Use of an agent based model and Monte Carlo analysis to estimate the effectiveness of emergency management interventions to reduce loss of life during extreme floods

Lumbroso, D. and Davison, M. (2016) Use of an agent based model and Monte Carlo analysis to estimate the effectiveness of emergency management interventions to reduce loss of life during extreme floods. Journal of Flood Risk Management.

Full text not available from this repository.
Official URL: http://onlinelibrary.wiley.com/doi/10.1111/jfr3.12...

Abstract

This paper describes the use of an agent-based model, known as the Life Safety Model (LSM) and a Monte Carlo analysis to assess the effectiveness of emergency management interventions in terms of loss of life, taking into account uncertainties in the physical characteristics of the population at risk, represented by people’s height and mass. The work considered Canvey Island as a case study, which is located in the Thames Estuary. The average ground level of the island is 1 m below the mean high tide level. Canvey Island is protected against inundation by a series of flood defences. In 1953, the island was inundated by the Great North Sea Flood that breached the defences and led to the deaths of 58 people. A number of emergency management interventions (e.g. safe havens, flood warnings) were considered to ascertain if the loss of life in 1953 could have been reduced. The LSM was found to be an effective tool to compare different emergency management measures in order to ensure that loss of life is minimised when an extreme flood event occurs.

Item Type: Article
Uncontrolled Keywords: agent-based model; floods; emergency management; loss of life; Monte Carlo analysis
Subjects: Floods > Flood impacts
Floods > General
Floods > Flood incident management
Divisions: Floods
Depositing User: Unnamed user with email i.services@hrwallingford.com
Date Deposited: 02 Apr 2020 09:53
Last Modified: 22 Jan 2024 15:14
URI: http://eprints.hrwallingford.com/id/eprint/1195

Actions (for site administrators only - login required)

View Item View Item