Hydrological Insights : Synergizing Groundwater Models, Remote Sensing, and AI for Water Sustainability

Hashemi, Hossein (EDT)/ Kumar, Amit (EDT)/ Kumar, Krishna (EDT)

Elsevier - Health Sciences Division（2025/12発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 320 p.
• 言語 ENG
• 商品コード 9780443363948

Full Description

Hydrological Insights: Synergizing Groundwater Models, Remote Sensing, and AI for Water Sustainability offers an in-depth exploration of hydrological modeling and its cutting-edge advancements, presented across six comprehensive sections. Part I establishes the foundational principles and methodologies of hydrological modeling, while Part II delves into sophisticated techniques and tools that enhance the accuracy and efficiency of hydrological studies. Part III highlights the powerful integration of remote sensing and artificial intelligence, showcasing how these technologies revolutionize modern hydrological practices.

Part IV focuses on environmental impact assessment and management strategies, outlining effective methods for sustainable water resource management. Part V covers the latest advancements in remote sensing and machine learning, emphasizing their pivotal role in contemporary hydrology. Finally, Part VI presents real-world case studies and future directions, offering practical insights and forward-looking perspectives. With meticulously crafted chapters that combine theoretical foundations with practical applications, this book is an essential resource for students, researchers, and professionals seeking to advance their understanding of hydrology through the integration of remote sensing and AI.

Contents

Part I: Foundations of Hydrological Modeling
1. Introduction to Data-Driven Groundwater Modeling: Methods, Applications & Challenges
2. InSAR-Based Estimation of Head and Storage Changes: Numerical Models and Data Driven Techniques
3. Surfacewater Flow as a Mitigation Measure for Land Subsidence Mitigation in Rural and Urban Areas
4. Hydro-Meteorological Droughts: Patterns, Trends, and the Role of Accumulation Periods on Groundwater Condition

Part II: Advanced Techniques in Hydrological Studies
5. Automated Hydrological Variable Estimation: Novel Approaches and Optimization Algorithms
6. Spatiotemporal Variability of Hydrometeorological Parametrs: Insights from River Basin Analysis
7. Monitoring Carbon Exchange in Wetlands and Peatlands Using InSAR-Based Methods
8. Impact of Drinking and Sanitary Water Separation on Drinking Water Quality: Groundwater Quality Mapping

Part III: Integration of Remote Sensing and Artificial Intelligence in Hydrology
9. InSAR-AI-Based Approach for Groundwater Level Prediction in Arid Regions
10. Spatiotemporal Variation of Environmental Hazards: Remote Sensing and AI Applications
11. Detecting Changes in Global Satellite-Based Hydrological Observations using AI Techniques
12. Satellite Monitoring of Infrastructure using Interferometric Synthetic Aperture Radar (InSAR)

Part IV: Environmental Impact Assessment and Management Strategies
13. Quantitative and Qualitative Assessment of Streamflow Variation: Climate vs. Human Impact
14. Assessing Contaminated Groundwater Sites in Industrial Areas with Limited Data Availability
15. Flood Spreading Project Suitability Mapping: Water Resources Management using Machine Learning Algorithms

Part V: Advances in Remote Sensing and Machine Learning
16. Advanced Machine Learning Algorithms for Assessing Groundwater Potential using Remote Sensing-Derived Data
17. Extreme Gradient Boosting and Random Forest Algorithms for Assessing Groundwater Spring Potential using DEM-Derived Factors
18. Remote Sensing Techniques and Machine Learning Algorithms in Groundwater Vulnerability Mapping

Part VI: Case Studies and Future Directions
19. Evaluation of Weather Radar Systems for Operational Use in Hydrological Studies
20. Towards Intelligent Assessment of Groundwater Resources: Trends, Challenges, and Future Directions