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<p>Floods pose significant risks to lives, livelihoods, and infrastructure in the Itang watershed of the Gambella Region, southwestern Ethiopia. This study assessed watershed-level flood vulnerability by integrating physical, social, and economic dimensions using 22 context-specific indicators. Primary data from 373 households across nine villages were combined with secondary geospatial and institutional data. Indicators were normalized using min–max scaling, and weights were assigned through the Iyengar and Sudarshan (1982) unequal weighting method, which gives higher importance to indicators with lower variability. A GIS-based Flood Vulnerability Index (FVI) was computed, producing spatially explicit vulnerability maps. Results showed considerable spatial heterogeneity: Itang Town recorded very high vulnerability (FVI = 0.89), Dorong high vulnerability (0.62), while Achewa, Ajuwa, Awgni, Adima, and Birhane Selam demonstrated moderate vulnerability (0.34–0.46). Akura and Aleha were least vulnerable (0.23). The analysis underscores the dominant role of social vulnerability and physical exposure in shaping flood risk, with economic fragility also recognized as an important but sometimes underrepresented factor. The study recommends that enhancing early warning systems, improving infrastructure, and adopting localized, community-based flood risk reduction strategies to strengthen resilience. This integrated, data-driven approach provides a practical framework for policymakers and NGOs aiming to reduce flood impacts in similar flood-prone areas.</p>

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Flood vulnerability analysis in the Itang watershed, lower Baro-Akobo basin, Southwestern Ethiopia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年9月26日

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  • Shibiru Chengu,
  • Mohammed Assen,
  • Elias Gebeyehu

摘要

Floods pose significant risks to lives, livelihoods, and infrastructure in the Itang watershed of the Gambella Region, southwestern Ethiopia. This study assessed watershed-level flood vulnerability by integrating physical, social, and economic dimensions using 22 context-specific indicators. Primary data from 373 households across nine villages were combined with secondary geospatial and institutional data. Indicators were normalized using min–max scaling, and weights were assigned through the Iyengar and Sudarshan (1982) unequal weighting method, which gives higher importance to indicators with lower variability. A GIS-based Flood Vulnerability Index (FVI) was computed, producing spatially explicit vulnerability maps. Results showed considerable spatial heterogeneity: Itang Town recorded very high vulnerability (FVI = 0.89), Dorong high vulnerability (0.62), while Achewa, Ajuwa, Awgni, Adima, and Birhane Selam demonstrated moderate vulnerability (0.34–0.46). Akura and Aleha were least vulnerable (0.23). The analysis underscores the dominant role of social vulnerability and physical exposure in shaping flood risk, with economic fragility also recognized as an important but sometimes underrepresented factor. The study recommends that enhancing early warning systems, improving infrastructure, and adopting localized, community-based flood risk reduction strategies to strengthen resilience. This integrated, data-driven approach provides a practical framework for policymakers and NGOs aiming to reduce flood impacts in similar flood-prone areas.