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A Quantitative Approach to Measure Adaptive Capacity to Floods

Undergraduate #61
Discipline: Ecology Environmental and Earth Sciences
Subcategory: Mathematics and Statistics

Xaimarie Hernandez Cruz - University of Puerto Rico at Mayaguez
Co-Author(s): Saylisse Davila, University of Puerto Rico at Mayaguez, Puerto Rico; Norbert Franqui, University of Puerto Rico at Mayaguez, Puerto Rico



In recent decades, natural hazards have gained relevance due to increased frequency, intensity, and the great devastation they have left behind around the world. Puerto Rico, a small island in the Caribbean, has attributes that makes it vulnerable to a variety of these natural hazards–most notably floods, tsunamis, and hurricanes. It is, thus, important that emergency managers create mitigation strategies against these phenomena to reduce the losses associated to them. While the Caribbean has recently experienced massive losses that can be linked to numerous natural hazards, historically, floods have been the leading cause of natural-hazard-driven damages in the region. This work addresses the development of an adaptive capacity index for tsunamis in the municipality of Rincón, PR. Adaptive capacity is the dimension of vulnerability that relates to what an individual does before, during, and after the onset of a natural hazard. This work proposes that adaptive capacity can be measured as a function of: mitigation, response, and recovery. Mitigation is what an individual or community does to prepare for a natural hazard. Response refers to how the individual reacts to the threat as it is unfolding. Lastly, recovery refers to how an individual or community recovers from the losses associated with the natural hazard once the state of emergency is over. Clearly, these dimensions are far more complex to quantify than other dimensions of vulnerability and this correlates with the lack of quantitative studies on adaptive capacity in the literature. Rincón was selected as the test bench, as it is challenging for emergency responders. Rincon’s low-lying coats and topography offers surfers great opportunities to catch waves. Its year-round warm weather attracts a remarkable number of winter birds, which contribute over 160,00 hotel registrations a year and a floating population eight times larger than its resident population. Emergency managers deal with a large number of tourists, mostly located within hazard-prone areas and almost completely ignorant of evacuation routes and, sometimes, even the area’s official language. Needless to say, Rincón was also greatly devastated by flood linked to hurricane María. To develop the adaptive capacity model, a conceptual framework was created based on literary research. This framework classified key variables of adaptive capacity into one of its three sub-dimensions. Using Cronbach’s alpha, the framework was reduced to the variables that significantly contributed to the measurement of the sub-dimensions. Using these variables and a custom survey, the adaptive capacity index was fitted as an Analytical Hierarchy Process (AHP) model. Results for this research include: (1) a conceptual framework for adaptive capacity, (2) a custom script for AHP analysis, and (3) the ranking of Rincon’s county sub-divisions in terms of adaptive capacity. The analysis of Rincon’s vulnerability will be further analyzed in the future.

Funder Acknowledgement(s): Sea Grant ; NOAA

Faculty Advisor: Saylisse Davila, saylisse.davila@upr.edu

Role: Of this research, I was responsible for collecting data, creating the conceptual framework, and writing the AHP script.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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