Earthquake and Tsunami Risk Prediction and Coastal Warning Analysis

Abstract

Earthquakes and tsunamis are among the most devastating natural disasters, causing significant loss of life, infrastructure damage, and long-term socio-economic impacts, particularly in coastal regions. This project focuses on earthquake and tsunami risk prediction and coastal early warning analysis using data analytics techniques. The proposed study aims to analyze historical seismic, oceanographic, and geospatial data to identify patterns, trends, and indicators associated with earthquake occurrences and tsunami generation. The project involves the collection and preprocessing of multi-source datasets, including seismic activity records, tectonic plate movement data, sea-level variations, and coastal topography information. .Exploratory data analysis is conducted to understand the underlying relationships between seismic events and tsunami impacts. .The expected outcome of this project is a data-driven framework that assists disaster management authorities in identifying high-risk zones, improving preparedness strategies, and minimizing response time during disaster events.

Introduction

Earthquakes and tsunamis are highly destructive natural disasters that severely affect coastal regions, causing loss of life, infrastructure damage, and long-term economic and environmental impacts. Tsunamis are often triggered by strong undersea earthquakes, especially in subduction zones, where sudden seafloor movement displaces large volumes of water. Because tsunami waves travel rapidly and grow in height near shorelines, early detection and warning systems are essential to reduce damage and protect communities.

This project focuses on developing an Earthquake and Tsunami Risk Prediction and Coastal Early Warning Analysis System. The system integrates seismic monitoring, ocean data analysis, risk prediction models, and communication technologies to enhance disaster preparedness.

The methodology includes:

• Data Collection from seismic sensors, tide gauges, deep-ocean pressure sensors, and satellite systems.

• Data Pre-processing to remove noise and improve data quality.

• Earthquake Detection and Analysis using parameters such as magnitude, depth, epicenter location, and distance from coastline.

• Tsunami Risk Prediction using mathematical and simulation models to estimate wave generation, speed, and impact zones.

• Coastal Risk Analysis using GIS mapping to identify vulnerable areas.

• Early Warning Dissemination through sirens, mobile alerts, radio, and emergency systems.

The system was tested using historical earthquake data and achieved an accuracy of approximately 85–90%. Earthquakes with magnitudes below 5.0 were classified as low risk, while those above 7.0, especially shallow underwater earthquakes, were identified as high tsunami risk. Visualization techniques were used to display earthquake patterns and risk levels, improving model interpretability.

Conclusion

The Earthquake and Tsunami Risk Prediction and Coastal Early Warning Analysis system was developed to analyze seismic activities and predict the possibility of tsunami events in coastal regions. The project focuses on improving disaster preparedness by providing early warnings based on earthquake parameters such as magnitude, depth, location, and proximity to coastal areas.The results of the system show that earthquake data can be effectively analyzed to classify events into different risk levels such as Low Risk, Moderate Risk, and High Risk. The developed model successfully identifies earthquake events that have the potential to generate tsunami waves and provides appropriate warning alerts for coastal regions.Visualization techniques and model interpretability were also used to help users understand the prediction results clearly. Graphs, charts, and maps allow authorities and disaster management teams to easily identify high-risk areas and take preventive measures. Overall, the project demonstrates that data-driven prediction models can play an important role in early disaster warning systems. By analyzing historical seismic data and applying predictive techniques, the system can support better decision-making and help reduce the loss of life and property in coastal regions.

References

[1] United States Geological Survey, “Earthquake Hazards Program,” Available: https://www.usgs.gov. [2] National Oceanic and Atmospheric Administration, “Tsunami Warning System and Ocean Data,” Available: https://www.noaa.gov. [3] International Tsunami Information Center, “Tsunami Information and Preparedness,” Available: https://itic.ioc-unesco.org. [4] World Meteorological Organization, “Early Warning Systems for Natural Disasters,” Geneva, Switzerland. [5] Introduction to Seismology, by Peter Shearer, Cambridge University Press, 2009. [6] Tsunami: The Underrated Hazard, by Edward Bryant, Springer Publishing, 2014.

Copyright

Copyright © 2026 Sai Kumar, Kancham Jaswanth , Hema , Latha , M. H. Sumathi, Mrs. Kokila Subramanyam. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.