Development of an Adaptive Solution to Increase Infrastructure System Resilience Based upon a Location-Allocation Methodology

Abstract

Infrastructure systems are critical to the normal functioning of our modern communities, enabling access to essential resources and services and also providing a platform for social and economic growth. These systems are currently being subjected to a multitude of challenges and must, therefore, adapt to ensure the needs of society can continue to be met. Perhaps the most problematic of these challenges is climate change. The high level of uncertainty within long-term climate projections means that they cannot reliably be used as a basis for informed decisions to permanently alter existing assets or change the design of infrastructure assets (through alteration to design codes, for example). Therefore, we need new tools to ensure our infrastructure systems are resilient by using adaptable approaches, which do not require accurate long-term climate scenarios to inform decisions. This paper develops a modified location-allocation modeling approach, which can provide an adaptive solution that utilizes deployable resources to increase the resilience of infrastructure systems. Specifically, this approach can be applied to indicate the optimal location to store resources so as to ensure a baseline level of service to our communities, either through the protection of critical assets (e.g., mobile flood defenses and grit storage) or the provision of a temporary service (e.g., electricity generators). The approach we have developed is based upon a modified location-allocation analysis, which determines an optimal location for one or more resource sites to provide supplies to a given set of demand points (e.g., hospitals and community centers). The novel contribution of the work is to the development of a methodology to assign a weighting to assets with only qualitative attributes within the location-allocation methodology. We use ArcGIS to undertake the analysis and apply our methodology to a real-world infrastructure case study and natural hazard threat.