Journal of Experimental Agriculture International

The homogeneity investigation of a series can be performed through several nonparametric statistical tests, which serve to detect artificial changes or non-homogeneities in climatic variables. The objective of this work was to evaluate two methodologies to verify the homogeneity of the historical climatological series of precipitation and temperature in Mato Grosso state. The series homogeneity evaluation was performed using the following non-parametric tests: Wald-Wolfowitz (for series with one or no interruption), Kruskal-Wallis (for series with two or more interruptions), and Mann-Kendall (for time series trend analysis). The results of the precipitation series homogeneity analysis from the National Waters Agency stations, analyzed by the Kruskal-Wallis and Wald-Wolfowitz tests, presented 61.54% of homogeneous stations, being well distributed throughout Mato Grosso state, whereas those of the trend analysis allowed to identify that 87.57% of the rainfall-gauging stations showed a concentrated positive trend, mainly in the rainy season. Out of the conventional stations of the National Institute of Meteorology of Mato Grosso, seven were homogeneous for the precipitation variable, five for maximum temperature and four stations were homogeneous for minimum temperature. For the trend analysis in the 11 stations, positive trends of random nature were observed, suggesting increasing alterations in the analyzed variables. Therefore, the trend analysis performed by the Mann-Kendall test in the precipitation, and maximum and minimum temperature climate series, indicated that several data series showed increasing trends, suggesting a possible increase in precipitation and temperature values over the years. The results of the Kruskal-Wallis and Wald-Wolfowitz tests for homogeneity presented more than 87% of homogeneous stations.