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Adequate availability of data directly influences the quality of hydrological studies. In this sense, procedures for filling gaps of observations are often applied in order to improve the length of hydrological series. One technique that can be used is the Artificial Neural Network (ANN), which process information from input data creating an output. This study aims to evaluate the application of ANN to fill missing data from monthly average streamflow series at Rio do Carmo Basin in the state of Minas Gerais, Brazil. A 26-years series (from 1989 to 2012) was used for ANN modelling while the two proceeding years, 2013 and 2014, were used to simulate failures pursuant to evaluating the performance of the ANN. The ANN construction was performed by the software WEKA that uses the multilayer perceptron model with sigmoidal activation functions. Four types of ANN were generated: five attributes and two (MLP1) or five (MLP2) neurons; and with three attributes and one (MLP3) or three (MLP4) neurons. The best-fit model to ANN was the MLP1, verified by Pearson correlation coefficients (0.9824), and coefficient of determination r² (0.9646). The model used five attributes, four input data (year, month, streamflow data from Acaiaca and Fazenda Paraíso stations) and one output data (streamflow from Fazenda Oriente station), that considered the temporal variation of streamflow. Hence, the utilization of the ANN generated by the WEKA was adequate and can be considered a simple approach, not requiring great computational programming knowledge.

This study created thematic heavy rainfall maps for Brazil, with durations of 5-, 30-, 60- and 120 minutes and 5 years of return period (T). The intensity-duration-frequency (IDF) relationships used were compiled from studies found in the literature (798 locations) and derived for 4411 rainfall gauges available in the Hidroweb information system, totaling 5209 rainfall data collected. To derive IDF relationships, Gumbel's probability distributions were used, with parameters estimated by the method of moments. Distribution adequacy was verified by the Kolmogorov-Smirnov test. Rainfall-intensity values obtained by IDF relationships were spatialized in Geographic Information Systems, allowing elaboration of the thematic maps. Thematic maps enable obtain rainfall intensities for places without rain gauge data and/or precarious time-series data. Therefore, these maps are a great tool for the design of hydraulic structures related to urban and rural micro-drainage.