Earth Observation to Address Inequities in Post-Flood Recovery

Floods impact communities worldwide, resulting in loss of life, damaged infrastructure and natural assets, and threatened livelihoods. Climate change and urban development in flood-prone areas will continue to worsen flood-related losses, increasing the urgency for effective tools to monitor recovery. Many Earth Observation (EO) applications exist for flood-hazard monitoring and provide insights on location, timing, and extent in near real-time and historically to estimate flood risk. Less attention has been paid to flood recovery, even though differing recovery rates and outcomes can have immediate and enduring distributional effects within communities. EO data are uniquely positioned to monitor post-flood recovery and inform policy on hazard mitigation and adaptation but remain underutilized. We encourage the EO and flood research community to refocus on developing flood recovery applications to address growing risk. Translation of EO insights on flood recovery among flood-affected communities and decision-makers is necessary to address underlying social vulnerabilities that exacerbate inequitable recovery outcomes and advocate for redressing injustices where disparate recovery is observed. We identify an unequivocal need for EO to move beyond mapping flood hazard and exposure toward post-flood recovery monitoring to inform recovery across geographic contexts. This commentary proposes a framework for remote sensing scientists to engage community-based partners to integrate EO with non-EO data to advance flood recovery monitoring, characterize inequitable recovery, redistribute resources to mitigate inequities, and support risk reduction of future floods

A preference for power: Willingness to pay for energy reliability versus fuel type in Vietnam

Developing countries are projected to experience the greatest increases in per capita energy use, motivating enormous investment in government-led energy projects. As energy fuel choices have large implications for pollution, a critical question surrounds citizens' preferences for renewable energy versus coal. While a robust literature suggests that citizens are willing to pay for renewables, the applicability of these findings to developing countries remains limited as many studies do not benchmark findings against preferences for increased capacity with dirtier fuels. We estimate citizens' willingness to pay for improved electricity reliability from coal versus renewable technologies using a contingent valuation experiment embedded in a nationally-representative survey of 14,000 respondents across Vietnam, the country with the greatest recent increase in coal consumption. We find that while households are willing to pay 95% more in their monthly electricity bill for renewables (USD 7.5 billion per year in aggregate), they are also willing to pay 62% more for coal plants (USD 4 billion per year). Additionally, income and satisfaction with governance drive support both for renewables and coal, suggesting that agenda setting by policymakers is critical. If citizens are not offered alternatives, a majority will support coal even as governance improves or citizens become wealthier.24 month embargo; available online 22 June 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Sorting over flood risk and implications for policy reform

Do individuals sort across flood risk? This paper applies a boundary discontinuity design to a residential sorting model to provide novel estimates of sorting across flood risk by race, ethnicity, and income. We find clear evidence that low income and minority residents are more likely to move into high risk flood zones. We then highlight the overall and distributional implications of proposed price and information reforms to the U.S. National Flood Insurance Program. While such reforms are likely welfare increasing overall, heterogeneous behavioral responses yield significant distributive effects that also alter the composition of residents in harm's way. (c) 2020 Elsevier Inc. All rights reserved.Gulf Research Program24 month embargo; available online 15 August 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Going Underwater? Flood Risk Belief Heterogeneity and Coastal Home Price Dynamics

How do climate risk beliefs affect coastal housing markets? This paper provides theoretical and empirical evidence. First, we build a dynamic housing market model and show that belief heterogeneity can reconcile prior mixed evidence on flood risk capitalization. Second, we implement a door-To-door survey in Rhode Island, finding significant flood risk underestimation and sorting based on risk perceptions and amenity values. Third, we estimate that coastal prices exceed fundamentals by 6\%-13\% in our benchmark area, with potentially higher overvaluation in other locations. Finally, we quantify both allocative inefficiency and distributional consequences arising from flood risk misperceptions and insurance policy reform.24 month embargo; published: 10 November 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Is Tropical Cyclone Surge, Not Intensity, What Kills So Many People in South Asia?

This paper statistically examines the hypothesis that the level of storm surge, not storm intensity, is primarily responsible for the large number of tropical cyclone fatalities in SouthAsia. Because the potential causal link between intensity and surge can confound statistical inference, the authors develop two fatality models using different assumptions on the relationship between storm surge and intensity. The authors find evidence that storm surge is a primary killer of people in South Asia relative to storm intensity. In a surge-pressure independence model, it is found that a 10-cm increase in storm surge results in a 14% increase in the number of fatalities. In a surge-pressure dependence model, a 10-cm increase in the level of surge not driven by minimumcentral pressure (MCP) leads to 9.9% increase in the number of fatalities. By contrast, a one-millibar (1 hPa) decrease in MCP leads to a 7.3% increase in the number of fatalities, some of which is also attributable to storm surge. In South Asia, adaptation strategies should target a higher level of storm surge instead of higher-intensity storms. Policies to combat surge include permanent relocation, temporary evacuation, changes in building structures, and coastal fortification.6 month embargo; Published Online: 15 February 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The Effects of The Menstrual Cycle and Contraceptive Use on Injury in Collegiate Athletes

PURPOSE: The purpose of this study was to investigate the role of hormone fluctuations in natural menstrual cycles on the rate of injury in collegiate athletes compared to those with less hormonal fluctuation due to estrogen based hormonal contraceptives (HC). This study hypothesized that athletes on their menses, characterized by low levels of estrogen, will have a lower rate of injury than those athletes not on their menses (higher rates of estrogen near ovulation). In addition, we hypothesized that those on a natural cycle will have higher rates of injury than those on HC. METHODS: Female athletes from Linfield University (n=59, ages 18-22 y/o), participating in a collegiate sport were recruited. Participants completed a weekly survey that tracked onset and completion of menses along with new injury occurrences. Injury type was recorded. RESULTS: The analysis showed that the injury rate tended to be lower in athletes that were on contraceptives (9 injuries versus 15 injuries across 12 weeks). In addition, injury rates were much lower during menses compared to the rest of the menstrual cycle, for those not on contraceptives. CONCLUSION: The results suggest that fluctuating hormone levels may affect injury rate in collegiate athletes. The constant hormone levels of contraceptive use may be beneficial in limiting injury

Flood Risk and Salience: New Evidence from the Sunshine State

A growing literature finds evidence that flood risk salience varies over time, spiking directly following a flood and then falling off individuals' cognitive radar in the following years. In this article, we provide new evidence of salience exploiting a hurricane cluster impacting Florida that was preceded and followed by periods of unusual calm. Utilizing residential property sales across the state from 2002 through 2012, our main estimate finds a salience impact of -8%, on average. The salience effect persists when we base estimation only on spatial variation in prices to limit confounding from other simultaneous changes due to shifting hedonic equilibria over time. These effects range from housing prices decreases of 5.4-12.3% depending on the year of sale. Understanding flood risk salience has important implications for flood insurance and disaster policy, the benefits transfer literature, and, more broadly, our understanding of natural disaster resilience. JEL Classification: Q51, Q54, R2112 month embargo; first published: 08 March 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Cumulative impacts in environmental justice: Insights from economics and policy

Disparities in health and socioeconomic well-being are a result of the cumulative impacts from multiple coinciding environmental, health, and social stressors. Addressing cumulative impacts is seen as a crucial step toward environmental justice (EJ). Using the case of the United States, we compare different methods to operationalize the concept for real-world application. We empirically demonstrate the extent to which non-White and low-income neighborhoods are subject to a wide array of burdens and how these burdens are reflected in national EJ indices and housing prices. We find that non-White and low-income neighborhoods are correlated with measures of multiple environmental burdens and social stressors but correlate to a lesser extent with natural disaster risk. Two existing EJ indices are only moderately correlated and more correlated with low-income status than with percent non-White. Models that employ the housing market for benefits estimation may fail to capture preferences to avoid multiple stressors due to issues including data availability and market frictions, such as discrimination. Finally, we highlight the challenges in cumulative impacts analysis for research and policy-making.24 month embargo; first published 7 March 2024This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]