Academic Journal

AFAR-WQS: A Quick and Simple Toolbox for Water Quality Simulation.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: AFAR-WQS: A Quick and Simple Toolbox for Water Quality Simulation.
Συγγραφείς: Rogéliz-Prada, Carlos A., Nogales, Jonathan
Πηγή: Water (20734441); Mar2025, Vol. 17 Issue 5, p672, 15p
Θεματικοί όροι: Water management, Water quality management, Object-oriented methods (Computer science), Water quality, Graph theory, Adaptive natural resource management
Περίληψη: Water quality management in large basins demands tools that balance scientific rigor with computational efficiency to avoid paralysis by analysis. While traditional models offer detailed insights, their complexity and resource intensity hinder timely decision-making. To address this gap, we present AFAR-WQS, an open-source MATLAB™ toolbox that introduces a novel integration of assimilation factors with graph theory and a Depth-First Search (DFS) algorithm to rapidly simulate 13 water quality determinants across complex topological networks. AFAR-WQS resolves cumulative processes in networks of up to 30,000 segments in just 163 s on standard hardware, enabling real-time scenario evaluations. Its object-oriented architecture ensures scalability, allowing customization for urban drainage systems or macro-basin studies while maintaining computational efficiency. Case studies demonstrate its utility in prioritizing sanitation investments, assessing water quality at the national scale and fostering stakeholder collaboration through participatory workshops. By bridging the gap between simplified and complex models, AFAR-WQS supports adaptive management in contexts of hydrological uncertainty, regulatory compliance, and climate change. The toolbox is freely available at GitHub, offering a transformative approach for integrated water resource management. [ABSTRACT FROM AUTHOR]
Copyright of Water (20734441) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Biomedical Index
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  Data: AFAR-WQS: A Quick and Simple Toolbox for Water Quality Simulation.
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  Data: Water (20734441); Mar2025, Vol. 17 Issue 5, p672, 15p
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  Data: <searchLink fieldCode="DE" term="%22Water+management%22">Water management</searchLink><br /><searchLink fieldCode="DE" term="%22Water+quality+management%22">Water quality management</searchLink><br /><searchLink fieldCode="DE" term="%22Object-oriented+methods+%28Computer+science%29%22">Object-oriented methods (Computer science)</searchLink><br /><searchLink fieldCode="DE" term="%22Water+quality%22">Water quality</searchLink><br /><searchLink fieldCode="DE" term="%22Graph+theory%22">Graph theory</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+natural+resource+management%22">Adaptive natural resource management</searchLink>
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  Data: Water quality management in large basins demands tools that balance scientific rigor with computational efficiency to avoid paralysis by analysis. While traditional models offer detailed insights, their complexity and resource intensity hinder timely decision-making. To address this gap, we present AFAR-WQS, an open-source MATLAB™ toolbox that introduces a novel integration of assimilation factors with graph theory and a Depth-First Search (DFS) algorithm to rapidly simulate 13 water quality determinants across complex topological networks. AFAR-WQS resolves cumulative processes in networks of up to 30,000 segments in just 163 s on standard hardware, enabling real-time scenario evaluations. Its object-oriented architecture ensures scalability, allowing customization for urban drainage systems or macro-basin studies while maintaining computational efficiency. Case studies demonstrate its utility in prioritizing sanitation investments, assessing water quality at the national scale and fostering stakeholder collaboration through participatory workshops. By bridging the gap between simplified and complex models, AFAR-WQS supports adaptive management in contexts of hydrological uncertainty, regulatory compliance, and climate change. The toolbox is freely available at GitHub, offering a transformative approach for integrated water resource management. [ABSTRACT FROM AUTHOR]
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  Group: Ab
  Data: <i>Copyright of Water (20734441) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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      – SubjectFull: Object-oriented methods (Computer science)
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      – SubjectFull: Graph theory
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              Text: Mar2025
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