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Cyclones are natural events that are created due to low pressures and bring very high wind speeds. These strong winds often cause high sea waves, which can have long-lasting effects on society. One common example of this impact is urban flood- ing, which can disrupt cities for days or even weeks. The powerful winds during cyclones can severely damage public infrastructure, homes, and personal property, leaving many people vulnerable and displaced. Among all affected groups, coastal communities suffer the most, as they are directly exposed to the storm’s force and its after-effects. Cyclones not only cause immediate physical destruction but also leave a lasting social and economic impact on the people living in these regions.
In this study, we have predicted the inundation heights caused by cyclones us- ing GIS techniques, a method that has not been applied in this way before. Paradip Port, a key gateway for trade on the eastern coast of India, was chosen as the study area. We selected Sentinel-1 data instead of Sentinel-2 because Sentinel-1 can pen- etrate cloud cover, making it more suitable for cyclone-related studies. Predicting flood heights is essential, as it helps disaster management teams take timely action and evacuate people safely, particularly those living in vulnerable coastal regions. Our analysis showed that flood height has a nonlinear relationship with cyclonic parameters such as wind speed, wave height, and surge height. We established an empirical relation between these variables, which was found to be quadratic in na- ture. Finally, we developed a time series model (SARIMA) using wind speed data from 2004 to 2024. The model was validated against data from 2023 and 2024, and the results showed a reasonable level of agreement, demonstrating the model’s reliability. Using this validated model, we forecasted wind speeds for the years 2025 and 2026. The predicted peaks in wind speed correspond to periods that may indicate the occurrence of probable cyclones.
KEYWORDS: Storm Surge, Inundation Height, Tropical Cyclones.
