This book represents a seminal collection of advanced research, novel methodologies, and transformative practices within the domains of water resources engineering, hydraulic engineering, and hydrology, with a strong emphasis on the integration of artificial intelligence and machine learning (AI/ML) in civil engineering.
This book embodies the progressive vision and interdisciplinary dialogue of a global academic and professional community committed to revolutionizing water infrastructure and management systems for a resilient and sustainable future. The compendium explores contemporary issues and scientific breakthroughs across a diverse range of topics such as hydrologic modeling, flood forecasting and mitigation, watershed management, groundwater assessment, climate-resilient water infrastructure, and urban storm water systems. It offers comprehensive insights into the design and optimization of hydraulic structures, sediment transport dynamics, erosion control, river engineering, and eco-hydraulics. Special attention is given to sustainable water resource planning, water quality modeling, and integrated water management strategies, reflecting the urgent need for adaptive solutions in the face of climate change and urban expansion.
A significant dimension of this volume is the exploration of AI/ML-driven approaches in civil and water resources engineering. Contributions demonstrate how machine learning algorithms, deep learning models, and data-driven techniques are revolutionizing flood prediction, rainfall-runoff modeling, real-time monitoring, water distribution networks, and decision support systems. These innovations enable more accurate forecasting, enhanced system efficiency, and informed policy making. Serving as an essential reference for researchers, academicians, industry professionals, and policymakers, this book offers a deep dive into state-of-the-art technologies and sustainable practices shaping the next generation of water infrastructure. The breadth and depth of its contributions provide actionable knowledge and strategic insights, fostering a sustainable, data-smart approach to water and hydraulic systems in a rapidly evolving environmental and technological landscape.
