Nonparametric tests for stationary analysis in hydrological data

One of the main problems for water resources management systems has been the climate change and the intensification of anthropogenic activities in river basins. In this context, this work aimed to analyze the dynamics of land use and cover and its influence on temporal variability on streamflow data. The behavior of hydrological data (streamflow and rainfall) over time was analyzed by applying the nonparametric tests of Mann Kendall and Pettitt. Images derived from orbital sensors using the Random Forest classifier assessed the anthropogenic influence in the area, land use, and cover classification. The rainfall data did not present significant changes over time, according to the applied tests. However, the low annual flow and average annual flow presented nonstationary behavior, with a trend of reduction over time. As rainfall did not change in its patterns over time, the main reason associated with the changes in streamflow regimes was associated with the changes in land use and land cover, especially in the areas for crops, that had an increase of 48% in the study period, which can contribute to increase the demand for water and affect the streamflow. The results obtained confirm the importance of this study for water management systems to adapt itself to the changes in hydrological behavior over time.