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Computational intelligence and optimization methods transform the way we approach sustainable water management, offering tools to address complex environmental challenges. As water resources face pressure from climate change, population growth, and industrial demand, advanced algorithms enable more efficient, data-driven decision-making. These techniques support the design of smarter distribution systems, predictive maintenance, real-time monitoring, and adaptive resource planning. By integrating computational intelligence into water management, organizations can enhance resilience, reduce waste, and ensure equitable, sustainable access to clean water. Computational Intelligence and Optimization Methods for Sustainable Water Management examines water resources management principles, machine learning applications, novel approaches to wastewater treatment, and emerging technologies for water supply, conservation, and management. It explores how modern solutions can be integrated with traditional methods to achieve sustainable and effective water management. This book covers topics such as water resources, natural disasters, and machine learning, and is a useful resource for hydraulics engineers, climatologists, academicians, researchers, and environmental scientists.