Assessment of Socio-Environmental Vulnerability Due to Tropical Cyclones in La Paz, Baja California Sur, Mexico

• Main Authors: Elvia Aida Marín-Monroy, Víctor Hernández Trejo, Miguel Angel Ojeda Ruiz de la Pena, Gerzain Avilés Polanco, Nuñez León Barbara
• Format: Article
• Language: English
• Published: MDPI AG 2020-02-01
• Series: Sustainability
• Subjects: risk index; vulnerable population; tropical cyclones; maps; mexico northwest
• Online Access: https://www.mdpi.com/2071-1050/12/4/1575

Climate change will increase the likelihood of adverse events such as droughts, forest fires, and intensification of tropical cyclones, which are known to cause flooding (IPCC, 2014). The effects of these events are a cause of concern for both authorities and citizens, so they prioritize actions that reduce adverse impacts, especially in cities with higher risk. Therefore, the objective of this work was to measure the degree of socio-environmental vulnerability of households to identify the risk areas in the city of La Paz, Baja California Sur, one of the regions with a high degree of incidence of hurricanes in the northwest of Mexico. For this, surveys were carried out with heads of households in 251 homes, and information was aggregated to calculate the vulnerability index through principal components analysis (PCA), which were stratified by the Dalenius−Hodges method, the degree of vulnerability was classified into three categories by the Opiyo method, considering three strata of the Likert scale, 1 = highly vulnerable, 2 = moderately vulnerable, 3 = less vulnerable. The results showed that households that are in the highly vulnerable category are 33% within a range of the index −3.77243 to −0.939141. Moderately vulnerable households constitute 36% with values from −0.929141 to 0.956385. While the least vulnerable represent 31% of households with an index range of 0.966385 to 5.6952. The results have revealed the levels of high and moderate socio-environmental vulnerability by tropical cyclones of 69% homes in La Paz. The above allowed to generate risk maps that will be taken into account in planning and civil protection over adverse events.