Flood hazard and risk assessment in Russia

Flood risk assessment is usually performed by application of sophisticated mathematical models of river flow. However, there are cases when it is required to assess the risk in the lack of data conditions or a limited time available. In such cases, it is advisable to use some simplifications, which provide reliable results faster. This study proposes a hybrid approach to the flood risk assessment combining quantitative and qualitative indicators. The article describes various methods to assess the flood risk, such as likelihood of flooding, magnitude of the flood, average annual damage, maximum damage and expectation of damage. The authors examined special cases of calculation of the mathematical expectation of harm and zoning in the corresponding indicators. This approach is designed for the conditions of the Russian Federation, but it can be adapted for other regions. It is based on the use of two types of risk maps. The first type of maps is intended to define the mathematical expectation of damage zones for reference building with possibility of risk calculation for other buildings using multiple factors. The second type of maps is designed for the purposes of land use regulation for floodplains based on a priori statistical estimates of flood risk.     

Flood hazard and risk assessment in Russia

The occurrence of rockfall incidents on the transportation network may cause injuries, and even casualties, as well as severe damage to infrastructure such as dwellings, railways, road corridors, etc. Passive protective measures (i.e., rockfall barriers, wire nets, etc.) are mainly deployed by operators of ground transport networks to minimize the impact of detrimental effects on these networks. In conjunction with these passive measures, active rockfall monitoring should ideally include the magnitude of each rockfall, its initial and final position, and the triggering mechanism that might have caused its detachment from the slope. In this work, the operational principle of a low-cost rockfall monitoring and alerting system is being presented. The system integrates measurements from a multi-channel seismograph and commercial cameras as the primary equipment for event detection. A series of algorithms analyze these measurements independently in order to reduce alarms originated by surrounding noise and sources other than rockfall events. The detection methodology employs two different sets of algorithms: Time–frequency analyses of the rockfall event’s seismic signature are performed using moving window pattern recognition algorithms, whereas image processing techniques are utilized to deliver object detection and localization. Training and validation of the proposed approach was performed through field tests that involved manually induced rockfall events and recording of sources (i.e., passing car, walking people) that may cause a false alarm. These validation tests revealed that the seismic monitoring algorithms produce a 4.17 % false alarm rate with an accuracy of 93 %. Finally, the results of a 34-day operational monitoring period are presented and the ability of the imaging system to identify and exclude false alarms is discussed. The entire processing cycle is 10–15 s. Thus, it can be considered as a near real-time system for early warning of rockfall events.