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Water resources systems are usually designed under the assumption of statistically stationary time series of precipitation and/or streamflow. However, this assumption must be previously verified if changes in climate and land use are issues of interest. In these cases, designs based on the assumption of stationary hydrologic time series should be revised, with the specific aim of verifying the possible impacts that these changes would have on the local water infrastructure. In this context, potentiated by intense controversies about climate change, this paper describes a collection of parametric and non-parametric statistical tests for detecting possible trends in the rainfall regime of the Metropolitan Region of Belo Horizonte, in southeastern Brazil. For this analysis data from 20 gauges, with 50 to 149-year series were collected in four groups of rainfall series: the annual rainfall series, the quarterly rainfall series, the halfyearly series and the annual maximum monthly rainfall series. Prior to the use of statistical tests, the 4 groups of precipitation series were submitted to a preliminary graphical analysis covering time series plots of a 10-year moving average and moving median, LOWESS smoothing (Locally Weighted Scatterplot Smoothing), linear regression and RAPS (Rescaled Adjusted Partial Sums) graphs, as well as an exploratory analysis for detecting and identifying possible trends and/or abrupt changes in data. After this graphical and exploratory study, the data were formally analyzed using TREND software, developed by the Australian Cooperative Research Center for Catchment Hydrology (CRCCH), aiming to identify possible trends or abrupt changes in point precipitation series within the region

Estudo para Identificação de Tendências do Regime Pluvial na Região Metropolitana de Belo Horizonte a Partir de Métodos Estatísticos