Application of Species Sensitivity Distribution (SSD) to Derivation of Water Quality Criteria for Pesticides

Deriving methods play an important role in water quality criteria is critical derivation. Species sensitivity distributions (SSD) is a common method used to derive water quality criteria in the world. A number of models are available for use to derive water quality criteria, but not all the models could well fit the toxicity data sets of pesticides. In order to select one that fits with high goodness, 4 typical pesticides were selected in the study to compare the models in goodness of fit. Results show that Sigmoid, Gaussian,Gompertz and Exponential growth were better than the other models in fitting curve tendency, rationality of HC₅ and goodness of fit. Therefore it is suggested that when utilizing SSD to derive criteria for pesticides, Sigmoid, Gaussian, Gompertz and Exponential growth should be used to get fitting curves first, and then the most optimal model should be chosen for use to determine benchmark values for the water quality criteria, so as to ensure scientificity of the derivation of the water quality criteria. The findings can serve as scientific references for selection of derivation methods for formulation of water quality criteria for pesticides.