An Interdisciplinary Agent-based Evacuation Model: Integrating Natural Environment, Built environment, and Social System for Community Preparedness and Resilience

Abstract. Previous tsunami evacuation simulations have mostly been based on arbitrary assumptions or inputs adapted from non-emergency situations, but a few studies have used empirical behavior data. This study bridges this gap by integrating empirical decision data from local evacuation expectations surveys and evacuation drills into an agent-based model of evacuation behavior for a Cascadia Subduction Zone community. The model also considers the impacts of liquefaction and landslides from the earthquake on tsunami evacuation. Furthermore, we integrate the slope-speed component from Least-cost-distance to build the simulation model that better represents the complex nature of evacuations. The simulation results indicate that milling time and evacuation participation rate have significant non-linear impacts on tsunami mortality estimates. When people walk faster than 1 m/s, evacuation by foot is more effective because it avoids traffic congestion when driving. We also find that evacuation results are more sensitive to walking speed, milling time, evacuation participation, and choosing the closest safe location than to other behavioral variables. Minimum tsunami mortality results from maximizing the evacuation participation rate, minimizing milling time, and choosing the closest safe destination outside of the inundation zone. This study's comparison of the agent-based model and BtW model finds consistency between the two models' results. By integrating the natural system, built environment, and social system, this interdisciplinary model incorporates substantial aspects of the real world into the multi-hazard agent-based platform. This model provides a unique opportunity for local authorities to prioritize their resources for hazard education, community disaster preparedness, and resilience plans.

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AN AGENT BASED MODEL FOR LAND USE POLICIES IN COASTAL AREAS

Coastal Engineering Proceedings ◽

10.9753/icce.v35.management.9 ◽

2017 ◽

pp. 9

Author(s):

Shima Nabinejad ◽

Holger SchÃ¼ttrumpf

Keyword(s):

Decision Making ◽

Land Use ◽

Social Interactions ◽

Crop Yields ◽

Flood Management ◽

Human Interaction ◽

Complex Nature ◽

Agent Based Model ◽

Agent Based ◽

Land Use Policies

Reducing the probability of flooding by flood defence structures might not be successful without appropriate actions taken in order to mitigate flood damages. Moreover, success depends on actions at both governmental and individual levels. Therefore, farmers as the inhabitant of flooding areas may contribute to flood management in terms of land use policies which lead to communication, human interaction, and adaptation. However, these social behaviors have not taken into account in flood management studies due to their complex nature and human has been only considered as the receptor of flooding without paying attention to multiple feedbacks over time horizons with a dynamic approach. In our study, we overcome this deficiency by employing Agent Based Model (ABM) of land use policy in flood risk management and address challenges regarding social interactions in this research area. Our Agent Based Model includes perspectives from engineering, decision making, and socio-economics allowing to model human-flood interactions. In this model, farmers are considered as individuals whose decisions depend on climatic conditions, crop yields, costs and prices, flood damage, personal risk perception, and their social interactions. This is achieved by integrating three main modules including hydrological module, flood analysis module, and decision making module in the frame of Agent Based Model. This paper has shed some light on main concepts of our Agent Based Model including the developed methodology, main modules, required information, and initial results. It also summarizes the components of the modules and the governed interactions.

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