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Optimizing Water Resource Management for Sustainable Development
Abstract
This paper explores the optimization of water resource management for sustainable development through AI-driven engineering. Through case studies and research insights, it investigates how artificial intelligence is revolutionizing traditional water management practices, including water supply, wastewater treatment, and watershed management. The study highlights the application of AI techniques such as hydroinformatics, predictive modeling, and optimization algorithms in enhancing water efficiency, improving water quality, and mitigating water-related risks. Additionally, it discusses the integration of AI with sensor networks, remote sensing, and decision support systems to enable real-time monitoring, adaptive control, and integrated water resource management. The paper also addresses challenges such as data scarcity, institutional capacity, and stakeholder engagement in the deployment of AI-driven engineering solutions in water management. It emphasizes the importance of cross-sectoral collaboration, regulatory frameworks, and community participation in leveraging AI's potential to ensure equitable access to clean water and promote sustainable water use.
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References
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