About this Research Topic
Specifically, this Research Topic aims to provide a platform for researchers, practitioners, and policymakers to share their latest findings and insights in the application of AI to water resources and quality management, particularly within the context of climate change. We believe that by fostering collaboration and knowledge exchange, this Research Topic will significantly contribute to addressing the complex and evolving challenges in the management of water resources and quality.
1. Water Resources and Quality Monitoring: We invite contributions that explore the use of AI in monitoring water resources and quality, both through remote sensing technologies and in-situ methods. Submissions should encompass advancements in sensor technology, satellite-based monitoring, and AI-driven data analysis to enhance real-time monitoring, early warning systems, and the detection of pollutants.
2. Modeling, Forecasting, and Simulation: AI holds great potential for improving the accuracy and efficiency of hydrological and water quality modeling. Papers on AI-driven hydrological models, flood forecasting, drought prediction, and water quality simulations are encouraged. Contributions on AI-enhanced decision support systems and predictive analytics for water resources are also welcome.
3. Water Management in the Context of Climate Change: Climate change poses a significant challenge to water resources and quality. We seek articles that examine the integration of AI in adaptive water resource management, including the optimization of water distribution networks, reservoir management, and climate-resilient infrastructure planning. Additionally, contributions on AI applications in water treatment and wastewater management to address changing water quality are of high relevance.
We welcome contributions, including original research articles, comprehensive reviews, case studies, and technical notes. Specific topics include, but are not limited to:
1. Machine learning and deep learning approaches for advanced hydrological and water quality modeling.
2. AI-driven remote sensing and sensor network technologies for improved data collection and analysis.
3. Application of AI for real-time water quality monitoring, including the detection of emerging contaminants.
4. AI-enhanced decision support systems for adaptive water resource management.
5. Case studies demonstrating the successful application of AI to address climate change impacts on water resources and quality.
Keywords: Artificial Intelligence, Water Resources, Water Quality, Climate Change, Remote Sensing
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.