This study developed four nonlinearity strength indicators for water quality responses based on cross sample entropy, Fourier transformation, non-sequence counting, and adjusted R² according to typical nonlinear load reduction-water quality responses suggested by previous studies. All the indicators were applied on typical numerical water quality simulation samples. Based on the calculation, the four indicators were compared with each other to provide suggestions on how to use them to detect the nonlinearity and measure the nonlinearity strength. Results show some overlaps among the four indicators, however, they are not interchangeable. The four indicators suggest seasonal differences, peak changes, short-term water quality deterioration, and averaged water quality changes respectively. After providing suggestions on how to use the four indicators to detect nonlinearity of water quality responses, this study further discusses the limitations on the nonlinearity definition and potential applications of the four indicators. This study will contribute to understanding, distinguishing, and analyzing the type of nonlinear water quality responses.