Nyando Basin Flood Risk Prediction System: A Production-Grade, Explainable Machine Learning Framework for Ward-Level Flood Susceptibility Mapping in Kisumu County, Kenya

A production-grade machine learning flood susceptibility system for the Nyando River Basin, Kisumu County, Kenya. XGBoost classifier achieving AUC-ROC 0.94 trained on open satellite data (CHIRPS, NASA DEM, Sentinel-1 SAR). Includes modular Python source package, 19 pytest unit tests, FastAPI prediction endpoint, and React web dashboard. 100% open data — Kenya DPA 2019 and GDPR compliant. Full codebase, training data, model weights, and unit tests published under MIT and CC-BY-4.0 at github.com/jameskoero/nyando-flood-ai.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-08
DOI
https://doi.org/10.5281/zenodo.20088662
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nyando Basin Flood Risk Prediction System: A Production-Grade, Explainable Machine Learning Framework for Ward-Level Flood Susceptibility Mapping in Kisumu County, Kenya

James Koero
Zenodo (CERN European Organization for Nuclear Research)
Flood Risk Assessment and Management
article

Nyando Basin Flood Risk Prediction System: A Production-Grade, Explainable Machine Learning Framework for Ward-Level Flood Susceptibility Mapping in Kisumu County, Kenya

James Koero
article en

Abstract

A production-grade machine learning flood susceptibility system for the Nyando River Basin, Kisumu County, Kenya. XGBoost classifier achieving AUC-ROC 0.94 trained on open satellite data (CHIRPS, NASA DEM, Sentinel-1 SAR). Includes modular Python source package, 19 pytest unit tests, FastAPI prediction endpoint, and React web dashboard. 100% open data — Kenya DPA 2019 and GDPR compliant. Full codebase, training data, model weights, and unit tests published under MIT and CC-BY-4.0 at github.com/jameskoero/nyando-flood-ai.

Zenodo (CERN European Organization for Nuclear Research)
Great Lakes University of Kisumu (KE)
Climate action
Openalex Percentile: Top 5%
Flood Risk Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.