Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants
River quality management involves complex challenges due to inherent uncertainties in various parameters, especially when dealing with controllable and uncontrollable pollutants. This study integrates a finite volume approach, called SEF (symmetric exponential function), with Monte Carlo simulations...
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Elsevier
2025-01-01
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Series: | Ecotoxicology and Environmental Safety |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S014765132500034X |
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author | Mohsen Dehghani Darmian Britta Schmalz |
author_facet | Mohsen Dehghani Darmian Britta Schmalz |
author_sort | Mohsen Dehghani Darmian |
collection | DOAJ |
description | River quality management involves complex challenges due to inherent uncertainties in various parameters, especially when dealing with controllable and uncontrollable pollutants. This study integrates a finite volume approach, called SEF (symmetric exponential function), with Monte Carlo simulations in MATLAB to solve the advection-dispersion equation, focusing on evaluating river quality protection tools by considering failure probability (Pf). Critical specifications for maintaining reliable river ecosystem performance are identified. We simulate assimilation capacity for managing river water quality against controllable pollutants to satisfy allowable pollution concentration at the high-reliability index. Using the Genetic Programming (GP) algorithm, a new accurate equation for assimilation capacity calculation is presented considering Pffor the first time. Results indicate that flow velocity significantly affects river assimilation capacity: increasing velocity can shift the river to a hazardous state while decreasing it allows for greater pollutant assimilation. Sustainable protection tools, including dilution flow and detention time, are considered to manage uncontrollable pollutants within a specific time (Tc) and river length constraints (Lc), safeguarding river water quality for both human and animal populations. Dilution flow is practical for specific base velocities but ineffective at high base flow rates. Conversely, detention time consistently protects water quality across all base flow velocities within the Lc constraint. Moreover, this study introduces the ratio of detention time to initial pollution contact duration as a vital water quality index to protect the rivers' environment. Combining numerical methods with reliability analysis and soft computing techniques, this research provides valuable insights into river system dynamics and protecting river water quality. |
format | Article |
id | doaj-art-3dbab34f915b4027915adbdf2fef3a34 |
institution | Kabale University |
issn | 0147-6513 |
language | English |
publishDate | 2025-01-01 |
publisher | Elsevier |
record_format | Article |
series | Ecotoxicology and Environmental Safety |
spelling | doaj-art-3dbab34f915b4027915adbdf2fef3a342025-01-23T05:26:09ZengElsevierEcotoxicology and Environmental Safety0147-65132025-01-01289117698Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutantsMohsen Dehghani Darmian0Britta Schmalz1Corresponding author.; Chair of Engineering Hydrology and Water Management, Technical University of Darmstadt, Darmstadt, GermanyChair of Engineering Hydrology and Water Management, Technical University of Darmstadt, Darmstadt, GermanyRiver quality management involves complex challenges due to inherent uncertainties in various parameters, especially when dealing with controllable and uncontrollable pollutants. This study integrates a finite volume approach, called SEF (symmetric exponential function), with Monte Carlo simulations in MATLAB to solve the advection-dispersion equation, focusing on evaluating river quality protection tools by considering failure probability (Pf). Critical specifications for maintaining reliable river ecosystem performance are identified. We simulate assimilation capacity for managing river water quality against controllable pollutants to satisfy allowable pollution concentration at the high-reliability index. Using the Genetic Programming (GP) algorithm, a new accurate equation for assimilation capacity calculation is presented considering Pffor the first time. Results indicate that flow velocity significantly affects river assimilation capacity: increasing velocity can shift the river to a hazardous state while decreasing it allows for greater pollutant assimilation. Sustainable protection tools, including dilution flow and detention time, are considered to manage uncontrollable pollutants within a specific time (Tc) and river length constraints (Lc), safeguarding river water quality for both human and animal populations. Dilution flow is practical for specific base velocities but ineffective at high base flow rates. Conversely, detention time consistently protects water quality across all base flow velocities within the Lc constraint. Moreover, this study introduces the ratio of detention time to initial pollution contact duration as a vital water quality index to protect the rivers' environment. Combining numerical methods with reliability analysis and soft computing techniques, this research provides valuable insights into river system dynamics and protecting river water quality.http://www.sciencedirect.com/science/article/pii/S014765132500034XFailure probabilityAssimilation capacityReliability simulationDilution flowWater quality protectionDetention time |
spellingShingle | Mohsen Dehghani Darmian Britta Schmalz Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants Ecotoxicology and Environmental Safety Failure probability Assimilation capacity Reliability simulation Dilution flow Water quality protection Detention time |
title | Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants |
title_full | Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants |
title_fullStr | Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants |
title_full_unstemmed | Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants |
title_short | Uncertainty analysis in river quality management considering failure probability: controllable and uncontrollable input pollutants |
title_sort | uncertainty analysis in river quality management considering failure probability controllable and uncontrollable input pollutants |
topic | Failure probability Assimilation capacity Reliability simulation Dilution flow Water quality protection Detention time |
url | http://www.sciencedirect.com/science/article/pii/S014765132500034X |
work_keys_str_mv | AT mohsendehghanidarmian uncertaintyanalysisinriverqualitymanagementconsideringfailureprobabilitycontrollableanduncontrollableinputpollutants AT brittaschmalz uncertaintyanalysisinriverqualitymanagementconsideringfailureprobabilitycontrollableanduncontrollableinputpollutants |