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EN
Hydrological information is essential for adequate water resources management as well as for water supply, energy supply, water allocation, among other services. However, this information does not always exist in quantity and quality to be used in hydrological or water management studies, and alternative methods are required to estimate minimum flows. Estimation based on homogeneous regions enables to transfer observation data from a known location to a location without data, but in the same region. Since the fluviometric stations in the state of Goiás (Brazil) are not uniformly distributed, the present work aimed at delimiting homogeneous regions of minimum flows, using the cluster grouping method with the K-means algorithm.Thus, 71 fluviometric stations with at least 5 years of continuous data were selected, obtained from the HIDROWEB system. In addition to the observed data, other variables were considered, such as drainage area, perimeter, specific minimum flows Q7,10, Q90, Q95 and average slope. The use of all these variables together with the observed data made it possible to determine,with great accuracy, 5 homogeneous regions of minimum flows based on the cluster analysis, enabling to obtain the minimum flows of reference for each region.In the selected homogeneous regions, it was possible to observe that the regions with the highest values of average slope presented smaller minimum flows, and the same could be observed under inverse conditions, i.e., lower values of average slope had higher minimum flows.It is also noteworthy that river monitoring is deficient in the center-south and center-north parts of the state of Goiás, making water resources management difficult. This fact indicates, therefore, the need to expand the river monitoring system throughout the state, especially in its southern and northern regions.
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