TECHNOLOGICAL INNOVATION FOR URBAN FLOOD DISASTERRISK REDUCTION IN KASARANI SUB-COUNTY, NAIROBICOUNTY, KENYA
DOI:
https://doi.org/10.5281/zenodo.22800369Keywords:
Technological innovation, urban flooding, disaster risk reduction, early warning systems, community participation, Kasarani, NairobiAbstract
Purpose of study: This study assessed the effectiveness of technological innovation in urban flood disaster risk reduction in Kasarani Sub-County, Nairobi County, Kenya. Specifically, it examined the types of technological innovations used, their effectiveness in minimising flood impacts, community awareness of technological solutions, and challenges affecting their implementation in flood disaster risk management.
Methodology: The study adopted a descriptive research design using quantitative and qualitative approaches. Data were collected from 291 respondents through structured questionnaires, key informant interviews, focus group discussions, and observation checklists. Quantitative data were analysed using descriptive statistics in SPSS Version 28, while qualitative data were transcribed, coded thematically, and triangulated with quantitative findings.
Findings: The findings established that early warning systems were the most widely used technological innovation (M = 4.18, SD = 0.74), followed by mobile-based alert platforms (M = 4.12, SD = 0.72) and GIS mapping technologies (M = 4.05, SD = 0.68). Early warning systems were also perceived as the most effective for timely flood notification, while social media supported real-time communication and GIS facilitated identification of flood-prone areas. Community awareness was generally moderate to high, although uptake varied across demographic groups. Major implementation challenges included unsupportive government policies and institutional frameworks (M = 4.36), limited funding (M = 4.22), poor internet connectivity and infrastructure (M = 4.10), limited access to digital devices, weak stakeholder coordination, and inadequate technical expertise.
Conclusion: The study concludes that technological innovation has contributed positively to urban flood disaster risk reduction in Kasarani Sub-County, particularly through early warning, communication, and hazard mapping. However, its benefits remain constrained by institutional, financial, infrastructural, and social limitations. Strengthening policy support, sustainable funding, digital infrastructure, stakeholder coordination, and inclusive community training is therefore essential.
Downloads
References
Ahmed, I., Ahmad, M., Jeon, G., & Chehri, A. (2024). An Internet of Things and AI-powered framework for long-term flood risk evaluation. IEEE Internet of Things Journal, 11(3), 3812–3819. https://doi.org/10.1109/JIOT.2023.3308564
Bakhtiari, V., Piadeh, F., Behzadian, K., & Kapelan, Z. (2023). A critical review for the application of cutting-edge digital visualisation technologies for effective urban flood risk management. Sustainable Cities and Society, 99, 104958. https://doi.org/10.1016/j.scs.2023.104958
Bakhtiari, V., Piadeh, F., Chen, A. S., & Behzadian, K. (2024). Stakeholder analysis in the application of cutting-edge digital visualisation technologies for urban flood risk management: A critical review. Expert Systems with Applications, 236, 121426. https://doi.org/10.1016/j.eswa.2023.121426
Bakhtiari, V., Piadeh, F., Chen, A. S., & Behzadian, K. (2024). Stakeholder analysis in the application of cutting-edge digital visualisation technologies for urban flood risk management: A critical review. Expert Systems with Applications, 236, 121426. https://doi.org/10.1016/j.eswa.2023.121426
Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational research. Human Relations, 61(8), 1139–1160. https://doi.org/10.1177/0018726708094863
Girotto, C. D., Piadeh, F., Bakhtiari, V., Behzadian, K., Chen, A. S., Campos, L. C., & Zolgharni, M. (2023). A critical review of digital technology innovations for early warning of water-related disease outbreaks associated with climatic hazards. International Journal of Disaster Risk Reduction, 100, 104151. https://doi.org/10.1016/j.ijdrr.2023.104151
Girotto, C., Piadeh, F., Bakhtiari, V., Behzadian, K., Chen, A. S., Campos, L. C., & Zolgharni, M. (2024). A critical review of digital technology innovations for early warning of water-related disease outbreaks associated with climatic hazards. International Journal of Disaster Risk Reduction, 100, 104151. https://doi.org/10.1016/j.ijdrr.2023.104151
Kamruzzaman, M., Daniell, K. A., Chowdhury, A., & Crimp, S. (2022). Facilitating learning for innovation in a climate-stressed context: Insights from flash flood-affected rice farming in Bangladesh. The Journal of Agricultural Education and Extension, 29(5), 617–641. https://doi.org/10.1080/1389224X.2022.2082497
Kiptum, A., Mwangi, E., Otieno, G., Njogu, A., Kilavi, M., Mwai, Z., MacLeod, D., Neal, J., Hawker, L., O'Shea, T., Saado, H., Visman, E., Majani, B., & Todd, M. C. (2023). Advancing operational flood forecasting, early warning and risk management with new emerging science: Gaps, opportunities and barriers in Kenya. Journal of Flood Risk Management, 18(1), e12884. https://doi.org/10.1111/jfr3.12884
Kiptum, A., Mwangi, E., Otieno, G., Njogu, A., Kilavi, M., Mwai, Z., MacLeod, D., Neal, J., Hawker, L., O'Shea, T., Saado, H., Visman, E., Majani, B., & Todd, M. C. (2025). Advancing operational flood forecasting, early warning and risk management with new emerging science: Gaps, opportunities and barriers in Kenya. Journal of Flood Risk Management, 18(1), e12884. https://doi.org/10.1111/jfr3.12884
Kiptum, A., Mwangi, E., Otieno, G., Njogu, A., Kilavi, M., Mwai, Z., MacLeod, D., Neal, J., Hawker, L., O'Shea, T., Saado, H., Visman, E., Majani, B., & Todd, M. C. (2023). Advancing operational flood forecasting, early warning and risk management with new emerging science: Gaps, opportunities and barriers in Kenya. Journal of Flood Risk Management, 16(1), e12884. https://doi.org/10.1111/jfr3.12884
Mulungo, M. A., Obiero, J. P., & Omuto, C. T. (2023). Hydrological modelling for flood risk analysis in selected sub-counties, Nairobi, Kenya. Journal of Engineering in Agriculture and the Environment. https://doi.org/10.37017/jeae-volume9-no2.2023-4
Naanyu, V., Njuguna, B., Koros, H., Andesia, J., Kamano, J., Mercer, T., Bloomfield, G., Pastakia, S., Vedanthan, R., & Akwanalo, C. (2023). Community engagement to inform development of strategies to improve referral for hypertension: Perspectives of patients, providers and local community members in western Kenya. BMC Health Services Research, 23, 854. https://doi.org/10.1186/s12913-023-09847-0
Naanyu, V., Njuguna, B., Koros, H., Andesia, J., Kamano, J., Mercer, T., Bloomfield, G., Pastakia, S., Vedanthan, R., & Akwanalo, C. (2023). Community engagement to inform development of strategies to improve referral for hypertension: Perspectives of patients, providers and local community members in western Kenya. BMC Health Services Research, 23, 854. https://doi.org/10.1186/s12913-023-09847-0
Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press. https://www.google.com/books/edition/Diffusion_of_Innovations_5th_Edition/9U1K5LjUOwEC
Rumson, A. G., & Hallett, S. H. (2019). Innovations in the use of data facilitating insurance as a resilience mechanism for coastal flood risk. Science of the Total Environment, 661, 598–612. https://doi.org/10.1016/j.scitotenv.2019.01.114
Tedla, H. Z., Bekele, T. W., Nigussie, L., Negash, E. D., Walsh, C. L., O'Donnell, G., & Haile, A. T. (2024). Threshold-based flood early warning in an urbanizing catchment through multi-source data integration: Satellite and citizen science contribution. Journal of Hydrology, 635, 131076. https://doi.org/10.1016/j.jhydrol.2024.131076
Trento Oliveira, L., Kuffer, M., Belgiu, M., & Dijkstra, A. M. (2024). Diagnostics of urban flooding in Nairobi. Zenodo. https://doi.org/10.5281/zenodo.14650088
United Nations Development Programme. (2023). Framework for multi-hazard early warning and early action system for Africa. https://www.undp.org/africa/publications/framework-multi-hazard-early-warning-and-early-action-system-africa
United Nations Office for Disaster Risk Reduction. (2022). Global assessment report on disaster risk reduction 2022: Our world at risk – Transforming governance for a resilient future. https://doi.org/10.18356/83cdc99a-en
United Nations Office for Disaster Risk Reduction. (2024, April 16). Accelerating the deployment of impact-based early warning products in Africa. https://www.undrr.org/news/accelerating-deployment-impact-based-early-warning-products-africa
United Nations Office for Disaster Risk Reduction. (2024, June 14). Italian contribution allows UNDRR to expand early warnings for early action in Kenya. https://www.undrr.org/news/italian-contribution-allows-undrr-expand-early-warnings-early-action-kenya
Wehn, U., & Evers, J. (2015). The social innovation potential of ICT-enabled citizen observatories to increase eParticipation in local flood risk management. Technology in Society, 42, 187–198. https://doi.org/10.1016/j.techsoc.2015.05.002
Yamane, T. (1967). Statistics: An introductory analysis (2nd ed.). Harper & Row. https://openlibrary.org/works/OL3906311W/Statistics
Downloads
Published
Issue
Section
License
Copyright (c) 2026 International Journal for Disaster Management and Risk Reduction
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
