Identifying and quantifying catchment pesticide hotspots in Mediterranean first-flush stormwaters: A synchronized watershed-scale grab sampling approach.

BACKGROUND: Mediterranean watersheds are characterized by extreme hydrological variability, where intense "first-flush" events mobilize accumulated agrochemicals. Conventional monitoring programs often fail to capture these high-energy, episodic pulses, resulting in a systemic underestimation of non-point source pollution and a critical lack of data-driven mitigation strategies. OBJECTIVES: This study established a diagnostic framework to identify and quantify pesticide "hotspots" across the 1100 km2 Kishon River basin. By employing a synchronized, watershed-scale sampling approach, we evaluated relationships between land-use intensity and pesticide richness to provide a monitoring framework for strategic catchment management. METHODS: Synchronized grab sampling was conducted at 25 stations during the initial winter storms of 2020 and 2021. Samples were screened for 110 compounds using LC-MS/MS. Statistical analysis utilized Linear Mixed Models (LMM) to evaluate the influence of agricultural intensity, while a dual-metric "Hotspot Index"-integrating concentration magnitude and compound richness-prioritized sub-basins for urgent intervention. RESULTS: Pesticides were ubiquitous (100% detection). High agriculture intensity was significantly associated (p < 0.001) with increased pesticide concentrations, with field crops exerting more influence on chemical richness than orchards. Notably, banned legacy compounds (e.g., Simazine) were detected at over 50% of stations, indicating high environmental persistence or unauthorized contemporary use. Four specific sub-basins met the hotspot criteria, consistently exceeding the 75th percentile for multiple pollution metrics. CONCLUSIONS: The synchronized framework effectively captured pesticide peaks typically underrepresented in routine monitoring. We propose a management shift with storm-triggered protocols. This transferable approach identifies critical spatial contamination patterns, providing a robust framework for prioritizing mitigation in Mediterranean agroecosystems globally.