Machine Learning Applications in Water and Energy Ecosystems

This book explores various aspects of the impact of climate change on natural ecosystems and energy systems, emphasizing the interactions between climatic parameters and other factors. It investigates the interactions among various climatic parameters and their direct and indirect impacts on natural ecosystems, human health, and socio-economic sectors in both developing and developed nations. Essential climatic parameters such as sunshine duration, rainfall, temperature, wind speed, and relative humidity are considered, as they are vital in shaping the stability and functionality of ecosystems.The book is specifically focused on the impact of climatic change on marine ecosystems, freshwater ecosystems, human health, energy systems, recent trends in management and mitigation measures of climatic impacts, and opportunities to enhance resilience against climate change impacts. It introduces modern scientific methods for environmental management through the integration of the latest machine learning applications.This book is a valuable resource for scientists and experts in NGOs and policymakers in the water and energy ecosystem fields, providing guidance on data storage and handling across both domains. Students and researchers in environmental science and engineering will also find it beneficial.

Balamurugan Paneerselvam is a researcher and academic in civil and environmental engineering. His work focuses on areas such as climate change impacts on groundwater systems, water quality assessment, human health risk analysis, and sustainable water resource management. He has published in peer-reviewed journals on topics including groundwater contamination, air quality modeling, sediment analysis, and wastewater treatment. His research also explores emerging themes such as the water-food-energy nexus and nature-based solutions for environmental sustainability. He also contributes to the academic community through roles such as editorial board member, guest editor, and reviewer for international journals. Nagavinothini Ravichandran is a researcher in offshore structural engineering. Her work focuses on the dynamic behavior of offshore structures under extreme environmental conditions such as waves, wind, and seismic forces. In recent years, her research has also addressed areas including machine learning-based structural analysis, climate change impacts on water systems, and sustainable energy solutions such as floating photovoltaic systems. Her research integrates computational methods, data-driven modeling, and structural engineering principles to solve complex real-world problems. She has received academic awards, including recognition for research publications and academic performance. She has also delivered keynote talks and engaged in collaborative research activities with international partners.