The study is dedicated to developing a structure to forecast risks of transport accidents in inland waterway transport. The authors have analysed international and Russian sources in ScienceDirect and eLIBRARY. As a result of the analysis, the need for the development of a system for the inland waterway transport of Russia has been detected. The combination of the statistical methods to forecast risks based on the accumulated data arrow on the transport accidents and the visualisation of the spread of contamination caused by a specific accident helps obtain a more comprehensive and full-fledged idea of risks associated with hazardous cargos as a result of grounding, flooding, ship collisions, etc.
Using the systemic approach and methods of generalization, mathematical logic, and accident decomposition, the objectives of the forecasting and analytical system, stages of its implementation, and the necessary risk portfolio have been determined as well as its place in the existing system of management and monitoring of emergencies and information flow exchange between various srtuctures of environmental management and monitoring. For the purposes of automation of calculation procedures in accordance with math models developed earlier and practical implementation of the suggested approaches, the architecture of the proposed forecasting and analytical system has been developed, and its component modules have been described. i.e., information entering, storage, and processing; forecasting the risk of transport accidents; evaluating their consequences; modelling the spread of contaminants, and mapping. When forming the modules, the combination of two approaches to forecasting consequences of transport accidents has been considered, that is, the «regulatory» approach performed in accordance with the effective and approved methodologies and the «modeling» approach to forecast using the advanced computational methods. Developing algorithms for the forecasting and analytical system and their testing is planned for further studies.
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