Avaliação da rede de monitoramento de qualidade das águas superficiais da Bacia do Rio das Velhas utilizando o método da entropia - Katiane Cristina de Brito Almeida (2013)
The present study has aimed to evaluate the spatial distribuition of the water quality monitoring network of Velhas river (MG), operated by IGAM, using the method of entropy. For that matter, it was used a software developed by Soares (2001), which allows you to check the efficiency of the data collected considering the information provided and thus stablish the priority levels of stations in the monitoring network. There were selected five parameters to study, considering the highest percentages of violation of DN COPAM/CERH N. 01/08 - feacal coliforms, Total Arsenic, Total Phosphorus, Turbidity and Dissolved Oxygen - and 19 monitoring stations located in the Velhas river. Due to the characteristics of the software used, which analyzes only five stations at time, with a maximum number of 21 data, it was necessary to group the stations into four sections. These clusters were defined by Cluster Analysis and validated using the nonparametric Kruskal-Wallis test followed by multiple comparisons, by significance level of 5%. The evaluation of the spatial distribuition of network monitoring was performed in two stages considering the priority level of maintenance of the stations in the network monitoring: as a function of each parameter individually and all together. According to the analysis of the results, considering the uncertainty involved in the production of information about the monitored parameters, it was possible to indicate that the mos important stations in the maintenance of the network were the BV067, BV141, BV142 and BV149. The stations showed that the worst results and that, theoretically, could be desactivated, were BV013, BV139, BV150 and BV148. Thus, it was concluded that the method of entropy can be an important decision tool for redesigning of monitoring networks, as it could identify stations that could or not to be prioritized in the network monitoring of Velhas river, considering the redundancy of the information contained in the various data sets.