Design Development of a Novel Sour Water Stripper

The major aims of this book, “Watershed Water Environment and Hydrology under the Influence of Anthropogenic and Natural Processes”, are to focus on innovative/new ideas on the watershed water environment from different perspectives across the field; distinguish the evolution of watershed water ecological and environmental quality; clarify the biogeochemical cycling of elements or pollutants; identify and quantify the sources of pollutants; and assess the ecological risk and human health risk of pollutants in the water environment at different watershed scales. In particular, eight peer-reviewed articles were collected, mainly reporting the hydrochemistry-based watershed weathering processes and their environmental implications, trace elements and their risks, and the nutrients cycle in river–reservoir systems. Overall, these papers contribute to several aspects of the watershed water environment and are valuable for river water resource protection and management.

This review presents the developments in artificial intelligence technologies for environmental pollution controls. A number of AI approaches, which start with the reliable mapping of nonlinear behavior between inputs and outputs in chemical and biological processes in  terms of prediction models to the emerging optimization and control algorithms that study the  pollutants removal processes and intelligent control systems, have been developed for environmental clean-ups. The characteristics, advantages and limitations of AI methods, including single and hybrid AI methods, were overviewed. Hybrid AI methods exhibited synergistic effects, but with computational heaviness.

Water resources management should be assessed under climate change conditions, as historic data cannot replicate future climatic conditions. - Climate change impacts on water resources are bound to affect all water uses, i.e., irrigated agriculture, domestic and industrial water supply, hydropower generation, and environmental flow (of streams and rivers) and water level (of lakes). - Bottom-up approaches, i.e., the forcing of hydrologic simulation models with climate change models’ outputs, are the most common engineering practices and considered as climate-resilient water management approaches. - Hydrologic simulations forced by climate change scenarios derived from regional climate models (RCMs) can provide accurate assessments of the future water regime at basin scales.