Agent-based modeling and simulation to assess flood preparedness and recovery of manufacturing small and medium-sized enterprises

Severe flooding has caused major damage and disruption to households, communities, businesses, and organizations in many parts of the world. In the United Kingdom (UK), flooding has been responsible for significant losses to the economy due to its impact on businesses, 99.9% of which are Small and Medium-sized Enterprises (SMEs). This paper reports on how agent-based modeling and simulation has been developed and used to assess the effectiveness of a range of physical/structural and social preparedness adaptation measures that can be implemented by manufacturing SMEs to reduce the impact of and expedite recovery from a major flood event. Results indicate the effectiveness of combinations of these adaptation measures in relation to a one in 1000 year flood event that has been modeled and simulated in a key industrial area of the UK which, in addition to having experienced severe flooding, has a high concentration of SMEs

Flood prevention solutions using remote sensing and agent-based modeling (Case study: Shoush city)

Among all the natural hazards in the country, according to recorded statistics and observations, floods have been the most destructive, and it has the highest frequency of occurrence. Floods are one of the known natural disasters that cause a lot of financial and human losses. This phenomenon can be controlled by identifying flood-prone areas and proper management. In the current era, due to human encroachment on rivers and land-use change or destruction of vegetation, flood damage has increased. These factors cause, in addition to increasing human and financial losses, damages such as soil erosion upstream and sedimentation downstream. In this research, using agent-based modeling in the NetLogo simulation environment, flood-prone areas in Shush city have been identified. The most important input was topography (digital elevation model) and then dynamic and temporal simulation was done by performing tessellation on the area and considering the rainfall in each cell as an agent. Using spatial analysis in ArcGIS software and comparing the simulation results with the location of the city and land use maps of the region, the possible causes of floods in this region have been investigated. Agent-based models with the incorporation of geospatial information systems (GIS) can be used as a new solution to solve spatial problems such as natural crises, destructive environmental impacts, and so on. Finally, preventive measures to prevent floods in this area are proposed

Assessing vulnerability and modelling assistance: using demographic indicators of vulnerability and agent-based modelling to explore emergency flooding relief response

Flooding is a significant concern for much of the UK and is recognised as a primary threat by most local councils. Those in society most often deemed vulnerable: the elderly, poor or sick, for example, often see their level of vulnerability increase during hazard events. A greater knowledge of the spatial distribution of vulnerability within communities is key to understanding how a population may be impacted by a hazard event. Vulnerability indices are regularly used – in conjunction with needs assessments and on-the-ground research – to target service provision and justify resource allocation. Past work on measuring and mapping vulnerability has been limited by a focus on income-related indicators, a lack of consideration of accessibility, and the reliance on proprietary data. The Open Source Vulnerability Index (OSVI) encompasses an extensive range of vulnerability indicators supported by the wider literature and expert validation and provides data at a sufficiently fine resolution that can identify vulnerable populations. Findings of the OSVI demonstrate the potential cascading impact of a flood hazard as it impacts an already vulnerable population: exacerbating pre-existing vulnerabilities, limiting capabilities and restricting accessibility and access to key services. The OSVI feeds into an agent-based model (ABM) that explores the capacity of the British Red Cross (BRC) to distribute relief during flood emergencies using strategies based upon the OSVI. A participatory modelling approach was utilised whereby the BRC were included in all aspects of the model development. The major contribution of this work is the novel synthesis of demographics analysis, vulnerability mapping and geospatial simulation. The project contributes to the growing understanding of vulnerability and response management within the NGO sector. It is hoped that the index and model produced will allow responder organisations to run simulations of similar emergency events and adjust strategic response plans accordingly