Target Audience

Hydrologists, water resource engineers, remote sensing specialists, GIS analysts, computational modelers, PhD candidates, and environmental agencies working in arid and semi-arid regions.

Description

This volume speaks to those who build the models, interpret the data, and make the predictions that guide water policy. Arid deltas face threats as complex as they are urgent. Climate change shifts precipitation patterns. Sea-level rise pushes saltwater into freshwater aquifers. Upstream dams alter flow regimes that persisted for millennia. Population growth multiplies demand. These aren't problems solved by guesswork. They require models simulating not just now, but different scenarios and policies.

This book provides those tools. It establishes the modeling context: physical processes, data requirements, and challenges unique to arid deltas. Then it moves systematically through the digital toolkit, remote sensing to extract water quality from satellite imagery and detect shoreline changes, GIS for groundwater vulnerability assessment, hydrodynamic and groundwater models for contaminant transport. Machine learning forecasts salinity intrusion and predicts water quality from sparse data. Case studies from the Nile, Indus, and Colorado deltas tie it together. The volume concludes with decision support systems, real-time sensor networks, and digital twins that simulate entire delta systems.

Table of Contents

Part I: Foundations of Delta Modeling

Chapter 1: The Role of Digital Modeling in Arid Delta Water Security

Chapter 2: Key Physical Processes and Data Requirements for Delta Modeling      (Booked)

Chapter 3: Climate Scenarios and Their Implications for Delta Hydrology

Part II: Remote Sensing and GIS for Delta Monitoring

Chapter 4: Remote Sensing of Delta Water Bodies: Optical and Radar Approaches

Chapter 5: GIS-Based Groundwater Vulnerability and Recharge Assessment

Chapter 6: Multi-Criteria Decision Analysis for Water Allocation

Part III: Hydrodynamic and Groundwater Modeling

Chapter 7: Modeling Surface Water Flow and Tidal Dynamics in Deltas

Chapter 8: Groundwater Flow and Saltwater Intrusion Simulation        (Booked)

Chapter 9: Coupled Surface Water-Groundwater and Contaminant Transport Models    (Booked)

Chapter 10: Model Calibration, Validation, and Uncertainty Analysis  

Part IV: Machine Learning and AI Applications

Chapter 11: Machine Learning for Hydrological Forecasting and Water Quality Prediction     (Booked)

Part V: Case Studies and Future Directions

Chapter 12: Integrated Case Studies: Nile, Indus, and Colorado Deltas

Chapter 13: Decision Support Systems and Emerging Technologies: From Sensor Networks to Digital Twins        (Booked)

📅 IMPORTANT DATES

📝 SUBMISSION GUIDELINES

• Submit an abstract of 250–300 words (clearly indicating the target chapter number from the Table of Contents)

• Include: chapter title, author name(s), full affiliation(s), email(s), and 5–7 keywords

• Send your abstract to: nanocure@yahoo.com

• Selected abstracts will be invited to submit full chapters

• All chapters will undergo editorial screening and peer review

• No Article Processing Charges (APC) / Free Publication

• Peer‑Reviewed Chapters | ISBN‑Indexed International Publication