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A Graph-based Modeling Framework for Tracing Hydrological Pollutant Transport in Surface Waters

Overview
Journal Comput Chem Eng
Date 2024 Jan 24
PMID 38264312
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Abstract

Anthropogenic pollution of hydrological systems affects diverse communities and ecosystems around the world. Data analytics and modeling tools play a key role in fighting this challenge, as they can help identify key sources as well as trace transport and quantify impact within complex hydrological systems. Several tools exist for simulating and tracing pollutant transport throughout surface waters using detailed physical models; these tools are powerful, but can be computationally intensive, require significant amounts of data to be developed, and require expert knowledge for their use (ultimately limiting application scope). In this work, we present a graph modeling framework - which we call HydroGraphs - for understanding pollutant transport and fate across waterbodies, rivers, and watersheds. This framework uses a simplified representation of hydrological systems that can be constructed based purely on open-source data (National Hydrography Dataset and Watershed Boundary Dataset). The graph representation provides a flexible intuitive approach for capturing connectivity and for identifying upstream pollutant sources and for tracing downstream impacts within small and large hydrological systems. Moreover, the graph representation can facilitate the use of advanced algorithms and tools of graph theory, topology, optimization, and machine learning to aid data analytics and decision-making. We demonstrate the capabilities of our framework by using case studies in the State of Wisconsin; here, we aim to identify upstream nutrient pollutant sources that arise from agricultural practices and trace downstream impacts to waterbodies, rivers, and streams. Our tool ultimately seeks to help stakeholders design effective pollution prevention/mitigation practices and evaluate how surface waters respond to such practices.

References
1.
Bauman A, Burt J, Feary D, Marquis E, Usseglio P . Tropical harmful algal blooms: an emerging threat to coral reef communities?. Mar Pollut Bull. 2010; 60(11):2117-22. DOI: 10.1016/j.marpolbul.2010.08.015. View

2.
Soranno P, Spence Cheruvelil K, Wagner T, Webster K, Bremigan M . Effects of Land Use on Lake Nutrients: The Importance of Scale, Hydrologic Connectivity, and Region. PLoS One. 2015; 10(8):e0135454. PMC: 4534397. DOI: 10.1371/journal.pone.0135454. View

3.
Xue J, Wang Q, Zhang M . A review of non-point source water pollution modeling for the urban-rural transitional areas of China: Research status and prospect. Sci Total Environ. 2022; 826:154146. DOI: 10.1016/j.scitotenv.2022.154146. View

4.
Burkholder J, Libra B, Weyer P, Heathcote S, Kolpin D, Thorne P . Impacts of waste from concentrated animal feeding operations on water quality. Environ Health Perspect. 2007; 115(2):308-12. PMC: 1817674. DOI: 10.1289/ehp.8839. View

5.
Walton C, Zak D, Audet J, Petersen R, Lange J, Oehmke C . Wetland buffer zones for nitrogen and phosphorus retention: Impacts of soil type, hydrology and vegetation. Sci Total Environ. 2020; 727:138709. DOI: 10.1016/j.scitotenv.2020.138709. View