Artificial Intelligence For Flood Forecasting : A Review

• Author(s):

  Samaanta R | Kevin K Joseph

• Keywords:

  AI, Flood Forecasting,GIS, Hydrological Modelling, HEC-RAS, SWAT.

• Abstract:

  Flooding Remains One Of India’s Most Pressing Natural Hazards, With The National Disaster Management Authority Reporting That Over 12% Of The Country’s Landaround 40 Million Hectaresis Vulnerable To Inundation. In 2024, Extreme Rainfall And Flooding Events Caused Nearly 900 Deaths And Displaced Thousands. Conventional Hydrological Models, Though Widely Adopted, Often Face Difficulties In Delivering Timely And Accurate Predictions. Progress In Artificial Intelligence (AI) Has Introduced New Possibilities For Enhancing Flood Forecasting, Where Machine Learning And Deep Learning Approaches Can Capture Nonlinear Hydrological Relationships And Improve Response Planning. This Paper Reviews Both Traditional Modelling Frameworks And Modern AI-based Strategies, Including Flood Alert Systems And Geospatial Mapping Solutions, And Evaluates Their Effectiveness In Disaster Preparedness. The Findings Indicate That AI Holds Strong Potential For Advancing Resilience In Flood-prone Regions.

---

Other Details

• Paper id:

  IJSARTV11I9104018

• Published in:

  Volume: 11 Issue: 9 September 2025

• Publication Date:

  2025-09-15

Download Article