Assessing Property Level Economic Impacts of Climate in the US, New Insights and Evidence from a Comprehensive Flood Risk Assessment Tool

Abstract

Hurricanes and flood-related events cause more direct economic damage than any other type of natural disaster. In the United States, that damage totals more than USD 1 trillion in damages since 1980. On average, direct flood losses have risen from USD 4 billion annually in the 1980s to roughly USD 17 billion annually from 2010 to 2018. Despite flooding’s tremendous economic impact on US properties and communities, current estimates of expected damages are lacking due to the fact that flood risk in many parts of the US is unidentified, underestimated, or available models associated with high quality assessment tools are proprietary. This study introduces an economic-focused Environmental Impact Assessment (EIA) approach that builds upon an our existing understanding of prior assessment methods by taking advantage of a newly available, climate adjusted, parcel-level flood risk assessment model (First Street Foundation, 2020a and 2020b) in order to quantify property level economic impacts today, and into the climate adjusted future, using the Intergovernmental Panel on Climate Change’s (IPCC) Representative Concentration Pathways (RCPs) and NASA’s Global Climate Model ensemble (CMIP5). This approach represents a first of its kind—a publicly available high precision flood risk assessment tool at the property level developed completely with open data sources and open methods. The economic impact assessment presented here has been carried out using residential buildings in New Jersey as a testbed; however, the environmental assessment tool on which it is based is a national scale property level flood assessment model at a 3m resolution. As evidence of the reliability of the EIA tool, the 2020 estimated economic impact (USD 5481 annual expectation) was compared to actual average per claim-year NFIP payouts from flooding and found an average of USD 5540 over the life of the program (difference of less than USD 100). Additionally, the tool finds a 41.4% increase in average economic flood damage through the year 2050 when environmental change is included in the model.

Climate change, riverine flood risk and adaptation for the conterminous United States

“…The dataset also includes an estimate of the first floor (ground-level) elevation for each building, the building type, the square footage, the replacement cost, and the market value for each property. Details regarding the development of this dataset are available in First Street Foundation (2020a) and Armal (2020) . Using this dataset, we calculated the EAD for each property under baseline climate conditions, as follows.…”

“…For each adaptation action, we combined unit costs of adaptation with available data on total building square footage ( First Street Foundation, 2020a ; Armal, 2020 ). We combined this information with the number of floors for each building to calculate the size of each building footprint, on which unit costs for property elevation are based.…”

“…For those properties, we assume that property acquisition is the most appropriate adaptation decision. We further assume that the acquisition cost would be the market value of the property, which is included in the property-level database (e.g., First Street Foundation, 2020a ; Armal et al, 2020 ).…”

“…In this paper, we leverage a new flood risk dataset for the conterminous United States ( Bates et al, 2021 ; Armal et al, 2020 ; First Street 2020a , First Street, 2020b ) to conduct a screening-level assessment of current and future flood risk, the costs of property-level flood adaptation, and the benefits of those adaptations under current and future climate regimes. We focus on three specific types of flood adaptation – floodproofing, elevation, and buyout/demolition – because each of these can be implemented at a property level, and because each of them can be subsidized in the United States if they can be shown to be cost-effective ( FEMA, 2015 ).…”

“…Our methodology is as follows: First, we use the expected annual damage (EAD) from flooding at each property in the United States as a metric of riverine flood risk under today’s climate. Using flood exposure information along with actual and imputed building size and construction type data (e.g., Armal et al, 2020 ), we then estimate the cost of adaptation for each property using simple decision rules to determine what type of adaptation is most appropriate for each property. This allows us to perform a simple benefit cost test for each property to determine which simulated adaptation investments may be cost-effective, under today’s climate conditions.…”