Artificial Intelligence-Driven Strategies for the Conservation of Surface Water Resources

This book is aimed at exploring the integration of AI-based techniques with sustainable water management which is one of the most important environmental issues of the 21st century. Critical factors including climate change, rapid urbanization, and exponential population increase have created much pressure on the surface water bodies. Moreover, traditional methods of water quality monitoring and their conservation practices are not enough to address this sufficiently. This book provides an interdisciplinary approach by incorporating artificial intelligence, data science, and environmental science for enhancing efficiency and precision for surface water resource management. Further, the book also examines how advanced AI models including machine learning, deep learning, and predictive analytics can be applied to hydrological studies, water quality indexing, as well as ecosystem monitoring and restoration. This book also explores the possibilities of real-time surface water monitoring for developing strong decision support systems via satellite imagery, remote sensing, and Internet of Things (IoT) technologies. The chapters cover practical approaches, case studies, and policy inferences. The book fosters innovative strategies in water conservation through using AI, not only as a computational tool, but as a catalyst. Therefore, this book offers a futuristic vision for conserving surface water ecosystems to ensure water equity in distribution and to adopt resilience in the era of global environmental change. It is useful for researchers, environmental planners, policymakers, and technologists working in water conservation and environmental sustainability.