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The Horn of Africa Drylands are increasingly experiencing severe droughts, which impose a threat on traditional livelihood strategies. Understanding adaptation behavior in rural communities is key to helping reduce the impact of these droughts. We investigate adaptation behavior by assessing four established economic and social psychological theories on decision making under risk: expected utility theory (EUT), rank dependent utility theory (RDU), protection motivation theory (PMT), and theory of planned behavior (PMT). To measure adaptation behavior and the theory constructs, we conducted a household survey in Kenya (N = 502). Regression analysis shows that the economic theories (EUT and RDU) have the best fit for our data. Risk and time preferences are found to play an important role in adaptation decisions. An analysis of differences in decision making for distinct types of adaptation measures shows that risk averse (agro‐)pastoralists are more likely to implement adaptation measures that are adjustments to their current livelihood practices, and less willing to invest in adaptation measures that require a shift to other livelihood activities. Moreover, we find significant effects for elements of the social psychological theories (PMT and TPB). A person's belief in their own ability to implement an adaptation measure (perceived self‐efficacy) and adaptation by family and friends are important factors in explaining adaptation decisions. Finally, we find that the type of adaptation measures that people implement is influenced by, among others, gender, education level, access to financial resources, and access to government support or aid. Our analysis gives insights into the drivers of individual adaptation decisions, which can enhance policies promoting adaptation of dryland communities. [ABSTRACT FROM AUTHOR]

Flood damage caused by hurricanes is expected to rise globally due to climate and socio-economic change. Enhanced flood preparedness among the coastal population is required to reverse this trend. The decisions and actions taken by individuals are thought to be influenced by risk perceptions. This study investigates the determinants that shape flood risk perceptions and the factors that drive flood risk misperceptions of coastal residents. We conducted a survey among 871 residents in flood-prone areas in Florida during a 5 d period in which the respondents were threatened to be flooded by Hurricane Dorian. This approach allows us to assess temporal dynamics in flood risk perceptions during an evolving hurricane threat. Among 255 of the same households, a follow-up survey was conducted to examine how flood risk perceptions varied after Hurricane Dorian failed to make landfall in Florida. Our results show that the flood experience and social norms have the most consistent relationship with flood risk perceptions. Furthermore, participants indicated that their level of worry regarding the dangers of flooding decreased after the near-miss of Hurricane Dorian compared to their feelings of worry during the hurricane event. Based on our findings, we offer recommendations for improving flood risk communication policies. [ABSTRACT FROM AUTHOR]

Coastal flooding and sea level rise (SLR) will affect farmers in coastal areas, as increasing salinity levels will reduce crop yields, leading to a loss of net annual income for farming communities. In response, farmers can take various actions. In order to assess such a response under SLR, we applied an agent-based model (ABM) to simulate the adaptation and migration decisions of farmers in coastal Mozambique. The ABM is coupled with a salinization module to simulate the relationship between soil salinity and SLR. The decision rules in the model (DYNAMO-M) are based on the economic theory of subjective expected utility. This theory posits that households can maximize their welfare by deciding whether to (a) stay and face losses from salinization and flooding, (b) stay and adapt (switching to salt-tolerant crops and enhancing physical resilience such as elevating houses), or (c) migrate to safer inland areas. The results show that coastal farmers in Mozambique face total losses of up to US$12.5 million per year from salt intrusion and up to US$800 million per year from flooding of buildings (RCP8.5 in the year 2080). Sorghum farmers may experience little damage from salt intrusion, while rice farmers may experience losses of up to US$15,000 per year. We show that medium-sized farmers (1-20 ha) are most at risk. This is because their farm size means that adaptation costs are substantial, while their incomes are too low to cover these costs. The number of households adapting varies between different districts (6%-50%), with salt adaptation being the most common, as costs are lowest. Despite adaptation measures, about 13%-20% of the total 300,000 farmers in coastal flood zones will migrate to safer areas under different settings of adaptive behaviour and different climatic and socioeconomic scenarios. [ABSTRACT FROM AUTHOR]

The article "All by myself? Testing descriptive social norm-nudges to increase flood preparedness among homeowners" examines the effectiveness of social norm-nudges in promoting flood preparedness among homeowners. The study conducted an online experiment with homeowners in two European countries and tested different norm-nudge messages. The results showed no evidence of a treatment effect, suggesting that the social norm-nudges did not influence flood preparedness. The study highlights the importance of tailoring norm-nudges to specific populations and contexts and calls for further research in the field of natural disaster risk reduction. [Extracted from the article]

Coastal flood risk is expected to increase as a result of climate change effects, such as sea level rise, and socioeconomic growth. To support policymakers in making adaptation decisions, accurate flood risk assessments that account for the influence of complex adaptation processes on the developments of risks are essential. In this study, we integrate the dynamic adaptive behavior of homeowners within a flood risk modeling framework. Focusing on building‐level adaptation and flood insurance, the agent‐based model (DYNAMO) is benchmarked with empirical data for New York City, USA. The model simulates the National Flood Insurance Program (NFIP) and frequently proposed reforms to evaluate their effectiveness. The model is applied to a case study of Jamaica Bay, NY. Our results indicate that risk‐based premiums can improve insurance penetration rates and the affordability of insurance compared to the baseline NFIP market structure. While a premium discount for disaster risk reduction incentivizes more homeowners to invest in dry‐floodproofing measures, it does not significantly improve affordability. A low interest rate loan for financing risk‐mitigation investments improves the uptake and affordability of dry‐floodproofing measures. The benchmark and sensitivity analyses demonstrate how the behavioral component of our model matches empirical data and provides insights into the underlying theories and choices that autonomous agents make. [ABSTRACT FROM AUTHOR]