In recent years, some non-parametric tests to determine trends of surface water quality have been proposed due to the fact that assumptions in the classical parametric tests (i.e., normality, linearity, independence) are usually not met by a typical surface water quality data. At the same time, statistical tests for trends of water quality are commonly confounded by several of the following problems: missing values, censored data (i.e., values reported as less than a specified quantity), flow relatedness and seasonality. For these reasons, several non-parametric tests (Sen's T, Spearman's Rho, Mann-Kendall, Seasonal Kendall, Mann-Whitney and Kruskall-Wallis'H Tests) have been used or developed in the last two decades. In this study, the surface water quality data of rivers in the Susurluk Basin were used. Four different non-parametric trend tests were selected to detect linear trends of surface water quality. These tests are the Sen's T test, the Spearman's Rho test, the Mann-Kendall test and the Seasonal Kendall test. The linear slopes (change per unit time) of trends are calculated by using a non-parametric estimator. In addition, the homogeneity in monthly trends are tested by using a method developed by Van Belle and Hughes. The results of non-parametric tests indicate that discharge and concentration of sediment have downward trends while temperature and concentrations of specific conductance, sodium, potassium, calcium+magnesium, bicarbonate and chloride generally have upward trends. However concentrations of carbonate, pH, sulfate, organic matter, and boron show no trends.