A stochastic model for disaggregating spatial-temporal rainfall data is presented.
In the model, the starting times of rain cells occur in a Poisson process,
where each cell has a random duration and a random intensity. In space, rain
cells have centres that are distributed according to a two dimensional Poisson
process and have radii that follow an exponential distribution. The model is
fitted to seven years of five-minute data taken from six sites across Auckland
City. The historical five-minute series are then aggregated to hourly depths
and stochastically disaggregated to five-minute depths using the fitted model.
The disaggregated series and the original five-minute historical series are then
used as input to a network flow simulation model of Auckland City’s combined
and wastewater system. Simulated overflow volumes predicted by the
network model from the historical and disaggregated series are found to have
equivalent statistical distributions, within sampling error. The results thus
support the use of the stochastic disaggregation model in urban catchment
Cowpertwait, P.S.P., Lockie, T. & Davis, M.D. (2004), A stochastic spatial-temporal disaggreation model for rainfall, Research Letters in the Information and Mathematical Sciences, 6, 109-122