We employ a structural model of location choice to estimate household sorting across the U.S. in response to hurricane risk. Using spatially detailed projections of future hurricane energy, we simulate regional population shifts and welfare impacts of hurricane risk-induced migration in 2100. We find heterogeneous responses to hurricane risk for households that vary by number of children, age, educational attainment, and prior exposure to hurricane risk. Under future hurricane risk, although changes are small, we find declines in regional population shares along the hurricane-prone coasts and negative overall welfare impact. However, ignoring the spatial heterogeneity of hurricanes underestimates these impacts.

Arizona has been at the forefront of groundwater management since the establishment of the Groundwater Management Act in 1980. The Central Arizona Groundwater Replenishment District (CAGRD) is a groundwater management mechanism that facilitates development in regions of Central Arizona where the use of groundwater is limited by law. Several stakeholders have raised concerns about some of the CAGRD’s operations; however, stakeholders have yet to agree on the definition of the problems, let alone how the CAGRD might be improved. This study uses statistical and inductive thematic content analysis of a survey to determine (1) the CAGRD issues that stakeholders view as problems and (2) whether opinions differ significantly among different stakeholder groups. This study also uses deductive thematic content analysis to examine semi-structured interviews with CAGRD experts in order to find potential solutions to the CAGRD-related issues that are considered problems by stakeholders. The survey results show that long-term uncertainties related to the availability of renewable water supplies and hydrologic disconnect, where groundwater pumping and replenishment take place in different sub-basins, are stakeholders’ chief concerns. Sector affiliation and CAGRD membership status are associated with stakeholders’ opinions on some, but not all, questions. The potential policy changes offered address problems identified by stakeholders. This research will inform forthcoming policy discussions regarding groundwater management in Central Arizona as the state’s decision makers look to improve the CAGRD in the context of water scarcity exacerbated by climate change.

In 2020, we developed a comprehensive methodology (henceforth, the methodology) to assess flood-related economic costs. The methodology covers direct damages, indirect effects, and losses and additional costs across 105 social, infrastructure, economic, and emergency response indicators. As a companion paper, this study presents findings from analysis of applying the methodology to investigate economic costs for major flood events between 2013 and 2017 and to assess gaps in the existing datasets across Canada, Mexico, and the United States. In addition, we conducted one case study from each country for an in-depth examination of the applicability of the methodology. Applying the methodology, Mexico showed the most complete flood indicator data availability and accessibility among the three countries. We found that most flood-related economic cost assessments evaluated only direct damages, and indirect effect data were rarely included in datasets in the three countries. Moreover, few of the records from Canada and the United States captured the losses and additional costs. Flood-related economic cost data at the municipal or county level were easily accessible in Mexico and the United States. Mexico’s National Center for Prevention of Disasters (Centro Nacional de Prevención de Desastres), unique among the three nations, provided access to centralized and comprehensive flood cost data. In the United States and Canada, data collection by multiple agencies that focus on different jurisdictions and scales of flood damage complicated comprehensive data collection and led to incomplete economic cost assessments. Our analysis strongly suggests that countries should aim to expand the set of data indicators available and become more granular across space and time while maintaining data quality. This study provides significant insights about approaches for collating spatial, temporal, and outcome-specific localized flood economic costs and the major data gaps across the three countries.

This study leverages a Random Forest model to predict flood hazard in Arizona, New Mexico, Colorado, and Utah, focusing on enhancing sustainability in flood management. Utilizing the National Flood Hazard Layer (NFHL), an intricate flood map of Arizona was generated, with the Random Forest Classification algorithm assessing flood hazard for each grid cell. Weather variable predictions from TerraClimate were integrated with NFHL classifications and Digital Elevation Model (DEM) analyses, providing a comprehensive understanding of flood dynamics. The research highlights the model’s capability to predict flood hazard in areas lacking NFHL classifications, thereby supporting sustainable flood management by elucidating weather’s influence on flood hazard. This approach aligns with sustainable development goals by aiding in resilient infrastructure design and informed urban planning, reducing the impact of floods on communities. Despite recognizing constraints such as input data precision and the model’s potential limitations in capturing complex variable interactions, the methodology offers a robust framework for flood hazard evaluation in other regions. Integrating diverse data sources, this study presents a valuable tool for decision-makers, supporting sustainable practices, and enhancing the resilience of vulnerable regions against flood hazards. This integrated approach underscores the potential of advanced modeling techniques in promoting sustainability in environmental hazard management.

We employ a structural model of location choice to estimate household sorting across the United States in response to hurricane risk. Using spatially detailed projections of future hurricane energy, we simulate regional population shifts and welfare effects of hurricane risk–induced migration in 2100. We find heterogeneous responses to hurricane risk for households that vary by number of children, age, educational attainment, and prior exposure to hurricane risk. Under future hurricane risk, although changes are small, we find declines in regional population shares along the hurricane-prone coasts and negative overall welfare effect. However, ignoring the spatial heterogeneity of hurricanes underestimates these effects.