TY - JOUR
T1 - Stakeholder engagement in multi-objective optimization of water quality monitoring network, case study
T2 - Karkheh Dam reservoir
AU - Nikoo, Mohammad Reza
AU - Pourshahabi, Shokoufeh
AU - Rezazadeh, Najmeh
AU - Shafiee, M. Ehsan
N1 - Publisher Copyright:
© 2017 IWA Publishing.
PY - 2017/7
Y1 - 2017/7
N2 - Reservoir water quality is important for water quality management downstream. A hierarchical approach is developed to present the monitoring locations within a format that satisfies the objectives of social stakeholders for making final decisions. First, a CE-QUAL-W2 model is applied to simulate water quality variables in the reservoir for a long time using a set of historic data. Second, transinformation entropy theory is used to quantify mutual information among a set of monitoring stations for each water quality variable. Then, a non-dominating sorting genetic algorithm-based model is developed for multi-objective optimization of the water quality monitoring network. Finally, a social choice method is applied to the identified non-dominated solutions to achieve a strategy that is compromised among stakeholders. The variations of the water quality variables at different depths and different seasons are investigated. The proposed approach is illustrated for Karkheh Reservoir in Iran. The number of optimized monitoring stations is the same for all seasons (three out of 22 potential stations) using different social choice methods. The results show the appropriate performance of the proposed methodology for optimization of reservoir water quality monitoring stations.
AB - Reservoir water quality is important for water quality management downstream. A hierarchical approach is developed to present the monitoring locations within a format that satisfies the objectives of social stakeholders for making final decisions. First, a CE-QUAL-W2 model is applied to simulate water quality variables in the reservoir for a long time using a set of historic data. Second, transinformation entropy theory is used to quantify mutual information among a set of monitoring stations for each water quality variable. Then, a non-dominating sorting genetic algorithm-based model is developed for multi-objective optimization of the water quality monitoring network. Finally, a social choice method is applied to the identified non-dominated solutions to achieve a strategy that is compromised among stakeholders. The variations of the water quality variables at different depths and different seasons are investigated. The proposed approach is illustrated for Karkheh Reservoir in Iran. The number of optimized monitoring stations is the same for all seasons (three out of 22 potential stations) using different social choice methods. The results show the appropriate performance of the proposed methodology for optimization of reservoir water quality monitoring stations.
KW - CE-QUAL-W2 model
KW - NSGA-II multi-objective optimization method
KW - Reservoir monitoring network
KW - Social choice
KW - Transinformation entropy
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U2 - 10.2166/ws.2016.196
DO - 10.2166/ws.2016.196
M3 - Article
AN - SCOPUS:85026390116
SN - 1606-9749
VL - 17
SP - 966
EP - 974
JO - Water Science and Technology: Water Supply
JF - Water Science and Technology: Water Supply
IS - 4
ER -