Water Scarcity Management
Toward the Application of Artificial Intelligence and Earth Observation Data
- 1st Edition - November 1, 2025
- Latest edition
- Editors: Omid Rahmati, Assefa M. Melesse, Amir Naghibi
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 2 6 7 2 2 - 2
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 2 6 7 2 3 - 9
Drought and the condition of water scarcity lead to several socio-economic, social and environmental impacts. Whatever the approaches of drought management, policymakers and… Read more
Drought and the condition of water scarcity lead to several socio-economic, social and environmental impacts. Whatever the approaches of drought management, policymakers and planners require novel methods to analyze data and model drought processes and its connection with water scarcity. In recent years, artificial intelligence-based and earth observation approaches have been progressively developed and applied in domain of water-related disasters. The target of this book is to present new advances and achievements in the fields of drought monitoring, analyzing, and modeling using artificial intelligence algorithms (e.g., machine learning, deep learning, etc.), statistical indices, and a diverse range of satellite remote sensing and geo-spatial data sets. Water Scarcity Management: Towards the Application of Artificial Intelligence and Earth Observation Data will help students gain knowledge on drought prediction using new free-access earth observation data and machine learning models. It will also guide scientists, researchers, and urban planners with the monitoring of water resources and key elements of hydrological cycle.
- Covers application of a range of diverse artificial intelligence algorithms for spatial modeling of drought susceptibility
- Includes real case studies from large geographical areas
- Offers earth observation satellite data for spatio-temporal analysis of drought and water scarcity
- Combines geo-environmental and topo-hydrological factors with drought and water scarcity issues
Academics and graduate students in the field of drought and water resources management learning about new approaches based on artificial intelligence and satellite remote sensing data
1. Water scarcity crisis: overview of challenges and solutions
2. Assessing Dust Storm Risks in Water-Scarce Regions: A Machine Learning Approach
3. An Integrated Machine Learning Framework for Flood Susceptibility Assessment
4. Application of GRACE satellite data to monitor groundwater storage and scarcity
5. Discover the world of drought and water scarcity indices: insights for a sustainable future
6. Exploring the Interplay of Water Scarcity and Dust Emissions
7. Groundwater potential mapping: a way for mitigating water scarcity
8. The role of climatic and anthropogenic factors in drying up of lakes
9. Integrated assessment of the vulnerability of socio-ecological coupled systems of coastal areas to drought
10. The effect of climatic and human factors on hydrological drought
11. Machine Learning-Driven Land Subsidence Prediction Using Radar Imagery
12. Remote Sensing for Assessing Ecosystem Drought Impact
13. Ground Subsidence and Groundwater Dynamics: the Role of InSAR Analysis in Confined Aquifer Systems
14. Drought mitigation and management measures
15. Technological Innovations in Water Conservation: Navigating Drought and Water Scarcity
16. Vegetation dynamics as a response to meteorological drought
17. Machine Learning in Groundwater Drought Forecasting: A Bibliometric Perspective
18. Decoding the Water Crisis in Iran: Policy Challenges and Resource Constraints
19. Human effects of dam construction on the downstream ecosystem
20. Climatic influences on vegetation degradation and soil moisture
21. Holistic Water Resource Management in Scarcity: Policy Frameworks and Practical Solutions
2. Assessing Dust Storm Risks in Water-Scarce Regions: A Machine Learning Approach
3. An Integrated Machine Learning Framework for Flood Susceptibility Assessment
4. Application of GRACE satellite data to monitor groundwater storage and scarcity
5. Discover the world of drought and water scarcity indices: insights for a sustainable future
6. Exploring the Interplay of Water Scarcity and Dust Emissions
7. Groundwater potential mapping: a way for mitigating water scarcity
8. The role of climatic and anthropogenic factors in drying up of lakes
9. Integrated assessment of the vulnerability of socio-ecological coupled systems of coastal areas to drought
10. The effect of climatic and human factors on hydrological drought
11. Machine Learning-Driven Land Subsidence Prediction Using Radar Imagery
12. Remote Sensing for Assessing Ecosystem Drought Impact
13. Ground Subsidence and Groundwater Dynamics: the Role of InSAR Analysis in Confined Aquifer Systems
14. Drought mitigation and management measures
15. Technological Innovations in Water Conservation: Navigating Drought and Water Scarcity
16. Vegetation dynamics as a response to meteorological drought
17. Machine Learning in Groundwater Drought Forecasting: A Bibliometric Perspective
18. Decoding the Water Crisis in Iran: Policy Challenges and Resource Constraints
19. Human effects of dam construction on the downstream ecosystem
20. Climatic influences on vegetation degradation and soil moisture
21. Holistic Water Resource Management in Scarcity: Policy Frameworks and Practical Solutions
- Edition: 1
- Latest edition
- Published: November 1, 2025
- Language: English
OR
Omid Rahmati
Dr. Omid Rahmati is a geo-environmental researcher and Assistant Professor at the Agricultural Research, Education, and Extension Organization (AREEO) in Iran. His research focuses on applying machine learning models to natural hazard mitigation and watershed management. He has authored and co-authored over 70 articles in international peer-reviewed journals, as well as several books and book chapters. Dr. Rahmati’s publications have been cited more than 12,500 times (H-index: 56), and he has been recognized as a Highly Cited Researcher. He is ranked among the World’s Top 1% of Scientists by Web of Science (Clarivate, 2021–2022) and listed in Stanford University’s “World’s Top 2% Scientists” from 2021 to 2025. His publications over the past decade reflect a broad and significant influence in his field.
Affiliations and expertise
Department of Watershed Management, Kurdistan Agricultural and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization, IranAM
Assefa M. Melesse
Dr. Assefa M. Melesse is a Distinguished University Professor of Water Resources Engineering at Florida International University. He earned his ME (2000) and PhD (2002) from the University of Florida in Agricultural Engineering. His areas of research and experience include climate change impact modeling, watershed modeling, ecohydrology, sediment transport, surface and groundwater interactions modeling, water–energy–carbon fluxes coupling and simulations, remote sensing hydrology, river basin management, and land cover change detection and scaling. Dr. Melesse is a registered Professional Engineer (PE), Board Certified Enviromental Engineer (BCEE) and also a Board Certified Water Resources Engineer (BC.WRE) with over 30 years of teaching and research experience, and has authored/edited 11 books, over 230 journal articles, and over 100 book chapters.
Affiliations and expertise
Distinguished University Professor of Water Resources Engineering, Florida International University, Miami, FL, USAAN
Amir Naghibi
Dr. Amir Naghibi is an Assistant Professor in the Division of Water Resources Engineering and the Center for Advanced Middle Eastern Studies at Lund University, Lund, Sweden. His work sits at the intersection of artificial intelligence (AI), computer science, remote sensing, and environmental systems modeling, addressing the water-climate-food-energy nexus. He develops advanced AI-driven decision support systems to address complex challenges in water resources, agriculture, climate adaptation, and natural hazard management. He has published more than 50 papers in peer-reviewed journals with over 6,000 citations and has been listed in Stanford University’s World’s Top 2% Scientists from 2020 to 2025, demonstrating his broad and significant scientific influence.
Affiliations and expertise
Assistant Professor, Water Resources Engineering and Center for Advanced Middle Eastern Studies, Lund University, Sweden