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Artificial Intelligence, Optimization, and Modeling Techniques in Water Resource Management: Interconnections and
Hoda S Razavi1, A Pouyan Nejadhashemi1,2, Kalyanmoy Deb3
1Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, Michigan, USA.
Summary
This review examines water management elements, finding that advanced models and AI show promise but face data and scalability challenges. Integrating these technologies can improve water quality protection and resource recovery.
Area of Science:
- Environmental Science
- Water Resource Management
- Computational Hydrology
Background:
- Effective water management relies on integrating diverse elements like watershed models, AI, and decision support systems.
- Existing frameworks often face challenges in scalability and data consistency, limiting optimal water resource utilization.
Purpose of the Study:
- To explore interrelationships among six key water management elements: watershed models, optimization algorithms, artificial intelligence, surrogate models, monitoring, and decision support systems.
- To identify potential synergies for enhanced water management practices and improved water quality protection.
Main Methods:
- Systematic literature review adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
- Identification, screening, eligibility assessment, and selection of relevant studies with cross-referencing.
Main Results:
- Advanced watershed models provide insights but struggle with spatial-temporal variations and scalability.
- Machine learning approaches show potential but are limited by data insufficiencies and inconsistencies.
- Interconnections between elements are established, but unexplored synergies require further investigation.
Conclusions:
- Integrating emerging technologies with established water management frameworks is crucial for advancing water quality protection.
- Addressing data limitations and scalability challenges is essential for maximizing the benefits of AI and advanced modeling in water management.
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