Droughts are a persistent and costly hazard impacting human and environmental systems. As climate variability continues to increase and socioeconomic development influences the distribution of wealth and people, drought risk is expected to increase in many parts of the world. The unique characteristics of droughtsnamely their slow onset, large spatiotemporal extent, human-influenced propagation, delayed impacts and teleconnection potential-make it difficult to correctly assess drought impact and calculate risk. Further complicating this calculation is the capacity for humans to make adaptive decisions before, during, and after a drought event, which in turn alters expected impacts. In this sense, droughts are equally a social and hydroclimatic issue. Risk perception is one of the main factors driving adaptation decisions, yet most models neglect how humans view and respond to risk, and in particular how experiences influence decisions through time. In this overview, we describe a framework that extends the traditional risk modeling approach to include the two-way feedback between the transient adaptation decisions and drought exposure, vulnerability and hazard. We discuss how a sociohydrologic, agent-based modeling setup, focused on individual and collective actions, can simulate the adaptive behaviors of different stakeholders to examine how emergent actions might influence projected drought risk. We suggest such an approach can provide a test-bed for understanding adaptive behaviors in an increasingly drought-prone world and could allow for better prioritization of drought adaptation strategies; refined understanding of future scenarios; and a vehicle to drive planning and resilience building. This article is categorized under: Science of Water > Water Extremes Engineering Water > Planning Water Engineering Water > Methods K E Y W O R D S adaptation, agent-based modeling, behavior, drought, risk, sociohydrology
In Eastern Africa, increasing climate variability and changing socioeconomic conditions are exacerbating the frequency and intensity of drought disasters. Droughts pose a severe threat to food security in this region, which is characterized by a large dependency on smallholder rain-fed agriculture and a low level of technological development in the food production systems. Future drought risk will be determined by the adaptation choices made by farmers, yet few drought risk models … incorporate adaptive behavior in the estimation of drought risk. Here, we present an innovative dynamic drought risk adaptation model, ADOPT, to evaluate the factors that influence adaptation decisions and the subsequent adoption of measures, and how this affects drought risk for agricultural production. ADOPT combines socio-hydrological and agent-based modeling approaches by coupling the FAO crop model AquacropOS with a behavioral model capable of simulating different adaptive behavioral theories. In this paper, we compare the protection motivation theory, which describes bounded rationality, with a business-as-usual and an economic rational adaptive behavior. The inclusion of these scenarios serves to evaluate and compare the effect of different assumptions about adaptive behavior on the evolution of drought risk over time. Applied to a semi-arid case in Kenya, ADOPT is parameterized using field data collected from 250 households in the Kitui region and discussions with local decision-makers. The results show that estimations of drought risk and the need for emergency food aid can be improved using an agent-based approach: we show that ignoring individual household characteristics leads to an underestimation of food-aid needs. Moreover, we show that the bounded rational scenario is better able to reflect historic food security, poverty levels, and crop yields. Thus, we demonstrate that the reality of complex human adaptation decisions can best be described assuming bounded rational adaptive behavior; furthermore, an agent-based approach and the choice of adaptation theory matter when quantifying risk and estimating emergency aid needs.
Improving assessments of droughts risk for smallholder farmers requires a better understanding of the interaction between individual adaptation decisions and drought risk. Agent-based modeling is increasingly used to capture the interaction between individual decision-making and the environment. In this paper, we provide a review of drought risk agent-based models with a focus on behavioral rules. This review leads to the conclusion that human decision rules in existing drought risk agent-based models are often based on ad hoc assumptions without a solid theoretical and empirical foundation. Subsequently, we review behavioral economic and psychological theories to provide a clear overview of theories that can improve the theoretical foundation of smallholder farmer behavior and we review empirical parameterization, calibration, and validation methods of those theories. Based on these reviews, we provide a conceptual framework that can give guidance for the integration of behavioral theories in agent-based models. We conclude with an agenda to guide future research in this field.
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