Hydrological Insights

Part I: Foundations of Hydrological Modeling<br>1. Introduction to Data-Driven Groundwater Modeling: Methods, Applications & Challenges<br>2. InSAR-Based Estimation of Head and Storage Changes: Numerical Models and Data Driven Techniques<br>3. Surfacewater Flow as a Mitigation Measure for Land Subsidence Mitigation in Rural and Urban Areas<br>4. Hydro-Meteorological Droughts: Patterns, Trends, and the Role of Accumulation Periods on Groundwater Condition<br><br>Part II: Advanced Techniques in Hydrological Studies<br>5. Automated Hydrological Variable Estimation: Novel Approaches and Optimization Algorithms<br>6. Spatiotemporal Variability of Hydrometeorological Parametrs: Insights from River Basin Analysis<br>7. Monitoring Carbon Exchange in Wetlands and Peatlands Using InSAR-Based Methods<br>8. Impact of Drinking and Sanitary Water Separation on Drinking Water Quality: Groundwater Quality Mapping<br><br>Part III: Integration of Remote Sensing and Artificial Intelligence in Hydrology<br>9. InSAR-AI-Based Approach for Groundwater Level Prediction in Arid Regions<br>10. Spatiotemporal Variation of Environmental Hazards: Remote Sensing and AI Applications<br>11. Detecting Changes in Global Satellite-Based Hydrological Observations using AI Techniques<br>12. Satellite Monitoring of Infrastructure using Interferometric Synthetic Aperture Radar (InSAR)<br><br>Part IV: Environmental Impact Assessment and Management Strategies<br>13. Quantitative and Qualitative Assessment of Streamflow Variation: Climate vs. Human Impact<br>14. Assessing Contaminated Groundwater Sites in Industrial Areas with Limited Data Availability<br>15. Flood Spreading Project Suitability Mapping: Water Resources Management using Machine Learning Algorithms<br><br>Part V: Advances in Remote Sensing and Machine Learning<br>16. Advanced Machine Learning Algorithms for Assessing Groundwater Potential using Remote Sensing-Derived Data<br>17. Extreme Gradient Boosting and Random Forest Algorithms for Assessing Groundwater Spring Potential using DEM-Derived Factors<br>18. Remote Sensing Techniques and Machine Learning Algorithms in Groundwater Vulnerability Mapping<br><br>Part VI: Case Studies and Future Directions<br>19. Evaluation of Weather Radar Systems for Operational Use in Hydrological Studies<br>20. Towards Intelligent Assessment of Groundwater Resources: Trends, Challenges, and Future Directions