PREDICTION OF FLOOD-PRONE ZONES USING TOPOGRAPHIC RAINFALL AND RIVER FLOW DATA
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Floods pose a critical threat to human life, infrastructure and the economic stability. Old ways of predicting floods use maps that don't change and reports that come in late which makes them not very helpful for making quick decisions and sending out early warnings.To make predicting floods we created a new system that uses information about the land past rainfall and river flows along with special computer programs and maps to create detailed flood risk zones. This system gets information from satellites and river sensors in almost real-time, which lets us update the risk maps and monitor the situation on a website.The system is designed so that different people can use it like administrators, emergency workers and the public.It has tools that help people understand the situation better on devices. We also added information about which buildings and roads might be affected, which helps figure out what to do. The system can send emails to people in areas that're at high risk when the water level gets too high which helps them know what to do and where to go. This new approach is better, than methods because it is more accurate responds faster and is easier to use. It helps cities prepare for floods communicate risks and respond to emergencies effectively.
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Sreevalli, J., Tej, B. T., Rakshitha, K. & Kumar, M. J. (2026). Prediction of Flood-Prone Zones using Topographic Rainfall and River Flow Data. International Journal of Science, Strategic Management and Technology, 02(03). https://doi.org/10.55041/ijsmt.v2i3.412
Sreevalli, Juturu, et al.. "Prediction of Flood-Prone Zones using Topographic Rainfall and River Flow Data." International Journal of Science, Strategic Management and Technology, vol. 02, no. 03, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i3.412.
Sreevalli, Juturu,Bille Tej,Ks Rakshitha, and M Kumar. "Prediction of Flood-Prone Zones using Topographic Rainfall and River Flow Data." International Journal of Science, Strategic Management and Technology 02, no. 03 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i3.412.
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