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Pre-whitening approaches have been widely used to remove the influence of serial correlations on the Mann-Kendall trend test (MKₚrew). However, previous studies indicate that this procedure may lead to a false reduction of the significance of a trend. An alternative approach (MKᵢnteract) has been proposed to improve the assessment of the significance of a trend in auto-correlated data. Therefore, the present study compared the performance of the MKₚrew and MKᵢnteract for detecting trends in auto-correlated series. Sets of Monte Carlo experiments were carried out to evaluate the occurrence of type I and II errors obtained from both approaches. The analyses were also based on 10-day values of the difference between precipitation and potential evapotranspiration (P-EP) obtained from the location of Campinas, State of São Paulo, Brazil. The results found in this study allow us to conclude that the MKᵢnterac outperformed the MKₚrew in correctly identifying the significance of trends and that, concerning agricultural interests, the decreasing trend described by the MKᵢnterac during the beginning of the crop growing seasons may reveal an unfavorable temporal distribution of the P-EP values.
Gabriel Constantino Blain (Thu,) studied this question.