Continuous rainfall simulation: estimation at ungauged locations

Abstract

Continuous simulation of extended rainfall sequences is becoming an increasingly important tool in rainfall-runoff modelling and design flood estimation. Recently, a nonparametric approach has been developed in which continuous (sub-daily) rainfall fragments are conditioned to daily rainfall on the current day and the rainfall state (wet or dry) on adjacent days using a k-nearest neighbour conditional resampling algorithm, with this method performing well in simulating both Intensity-Frequency-Duration characteristics and antecedent moisture when tested in Sydney, Australia. A limitation of this approach, however, is that extended pluviograph records at the location of interest are required, limiting applicability to only a small number of locations across Australia where such records are available. In this paper we propose an extension in which sub-daily fragments from nearby pluviograph records can be substituted for at-site data, potentially widening the applicability of the method to all locations for which extended daily data is available or for which such data can be stochastically generated. A preliminary analysis involving the substitution of nearby stations for the Sydney Observatory Hill record suggests that the method performs well in preserving sub-daily rainfall characteristics across the full range of historical exceedance probabilities. Furthermore, an analysis of the factors which determine whether a daily/sub-daily record at one location is substitutable for that at another location suggests that the two stations must be at similar latitudes, with differences in longitude, elevation and distance to coast found to be less important. The analysis therefore suggests that the non-parametric continuous simulation approach is likely to perform well in representing the historical rainfall pattern at ungauged locations, and as such comprises a potentially viable approach in the generation of extended synthetic sequences for use in rainfall-runoff modelling and design flood estimation.