Matches in SemOpenAlex for { <https://semopenalex.org/work/W3122132020> ?p ?o ?g. }
- W3122132020 endingPage "111964" @default.
- W3122132020 startingPage "111964" @default.
- W3122132020 abstract "Coastal aquifer management (CAM) considering conjunctive optimization of pumping and injection system for seawater intrusion (SI) mitigation poses significant decision-making challenges. CAM needs to pose multiple objectives and massive decision variables to explore tradeoff strategies between the conflicting resources, economic, and environmental requirements. Here, we investigate a joint artificial injection scheme for ameliorating SI by establishing an evolutionary multi-objective decision-making framework that combines simulation-optimization (S-O) modelling with a cost-benefit analysis, and demonstrate the framework on a large-scale CAM case in Baldwin County, Alabama. First, a SI numerical model, using SEAWAT, was configured to predict the vulnerable region as an SI encroachment area with the scenarios of minimum and maximum pumping capacity. As a result, a smaller number of candidate sites were selected in the SI encroachment area for implementing groundwater injection to avoid the computationally infeasible SI optimization with an inordinate number of injection related decision variables. Second, the effective S-O methodology of niched Pareto tabu search combined with a genetic algorithm (NPTSGA), which considers the moving-well option, was applied to discover optimal pumping/injection (P/I) strategies (including P/I rates and injection well locations) between three conflicting management objectives under complicated SI constraints. Third, for practical operation of the P/I schemes, a cost-benefit analysis provides judgment criteria to allow decision-makers to implement more sustainable P/I strategies to capture the different realistic preferences. The implementation of three extreme optimization solutions for the case study indicates that, compared to the initial unoptimized scheme, a maximum increase of a factor of 3 in groundwater extraction rates, a maximum reduction of 17% in extent of SI, and a maximum 82.3 million US dollars in comprehensive benefits are specifically achieved by conjunctive P/I optimization. The robustness in the decision alternatives attributed to the uncertainty in physical parameters of hydraulic conductivity was discovered through global sensitivity analysis. The proposed framework provides a decision support system for multi-objective CAM with combined pumping control and engineering measures for SI mitigation." @default.
- W3122132020 created "2021-02-01" @default.
- W3122132020 creator A5001511426 @default.
- W3122132020 creator A5011160537 @default.
- W3122132020 creator A5013075319 @default.
- W3122132020 creator A5016744162 @default.
- W3122132020 creator A5019066030 @default.
- W3122132020 creator A5031544034 @default.
- W3122132020 creator A5036442264 @default.
- W3122132020 date "2021-03-01" @default.
- W3122132020 modified "2023-10-17" @default.
- W3122132020 title "A conjunctive management framework for the optimal design of pumping and injection strategies to mitigate seawater intrusion" @default.
- W3122132020 cites W1535712589 @default.
- W3122132020 cites W1961031542 @default.
- W3122132020 cites W1965772894 @default.
- W3122132020 cites W1969431983 @default.
- W3122132020 cites W1971130396 @default.
- W3122132020 cites W1971906047 @default.
- W3122132020 cites W1973056138 @default.
- W3122132020 cites W1992169317 @default.
- W3122132020 cites W1996174788 @default.
- W3122132020 cites W2013926627 @default.
- W3122132020 cites W2016120708 @default.
- W3122132020 cites W2028542434 @default.
- W3122132020 cites W2029397954 @default.
- W3122132020 cites W2037266505 @default.
- W3122132020 cites W2055273642 @default.
- W3122132020 cites W2058338230 @default.
- W3122132020 cites W2062497590 @default.
- W3122132020 cites W2069843249 @default.
- W3122132020 cites W2078812770 @default.
- W3122132020 cites W2086244540 @default.
- W3122132020 cites W2086838942 @default.
- W3122132020 cites W2087177845 @default.
- W3122132020 cites W2110842075 @default.
- W3122132020 cites W2126105956 @default.
- W3122132020 cites W2128682749 @default.
- W3122132020 cites W2142642554 @default.
- W3122132020 cites W2151233584 @default.
- W3122132020 cites W2152885039 @default.
- W3122132020 cites W2171867603 @default.
- W3122132020 cites W223083778 @default.
- W3122132020 cites W2361455957 @default.
- W3122132020 cites W2402327203 @default.
- W3122132020 cites W2591554033 @default.
- W3122132020 cites W2592725336 @default.
- W3122132020 cites W2606666270 @default.
- W3122132020 cites W2617623833 @default.
- W3122132020 cites W2762252288 @default.
- W3122132020 cites W2781545775 @default.
- W3122132020 cites W2789921669 @default.
- W3122132020 cites W2794524994 @default.
- W3122132020 cites W2890692322 @default.
- W3122132020 cites W2898511024 @default.
- W3122132020 cites W2953145625 @default.
- W3122132020 cites W2963533171 @default.
- W3122132020 cites W2997500243 @default.
- W3122132020 cites W3002000844 @default.
- W3122132020 cites W3045305483 @default.
- W3122132020 cites W2023709822 @default.
- W3122132020 doi "https://doi.org/10.1016/j.jenvman.2021.111964" @default.
- W3122132020 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33485034" @default.
- W3122132020 hasPublicationYear "2021" @default.
- W3122132020 type Work @default.
- W3122132020 sameAs 3122132020 @default.
- W3122132020 citedByCount "23" @default.
- W3122132020 countsByYear W31221320202021 @default.
- W3122132020 countsByYear W31221320202022 @default.
- W3122132020 countsByYear W31221320202023 @default.
- W3122132020 crossrefType "journal-article" @default.
- W3122132020 hasAuthorship W3122132020A5001511426 @default.
- W3122132020 hasAuthorship W3122132020A5011160537 @default.
- W3122132020 hasAuthorship W3122132020A5013075319 @default.
- W3122132020 hasAuthorship W3122132020A5016744162 @default.
- W3122132020 hasAuthorship W3122132020A5019066030 @default.
- W3122132020 hasAuthorship W3122132020A5031544034 @default.
- W3122132020 hasAuthorship W3122132020A5036442264 @default.
- W3122132020 hasConcept C107826830 @default.
- W3122132020 hasConcept C111368507 @default.
- W3122132020 hasConcept C127313418 @default.
- W3122132020 hasConcept C158251709 @default.
- W3122132020 hasConcept C17409809 @default.
- W3122132020 hasConcept C187320778 @default.
- W3122132020 hasConcept C197248824 @default.
- W3122132020 hasConcept C2991897412 @default.
- W3122132020 hasConcept C39432304 @default.
- W3122132020 hasConcept C41008148 @default.
- W3122132020 hasConcept C524765639 @default.
- W3122132020 hasConcept C75622301 @default.
- W3122132020 hasConcept C76177295 @default.
- W3122132020 hasConcept C78762247 @default.
- W3122132020 hasConceptScore W3122132020C107826830 @default.
- W3122132020 hasConceptScore W3122132020C111368507 @default.
- W3122132020 hasConceptScore W3122132020C127313418 @default.
- W3122132020 hasConceptScore W3122132020C158251709 @default.
- W3122132020 hasConceptScore W3122132020C17409809 @default.
- W3122132020 hasConceptScore W3122132020C187320778 @default.
- W3122132020 hasConceptScore W3122132020C197248824 @default.