Análise integrada dos fatores atuantes no regime hídrico nas regiões hidrográficas do oeste de Santa Catarina.

Abstract

Integrated water resource management has been a major challenge, especially under critical hydrological event conditions, which seem to be becoming more frequent and intense in recent years. In addition to the effects generated by climate change, demographic and economic growth is what most impacts water as a resource. This work aimed to analyze the interannual behavior of the minimum specific flows (Q95%), maximum specific flows (Q5%), and annual averages. The intra-annual behavior of the minimum specific flows (Q95%) is also evaluated, as well as its variability from the 1960s onwards in the west of Santa Catarina state. Physical characterization was carried out with a historical approach to the region, the evolution of land use, and the evolution of consumptive water demands. Fluviometric data from 19 stations from the National Water Agency's (ANA) Hidroweb database were used, which were analyzed under different criteria and different periods. Based on a year-to-year (and month-to-month) criterion, the analysis of specific flows was carried out with the application of non-parametric tests, adopting a significance level of 5%. Using Artificial Neural Networks (ANNs), we sought to determine the main factors of importance in the temporal behavior of specific flows. The results show that there were changes in land use in the west of Santa Catarina, the consumptive water demands increased over time, and the specific flows suffered significant spatio-temporal variability. The minimum annual specific flows (Q95%) and the maximum specific flows (Q5%) showed statistically significant changes as the contribution area varies, indicating a greater sensitivity and vulnerability of small basins to extreme events. Physical characteristics such as average slope and altitude are correlated with the minimum (Q95%) and maximum (Q5%) annual specific flows. Moreover, changes in patterns and variability of specific flows over time in the region were observed. The models generated based on ANNs indicate that these observations correlate with precipitation patterns in the region, as well as processes of anthropogenic intervention.