Agricultural runoff is a major source of water quality impairments and is prevalent in areas where agricultural operations focus on maintaining global food security. To alleviate downstream impacts, best management practices are used to cultivate food systems and enhance soil nutrient cycling. When runoff events do occur, tracing the impairments often involves complex and costly methods to determine analyte concentrations and forecast mitigation techniques. Fluorescent dissolved organic matter (fDOM) is an innovative approach to understanding parent source materials and carbon signatures from runoff. Fluorescence and absorbance indices can distinguish intensities of the carbon molecular weight, biological activity, and humification that can trace the environmental availability of carbon sources. Comprehensive data sets can be combined using parallel factor analysis (PARAFAC) to determine parent source components. Integrating these analyses can provide real-time high-frequency data to empower policymakers and land managers to make informed decisions aimed at reducing the environmental degradation associated with modern intensive agriculture.
Moni et al. (Mon,) studied this question.