An AHP-based multicriteria screening framework for preventive pesticide monitoring in data-limited tropical rice catchments

Abstract

Preventive pesticide monitoring in tropical agricultural catchments is frequently constrained by limited analytical capacity, incomplete environmental datasets, and the large number of potentially relevant compounds requiring evaluation. To address these limitations, this study developed and applied a multicriteria screening framework for prioritizing agrochemical residues in support of preventive surface water monitoring in a tropical rice-growing catchment in Colombia. The framework integrated four criteria associated with environmental relevance: human health concern, aquatic toxicity, transport potential, and use-based occurrence proxies. An analytic hierarchy process approach was used to derive criterion weights and evaluate prioritization consistency. A total of 162 pesticides associated with rice production were evaluated. Cypermethrin, isopyrazam, 2,4-D, chlorpyrifos, oxadiazon, mancozeb, fentin hydroxide, triadimenol, permethrin, and malathion were identified as the highest priority compounds, reflecting different combinations of toxicological relevance, transport-related behavior, mobility potential, and expected occurrence. Sensitivity analysis demonstrated stable ranking behavior under moderate weight perturbations. The prioritization generated operationally relevant outputs for monitoring design, including environmental matrix selection according to mobility and partitioning behavior, rainfall- and application-related sampling windows, and analytical targeting guidance. Overall, the framework provides a transferable screening tool for supporting preventive pesticide-monitoring strategies in tropical agricultural catchments under data-limited conditions.