Flood Risk Assessment Isiolo River Basin, Kenya

Flood Risk Assessment Isiolo River Basin, Kenya: Feasibility of the SLAMDAM in the Isiolo River Basin using the FIS Tool

Cheaz, Tristan (TU Delft Civil Engineering & Geosciences)
Kromwijk, Dominique (TU Delft Civil Engineering & Geosciences)
Middelbeek, Lisanne (TU Delft Civil Engineering & Geosciences)
Nelen, Louis (TU Delft Civil Engineering & Geosciences; TU Delft Technology, Policy and Management)
Sutarto Hardjosusono, Sunar (TU Delft Civil Engineering & Geosciences)

van de Giesen, N.C. (mentor)
Ninan, Johan (graduation committee)
van den Eijnden, A.P. (graduation committee)

Delft University of Technology

Water Management

Civil Engineering Consultancy Project

2022-11-29

This report provides a flood risk assessment of the Isiolo River Basin, in collaboration with Nelen & Schuurmans (3Di, FIS Tool) and Zephyr Consulting (SLAMDAM). This flood risk assessment includes a study of the current flood risk management in Kenya, and in the Isiolo River Basin in particular, because the need for proper flood management is urgent: various climate studies predict an increase in rainfall and an increase in flood risk as a result of the effects of climate change.

Current flood risk management is inadequate. Kenya has defined 21 flood-prone areas whereof one of them is Isiolo Town. Isiolo Town is located in the ENN basin which is, relatively, the most prone to the effects of climate change compared to the other basins. Furthermore, the ENN basin currently has the highest poverty rate and avoidance of further enlargement in poverty rate is important, so there is a need to mitigate flood risks. Since Isiolo Town is located in the Isiolo River Basin, this basin has been chosen for an in-depth study.

The Isiolo River Basin is an Arid Semi-Arid Land region which is often prone to flash floods. Isiolo Town is a flat area located downstream of mountainous area, the rain which falls upstream flows fast downstream and converges into town, often resulting in inundation. Many hazards, both natural and others, are increasing the flood risk in the basin and specifically Isiolo Town.

This flood risk demands flood risk mitigation measures. One possible measure is the SLAMDAM. The SLAMDAM is a movable water-filled flood-barrier. One dam has a length of 5 meters and a height of 1 meter and the dams can be connected to a desired length. The water stored in the dam can be used afterwards for irrigation or other uses.
To recommend effective areas to implement the SLAMDAM, 3Di and the FIS Tool are used. 3Di is a hydrodynamic model and it creates flood maps for different rain events. These flood maps are used as input for the FIS Tool. The FIS Tool calculates the benefits for deploying the SLAMDAM at a certain location for a particular length. The locations which result in the highest benefit are recommended to deploy the SLAMDAM in case of particular rain events. However, a site visit is required to see whether the modelled situation aligns with the real-life situation and to see whether boundary conditions are met.
The SLAMDAM is also compared to other flood risk mitigation measures. Some were analysed using the FIS Tool, whereas others are evaluated based on five self-formulated ranking criteria. These criteria form the base of a scoring matrix where each relevant mitigation measure is scored on.

The performed research has shown the SLAMDAM to rank the best compared to other mitigation measures, both when using the scoring matrix and when using the FIS Tool. However, it is highly recommended to use the SLAMDAM in combination with a Flood Early Warning System. In this way the community downstream can be warned in time to deploy the SLAMDAM. The FIS Tool is found to be especially valuable in finding proper locations for deployment and the dam can be stored close to these locations, enabling fast deployment of the dam in case of need.

Flood risk
SLAMDAM
FIS Tool
3Di
Kenya
Isiolo River Basin

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For this project, the disciplines are Water Management, Geo-Engineering and Civil Engineering | Construction Management and Engineering.

Student theses

student report

© 2022 Tristan Cheaz, Dominique Kromwijk, Lisanne Middelbeek, Louis Nelen, Sunar Sutarto Hardjosusono