Moskva, Moscow, Russian Federation
The main difficulty of describing natural emergency as a random process is the large number of parameters that must be quantified. Authors suggest threating the onset of emergency as a discrete random variable; each possible implementation corresponds to the defined size of the expected damage to transportation infrastructure. The analysis of the engineering and environmental surveys via geo-information technologies identified expected probability of occurrence and scale of the annual damage for 10 types of emergency situations on long-term (up to 2030) for State Company Russian Highways road network.
road network planning, emergencies risk, damage forecasting, GIS technology.
1. Введение
Чрезвычайные ситуации (ЧС) природного и техногенного происхождения неизбежно связаны с нарушением нормального режима жизнедеятельности, разрушением инфраструктуры, нанесением вреда здоровью и созданием угрозы для жизни людей. Ежегодные расходы на ликвидацию только наиболее острых последствий ЧС составляют в России, по оценкам 2013 г., 224,4 млрд руб. [1].
В предлагаемых различными исследователями методах оценки и прогнозирования вреда от ЧС можно выделить два основных направления. Первое не предполагает формализованного описания процессов ЧС и основано на построении многоаспектных экономико-математических моделей, в которых прогнозирование вреда основывается на статистических данных о вреде за прошлые периоды [2–4]. При этом повышение точности прогноза достигается либо за счет использования статистических методов, наиболее эффективных при решении конкретных задач [5–7], либо в результате учета особенностей отдельных видов ЧС [8]. Вторая группа методов оценки и прогнозирования вреда основана на формальных вероятностных моделях, в которых в явном виде присутствуют параметры риска (вероятности) возникновения ЧС [9, 10]. Подобный подход позволяет более адекватно описывать процессы неблагоприятных природных явлений, в том числе с учетом особенностей их отдельных видов. В то же время возникают дополнительные трудности по количественной оценке параметров, входящих в вероятностные модели. Особенно заметно эти трудности проявляются при рассмотрении больших территорий, в пределах которых характер проявления ЧС существенно различается, а значит, различны и значения параметров в их формализованном описании. Особенности определения вреда для линейных и пространственно-распределенных объектов рассмотрены, например в [11–14].
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