Flood Vulnerability and Risk Mapping in Tana River River County, Kenya, Using Multi-Criteria Decision Analysis and GIS


  • Alfayo Koskei Egerton University


Flood hazard mapping, flood exposure mapping, environmental vulnerability to floods, GIS, Tana River.


Flood is one of the major recurring and seasonal environmental problems in Kenya and often causes huge losses of life and economy through destruction of property. The increase in magnitude and frequency of floods and landslides are attributed to human activities in the most vulnerable areas and climate change phenomena such as Indian Ocean Dipole. Among the notable and vulnerable areas is the Tana Delta. The ?ood vulnerability mapping of the region is crucial for wetland management, early warning system and development of response initiatives. The purpose of this study was to develop flood vulnerability maps for flood prediction in the study area. GIS-based methodologies were used to map the distribution and extent of floods and landslides which include spatial distribution models such as Digital Surface Model (DSM), Digital Elevation Models (DEM) and Landsat Imagery. Geographical Information System (GIS)/Remote Sensing (RS)-based multi-criteria approach was used to select the flood causal factors and vulnerability assessment. Relative weight of each factor was determined using Analytical Hierarchical Process (AHP). The first step in the flood vulnerability analysis was to identify the factors. Then each factor was analyzed with satellite images in the GIS environment, weighted and overlaid to produce the flood vulnerability maps. The results show that although very highly vulnerable areas cover the smallest proportion in the study areas (6%) a sizable proportion of areas has substantial vulnerability (20%). The extremely low and minimal flood vulnerability classes cover 11.1% and 27.4%, respectively. The model predicted that a total of 217,882 hectares of land would be inundated during a rainy period. Areas that are under highly vulnerable in the study area include Garsen North, Mikindu, Chewani and Kipini West. The extremely highly vulnerable areas are: Garsen Central and Garsen South. All these areas are within high and extremely high hazard zones and are dominated by low elevation and slope degree. These vulnerability maps are critical in mapping the flood and landslide events in order to develop a clear roadmap to an early warning system.


Abram, N. J., Hargreaves, J. A., Wright, N. M., Thirumalai, K., Ummenhofer, C. C., & England, M. H. (2020). Palaeoclimate perspectives on the Indian Ocean dipole. Quaternary Science Reviews, 237, 106302.

Ajjur, S. B., & Mogheir, Y. K. (2020). Flood hazard mapping using a multi-criteria decision analysis and GIS (case study Gaza Governorate, Palestine). Arabian Journal of Geosciences, 13(2), 1-11.

Calder, I. (1992). The hydrological impact of land-use change. 91–101.

Chawan, A. C., Kakade, V. K., & Jadhav, J. K. (2020). Automatic Detection of Flood Using Remote Sensing Images. Journal of Information Technology, 2(01), 11-26.

Cloke, H. L., Wetterhall, F., He, Y., Freer, J. E., & Pappenberger, F. (2013). Modelling climate impact on floods with ensemble climate projections. Quarterly Journal of the Royal Meteorological Society, 139(671), 282-297.

Danumah, J. H., Odai, S. N., Saley, B. M., Szarzynski, J., Thiel, M., Kwaku, A., ... & Akpa, L. Y. (2016). Flood risk assessment and mapping in Abidjan district using multi-criteria analysis (AHP) model and geoinformation techniques, (cote d’ivoire). Geoenvironmental Disasters, 3(1), 1-13.

Degiorgis, M., Gnecco, G., Gorni, S., Roth, G., Sanguineti, M., & Taramasso, A. C. (2012). Classifiers for the detection of flood-prone areas using remote sensed elevation data. Journal of hydrology, 470, 302-315.

Duvail, S., Médard, C., Hamerlynck, O., & Nyingi, D. W. (2012). Land and water grabbing in an East African coastal wetland: The case of the Tana delta. Water Alternatives, 5, 322–343.

Elkhrachy, I. (2015). Flash flood hazard mapping using satellite images and GIS tools: A case study of Najran City, Kingdom of Saudi Arabia (KSA). The Egyptian Journal of Remote Sensing and Space Science, 18(2), 261–278.

Gemitzi, A., Petalas, C., Tsihrintzis, V. A., & Pisinaras, V. (2006). Assessment of groundwater vulnerability to pollution: A combination of GIS, fuzzy logic and decision making techniques. Environmental Geology, 49(5), 653–673.

Gourav, P., Kumar, R., Gupta, A., & Arif, M. (2020). Flood hazard zonation of Bhagirathi river basin using multi-criteria decision-analysis in Uttarakhand, India. Int J Emerg Technol, 11(1), 62-71.

Haan, C. T., Barfield, B. J., & Hayes, J. C. (1994). Design hydrology and sedimentology for small catchments. Elsevier.

Huong, H. T. L., & Pathirana, A. (2013). Urbanization and climate change impacts on future urban flooding in Can Tho city, Vietnam. Hydrology and Earth System Sciences, 17(1), 379-394.

Islam, M. M., & Sado, K. (2000). Development of flood hazard maps of Bangladesh using NOAA-AVHRR images with GIS. Hydrological Sciences Journal, 45(3), 337–355.

Kateb, Z., Bouchelkia, H., Benmansour, A., & Belarbi, F. (2020). Sediment transport modeling by the SWAT model using two scenarios in the watershed of Beni Haroun dam in Algeria. Arabian Journal of Geosciences, 13(14), 1-17.

Kazakis, N., Kougias, I., & Patsialis, T. (2015). Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope–Evros region, Greece. Science of the Total Environment, 538, 555-563.

Kowalzig, J. (2008). Climate, Poverty, and Justice: What the Poznan UN climate conference needs to deliver for a fair and effective global deal. Oxfam.

Kundu, A., & Goswami, B. (2008). A note on seismic evidences during the sedimentation of Panchet Formation, Damodar Basin, Eastern India: Banspetali Nullah Revisited. J. Geol. Soc. India, 72, 400-404.

Leauthaud, C., Belaud, G., Duvail, S., Moussa, R., Grunberger, O., & Albergel, J. (2013). Characterizing floods in the poorly gauged wetlands of the Tana River Delta, Kenya, using a water balance model and satellite data. Hydrology and Earth System Sciences, 17(8), 3059-3079.

Leauthaud-Harnett, C., Belaud, G., Duvail, S., Moussa, R., Grünberger, O., & Albergel, J. (2016). Characterizing floods in the poorly gauged wetlands of the Tana River Delta, Kenya, using a water balance model and satellite data. In 5. International EcoSummit: Ecological Sustainability: Engineering Change.

Li, L., Hong, Y., Wang, J., Adler, R. F., Policelli, F. S., Habib, S., Irwn, D., Korme, T., & Okello, L. (2009). Evaluation of the real-time TRMM-based multi-satellite precipitation analysis for an operational flood prediction system in Nzoia Basin, Lake Victoria, Africa. Natural Hazards, 50(1), 109–123.

Lu, B., & Ren, H. L. (2020). What caused the extreme Indian Ocean dipole event in 2019?. Geophysical Research Letters, 47(11), e2020GL087768.

Maingi, J. K., & Marsh, S. E. (2002). Quantifying hydrologic impacts following dam construction along the Tana River, Kenya. Journal of Arid Environments, 50(1), 53-79.

Malczewski, J. (2006). GIS?based multicriteria decision analysis: A survey of the literature. International Journal of Geographical Information Science, 20(7), 703–726.

Malczewski, J., & Rinner, C. (2015). Multicriteria decision analysis in geographic information science. Springer.

Masoudian, M. (2009). The topographical impact on effectiveness of flood protection measures (Vol. 18). kassel university press GmbH.

Mastin, M. C. (2009). Watershed models for decision support for inflows to potholes reservoir, Washington. U. S. Geological Survey.

Mu, D., Luo, P., Lyu, J., Zhou, M., Huo, A., Duan, W., ... & Zhao, X. (2021). Impact of temporal rainfall patterns on flash floods in Hue City, Vietnam. Journal of Flood Risk Management, 14(1), e12668.

Najafi, M. R., Zhang, Y., & Martyn, N. (2021). A flood risk assessment framework for interdependent infrastructure systems in coastal environments. Sustainable Cities and Society, 64, 102516.

Norman, L., Huth, H., Levick, L., Shea Burns, I., Phillip Guertin, D., Lara?Valencia, F., & Semmens, D. (2010). Flood hazard awareness and hydrologic modelling at Ambos Nogales, United States–Mexico border. Journal of Flood Risk Management, 3(2), 151–165.

Nyarko, B. K. (2002). Application of a rational model in GIS for flood risk assessment in Accra, Ghana. Journal of Spatial Hydrology, 2(1).

OCHA. (2018, February 15). OCHA. https://www.unocha.org/southern-and-eastern-africa-rosea/kenya

Olang, L., & Fürst, J. (2011). Effects of land cover change on flood peak discharges and runoff volumes: Model estimates for the Nyando River Basin, Kenya. Hydrological Processes, 25(1), 80–89.

Opere, A. (2013). Floods in Kenya. In Developments in Earth Surface Processes (Vol. 16, pp. 315-330). Elsevier.

Otieno, O. M., Abdillahi, H. S., Wambui, E. M., & Kiprono, K. S. (2019). Flood Impact-Based Forecasting for Early Warning and Early Action in Tana River Basin, Kenya. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences.

Otolo, J., & Wakhungu, J. (2013). Factors influencing livelihood zonation in Kenya. International Journal of Education and Research, 1(12), 1–10.

Ouma, Y., & Tateishi, R. (2014). Urban flood vulnerability and risk mapping using integrated multi-parametric AHP and GIS: methodological overview and case study assessment. Water, 6(6), 1515–1545.

Quandt, A. (2016). Adapting livelihoods to floods and droughts in arid Kenya: Local perspectives and insights. African Journal of Rural Development, 1(1), 51.

Rahman, M. S., & Di, L. (2020). A systematic review on case studies of remote-sensing-based flood crop loss assessment. Agriculture, 10(4), 131.

Rahmati, O., Zeinivand, H., & Besharat, M. (2016). Flood hazard zoning in Yasooj region, Iran, using GIS and multi-criteria decision analysis. Geomatics, Natural Hazards and Risk, 7(3), 1000-1017.

Rizeei, H. M., Saharkhiz, M. A., Pradhan, B., & Ahmad, N. (2016). Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models. Geocarto International, 31(10), 1158–1177.

Saaty, T. L. (1990a). An exposition of the AHP in reply to the paper “remarks on the analytic hierarchy process.” Management Science, 36(3), 259–268.

Saaty, T. L. (1990b). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9–26.

Saaty, T. L. (1991). Some mathematical concepts of the analytic hierarchy process. Behaviormetrika, 18(29), 1–9.

Scheuer, S., Haase, D., & Meyer, V. (2011). Exploring multicriteria flood vulnerability by integrating economic, social and ecological dimensions of flood risk and coping capacity: From a starting point view towards an end point view of vulnerability. Natural Hazards, 58(2), 731–751.

Solín, ?. (2012). Spatial variability in the flood vulnerability of urban areas in the headwater basins of Slovakia. Journal of Flood Risk Management, 5(4), 303–320.

Youssef, A. M., Pradhan, B., & Hassan, A. M. (2011). Flash flood risk estimation along the St. Katherine road, southern Sinai, Egypt using GIS based morphometry and satellite imagery. Environmental Earth Sciences, 62(3), 611–623.



How to Cite

Koskei, A. (2022) “Flood Vulnerability and Risk Mapping in Tana River River County, Kenya, Using Multi-Criteria Decision Analysis and GIS ”, Egerton University International Conference. Available at: https://conferences.egerton.ac.ke/index.php/euc/article/view/41 (Accessed: 18 May 2024).



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