Rainfall data are usually gathered at daily timescales due to the availability of daily rain-gauges throughout the world. However, rainfall data at fine timescale are required for certain hydrologic modellings such as crop simulation modelling, erosion modelling etc. Limited availability of such data leads to the option of daily rainfall disaggregation. This research investigates the use of a stochastic rainfall disaggregation model on a regional basis to disaggregate daily rainfall into any desired fine timescale in the State of Queensland, Australia. With the incorporation of seasonality into the variance relationship and capping of the fine timescale maximum intensities, the model was found to be a useful tool for disaggregating daily rainfall in the regions of Queensland. The degree of model complexity in terms of binary chain parameter calibration was also reduced by using only three parameters for Queensland. The resulting rainfall Intensity-Frequency-Duration (IFD) curves better predicted the intensities at fine timescale durations compared with the existing Australian Rainfall and Runoff (ARR) approach. The model has also been linked to the SILO Data Drill synthetic data to disaggregate daily rainfall at sites where limited or no fine timescale observed data are available. This research has analysed the fine timescale rainfall properties at various sites in Queensland and established sufficient confidence in using the model for Queensland.

Global Circulation Models of climate predict not only a change of annual precipitation amounts but also a shift in the daily distribution. To improve the understanding of the importance of daily rain pattern for annual plant communities, which represent a large portion of semi-natural vegetation in the Middle East, I used a detailed, spatially explicit model. The model explicitly considers water storage in the soil and has been parameterized and validated with data collected in field experiments in Israel and data from the literature. I manipulated daily rainfall variability by increasing the mean daily rain intensity on rainy days (MDI, rain volume/day) and decreasing intervals between rainy days while keeping the mean annual amount constant. In factorial combination, I also increased mean annual precipitation (MAP). I considered five climatic regions characterized by 100, 300, 450, 600, and 800 mm MAP. Increasing MDI decreased establishment when MAP was >250 mm but increased establishment at more arid sites. The negative effect of increasing MDI was compensated by increasing mortality with increasing MDI in dry and typical Mediterranean regions (c. 360–720 mm MAP). These effects were strongly tied to water availability in upper and lower soil layers and modified by competition among seedlings and adults. Increasing MAP generally increased water availability, establishment, and density. The order of magnitudes of MDI and MAP effects overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation. The effect size of MAP and MDI followed a sigmoid curve along the MAP gradient indicating that the semi-arid region (≈300 mm MAP) is the most sensitive to precipitation change with regard to annual communitie

Extreme rainfall events are responsible for social disorder and economic problems, especially in large urban centers. Densely populated areas suffer from flooding , landslide and building destruction that cause deaths and wide-spread diseases, such as malaria, dengue and leptospirosis. They are recurrent phenomena that wear down the life of the urban population, particularly the least privileged ones. The focal area of this work was the Metropolitan Region of São Paulo (MRSP), Brazil, one of the largest cities in the world. Rainfall daily totals of 21 rain gage network in the MRSP were analyzed to i) estimate the annual maximum daily rainfall (PMDA), by means of the Gumbel distribution; II) group different rainfall rates into classes (from drizzle to extreme rates) and verify the similarity between seasons (clustering), that is annual and seasonal rain rates, for the period 1947 to 1998, making use of the technique known as Cluster Analysis, and III) identify possible trends of three rain rate classes (drizzle, moderate and above 30.0 mm / day) for the annual and seasonal periods, for the whole dataset length of each gage, using the Mann-Kendall trend test. The results showed that the maximum daily rainfall observed data fit the Gumbel distribution in the annual period, with the estimated annual daily maximum rain rate equal to 239.3 mm / day with a return period of 500 years in Barrocada gage, located in MRSP north-central region. Cluster analysis showed little similarity amongst gages, with respect to some rain rate classes, both in the number of events and the classes rain totals, in the annual and seasonal periods. The Mann-Kendall test showed significant increasing trend of the cumulative totals for a larger number of gages for both annual and seasonal periods. The trend of the number of drizzle events class was significantly upward for most gages, again both in the annual and seasonal periods, but not all gages presented increasing trend for the moderate events class. Also, significant increasing trend of the rain rate classes above 30.0 mm / day was found at some gages in the year period. In general, there was significant upward trend of rain rate classes in the MRSP. / Fundação de Amparo a Pesquisa do Estado de Alagoas / Eventos extremos de chuva são responsáveis por distúrbios sociais e problemas econômicos, principalmente nos grandes centros urbanos. Áreas densamente povoadas sofrem deslizamentos, inundações e destruição de construções, que causam mortes e doenças em larga escala, tais como malária, dengue e leptospirose. Eles são fenômenos recorrentes que desgastam a vida da população urbana, principalmente aos menos privilegiados. A área de foco deste trabalho foi a Região Metropolitana de São Paulo (RMSP), Brasil, uma das maiores cidades do mundo. Foi analisada uma rede de 21 estações, na RMSP, com totais diários de precipitação para: i) estimar a precipitação máxima diária anual (PMDA), por meio da distribuição de Gumbel, ii) grupos com diferentes taxas de precipitação dentro das classes (de chuvisco a precipitação extrema), e, verificar a similaridade entre as estações (clustering), para taxas de precipitação anual e sazonal, para o período de 1947 a 1998, fazendo uso da técnica conhecida como análise de cluster, e III) identificar possíveis tendências nas três classes de taxa de precipitação (chuvisco, moderado e acima de 30mm/dia) para os períodos anuais e sazonais, para o comprimento total de cada estação, utilizando o teste de tendência de Mann-Kendall. Os resultados mostraram que os dados observados de precipitação máxima diária se ajustam à distribuição de Gumbel no período anual, com taxa anual estimada de precipitação máxima diária igual a 239,3 mm/dia com período de retorno de 500 anos na estação Barrocada, localizada na região centro-norte da RMSP. A análise de agrupamento mostrou pouca similaridade entre as estações, com relação a algumas taxas de classes de precipitação, tanto em número de eventos das classes de precipitação total, nos períodos anuais como sazonais. O teste de Mann-Kendall apresentou tendência de aumento significativo dos totais acumulados em um maior número de estações para ambos os períodos, anuais e sazonais. A tendência do número de eventos de classe chuvisco, foi significativamente alta para a maioria das estações, novamente tanto em períodos anuais como sazonais, mas nem todas as estações apresentaram tendência de aumento para a classe de eventos moderados. Além disso, a tendência de aumento significativo das classes de taxa de precipitação acima de 30 mm/dia foi encontrada em algumas estações no período anual. Em geral, houve tendência de aumento significativo das taxas de classes de precipitação na RMSP.

Flood estimation is often required in hydrologic design and has important economic significance. For example, in Australia, the annual spending on infrastructure requiring flood estimation is of the order of $650 million ARR (I.E. Aust., 1998). Rainfall-based flood estimation techniques are most commonly adopted in practice. These require several inputs to convert design rainfalls to design floods. Of all the inputs, loss is an important one and defined as the amount of precipitation that does not appear as direct runoff. The concept of loss includes moisture intercepted by vegetation, infiltration into the soil, retention on the surface, evaporation and loss through the streambed and banks. As these loss components are dependent on topography, soils, vegetation and climate, the loss exhibits a high degree of temporal and spatial variability during the rainfall event. In design flood estimation, the simplified lumped conceptual loss models were used because of their simplicity and ability to approximate catchment runoff behaviour. In Australia, the most commonly adopted conceptual loss model is the initial losscontinuing loss model. For a specific part of the catchment, the initial loss occurs prior to the commencement of surface runoff, and can be considered to be composed of the interception loss, depression storage and infiltration that occur before the soil surface saturates. ARR (I. E. Aust., 1998) mentioned that the continuing loss is the average rate of loss throughout the remainder of the storm. At present, there is inadequate information on design losses in most parts of Australia and this is one of the greatest weaknesses in Australian flood hydrology. Currently recommended design losses are not compatible with design rainfall information in Australian Rainfall and Runoff. Also design losses for observed storms show a wide variability and it is always difficult to select an appropriate value of loss from this wide range for a particular application. Despite the wide variability of loss values, in the widely used Design Event Approach, a single value of initial and continuing losses is adopted. Because of the non-linearity in the rainfall-runoff process, this is likely to introduce a high degree of uncertainty and possible bias in the resulting flood estimates. In contrast, the Joint Probability Approach can consider probability-distributed losses in flood estimation. In ARR (I. E. Aust., 1998) it is recommended to use a constant continuing loss value in rainfall events. In this research it was observed that the continuing loss values in the rainfall events were not constant, rather than it decays with the duration of the rainfall event. The derived loss values from the 969 rainfall and streamflow events of Queensland catchments would provide better flood estimation than the recommended design loss values in ARR (I. E. Aust., 1998). In this research, both the initial and continuing losses were computed using IL-CL loss model and a single median loss value was used to estimate flood using Design Event Approach. Again both the initial and continuing losses were considered to be random variables and their probability distribution functions were determined. Hence, the research showed that the probability distributed loss values can be used for Queensland catchments in near future for better flood estimate. The research hypothesis tested was whether the new loss value for Queensland catchments provides significant improvement in design flood estimation. A total of 48 catchments, 82 pluviograph stations and 24 daily rainfall stations were selected from all over Queensland to test the research hypothesis. The research improved the recommended design loss values that will result in more precise design flood estimates. This will ultimately save millions of dollars in the construction of hydraulic infrastructures.