Providing an extensive comparative and international study of water innovations and the issues that arise in their implementation, David Lewis Feldman analyses the technical, economic, health and environmental impacts of water innovations and their policy implications. Discussing desalination, rainwater harvesting, wastewater reuse, and demand-side innovations as well as emerging cyber-infrastructure issues, The Governance of Water Innovations analyses the historical and contemporary challenges involved in water innovations. With a global reach, exploring water innovations across The Americas, Asia, Australia and Europe, chapters consider potential areas of contention involving land use, aesthetics, recreational impacts, user costs, and environmental quality. Illuminating the importance of these challenges and determining the most effective and equitable ways of meeting them, Feldman advises how innovations should be deployed, governed and implemented democratically in ways that harbour public acceptance, trust, and engagement for a water resilient future. A comprehensive study of the governance of water innovations, this book will prove invaluable to students and scholars of public policy, environmental and water studies and geopolitics. With its pioneering analysis of adaptive governance, it will also prove an essential reference guide to practitioners, professionals and policymakers working in water governance and management, including water agency officials and water resource legislators.

Authoritative reference on the state of the art in the field with additional coverage of important foundational concepts Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning presents cutting-edge research advances in the rapidly growing areas in optical and RF electromagnetic device modeling, simulation, and inverse-design. The text provides a comprehensive treatment of the field on subjects ranging from fundamental theoretical principles and new technological developments to state-of-the-art device design, as well as examples encompassing a wide range of related sub-areas. The content of the book covers all-dielectric and metallodielectric optical metasurface deep learning-accelerated inverse-design, deep neural networks for inverse scattering, applications of deep learning for advanced antenna design, and other related topics. To aid in reader comprehension, each chapter contains 10-15 illustrations, including prototype photos, line graphs, and electric field plots. Contributed to by leading research groups in the field, sample topics covered in Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning include: Optical and photonic design, including generative machine learning for photonic design and inverse design of electromagnetic systems RF and antenna design, including artificial neural networks for parametric electromagnetic modeling and optimization and analysis of uniform and non-uniform antenna arrays Inverse scattering, target classification, and other applications, including deep learning for high contrast inverse scattering of electrically large structures Advances in Electromagnetics Empowered by Artificial Intelligence and Deep Learning is a must-have resource on the topic for university faculty, graduate students, and engineers within the fields of electromagnetics, wireless communications, antenna/RF design, and photonics, as well as researchers at large defense contractors and government laboratories.