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

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...

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Veröffentlicht in:	arXiv.org 2023-04
Hauptverfasser:	Cole, David L, Ruiz-Mercado, Gerardo J, Zavala, Victor M
Format:	Artikel
Sprache:	eng
Schlagworte:	Agricultural practices Algorithms Data analysis Datasets Decision analysis Decision making Graph representations Graph theory Graphical representations Human influences Hydrology Machine learning Modelling Pollutants Pollution abatement Pollution sources Pollution transport Rivers Surface water Topology optimization Tracing Upstream Watersheds
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