Use of Chemcatcher passive sampler as a watershed-investigation tool to assess first flush polar pesticide pollution in an Eastern Mediterranean River basin.

Characterizing first flush pesticide contamination in ephemeral streams within Mediterranean climates poses significant challenges. Quantifying spatial and temporal differences in chemical pollutants is critical to designing strategic watershed-based restoration plans aimed at protecting aquatic ecosystems. In regions with extended dry periods and intensive agricultural activities, new innovative water quality monitoring methods are needed. This study investigated the efficacy of the Chemcatcher passive sampler as a viable complementary method for assessing pesticide concentrations throughout the Kishon river basin, north-west Israel. A new Chemcatcher deployment apparatus was used in 19 tributaries at 25 watershed locations to capture the first winter storm runoff events. Polar pesticides were identified and quantified using a novel LC/MS targeted and non-targeted screening workflow, identifying 120 compounds, including fungicides, herbicides, insecticides, and their metabolites and quantifying 84 compounds. Time-weighted average concentrations ranged from sub-nanogram per liter to >1800 ng L-1. Pesticide concentrations were positively correlated with agricultural land use categories. Results showed the importance of capturing first flush storm flows, revealing some sites with exceedingly high cumulative concentrations (>2500 ng L-1). Diuron, 2,4-D, imidacloprid and tebuconazole were detected at all sites. Multivariate statistical analysis identified pesticides that posed a risk within the catchment. Concentrations of bromacil, diuron, fenamiphos, imidacloprid, and methoxyfenozide were classified as very high risk, based on their probable no-effect concentrations. This study demonstrates a new method for using passive sampling to monitor first flush stormwaters in ephemeral streams and defines a strategic catchment sampling approach for Mediterranean catchments, with new analytic and statistical tools, to advance informed watershed management decision-making.