Flood Predictions using Previous Streamflow Magnitudes Applying Geographical Information System and Statistical Tools

Ugwu S. J., Abubakar M., Ajoge H. N., Shamsu M. Adamu, Didam Y. M., Aminu G. H., Adedokun A. A.

Abstract


Floods constitute 30% of natural disasters globally (1900–2020), causing 19% of fatalities and affecting 48% of impacted populations. In Kaduna State, recurrent flooding of the Kaduna River severely impacts communities like Rafin Gusa, Kabala Doki, Barnawa, and others. This study examines the region’s flood history using GPS-based assessments to map flood extents, river profiles, and hydrographs. Results reveal a strong correlation between elevation and distance along the river’s flood-prone areas (downstream R² = 0.9267, upstream R² = 0.8058), with the downstream being more vulnerable. The river’s highest discharge, 22,130 m³/s, occurred in 2012, based on a 16-year hydrograph (2008–2024). Pour point analysis highlights high-risk zones at elevated areas due to faster water flow from steep slopes. The study provides a model to forecast future flooding, offering insights for policymakers to monitor and mitigate flood risks effectively.


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References


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