Optimal tracer identification for dissolved organic matter (DOM) source tracking in watersheds using point source effluent load data

In this study, we characterized the optical and molecular weight (MW) properties of dissolved organic matter (DOM) with various sources in an agriculture-forestry watershed. We proposed a guideline to identify optimum DOM source tracers for downstream rivers during both rain and non-rain events, uti...

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Veröffentlicht in:Environmental technology & innovation 2023-11, Vol.32, p.103423, Article 103423
Hauptverfasser: Oh, Haeseong, Jung, Ka-Young, Kim, Bo Young, Lee, Byung Joon, Shin, Hyun-Sang, Hur, Jin
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container_start_page 103423
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creator Oh, Haeseong
Jung, Ka-Young
Kim, Bo Young
Lee, Byung Joon
Shin, Hyun-Sang
Hur, Jin
description In this study, we characterized the optical and molecular weight (MW) properties of dissolved organic matter (DOM) with various sources in an agriculture-forestry watershed. We proposed a guideline to identify optimum DOM source tracers for downstream rivers during both rain and non-rain events, utilizing the load of dissolved organic carbon (DOC) from point sources. Six descriptors were pre-selected based on established criteria in the literature, and fifteen pairs of these descriptors were evaluated for their applicability in end-member mixing analysis (EMMA). The results from EMMA provided inconsistent estimates of relative contributions from DOM sources across the fifteen pairs, with optical descriptors outperforming MW-based descriptors and their combinations. The optimal source tracers were determined by comparing relative contributions of DOM from upstream effluent wastewater using DOC load ratios calculated from on-site monitoring data and predictions based on EMMA. The pair of optical descriptors, HIX (humification index) and BIX (biological index), closely matched the measured load ratios with minimal discrepancies (0.4 ± 0.4 %). According to the EMMA results using pairs of HIX and BIX, non-rain events were primarily influenced by oil-cake fertilizer and treated effluent wastewater, while rain event samples were dominated by manure and soils. These findings offer insights into managing non-point organic pollution sources in agricultural-forestry watersheds, contributing to our understanding of carbon and nutrient cycling in aquatic systems. Notably, this study proposes a validation guideline that employs load ratios of point sources, such as effluent wastewater, to enhance source tracking accuracy. [Display omitted] •Optical and MW descriptors used for source tracking during non-rain and rain events.•Point source DOC load data improves identification of optimal DOM tracer pair.•Optical descriptors outperformed MW-based descriptors in tracking DOM sources.•Identified primary sources in downstream stream during non-rain and rain events•Proposed validation guideline enhances accuracy of source tracking.
doi_str_mv 10.1016/j.eti.2023.103423
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According to the EMMA results using pairs of HIX and BIX, non-rain events were primarily influenced by oil-cake fertilizer and treated effluent wastewater, while rain event samples were dominated by manure and soils. These findings offer insights into managing non-point organic pollution sources in agricultural-forestry watersheds, contributing to our understanding of carbon and nutrient cycling in aquatic systems. Notably, this study proposes a validation guideline that employs load ratios of point sources, such as effluent wastewater, to enhance source tracking accuracy. 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subjects dissolved organic carbon
Dissolved organic matter
End-member mixing analysis
environmental technology
fertilizers
Fluorescence
guidelines
humification
molecular weight
Non-point sources
pollution
rain
Size exclusion chromatography
Source tracking
wastewater
watersheds
title Optimal tracer identification for dissolved organic matter (DOM) source tracking in watersheds using point source effluent load data
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