Bushfire emergency response uncertainty quantification

Abstract

Today, scenarios based on computer simulations are a fundamental tool for informing decision making at different levels of an organisation. When decisions concern the potential behaviour of complex systems, then uncertainty quantification (UQ) is paramount to provide appropriate levels of information for effective decision making. This is especially true for the Department of Defence which needs to make decisions on highly complex systems of systems, in uncertain future scenarios. However, it is useful to explore the tools and techniques required to analyse and communicate this uncertainty in an unclassified manner. Therefore, this project developed an unclassified, bushfire emergency response simulation to understand how to model, manage and communicate the impact of uncertainty in complex systems, as a surrogate for similar Defence problems. In this scenario, the fire is a threat and can exhibit behaviours characteristic of a complex system. The fire interacts with a network of response unit models, which in response to the complex behaviour of the fire, exhibit complex and uncertain behaviour, all while following mostly simple, deterministic logic. These models are comprised of the assets to be protected, command and control assets, fixed and mobile sensing assets, and assets within the response team with different capabilities to move and fight the fire (Fig. 1). The simulator is intended to capture key emergency response dynamic characteristics. This is the first in a series of papers utilising bushfire emergency response simulation as a surrogate for Defence problems to explore the quantification of uncertainty in modelling, simulation and analysis of complex systems. This paper addresses the effects of input and output uncertainty, while future papers will address other sources of uncertainty, such as uncertainty in the operational environment, mission, agent behaviour, and importantly the communication of the impact of these various sources of uncertainty to decision makers.