A model of rainfall based on finite-state cellular automata

The purpose of this paper is to demonstrate that a finite state cellular automata model is suitable for modeling rainfall in the space-time plane. The time-series properties of the simulated series are matched with historical rainfall data gathered from Whenuapai, NZ. The spatial scale of the model cells in related to land-area by optimizing the cross-correlation between sites at lag 0 relative to rainfall data collected from Auckland, NZ. The model is shown to be adequate for simulation in time, but inadequate in spatial dimension for short distances

A stochastic spatial-temporal disaggreation model for rainfall

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 studies

Quantitative assessment of sewer overflow performance with climate change in northwest England

Changes in rainfall patterns associated with climate change can affect the operation of a combined sewer system, with the potential increase in rainfall amount. This could lead to excessive spill frequencies and could also introduce hazardous substances into the receiving waters, which, in turn, would have an impact on the quality of shellfish and bathing waters. This paper quantifies the spilling volume, duration and frequency of 19 combined sewer overflows (CSOs) to receiving waters under two climate change scenarios, the high (A1FI), and the low emissions (B1) scenarios, simulated by three global climate models (GCMs), for a study catchment in northwest England. The future rainfall is downscaled, using climatic variables from HadCM3, CSIRO and CGCM2 GCMs, with the use of a hybrid generalized linear–artificial neural network model. The results from the model simulation for the future in 2080 showed an annual increase of 37% in total spill volume, 32% in total spill duration, and 12% in spill frequency for the shellfish water limiting requirements. These results were obtained, under the high emissions scenario, as projected by the HadCM3 as maximum. Nevertheless, the catchment drainage system is projected to cope with the future conditions in 2080 by all three GCMs. The results also indicate that under scenario B1, a significant drop was projected by CSIRO, which in the worst case could reach up to 50% in spill volume, 39% in spill duration and 25% in spill frequency. The results further show that, during the bathing season, a substantial drop is expected in the CSO spill drivers, as predicted by all GCMs under both scenarios

Intensity-duration-frequency ratios obtained from annual records and partial duration records in the locality of Pelotas - RS, Brazil Relações intensidade-duração-frequência obtidas a partir de séries anual e de duração parcial para a localidade de Pelotas-RS

The intensity-duration-frequency occurrence ratio (IDF) is a tool commonly used for precipitation-runoff data transformation, which is established from observations of intense precipitations over a period sufficiently long as to allow the occurrence of extremes at the observation site. This study focused on verifying the existence or absence of new data, in terms of IDF ratio, by using partial duration records produced from data on maximum daily disaggregated rainfall for pre determined durations. The partial duration records considered a base value of 55 mm, totaling 279 values. After the rainfall series were established, their independence and seasonality were assessed. Using the Student's t-test statistics, it was established that no new data, as IDF ratio, emerged from the analysis of the partial duration series with the recommended base value of precipitation, as compared to the historical records.<br>A relação intensidade-duração-frequência de ocorrência (IDF) é uma ferramenta utilizada nos processos de transformação chuva-vazão, e sua determinação deve ser obtida a partir de observações de chuvas intensas, durante um período de tempo longo e representativo dos eventos extremos do local. O presente trabalho teve como objetivo verificar a existência ou não de ganho de informação, em termos de relação IDF, ao serem utilizadas séries de duração parcial, a partir dos dados de chuva máxima diária desagregada, em durações preestabelecidas. Quanto à série de duração parcial, foi utilizado o valor-base preestabelecido de 55 mm, constituindo então 279 valores. Posteriormente à constituição das séries de chuva, foi avaliada a independência e a estacionaridade dos valores contidos nas mesmas. Pela metodologia do teste "t" de Student, constatou-se que não há ganho de informação em termos de relação IDF quando utilizada a série de duração parcial, com o valor-base preestabelecido de precipitação, comparativamente à série de registros históricos