BAYESIAN NETWORK FOR RISK ASSESSMENT OF ABRASION PROCESSES IN THE COASTAL AREA OF THE SEA OF AZOV

Abstract

The coast of the Sea of Azov is characterized by a high population density and economic development. At the same time, a significant part of the sea coast is subject to abrasion. High coastal cliff retreat rates determine the relevance of assessing possible losses in this region. The aim of the work is to develop a model for assessing the risk of abrasion processes in the coastal zone of the Sea of Azov. Bayesian networks, which are often used to study coastal processes, were selected as a model toolkit. To assess the abrasion hazard in the coastal zone of the Sea of Azov, a network, consisting of two subnets, is proposed. The “Hazard Assessment” subnet describes the effect of exogenous factors on the abrasion rate. The “Risk Assessment” subnet is designed to determine the consequences (the magnitude of expected losses) of the abrasion process. The main attention is paid to the characteristics of the Bayesian network nodes. In the model, the risk from hazardous coastal processes is expressed in natural terms: the lost land area and the number of damaged facilities located on the coast. The Bayesian model is coupled with a geographic information system on base of the geospatial representation of the study region. An example of assessment the lost land area for a part of the Taganrog Bay coast is considered. Comparison of the losses estimates based on Bayesian network and average abrasion rate is given. Proposed probabilistic method provide additional information, enriching the decision-making process.