Flood Inundation Mapping for the Tana River Delta in Kenya

This study aimed at mapping flood inundation areas in the Tana River Delta. The 30 m DEM and digitized streams and road networks data were collected through remote sensing techniques followed by ground truthing. The data used also included Tana River discharge data at Garsen gauging station. Probability distributions were fitted on the annual maximum discharges. The 4 parameter generalized Gamma probability distribution was the best-fitting distribution according to goodness-of-fit criteria and the Q-Q plots and was used to generate the flood quantiles for different return periods. The generated flood quantiles were; 286 m3 /s, 369 m3 /s, 400 m3 /s, 405 m3 /s, 439 m3 /s, and 449 m3 /s for 2-year, 5-year, 10-year, 20-year 50-year, and 100-year return periods respectively. GIS Flood Tool in ArcGIS used flood quantiles to produce flood extents and inundation depths. The largest part of the Tana River delta was predicted to be flooded with inundation depths of upto 1.8 m causing inundation of settlements and leading to the death of people and livestock, as well as the destruction of properties and infrastructure including roads and buildings, farms, crops, among others. The study established that 31% of the schools located along the Tana River in the Garsen sub-catchment are exposed to inundation depths above 0.5 m. Different flood management options were identified for Tana River Delta and were subjected to Multicriteria Analysis for a decision to be arrived at in choosing the best. Advanced technology in recession agriculture, early warning systems, and forecasting were ranked as the optimal options for managing floods in Tana River Delta. The outcomes of this study contribute to preparedness for floods and guide development decisions within the mapped areas.

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Publication Details

Journal
Tanzania Journal of Engineering and Technology
Published
2025-04-11
DOI
https://doi.org/10.52339/tjet.v44i1.981
Primary Topic
Flood Risk Assessment and Management
Type
article
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article

Flood Inundation Mapping for the Tana River Delta in Kenya

Joel Nobert, Patrick Valimba, Anne Mugatha
Tanzania Journal of Engineering and Technology
Flood Risk Assessment and Management
article

Flood Inundation Mapping for the Tana River Delta in Kenya

Joel Nobert, Patrick Valimba, Anne Mugatha
article en

Abstract

This study aimed at mapping flood inundation areas in the Tana River Delta. The 30 m DEM and digitized streams and road networks data were collected through remote sensing techniques followed by ground truthing. The data used also included Tana River discharge data at Garsen gauging station. Probability distributions were fitted on the annual maximum discharges. The 4 parameter generalized Gamma probability distribution was the best-fitting distribution according to goodness-of-fit criteria and the Q-Q plots and was used to generate the flood quantiles for different return periods. The generated flood quantiles were; 286 m3 /s, 369 m3 /s, 400 m3 /s, 405 m3 /s, 439 m3 /s, and 449 m3 /s for 2-year, 5-year, 10-year, 20-year 50-year, and 100-year return periods respectively. GIS Flood Tool in ArcGIS used flood quantiles to produce flood extents and inundation depths. The largest part of the Tana River delta was predicted to be flooded with inundation depths of upto 1.8 m causing inundation of settlements and leading to the death of people and livestock, as well as the destruction of properties and infrastructure including roads and buildings, farms, crops, among others. The study established that 31% of the schools located along the Tana River in the Garsen sub-catchment are exposed to inundation depths above 0.5 m. Different flood management options were identified for Tana River Delta and were subjected to Multicriteria Analysis for a decision to be arrived at in choosing the best. Advanced technology in recession agriculture, early warning systems, and forecasting were ranked as the optimal options for managing floods in Tana River Delta. The outcomes of this study contribute to preparedness for floods and guide development decisions within the mapped areas.

Tanzania Journal of Engineering and TechnologyVol. 44(1)
University of Dar es Salaam (TZ), University Health Care System (US)
Openalex Percentile: Top 92%
Flood Risk Assessment and Management
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