Decoupled storm-phase source dynamics of dissolved and particulate organic matter in an agricultural watershed

초록

Storm events strongly regulate organic matter (OM) mobilization in agricultural watersheds, yet potential differences in the source evolution of dissolved and particulate OM (DOM and POM) across storm phases remain poorly constrained. Here, we conducted hydrograph phase-resolved storm sampling during two rainfall events and applied end-member mixing analysis (EMMA) to quantify phase-specific OM source dynamics. Source contributions were traced using δ13C–δ15N for POM and fluorescence indices for DOM. Bulk water-quality parameters and POM concentrations increased with discharge during the monitored events, closely tracking suspended solids and particulate nutrients, suggesting cumulative mobilization under event-specific hydrological conditions rather than a clear first-flush-like decline. EMMA results indicated highly dynamic POM source evolution, with leaf litter/riparian vegetation initially contributing 60–67% of POM during the early stage but declining to ∼29% near peak flow as soil-derived POM increased sharply to ∼51%, consistent with discharge-associated particulate mobilization and progressive source-area activation during storm progression. In contrast, DOM showed comparatively buffered dynamics and a strong manure/compost-like signature within the FI–BIX-based EMMA framework, contributing ∼37–58% across storm phases, suggesting persistent leaching and flushing from manure-amended areas once source areas became connected to active flow paths. Source-specific OC fluxes were concentrated in short high-flow windows, with sharp POC pulses near peak discharge and more persistent DOC export into recession. These findings indicate decoupled POM and DOM transport during the monitored storms and highlight the value of phase-resolved, OM-specific source apportionment for interpreting storm-driven carbon export and informing targeted watershed management. © 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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