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The United States Weather Bureau had published Technical Paper No. 40 (TP-40) in 1961 which provides a rainfall atlas for the United States. These rainfall frequencies have been used by engineers throughout the United States including Jefferson Parish, Louisiana. Rainfall from Audubon and the New Orleans International Airport rain gauge stations were used with the Log Pearson Method to provide rainfall frequency for Jefferson Parish, Louisiana. The results from the frequency rainfall that were developed for this research along with the current Jefferson Parish design storm rainfall were applied to a typical urban development to evaluate the extent of flooding.

The scarcity of data poses a challenging obstacle for the study of natural disasters, especially in developing countries where the social vulnerability plays as important a role as the physical vulnerability.  The work presented in this thesis is oriented towards the demonstration of the usefulness of press archives as a data source for the temporal and spatial analysis of landslides in Tegucigalpa, Honduras for the period between 1980 and 2005.  In the last four decades, Tegucigalpa has been characterized by a disorganized urban growth that has significantly contributed to the destabilization of the city’s slopes.  In the first part of the thesis, a description of the database compilation procedure is provided.  The limitations of using data derived from press archives have also been addressed to indicate how these affect the subsequent landslide analyses.  In the second part, the temporal richness offered by press archives has allowed the establishment of rainfall thresholds for landslide occurrence.  Through the use of the critical rainfall intensity method, the analysis of rainfall thresholds for 7, 15, 30 and 60 antecedent days shows that the number of yielded false alarms increases with the threshold duration.  A new method based on the rainfall frequency contour lines was proposed to improve the distinction between days with and without landslides.  This method also offers the possibility to identify the landslides that may only occur with a major contribution of anthropogenic disturbances as well as those landslides induced by high-magnitude rainfall events.  In the third part, the matrix method has been employed to construct two landslide susceptibility maps: one based on the multi-temporal press-based landslide inventory and a second one based on the landslide inventory derived from an aerial photograph interpretation carried out in 2014.  Despite the low spatial accuracy provided by the press archives in locating the landslides, both maps exhibit 69% of consistency in the susceptibility classes and a good agreement in the areas with the highest propensity to landslides.  Finally, the integration of these studies with major actions required to improve the process of landslide data collection is proposed to prepare Tegucigalpa for future landslides.

The rainfall specifics characteristics vary from one region to another. The knowledge of the rainfall potential to cause erosion is necessary to plan agricultural and civil engineering activities. For Quarai and Rio Grande (RS, Brazil), were determined the rainfall erosivity and its relationship with precipitation and rainfall coefficient, rainfall patterns and rainfall return period. Were used rainfall data charts of 38 years of Quarai (1966-2003) and 23 years of Rio Grande (1957, 1959-1978 e 1980-1981). For each erosive rainfall were separated the segments of the rainfall chart with the same intensity and the data registered in worksheet. With the software Chuveros were estimated the mean monthly and annual rainfall erosivity, the EI30 index in the International System of Units and the rainfall patterns. The mean monthly values of precipitation and erosivity index were expressed as percentages of the mean annual values of precipitation and erosivity index, respectively, to obtain the curve of accumulated distribution of precipitation and erosivity index in function of time. The rainfall coefficient (Rc) was calculated. Were performed Pearson correlations and linear regressions between the erosivity index EI30 and the mean annual values of precipitation and rainfall coefficient.. The rainfall return period were calculated for 2, 5, 10, 20, 50 e 100 years. The mean annual values of EI30 for Quarai and Rio Grande were 9292.1 e 5135.0 MJ mm ha-1 h-1 ano-1, respectively. Were obtained the equations EI30 = -754.37 + 13.50 p (r2 = 0.85) e EI30 = - 47.35 + 82.72 Rc (r2 = 0.84) for Quarai. For Rio Grande the equations were not significant. In relation to the total of the rainfalls studied for each place, 44.3% of the number and 90.4% of the volume were erosive in Quarai, and 32.6% of the number and 99.3% of the volume were erosive in Rio Grande. The method of extreme distribution type I was adequate for obtaining the curves of intensity-duration-frequency. The rainfall return periods may be calculated by the equations using the values of the parameters found, or by the figures of intensity-durationfrequency. / As características específicas das chuvas variam de uma região a outra. O conhecimento da potencialidade das chuvas em causar erosão é necessário para planejar atividades agrícolas e de engenharia civil. Para as localidades de Quarai e Rio Grande (RS), foram determinados a erosividade da chuva e a relação com a precipitação e o coeficiente de chuva, os padrões da chuva e o período de retorno da chuva. Utilizaram-se dados pluviográficos de 38 anos de Quarai (1966-2003) e 23 anos de Rio Grande (1957, 1959-1978 e 1980-1981). Para cada chuva erosiva foram separados os segmentos do pluviograma com a mesma intensidade e registrados os dados em planilha. Com o programa Chuveros foram calculadas a erosividade mensal, anual e média das chuvas pelo índice EI30 no Sistema Internacional de Unidades e os padrões de chuva. Os valores médios mensais da precipitação e do índice de erosividade foram expressos como percentagens do valor médio anual da precipitação e do índice de erosividade respectivamente, para obter a curva de distribuição acumulada da precipitação e do índice de erosividade em função do tempo. O coeficiente de chuva (Rc) foi calculado. Foram realizadas correlações de Pearson e regressões lineares simples entre o índice de erosividade EI30 e os valores médios anuais de precipitação e de coeficiente de chuva. O período de retorno foi calculado para 2, 5, 10, 20, 50 e 100 anos. Os valores médios anuais de EI30 para Quarai e Rio Grande foram 9292,1 e 5135,0 MJ mm ha-1 h-1 ano-1, respectivamente. Para Quarai, obtiveram-se as equações EI30 = -754,37 + 13,50 p (r2 = 0,85) e EI30 = -47,35 + 82,72 Rc (r2 = 0,84). Para Rio Grande as equações não foram significativas. Em relação ao total das chuvas estudadas em cada localidade, 44,3% do número e 90,4% do volume foram erosivas em Quarai, e 32,6% do número e 99,3% do volume foram erosivas em Rio Grande. O método da distribuição extrema tipo I foi adequado para obter as curvas de intensidade duração-freqüência. Os períodos de retorno da chuva podem ser calculados através das equações utilizando os valores dos parâmetros achados, ou pelos gráficos das curvas de intensidade-duração-freqüência.