Analysis of the ecological vulnerability of the Krasnodar Krai population using a multifactor demographic model

In a global context, the complex concept of disaster risk, vulnerability and risk has changed over the past twenty years. However, its methods and models are being developed at different levels in foreign countries and Russia. In this article, the authors examine current issues related to assessing the environmental vulnerability of Russians during river floods in the South. An example of ten model subjects from Krasnodar Krai located in the Kuban River basin is used to test the Multifactor Demographic Environmental Vulnerability Model. Vulnerability assessment algorithm consists of three interconnected blocks: variable selection and calculation; developing a ranking matrix for obtained quantitative indicators, calculated individually for each model subject (municipality) using a unified methodology and creating a cartographic spatial model ranking the environmental vulnerability of the model subjects. The QGIS geographic information system was used to create a cartographic model of the spatial distribution of vulnerable population groups. There are two factors in the model: demographics (including persons aged 0 to 19 years and those aged 65 and older, and persons with disabilities, i.e., the proportion of disabled individuals, type of residential premises occupied and household composition, and lack of familiarity with the location of residence) and socioeconomics (low-income groups, dependents, telecommunications, and level of education). Areas (Armavir and Krasnodar municipalities, Krymsk and Ust-Labinsk rayons) and populations (elderly, individuals with disabilities, and one-person households in an individual house, and households in an individual house) that are most vulnerable were identified. The results obtained may contribute to improving the efficiency of management decisions at the county level taken by emergency management authorities, demographic policy, spatial planning and urban development, health, and social protection, to reduce the risk of disasters from floods.

quality of life, environmental risk, riverine floods, Krasnodar Krai, geoinformation mapping, economic and demographic model, health and social care issues