COMPARISON OF CLASSICAL AND THEIL-KENDALL METHODS IN ASSESSING THE SIGNIFICANCE OF LINEAR TREND OF PRECIPITATION IN SOUTH-EASTERN POLAND

Two methods of linear trend estimation: the ordinary least squares (OLS, parametric) and Theil-Kendall (TK, nonparametric) are compared in the paper. The comparison was made using 65 time series of annual totals, Pa, and annual daily maximum, Pmax, of precipitation, 30-year long each, recorded in the south-eastern part of Poland (the Upper Vistula catchment). The OLS and TK slope coefficients of trends revealed high similarity for both Pa and Pmax series. The signs of slopes are the same for 64 sites for Pa and 63 sites for Pmax with positive signs prevailing: the numbers of decreasing trends for Pa OLS and TK slopes were 3 and 4, respectively, and, for Pmax, 13 for both OLS and TK slopes. In trend significance testing, both methods produced similar results for Pa time series: out of 16 significant trends, 13 were determined with both OLS and TK at the same sites. For Pmax series such agreement was found for 4 trends out of 10. Spatial distribution of significant trends showed a kind of clustering in certain parts of the investigated area. ...

RECENT TRENDS IN ANNUAL MAXIMUM FLOWS WITHIN THE UPPER VISTULA RIVER CATCHMENT

All uninterrupted time series of annual maximum flows of size at least 30 recorded in the period 1951-2016 in the Upper Vistula River catchment, were taken into trend analysis. Each of the 138 time series ended not earlier than in 2012. To estimate the trend, the nonparametric Theil-Kendall linear regression method was used. After removing the trend, lag-1 Kendall rank autocorrelation coefficient was calculated and, if the coefficient was significant at 5% level, was used to correct the variance of the Kendall S statistic which otherwise remained unchanged. Finally, the variance-corrected Mann-Kendall trend test was used, detecting 22 significant (at 5% level) linear trends of which only two were the effect of autocorrelation. All 138 significant and non-significant trends showed certain areal clustering clearly visible on the map of the catchment, which suggested dividing the area into three parts according the direction of trend and/or the number of statistically significant trends. Generally, the trends in the southern of the Upper Vistula River catchment are increasing, the opposite is true for the northern part. This finding does not concern the north-west part of the catchment where both kinds of trends are observed, which may be explained by strong anthropogenic influence. ...