Flood exposure assessment in Rivers State, Nigeria

  • Authors

    2023-09-17
    https://doi.org/10.14419/ijpr.v11i2.32340
  • The primary procedure in emergency response and disaster risk management is identifying the scope of a natural hazard, such as determining regions at high risk. After this, exposure mapping helps estimate the disaster's potential impact - for instance, determining the number of possible people or facilities affected. Employing Earth Observation (EO) data gathered from satellites is commonly used to map areas with a high susceptibility to natural disasters. The purpose of this work was to evaluate flood exposure in Rivers State. The objectives included assessing the probable effects on local and urban settlement, and establishing the magnitude of damage on farmland. The research leverages multiple data sources, including Globalland 30, Global Human Settlement Population Layer. Quantum GIS played a significant role in assessing the vulnerability and exposure scale of both people and farmlands to flood risks. The primary analyses conducted involved zonal statistics and overlaps analysis. The study shows an estimated 161,537 people are impacted by this exposure. The flooding affects farmlands that cover approximately 5,591 hectares. Furthermore, estimated urban-rural area impacted by flooding is around 29,775,178 square meters, or 2,978 hectares This is executed largely for risk management or emergency response after events like floods, wind storms or landslides. For managing risks prior to a disaster, it's crucial to compare varying damage models with the corresponding exposure, delivering a comprehensive outlook on potential impacts.

  • References

    1. Aggarwal, A. (2016). Exposure, Hazard and Risk Mapping during a Flood Event Using Open Source Geospatial Technology. Geomat-ics, Natural Hazards and Risk, 7, 1426-1441. https://doi.org/10.1080/19475705.2015.1069408.
    2. Cardona, O. D. (2005). Indicators for Disaster Risk and Risk Management. Program for Latin America and the Caribbean: Summary Report, Instituto de Estudios Ambientales, Universidad Nacional de Columbia.
    3. Daniela R, Khan,U., & Armenakis C,. (2010). Flood risk mapping using GIS and multi-criteria analysis:A greater toronto area case study. Geosciences,8(8),275. https://doi.org/10.3390/geosciences8080275.
    4. Dilley, M. (2005). Natural Disaster Hotspots: A Global Risk Analysis (Vol. 5). World Bank Publications. https://doi.org/10.1596/0-8213-5930-4.
    5. Esmaiel, A., Abdrabo, K. I., Saber, M., Sliuzas, R. V, Atun, F., Kantoush, S. A., & Sumi, T. (2022). Progress in Disaster Science Inte-gration of Flood Risk Assessment and Spatial Planning for Disaster Management in Egypt. Progress in Disaster Science, 15, Article ID: 100245. https://doi.org/10.1016/j.pdisas.2022.100245.
    6. Hagos, Y. G., Andualem, T. G., Yibeltal, M., & Mengie, M. A. (2022). Flood Hazard Assessment and Mapping Using GIS Integrated with Multi-Criteria Decision Analysis in Upper Awash River basin, Ethiopia. Applied Water Science, 12, 1-18. https://doi.org/10.1007/s13201-022-01674-8.
    7. Lekamlage, K., Chathurani, N., Acharilage, H., & Arunashantha, S. (2022). Case Study on Identification of Flood Hazard in the Lower Catchment Area of the Attanagalu Oya River Basin. Journal of Geoscience and Environment Protection, 10, 305-318. https://doi.org/10.4236/gep.2022.107018.
    8. Lin, L., Di, L., Yu, E. G., Kang, L., Shrestha, R., Rahman, M. S., Tang, J., Deng, M., Sun, Z., Zhang, C., & Hu, L. (2016). A Review of Remote Sensing in Flood Assessment. In 2016 5th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2016 (pp. 1-4). IEEE. https://doi.org/10.1109/Agro-Geoinformatics.2016.7577655.
    9. Mahsa S., Masoud M., Mehdi Z, Zahra A, Alireza G, (2012) Flood risk assessment using GIS (Case study:Golestan prov-ince,iran).(n.d.).Re searchGate.
    10. Pelling, M. (2012). The Vulnerability of Cities: Natural Disasters and Social Resilience. Routledge. https://doi.org/10.4324/9781849773379.
    11. Pushpakumara, T. D. C., & Achala Isuru, T. V. (2018). Flood Modelling and Analyzing of Attanagalu Oya River Basin Using Geo-graphic Information System. International Journal of Advanced Remote Sensing and GIS, 7, 2712-2718. https://doi.org/10.23953/cloud.ijarsg.366.
    12. Samu, R., & Kentel, A. S. (2018). An Analysis of the Flood Management and Mitigation Measures in Zimbabwe for a Sustainable Fu-ture. International Journal of Disaster Risk Reduction, 31, 691-697. https://doi.org/10.1016/j.ijdrr.2018.07.013.
    13. Schelhorn, S. J., Herfort, B., Leiner, R., Zipf, A., & De Albuquerque, J. P. (2014). Identifying Elements at Risk from OpenStreetMap: The Case of Flooding. In ISCRAM 2014 Conference Proceedings 11th International Conference on Information Systems for Crisis Re-sponse and Management (pp. 508-512). The Pennsylvania State University
    14. UNISDR (2017). Words into Action Guidelines: National Disaster Assessment.
    15. https://www.undrr.org/publication/words-action-guidelines-national-disaster-risk-assessment
    16. Ziegelaar, M.; & Kuleshov, Y. (2022). Flood Exposure Assessment and Mapping: A Case Study for Australia’s Hawkesbury-Nepean Catchment. 2022 edition of Hydrology (volume 9, page 193). https://doi.org/10.3390/hydrology9110193.
  • Downloads

  • How to Cite

    M .Menegbo, E., & J. Emengini , E. (2023). Flood exposure assessment in Rivers State, Nigeria. International Journal of Physical Research, 11(2), 31-35. https://doi.org/10.14419/ijpr.v11i2.32340