Availability of precipitation data is very important in every aspect related to hydrology. Readings from the ground stations are reliable and are used in hydrological models to do various analysis. However, the predictions are always associated with uncertainties due to the limited number of ground stations, which requires interpolation of the data. Meanwhile, groundbreaking approach in capturing precipitation events from vantage point through satellites in space has created a platform to not only merge ground data with satellite estimates to produce more accurate result, but also to find the data where ground stations are not available or scarcely available. Nevertheless, the data obtained through these satellite missions needs to be verified on its temporal and spatial resolution as well as the uncertainties associated before we make any decisions on its basis. This study focuses on finding and evaluating data obtained from two multi-satellite precipitation measurements missions: i) Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) ii) Global Precipitation Measurement (GPM) mission. GPM is the latest mission launched on Feb 28, 2014 after the successful completion of TRMM mission which collected valuable data for 17 years since its launch in November 1997. Both near real time and final version precipitation products for TMPA and GPM are considered for this study. Two study areas representing eastern and western parts of the United States of America (USA) are considered: i) Charlotte (CLT) in North Carolina ii) San Francisco (SF) in California. Evaluation is carried out for daily accumulated rainfall estimates and single rainfall events. Statistical analysis and error categorization of daily accumulated rainfall estimates were analyzed in two parts: i) Ten yeas data available for TMPA products were considered for historical analysis ii) Both TMPA and GPM data available for a ten-month common period was considered for GPM Era analysis. To study how well the satellite estimates with their finest temporal and spatial resolution capture single rainfall event and to explore their engineering application potential, an existing model of SF watershed prepared in Infoworks Integrated Catchment Model (ICM) was considered for hydrological simulation. Infoworks ICM is developed and maintained by Wallingford Software in the UK and SF watershed model is owned by San Francisco Public Works (SFPW). The historical analysis of TMPA products suggested overestimation of rainfall in CLT region while underestimation in SF region. This underestimation was largely associated with missed-rainfall events and negative hit events in SF. This inconsistency in estimation was evident in GPM products as well. However, in the study of single rainfall events with higher magnitude of rainfall depth in SF, the total rainfall volume and runoff volume generated in the watershed were over-estimated. Hence, satellite estimates in general tends to miss rainfall events of lower magnitude and over-estimate rainfall events of higher magnitude. From statistical analysis of GPM Era data, it was evident that GPM has been able to correct this inconsistency to some extent where it minimized overestimation in CLT region and minimized negative error due to underestimation in SF. GPM products fairly captured the hydrograph shape of outflow in SF watershed in comparison to TMPA. From this study, it can be concluded that even though GPM precipitation estimates could not quiet completely replace ground rain gage measurements as of now, with the perpetual updating of algorithms to correct its associated error, it holds realistic engineering application potential in the near future.

Conselho Nacional de Desenvolvimento Científico e Tecnológico / The knowledge of intense precipitation is primordial in hydraulic structures design. However, the determination of this variable stumbles on its monitoring deficiency. Thus, the use of statistical methods, such as regional frequency analysis, aims to support the determination or caracterization of these precipitation. The purpose of this study was to identify behavioral patterns of daily intense precipitation that allows the estimative of design storm in ungauged basins. The study was directed to the southernmost state of Brazil, Rio Grande do Sul (RS), a region with one of the world highest intense precipitation events. The hydrometeorological monitoring of the region is accomplished mainly by the National Water Agency (ANA). In this study were analyzed 1070 rain gauges, containing records between 1912 and 2014. Firstly, the consistency procedure was performed, by pre-analyzing and classifying the precipitation events (adapted Z score), selection of annual maximum series of continuous periods, and punctual validation. In the second stage, the maximum events were submitted to a regional frequency analysis, based on the regionalization method of Hoskins e Wallis. Finally, was demonstrated a precipitation estimative method for ungauged basins. The results of the pre-analysis characterized the periods of greatest temporal and spatial continuity from the available records, which occurred in the decade of 1970. On the other hand, this period has the greatest number of monitoring inconsistencies. The classification of the precipitation records indicated possible inconsistent data. Parallel to this, the selection process allowed the elaboration of maximum series of 15 and 30 years, uninterrupted, which occurred between 1963 and 1977, and between 1971 and 2000, with 91 and 40 gauges, respectively. Among the series, 163 events were indicated as possibly inconsistent data, which then were analyzed by the punctual validation, resulting in more trustworthy maximum series. The results of the maximum series regionalization indicated that RS has from two to three regions of homogenous behavior. The estimative from the 15 years series generated the most accurate values for Return Periods (T) lower than ten years. In opposite, the 30 years series resulted in better approximations for T greater than 20 years. Nevertheless, the quality of the estimates is prejudiced in the regions with a low density of gauges. The processes applied to the consistency analysis were effective, and the suggested methodology demonstrated to be appropriate and flexible. / O conhecimento das precipitações intensas é primordial no projeto de estruturas hidráulicas. No entanto, a determinação desta variável esbarra nas deficiências do seu monitoramento. Assim, o emprego de métodos estatísticos, como análise de frequência regional visa auxiliar na determinação ou caracterização dessas precipitações. O objetivo deste estudo foi identificar padrões comportamentais das precipitações intensas diárias que possibilitem estimar chuvas de projetos em locais sem informações. O estudo foi direcionado ao estado do Rio Grande do Sul, Brasil, cujas precipitações intensas estão entre as maiores do mundo. Seu monitoramento hidrometeorológico é efetuado, principalmente, pela Agência Nacional de Águas (ANA). Foram analisadas 1070 estações pluviométricas, com registros entre os anos de 1912 a 2014. Foi realizado, primeiramente, o processo de consistência, que contou com: pré-análise e classificação dos eventos de precipitação (Z-score adaptado), seleção de séries de máximos anuais de períodos contínuos, e validação pontual. Na segunda etapa, os eventos de máximos foram submetidos a uma análise regional de frequências, baseada no método de regionalização de Hosking e Wallis, em seguida, foi demostrada uma forma de estimar as precipitações em locais sem dados. Os resultados da pré-análise caracterizaram os momentos de maior continuidade temporal e espacial dos registros disponíveis, os quais ocorreram em meados da década de 70. Por outro lado, este período também foi o com maior número de inconsciências no monitoramento. A classificação dos registros de precipitação indicou possíveis dados inconsistentes. Paralelo a isto, o processo de seleção permitiu a construção de séries de máximos de 15 e 30 anos, ininterruptos, os quais ocorreram entre 1963 a 1977 e, 1971 a 2000, com 91 e 40 estações, respectivamente. Dentre estas séries, 163 eventos foram indicados como possíveis dados inconsistentes, os quais passaram pelo processo de validação pontual, resultando em séries de máximos de maior confiabilidade. O resultado da regionalização das séries de máximos demonstrou que o Estado possui de duas a três regiões de comportamento homogêneo. As estimativas produzidas pelas regiões formadas pelas séries de 15 anos produziram valores mais precisos para tempos de retorno (Tr) inferior a dez anos. Já as séries de 30 anos resultaram numa melhor precisão nas estimativas com Tr superior a 20 anos. Contudo, a qualidade das estimativas é prejudicada nas regiões em que a densidade de estações é baixa. Os processos empregados na análise de consistência foram eficientes, e a metodologia sugerida demonstrou ser flexível e aplicável.

The thesis is divided in two parts. The first part deals with the areal distribution of short-term convective rainfalls with regard to the influence of altitude. Precipitation estimates based on combination of rain gauge and radar data are used for this purpose. Statistical tests proved that the areal distribution of hourly convective rainfalls does not depend on altitude. Besides data containing precipitation events only, all measured data were statistically analysed regardless of the fact whether precipitation occurred or not. In this case it was found out that the relationship between hourly rainfall totals and altitude depends on the considered threshold of rainfall totals. When all data were considered, i.e. a threshold value was set to zero, an increase of rainfall totals well correlated with altitude. The dependence slowly disappeared with an increasing threshold. The areal distribution of 6 hour rainfall totals proved higher values in the area of south Bohemia. The most frequent synoptic patterns were northwest cyclonic situations (NWC) and cyclone over the Central Europe (C). The second part of the thesis is focused on satellite data exploitation, as measured by meteorological satellite Meteosat Second Generation, for convective precipitation estimates. The Convective Rainfall Rate (CRR) algorithm,...