cases the best fit of the GP distribution is to a PDS series substantially larger than its corresponding AMS. In most cases, the standard error of the estimated 100-year intensity, through the best fitted GP to PDS, is smaller than that estimated through the GEV fitted to the corresponding AMS. All these make the proposed procedure superior to the current ones. It also enables interpolated predictions down to recurrence intervals of N/n years (N is number of years of complete records and n is PDS size). The use of large samples would reduce the sensitivity of predicted intensities to sampling variations.