Multi-Objective Optimization for Sustainable Groundwater Management
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrogeology".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 96
Special Issue Editors
Interests: hydrogeology; groundwater; remote sensing and GIS; machine learning; natural resource management; geohazard; engineering geology
Special Issue Information
Dear Colleagues,
Groundwater resources face escalating challenges due to over-extraction, climate variability, pollution, and competing socio-economic demands. Addressing these complex and interrelated issues necessitates advanced decision-support tools that evaluate trade-offs and synergies among multiple management goals. Multi-objective optimization (MOO) has emerged as an effective means to tackling these challenges as it can simultaneously optimize conflicting objectives—such as maximizing groundwater availability, ensuring water quality, minimizing operational costs, and sustaining ecological integrity.
This Special Issue aims to showcase cutting-edge research on the application and advancement of multi-objective optimization techniques in groundwater management. We welcome high-quality contributions that integrate MOO with numerical groundwater models, hydroinformatics, geospatial tools, and machine learning methods. Topics may include—but are not limited to—conjunctive surface–groundwater use, aquifer storage optimization, contaminant remediation, water allocation under uncertainty, and adaptive management under climate change.
We particularly encourage the submission of interdisciplinary studies that couple hydrological science with computational intelligence and policy frameworks. Our goal is to provide actionable insights and innovative methodologies that enhance the resilience and sustainability of groundwater systems from across the world.
Dr. Shankar Karuppannan
Dr. Nafyad Serre Kawo
Guest Editors
Manuscript Submission Information
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Keywords
- multi-objective optimization
- groundwater management
- sustainable water resources
- decision support systems
- aquifer modeling
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