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Demonstrates flood risk prediction in Kisumu County, suggesting improved local preparedness.
Revised and corrected Version 2.1 of the Nyando Basin Flood Risk Prediction System. Corrections in this version: population updated to 161,000 residents of Nyando sub-county, training dataset confirmed as 2,308 real Google Earth Engine satellite observation points, primary model confirmed as GradientBoosting achieving AUC-ROC 0.9717, F1 0.9022, spatial CV 0.9727 plus or minus 0.004, test suite expanded to 41 pytest unit tests with GitHub Actions CI/CD. The system delivers real-time 72-hour ward-level flood susceptibility scores for five wards of Nyando sub-county. Built entirely on Android using Termux and Google Colab from Kisumu, Kenya. Live API: https://nyando-flood-api.onrender.com/docs Dashboard: https://nyando-flood-ai.vercel.app Repository: https://github.com/jameskoero/nyando-flood-ai
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James Koero (2026) studied this question.
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