Community-based early warning systems (CBEWS) are increasingly promoted as an effective means of reducing disaster risk in climate-vulnerable settings, yet rigorous empirical assessments of their operational performance remain limited, particularly in sub-Saharan Africa. This qualitative single-case study applies the United Nations Office for Disaster Risk Reduction (UNDRR) four-pillar framework and draws on key informant interviews (n = 18), household interviews (n = 28), and four focus group discussions (n = 42) to examine the capacity and functioning of CBEWS among small-scale fishing communities along the southern shoreline of Lake Kariba, Zimbabwe. The findings indicate that while communities possess substantial local risk knowledge and well-established informal communication networks, system performance is constrained by inadequate monitoring infrastructure, poorly maintained equipment, limited accessibility and relevance of official forecasts, and insufficient response resources. Although formal structures and basic preparedness measures are in place, interconnected operational weaknesses undermine system reliability during hazardous events. Climate change is further reducing the predictability of traditional environmental indicators and weakening confidence in formal meteorological information, complicating risk anticipation and response. The study argues for a shift toward the continuous co-production of hybrid knowledge systems through sustained collaboration among holders of indigenous, scientific, practical, and technology-mediated knowledge. It proposes actionable recommendations to strengthen CBEWS in lacustrine and small-scale fishery contexts across Africa, including the establishment of co-production platforms, investment in resilient last-mile infrastructure, the integration of informal and formal risk-financing mechanisms, and the institutionalisation of community-based early warning roles. These findings contribute to efforts to operationalise the Sendai Framework and the Early Warnings for All initiative in resource-constrained rural environments.
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- Article
Operational Performance of Community-Based Early Warning Systems for Climate-Related Hazards: Evidence from Lake Kariba, Zimbabwe
Author Information
Received: 15 Jan 2026 | Revised: 04 Feb 2026 | Accepted: 25 Feb 2026 | Published: 18 Mar 2026
Abstract
Keywords
community early warning | disaster risk reduction | climate adaptation | hybrid knowledge | small-scale fisheries | Zimbabwe
References
- 1.
Intergovernmental Panel on Climate Change (IPCC). Climate Change 2022: Impacts, Adaptation and Vulnerability. Working Group II Contribution to the IPCC Sixth Assessment Report; IPCC: Geneva, Switzerland, 2022.
- 2.
United Nations Office for Disaster Risk Reduction (UNDRR). Global Assessment Report on Disaster Risk Reduction 2025: Resilience Pays: Financing and Investing for our Future; UNDRR: Geneva, Switzerland, 2025.
- 3.
Intergovernmental Panel on Climate Change (IPCC). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change; Cambridge University Press: Cambridge, UK, 2021.
- 4.
Islam, N.; Winkel, J. Climate Change and Social Inequality; DESA Working Paper No. 152; Department of Economic & Social Affairs: New York, NY, USA, 2017. Available online: https://www.un.org/esa/desa/papers/2017/wp152_2017.pdf (accessed on 20 November 2025).
- 5.
O’Sullivan, A.; Omukuti, J.; Ryder, S.S. Global Surpluses of Extraction and Slow Climate Violence: A Sociological Framework. Sociol. Inq. 2022, 93, 320–340. https://doi.org/10.1111/soin.12518.
- 6.
Islam, M.M.; Hasan, M.; Mia, M.S.; et al. Early Warning Systems in Climate Risk Management: Roles and Implementations in Eradicating Barriers and Overcoming Challenges. Nat. Hazards Res. 2025, 5, 523–538. https://doi.org/10.1016/j.nhres.2025.01.007.
- 7.
World Meteorological Organization (WMO). The UN Global Early Warning Initiative for the Implementation of Climate Adaptation: Executive Action Plan 2023–2027; World Meteorological Organization: Geneva, Switzerland, 2022.
- 8.
United Nations Office for Disaster Risk Reduction (UNDRR). The Sendai Framework Terminology on Disaster Risk Reduction; UNDRR: Geneva, Switzerland, 2017. Available online: https://www.undrr.org/terminology/early-warning-system (accessed on 17 November 2025).
- 9.
Smith, P.J.; Brown, S.; Dugar, S. Community-Based Early Warning Systems for Flood Risk Mitigation in Nepal. Nat. Hazards Earth Syst. Sci. 2017, 17, 423–437. https://doi.org/10.5194/nhess-17-423-2017.
- 10.
International Federation of Red Cross and Red Crescent Societies (IFRC). Early Warning Early Action: A Regional Guideline for Effective Engagement; IFRC South East Asia Regional Office: Bangkok, Thailand, 2010.
- 11.
United Nations International Strategy for Disaster Reduction (UNISDR). Sendai Framework for Disaster Risk Reduction 2015–2030; UNISDR: Geneva, Switzerland, 2015.
- 12.
Tupper, A.C.; Fearnley, C.J. Mind the Gaps in Disaster Early-Warning Systems—And Fix Them. Nature 2023, 623, 479. https://doi.org/10.1038/d41586-023-03510-8.
- 13.
Baudoin, M.-A.; Henly-Shepard, S.; Fernando, N.; et al. From Top-Down to ‘Community-Centric’ Approaches to Early Warning Systems: Exploring Pathways to Improve Disaster Risk Reduction Through Community Participation. Int. J. Disaster Risk Sci. 2016, 7, 163–174. https://doi.org/10.1007/s13753-016-0085-6.
- 14.
Canwat, V. Social Innovations and Drivers in Flood Early Warning Systems: A Community-Based Transboundary Perspective from Elegu Flood Plain in Northern Uganda. J. Flood Risk Manag. 2023, 18, e12930. https://doi.org/10.1111/jfr3.12930.
- 15.
Dixon, N.; Smith, A.; Pietz, M. A Community-Operated Landslide Early Warning Approach: Myanmar Case Study. Geoenviron. Disasters 2022, 9, 18. https://doi.org/10.1186/s40677-022-00220-7.
- 16.
Pham, T.D.M.; Thieken, A.H.; Bubeck, P. Community-Based Early Warning Systems in a Changing Climate: An Empirical Evaluation from Coastal Central Vietnam. Clim. Dev. 2024, 16, 673–684. https://doi.org/10.1080/17565529.2024.2307398.
- 17.
Sufri, S.; Dwirahmadi, F.; Phung, D.; et al. A Systematic Review of Community Engagement (CE) in Disaster Early Warning Systems (EWSs). Prog. Disaster Sci. 2020, 5, 100058. https://doi.org/10.1016/j.pdisas.2019.100058.
- 18.
Marchezini, V. What Is a Sociologist Doing Here? An Unconventional People-Centered Approach to Improve Warning Implementation in the Sendai Framework for Disaster Risk Reduction. Int. J. Disaster Risk Sci. 2020, 11, 218–229. https://doi.org/10.1007/s13753-020-00262-1.
- 19.
Domingos, B.; Nagamatsu, S. Why Are Community-Based Early Warning Systems Inadequate? A Case Study of the Licungo River Basin, in Mozambique. IDRiM J. 2024, 14, 95–126. https://doi.org/10.5595/001c.123357.
- 20.
Macherera, M.; Chimbari, M.J. A Review of Studies on Community Based Early Warning Systems. Jàmbá J. Disaster Risk Stud. 2016, 8, a206. https://doi.org/10.4102/jamba.v8i1.206.
- 21.
Muringai, T.R.; Naidoo, D.; Mafongoya, P. The Challenges Experienced by Small-Scale Fishing Communities of Lake Kariba, Zimbabwe. J. Transdiscipl. Res. South. Afr. 2020, 16, a704. https://doi.org/10.4102/td.v16i1.704.
- 22.
UNISDR. Developing Early Warning Systems: A Checklist. Third International Conference on Early Warning (EWC III); UNISDR: Geneva, Switzerland, 2006. Available online: https://www.undrr.org/publication/developing-early-warning-systems-checklist-third-international-conference-early-warning (accessed on 20 November 2025).
- 23.
United Nations Office for Disaster Risk Reduction (UNDRR). Executive Summary. In Gender-Responsive and Disability-Inclusive Early Warning and Early Action in the Pacific Region; United Nations: New York, NY, USA, 2023. https://doi.org/10.18356/9789210028998c002.
- 24.
Basher, R. Global Early Warning Systems for Natural Hazards: Systematic and People-Centred. Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2006, 364, 2167–2182. https://doi.org/10.1098/rsta.2006.1819.
- 25.
García, C. Designing and Implementing More Effective Integrated Early Warning Systems in Mountain Areas: A Case Study from Northern Italy. J. Alp. Res. Rev. De Géographie Alp. 2012, 100-1. https://doi.org/10.4000/rga.1679.
- 26.
Tarchiani, V.; Massazza, G.; Rosso, M.; et al. Community and Impact Based Early Warning System for Flood Risk Preparedness: The Experience of the Sirba River in Niger. Sustainability 2020, 12, 1802. https://doi.org/10.3390/su12051802.
- 27.
Food and Nutrition Council (FNC). 2022 District Food and Nutrition Security Profile: Kariba; Government of Zimbabwe: Harare, Zimbabwe; World Food Programme: Rome, Italy, 2022. Available online: https://www.fnc.org.zw/wp-content/uploads/2023/04/Kariba-District-Profile.pdf (accessed on 19 November 2025).
- 28.
Ndhlovu, N.; Saito, O.; Djalante, R.; et al. Assessing the Sensitivity of Small-Scale Fishery Groups to Climate Change in Lake Kariba, Zimbabwe. Sustainability 2017, 9, 2209. https://doi.org/10.3390/su9122209.
- 29.
Nkoka, F.S. Mainstreaming Disaster Risk Reduction and Climate Change Adaptation into Local Development Planning in Zimbabwe (Vol. 4 of 4): Early Warning System and Serve People at the Community Level; World Bank Group: Washington, DC, USA, 2019.
- 30.
Khoza, S.; Nhamo, G. Revisiting Zimbabwe’s Early Warning Systems in the Light of Tropical Cyclone Idai. In Cyclones in Southern Africa: Volume 2—Foundational and Fundamental Topics; Nhamo, G., Dube, K., Eds.; Springer: Cham, Switzerland, 2021; pp. 53–70. https://doi.org/10.1007/978-3-030-74262-1_4.
- 31.
Civil Protection Department. Roles and Organisation of the Civil Protection Department and Disaster Risk Management; Presentation; Government of Zimbabwe: Harare, Zimbabwe, 2024.
- 32.
Chinguwo, D.; Deus, D. Assessment of Community-Based Flood Early Warning System in Malawi. Jàmbá J. Disaster Risk Stud. 2022, 14, 1166. https://doi.org/10.4102/jamba.v14i1.1166.
- 33.
Le, S.T.H.; Bond, J.; Dung, N.T.; et al. Farmers’ Barriers to the Access and Use of Climate Information in the Mountainous Regions of Thừa Thiên Huế Province, Vietnam. Clim. Serv. 2021, 24, 100267. https://doi.org/10.1016/j.cliser.2021.100267.
- 34.
Aguirre-Ayerbe, I.; Merino, M.; Aye, S.L.; et al. An Evaluation of Availability and Adequacy of Multi-Hazard Early Warning Systems in Asian Countries: A Baseline Study. Int. J. Disaster Risk Reduct. 2020, 49, 101749. https://doi.org/10.1016/j.ijdrr.2020.101749.
- 35.
Lauer, M. Oral Traditions or Situated Practices? Understanding How Indigenous Communities Respond to Environmental Disasters. Hum. Organ. 2012, 71, 176–187. https://doi.org/10.17730/humo.71.2.j0w0101277ww6084.
- 36.
Mutasa, M. Knowledge Apartheid in Disaster Risk Management Discourse: Is Marrying Indigenous and Scientific Knowledge the Missing Link? Jàmbá J. Disaster Risk Stud. 2015, 7, 1–10. https://doi.org/10.4102/jamba.v7i1.150.
- 37.
Walker, D.W.; Smigaj, M.; Tani, M. The benefits and negative impacts of citizen science applications to water as experienced by participants and communities. Wiley Interdiscip. Rev. Water 2021, 8, e1488.
- 38.
Klimes, M.; Michel, D.; Yaari, E.; et al. Water Diplomacy: The Intersect of Science, Policy and Practice. J. Hydrol. 2019, 575, 1362–1370. https://doi.org/10.1016/j.jhydrol.2019.02.049.
- 39.
Tengö, M.; Brondizio, E.S.; Elmqvist, T.; et al. Connecting Diverse Knowledge Systems for Enhanced Ecosystem Governance: The Multiple Evidence Base Approach. Ambio 2014, 43, 579–591. https://doi.org/10.1007/s13280-014-0501-3.
- 40.
Nguyen, C.D.; Ubukata, F.; Nguyen, Q.T.; et al. Long-Term Improvement in Precautions for Flood Risk Mitigation: A Case Study in the Low-Lying Area of Central Vietnam. Int. J. Disaster Risk Sci. 2021, 12, 250–266. https://doi.org/10.1007/s13753-020-00326-2.
- 41.
Njaya, F.; Kafumbata, D.; Mtapika, D.; et al. Weather Information Sources, Dissemination, and Utilisation in Small-Scale Fishing Communities in Southern Malawi. Environ. Commun. 2020, 14, 1120–1136. https://doi.org/10.1080/17524032.2020.1780454.
- 42.
Mukoka, M.; Mhango, O.; Twabi, H.H.; et al. The Influence of Social Networks in Adoption of Integrated Health Interventions: A Qualitative Study of Fishermen in Malawi. PLOS Glob. Public Health 2025, 5, e0004581. https://doi.org/10.1371/journal.pgph.0004581.
- 43.
Thieken, A.H.; Bubeck, P.; Heidenreich, A.; et al. Performance of the Flood Warning System in Germany in July 2021—Insights from Affected Residents. Nat. Hazards Earth Syst. Sci. 2023, 23, 973–990. https://doi.org/10.5194/nhess-23-973-2023.
- 44.
Sahana, M.; Patel, P.P.; Rehman, S.; et al. Assessing the Effectiveness of Existing Early Warning Systems and Emergency Preparedness towards Reducing Cyclone-Induced Losses in the Sundarban Biosphere Region, India. Int. J. Disaster Risk Reduct. 2023, 90, 103645. https://doi.org/10.1016/j.ijdrr.2023.103645.
- 45.
Ramadhani, J.; Seme, S. Unlocking the Perceptions of Fishing Communities for a Credible and Effective Weather Forecasting and Early-Warning System in Zanzibar, Tanzania. Int. J. Innov. Res. Dev. 2024, 12, 59–68. https://doi.org/10.24940/ijird/2023/v12/i11/NOV23005.
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