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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xiii 7. Preface - p. xvii 8. Chapter 1. Water scarcity crisis: overview of challenges and solutions - p. 1 9. Chapter 2. Assessing dust storm risks in water-scarce regions: a machine learning approach - p. 13 10. Chapter 3. An integrated machine learning framework for flood susceptibility assessment - p. 25 11. Chapter 4. Application of Gravity Recovery and Climate Experiment satellite data to monitor groundwater storage and scarcity - p. 65 12. Chapter 5. Discover the world of drought and water scarcity indices: insights for a sustainable future - p. 83 13. Chapter 6. Exploring the interplay of water scarcity and dust emissions - p. 101 14. Chapter 7. Groundwater potential mapping: a way for mitigating water scarcity - p. 109 15. Chapter 8. The role of climatic and anthropogenic factors in drying up of lakes - p. 121 16. Chapter 9. Integrated assessment of the vulnerability of socio-ecological coupled systems of coastal areas to drought - p. 139 17. Chapter 10. The effect of climatic and human factors on hydrological drought - p. 155 18. Chapter 11. Machine learning-driven land subsidence prediction using radar imagery - p. 175 19. Chapter 12. Remote sensing for assessing ecosystem drought impact - p. 205 20. Chapter 13. Ground deformation and groundwater dynamics: the role of interferometric synthetic aperture radar analysis in confined aquifer systems - p. 223 21. Chapter 14. Drought mitigation and management measures - p. 239 22. Chapter 15. Technological innovations in water conservation: navigating drought and water scarcity - p. 255 23. Chapter 16. Vegetation dynamics as a response to meteorological drought - p. 269 24. Chapter 17. Machine learning in groundwater drought forecasting: a bibliometric perspective - p. 293 25. Chapter 18. Decoding the water crisis in Iran: policy challenges and resource constraints - p. 305 26. Chapter 19. Human effects of dam construction on the downstream ecosystem - p. 325 27. Chapter 20. Climatic influences on vegetation degradation and soil moisture - p. 341 28. Chapter 21. Holistic water resource management under scarcity: integrating policy frameworks with practical solutions - p. 357 29. Index - p. 375
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.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iv 6. List of contributors - p. xiii 7. Preface - p. xvii 8. Chapter 1. Water scarcity crisis: overview of challenges and solutions - p. 1 9. Chapter 2. Assessing dust storm risks in water-scarce regions: a machine learning approach - p. 13 10. Chapter 3. An integrated machine learning framework for flood susceptibility assessment - p. 25 11. Chapter 4. Application of Gravity Recovery and Climate Experiment satellite data to monitor groundwater storage and scarcity - p. 65 12. Chapter 5. Discover the world of drought and water scarcity indices: insights for a sustainable future - p. 83 13. Chapter 6. Exploring the interplay of water scarcity and dust emissions - p. 101 14. Chapter 7. Groundwater potential mapping: a way for mitigating water scarcity - p. 109 15. Chapter 8. The role of climatic and anthropogenic factors in drying up of lakes - p. 121 16. Chapter 9. Integrated assessment of the vulnerability of socio-ecological coupled systems of coastal areas to drought - p. 139 17. Chapter 10. The effect of climatic and human factors on hydrological drought - p. 155 18. Chapter 11. Machine learning-driven land subsidence prediction using radar imagery - p. 175 19. Chapter 12. Remote sensing for assessing ecosystem drought impact - p. 205 20. Chapter 13. Ground deformation and groundwater dynamics: the role of interferometric synthetic aperture radar analysis in confined aquifer systems - p. 223 21. Chapter 14. Drought mitigation and management measures - p. 239 22. Chapter 15. Technological innovations in water conservation: navigating drought and water scarcity - p. 255 23. Chapter 16. Vegetation dynamics as a response to meteorological drought - p. 269 24. Chapter 17. Machine learning in groundwater drought forecasting: a bibliometric perspective - p. 293 25. Chapter 18. Decoding the water crisis in Iran: policy challenges and resource constraints - p. 305 26. Chapter 19. Human effects of dam construction on the downstream ecosystem - p. 325 27. Chapter 20. Climatic influences on vegetation degradation and soil moisture - p. 341 28. Chapter 21. Holistic water resource management under scarcity: integrating policy frameworks with practical solutions - p. 357 29. Index - p. 375
