a b s t r a c t Study region: The study was conducted in the Rio Grande do Sul state -Brazil. Study focus: Studies about heavy rainfall events are crucial for proper flood management in river basins and for the design of hydraulic infrastructure. In Brazil, the lack of runoff monitoring is evident, therefore, designers commonly use rainfall intensity-duration-frequency (IDF) relationships to derive streamflow-related information. In order to aid the adjustment of IDF relationships, the probabilistic modeling of extreme rainfall is often employed. The objective of this study was to evaluate whether the GEV and Kappa multiparameter probability distributions have more satisfying performance than traditional two-parameter distributions such as Gumbel and Log-Normal in the modeling of extreme rainfall events in southern Brazil. Such distributions were adjusted by the L-moments method and the goodness-of-fit was verified by the Kolmogorov-Smirnov, Chi-Square, Filliben and Anderson-Darling tests. New hydrological insights for the region: The Anderson-Darling and Filliben tests were the most restrictive in this study. Based on the Anderson-Darling test, it was found that the Kappa distribution presented the best performance, followed by the GEV. This finding provides evidence that these multiparameter distributions result, for the region of study, in greater accuracy for the generation of intensity-duration-frequency curves and the prediction of peak streamflows and design hydrographs. As a result, this finding can support the design of hydraulic structures and flood management in river basins.

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R E S U M OA gestão de cheias em bacias hidrográficas brasileiras deve ser discutida e priorizada, porém o cenário atual indica lacunas quanto às informações hidrológicas com variabilidade espacial e temporal condizentes. A modelagem probabilística de eventos extremos de precipitação, buscando a extrapolação para uma frequência e duração, pode servir como excelente ferramenta de análise e tomada de decisões. O objetivo principal deste trabalho foi analisar o ajuste de diferentes modelos probabilísticos a séries de precipitação máxima diária anual no Rio Grande do Sul. Séries pluviométricas de 342 estações foram ajustadas às distribuições Log-Normal a 2 e 3 parâmetros e Gumbel e a adequação foi realizada pelos testes de Kolmogorov-Smirnov e Qui-Quadrado. Todas as distribuições de probabilidade consideradas foram adequadas; entretanto, a distribuição Log-Normal a 3 parâmetros apresentou os melhores ajustes segundo os resultados do teste Qui-Quadrado. Os parâmetros das distribuições de probabilidades apresentaram variabilidade ao longo do estado e forte relação com a localização, sugerindo que a regionalização de chuvas intensas pode ser empregada no Rio Grande do Sul como excelente ferramenta de gestão.Probabilistic modelling of extreme rainfall events in the Rio Grande do Sul state A B S T R A C T Flood management in Brazilian watersheds must be discussed and prioritized, however, the current scenario indicates that there are gaps in hydrological information with respect to its spatial and temporal variability. The probabilistic modelling of extreme rainfall events, having as goal to extrapolate values for a given frequency and duration, can be used as an excellent tool for analysis and decision-making. The main objective of this study was to analyse the adjustment of different probabilistic models for series of annual maximum daily rainfall in Rio Grande do Sul. Series of 342 rain gauges were adjusted to 2-parameter Log-Normal, 3-parameter Log-Normal and Gumbel probability distributions and goodnessof-fit tests were based on the Kolmogorov-Smirnov and Chi-Square procedures. It was found that all the distributions presented adequate results, however, 3-parameter LogNormal distribution had the best performance in accordance with the Chi-Square test. The parameters of probability distribution presented variability over the state and a pronounced relationship with the location of rain gauges. This suggests that regionalization of highintensity rainfall can be employed in Rio Grande do Sul as an excellent management tool. Palavras-chave:chuvas intensas distribuição de probabilidade regionalização hidrológica

The objective of this study was to evaluate, based on a data-scarce basin in southern Brazil, the potential of the Lavras Simulation of Hydrology (LASH) model for estimating daily streamflows, annual streamflow indicators and the flow-duration curve. It was also used to simulate the different runoff components and their consistency with the basin physiographical characteristics. The statistical measures indicated that LASH can be considered suitable according to widely used classifications and when compared with other studies involving hydrological models. LASH also showed satisfactory results for annual indicators, especially for maximum and average annual streamflows, as well as for the flowduration curve. It was found that the model was consistent with the basin characteristics when simulating runoff components. The results obtained in this study allowed us to conclude that the LASH model has the potential to aid practitioners in water resources management of basins with scarce data and similar soil and land-use conditions.

Knowledge on multi-scale and localized control of saturated soil hydraulic conductivity (Ksat) at the watershed scale is lacking. The objective of this study was to evaluate the multi-scale spatial relationships among Ksat and environmental factors (i.e., soil and topographic attributes and land-use systems) using wavelet coherency and multiple wavelet coherence methods. In the Fragata River Watershed (FRW) in southern Brazil, one hundred points were distributed at equal distances along a 15-km transect. In the 0-20 cm layer, clay and sand fractions, organic carbon content, bulk density, macroporosity, Ksat, and soil water retention curve were determined from soil sampled at each point. The digital elevation model was used for obtaining topographic attributes. A land-use map was developed by use of satellite images. All data sets were analyzed using descriptive statistics, and the relationship among Ksat and the other variables was evaluated through the Spearman correlation coefficient. Wavelet coherency and multiple wavelet coherence were used to examine the correlation among Ksat and each of the explanatory variables and to investigate the scale-specific and localized multivariate relationships among Ksat and predictor variables, respectively. According to the bivariate wavelet coherency and multiple wavelet coherence analyses, macroporosity showed the greatest mean wavelet coherence and percent area of significance coherence with Ksat. The variations of soil macroporosity itself were enough to explain the variations in Ksat in a multiple-scale andlocation domain. Soil macroporosity could be used as a proxy for assessing runoff potential at different land-use systems with different scales in the FRW in southern Brazil.