{"title":"Index-based mapping and assessment of flood vulnerability for climate adaptation at the neighborhood level: A case study of Santo Domingo, the Dominican Republic","authors":"Kirverlin Valera , Ayyoob Sharifi","doi":"10.1016/j.ijdrr.2025.105362","DOIUrl":null,"url":null,"abstract":"<div><div>Urban flooding is a growing challenge in densely populated cities, leading to significant human and economic losses worldwide. While progress has been made in flood risk management, assessments of neighborhood-level vulnerability remain neglected in cities across Latin America and the Dominican Republic. This study addressed this gap by developing a Flood Vulnerability Index (FVI) for Santo Domingo, integrating geospatial analysis and multi-criteria decision-making methods. Key indicators were identified through a literature review and expert consultations. The Analytical Hierarchy Process (AHP) was used to assign weights to the indicators integrating exposure, sensitivity, and adaptive capacity. These were then aggregated to construct the FVI. The results, mapped at the neighborhood level and classified into vulnerability categories revealed disparities among neighborhoods of Santo Domingo, with 67 % of the neighborhoods moderately vulnerable, 19 % highly vulnerable, 13 % low vulnerable, and 6 % very highly vulnerable. Adaptive capacity emerged as the most significant determinant of vulnerability, surpassing exposure and sensitivity, emphasizing the need to prioritize interventions that enhance urban resilience. Several solutions have been proposed to bolster the adaptation capacity and mitigate the vulnerability of neighborhoods. Key policy recommendations include enhancing early warning systems, expanding urban green spaces, and improving flood protection infrastructure. This study provides a robust, GIS-based framework for identifying vulnerable areas and guiding targeted adaptation strategies. The framework can facilitate identifying vulnerable areas and guiding targeted adaptation strategies, offering valuable insights for urban planners, policymakers, and local communities in Santo Domingo and similar urban contexts.</div></div>","PeriodicalId":13915,"journal":{"name":"International journal of disaster risk reduction","volume":"120 ","pages":"Article 105362"},"PeriodicalIF":4.2000,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of disaster risk reduction","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212420925001864","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
Index-based mapping and assessment of flood vulnerability for climate adaptation at the neighborhood level: A case study of Santo Domingo, the Dominican Republic
Urban flooding is a growing challenge in densely populated cities, leading to significant human and economic losses worldwide. While progress has been made in flood risk management, assessments of neighborhood-level vulnerability remain neglected in cities across Latin America and the Dominican Republic. This study addressed this gap by developing a Flood Vulnerability Index (FVI) for Santo Domingo, integrating geospatial analysis and multi-criteria decision-making methods. Key indicators were identified through a literature review and expert consultations. The Analytical Hierarchy Process (AHP) was used to assign weights to the indicators integrating exposure, sensitivity, and adaptive capacity. These were then aggregated to construct the FVI. The results, mapped at the neighborhood level and classified into vulnerability categories revealed disparities among neighborhoods of Santo Domingo, with 67 % of the neighborhoods moderately vulnerable, 19 % highly vulnerable, 13 % low vulnerable, and 6 % very highly vulnerable. Adaptive capacity emerged as the most significant determinant of vulnerability, surpassing exposure and sensitivity, emphasizing the need to prioritize interventions that enhance urban resilience. Several solutions have been proposed to bolster the adaptation capacity and mitigate the vulnerability of neighborhoods. Key policy recommendations include enhancing early warning systems, expanding urban green spaces, and improving flood protection infrastructure. This study provides a robust, GIS-based framework for identifying vulnerable areas and guiding targeted adaptation strategies. The framework can facilitate identifying vulnerable areas and guiding targeted adaptation strategies, offering valuable insights for urban planners, policymakers, and local communities in Santo Domingo and similar urban contexts.
期刊介绍:
The International Journal of Disaster Risk Reduction (IJDRR) is the journal for researchers, policymakers and practitioners across diverse disciplines: earth sciences and their implications; environmental sciences; engineering; urban studies; geography; and the social sciences. IJDRR publishes fundamental and applied research, critical reviews, policy papers and case studies with a particular focus on multi-disciplinary research that aims to reduce the impact of natural, technological, social and intentional disasters. IJDRR stimulates exchange of ideas and knowledge transfer on disaster research, mitigation, adaptation, prevention and risk reduction at all geographical scales: local, national and international.
Key topics:-
-multifaceted disaster and cascading disasters
-the development of disaster risk reduction strategies and techniques
-discussion and development of effective warning and educational systems for risk management at all levels
-disasters associated with climate change
-vulnerability analysis and vulnerability trends
-emerging risks
-resilience against disasters.
The journal particularly encourages papers that approach risk from a multi-disciplinary perspective.