TY - JOUR
T1 - Does a Citizen Science Approach Enhance the Effectiveness of Flood Early Warning Systems? Evidence from the Akaki Catchment, Ethiopia
AU - Nigussie, Likimyelesh
AU - Bekele, Tilaye Worku
AU - Haile, Alemseged Tamiru
AU - Mdee, Anna
AU - Nicol, Alan
AU - Cohen, Joshua
AU - Osei-Amponsah, Charity
AU - Tedla, Hailay Zeray
AU - Demissie, Kirubel
N1 - Publisher Copyright:
© 2025 The Author(s).
PY - 2025
Y1 - 2025
N2 - Flooding has emerged as a significant concern in the Akaki catchment area of Ethiopia, affecting settlements and properties. Early warning systems (EWSs) are implemented to reduce flood risks, but power dynamics among at-risk communities and stakeholders have raised concerns about the reliable accessibility of warning information. We integrated a citizen science approach into existing flood EWSs to promote inclusivity, local perspectives, and equitable expertise distribution in flood early warning. It draws on primary data collected through diverse methods, alongside an extensive review of documents from the years 2021 to 2022. The analysis of qualitative data indicates the integration of citizen science into a flood EWSs delivers dependable early warning information and encourages the establishment of networks. This approach reduces dependence on external entities, enhances local decision-making capabilities, and promotes a sense of ownership, empowerment, and trust. This can transform the dynamics and responsibilities linked to flood management. However, the longer-term participation of citizen scientists in flood EWSs is challenging due to the disparity between commitment levels and benefits, lack of legal frameworks, and insufficient recognition of community diversity within policy frameworks. The research herein emphasizes the significance of understanding power dynamics and institutional capacities in integrating citizen science into flood EWSs. It offers valuable perspectives for policymakers, practitioners, and communities on participatory governance, social equity, and the resilience of communities in the face of environmental challenges.
AB - Flooding has emerged as a significant concern in the Akaki catchment area of Ethiopia, affecting settlements and properties. Early warning systems (EWSs) are implemented to reduce flood risks, but power dynamics among at-risk communities and stakeholders have raised concerns about the reliable accessibility of warning information. We integrated a citizen science approach into existing flood EWSs to promote inclusivity, local perspectives, and equitable expertise distribution in flood early warning. It draws on primary data collected through diverse methods, alongside an extensive review of documents from the years 2021 to 2022. The analysis of qualitative data indicates the integration of citizen science into a flood EWSs delivers dependable early warning information and encourages the establishment of networks. This approach reduces dependence on external entities, enhances local decision-making capabilities, and promotes a sense of ownership, empowerment, and trust. This can transform the dynamics and responsibilities linked to flood management. However, the longer-term participation of citizen scientists in flood EWSs is challenging due to the disparity between commitment levels and benefits, lack of legal frameworks, and insufficient recognition of community diversity within policy frameworks. The research herein emphasizes the significance of understanding power dynamics and institutional capacities in integrating citizen science into flood EWSs. It offers valuable perspectives for policymakers, practitioners, and communities on participatory governance, social equity, and the resilience of communities in the face of environmental challenges.
KW - Akaki catchment area
KW - citizen science
KW - community-based flood early warning system
KW - disaster risk management
KW - Ethiopia
KW - power dynamics
UR - http://www.scopus.com/inward/record.url?scp=85219658063&partnerID=8YFLogxK
U2 - 10.5334/cstp.763
DO - 10.5334/cstp.763
M3 - Article
AN - SCOPUS:85219658063
SN - 2057-4991
VL - 10
JO - Citizen science
JF - Citizen science
IS - 1
M1 - 9
ER -