IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v110y2022i3d10.1007_s11069-021-05015-x.html
   My bibliography  Save this article

The essential contribution of indigenous knowledge to understanding natural hazards and disaster risk: historical evidence from the Rwenzori (Uganda)

Author

Listed:
  • Bosco Bwambale

    (Vrije Universiteit Brussel
    Mountains of the Moon University)

  • Martine Nyeko

    (Gulu University)

  • John Sekajugo

    (Vrije Universiteit Brussel
    Mountains of the Moon University)

  • Matthieu Kervyn

    (Vrije Universiteit Brussel)

Abstract

The integration of indigenous knowledge into understanding disasters from natural hazards is hitherto hampered by the limited conceptualization of the process that shapes indigenous knowing. This study proposed a framework, structuring the processes that shape indigenous knowledge on disaster risk. Bearing that framework in mind, the evolution of disaster risk as understood by indigenous people was investigated based on the case floods in the Rwenzori. Data are collected using participatory ethnographic methods and analyzed through an inductive-analytical approach. Findings indicated indigenous knowledge framed along lived experiences, fostered by open knowledge production in the cultural institutions. This enabled rationalization of successive floods, over time, favoring a conceptualization of the context-specific processes through which flooding turns into disaster. This indigenous conceptualization not only exposes blind spots in the scientific evidence on context-specific processes of floods; it further illustrated how, through history, flood risk is a primary consequence of pressures that are sociopolitical and capitalist in nature. These pressures tend to undermine indigenous knowledge of flood risk specificities, favor watershed degradation, aggravate exposure, and hamper community-based investments that would enhance resilience. This exposition of distal pressures neglected by scientists highlights the indispensable role of indigenous perspectives in understanding context-specific disaster risk. Graphic abstract Indigenous knowledge construction framework and its influencing factors in practice.

Suggested Citation

  • Bosco Bwambale & Martine Nyeko & John Sekajugo & Matthieu Kervyn, 2022. "The essential contribution of indigenous knowledge to understanding natural hazards and disaster risk: historical evidence from the Rwenzori (Uganda)," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(3), pages 1847-1867, February.
  • Handle: RePEc:spr:nathaz:v:110:y:2022:i:3:d:10.1007_s11069-021-05015-x
    DOI: 10.1007/s11069-021-05015-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-021-05015-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-021-05015-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nabajit Hazarika & Tanuj Tayeng & Apurba Kumar Das, 2016. "Living in troubled waters: stakeholders’ perception, susceptibility and adaptations to flooding in the Upper Brahmaputra plain," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 1157-1176, September.
    2. Martin Kabenge & Joshua Elaru & Hongtao Wang & Fengting Li, 2017. "Characterizing flood hazard risk in data-scarce areas, using a remote sensing and GIS-based flood hazard index," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1369-1387, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohammed Sarfaraz Gani Adnan & Ashraf Dewan & Khatun E. Zannat & Abu Yousuf Md Abdullah, 2019. "The use of watershed geomorphic data in flash flood susceptibility zoning: a case study of the Karnaphuli and Sangu river basins of Bangladesh," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(1), pages 425-448, October.
    2. Alaa Ahmed & Guna Hewa & Abdullah Alrajhi, 2021. "Flood susceptibility mapping using a geomorphometric approach in South Australian basins," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 629-653, March.
    3. Preeti Ramkar & Sanjaykumar M. Yadav, 2021. "Flood risk index in data-scarce river basins using the AHP and GIS approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(1), pages 1119-1140, October.
    4. Chengwei Lu & Jianzhong Zhou & Zhongzheng He & Shuai Yuan, 2018. "Evaluating typical flood risks in Yangtze River Economic Belt: application of a flood risk mapping framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(3), pages 1187-1210, December.
    5. Alaa Ahmed & Abdullah Alrajhi & Abdulaziz Alquwaizany & Ali Al Maliki & Guna Hewa, 2022. "Flood Susceptibility Mapping Using Watershed Geomorphic Data in the Onkaparinga Basin, South Australia," Sustainability, MDPI, vol. 14(23), pages 1-23, December.
    6. Nikunj K. Mangukiya & Ashutosh Sharma, 2022. "Flood risk mapping for the lower Narmada basin in India: a machine learning and IoT-based framework," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(2), pages 1285-1304, September.
    7. Antonio J. Sanhouse-García & Jesús Gabriel Rangel-Peraza & Sergio A. Rentería-Guevara & Yaneth A. Bustos-Terrones & Zuriel D. Mora-Félix & Wenseslao Plata-Rocha & Sergio Alberto Monjardin-Armenta, 2021. "Flood-Prone Area Delineation in Urban Subbasins Based on Stream Ordering: Culiacan Urban Basin as a Study Case," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    8. Phukan, Mayur Mausoom & Hazarika, Nabajit & Bora, Plaban & Borah, Tapanjit & Konwar, Bolin Kumar, 2020. "Leveraging microalga feedstock for biofuel production and wasteland reclamation using remote sensing and ex situ experimentation," Renewable Energy, Elsevier, vol. 159(C), pages 973-981.
    9. Maelaynayn El baida & Farid Boushaba & Mimoun Chourak & Mohamed Hosni & Hichame Sabar, 2024. "Classification machine learning models for urban flood hazard mapping: case study of Zaio, NE Morocco," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(11), pages 10013-10041, September.
    10. Brian Nalumenya & Matteo Rubinato & Jade Catterson & Michael Kennedy & Hilary Bakamwesiga & Disan Wabwire, 2024. "Assessing the Potential Impacts of Contaminants on the Water Quality of Lake Victoria: Two Case Studies in Uganda," Sustainability, MDPI, vol. 16(20), pages 1-25, October.
    11. Ahmed M. Youssef & Ali M. Mahdi & Hamid Reza Pourghasemi, 2023. "Optimal flood susceptibility model based on performance comparisons of LR, EGB, and RF algorithms," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(2), pages 1071-1096, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:110:y:2022:i:3:d:10.1007_s11069-021-05015-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.