摘要：Introduction: Climate change is a certain, irrefutable, undisputed, clear, unequivocal, and imminent reality, and potentially a serious threat and challenge to the agricultural sector. It has become clear that the earth’s climate has changed in a manner that has induced many negative impacts on its human and non-human residents. In fact, it has been confirmed that climate change, directly and indirectly, influences all aspects of life worldwide. Scientific evidence suggests that projected climate change will significantly impact the hydrological cycle, water balance, and runoff characteristics. This will, in turn, cause water scarcity and insecurity. Agriculture and water resources are vulnerable to global climate change. Climate change impacts the water sector in a manner that reduces the harvest and income of farmers, thereby exacerbating poverty and many other social problems. Therefore, the influence of climate variability on water resources raises major international concern, as it may cause severe stress on whole societies, particularly farmers, due to the huge negative impacts on agricultural production. Agricultural and farming practices should, therefore, adapt to the changing environment in order to avoid or alleviate related risks. Consequently, understanding adaptation to climate change has become a major concern for farmers to facilitate adaptation actions and assist them in improving their adaptive capacity. The aim of the present study was to investigate farmers’ adaptation behaviors in facing water scarcity. This research ideally provides a first knowledge base for the development of public policy measures aiming to increase climate change adaptation measures among Iranian farmers. Materials and Methods: The aim of the present study was to investigate farmers’ adaptation behaviors in facing water scarcity using the protection motivation theory and cognitive theory of the stress model. A quantitative cross-sectional survey was designed to investigate farmers’ adaptation responses to water shortage. The statistical population was farmers of Shoushtar County in Khuzestan province. The sample size was determined and selected using the Bartlett table (n=251) and Random sampling. The data were collected through a nationwide self-administered questionnaire. To measure the variables, statements that closely followed the measurement of these constructs in prior studies were used. In designing the questionnaire, a 5-point Likert scale for all the variables was used to reduce the statistical problem of extreme skewness. The face validity of the questionnaire was confirmed by a panel of experts. The questionnaire’s internal reliability was investigated using the Cronbach’s alpha coefficient. All scales indicated a good-to-excellent reliability index (0.6–0.88). To analyze the data, SPSS20 and AMOS20 were used. Discussion of Results and Conclusions: To investigate the causal relationship between research variables, structural equation modeling was used using Amos20 software to analyze the factors affecting adaptation behavior. The results of structural equation modeling analysis revealed that in protection motivation theory, the response efficacy, collective efficacy, and response cost regarding climate change were significant predictors of adaptation behavior. Protection motivation theory can explain approximately 33%, of the variance in pro-environmental behavior. The results of cognitive theory of stress analysis showed that demand appraisal, self-efficacy, and collective efficacy had direct effects on problem-focused coping, and coping had direct effects on adaptation. The explanatory power of this model explained 28% of the variance in adaptation behavior. Moreover, the results of the study revealed that demand appraisal, self-efficacy, and collective efficacy had an indirect and significant relationship with adaptation. The results of this study could be useful for decision-makers and researchers in other countries in the Middle East and North Africa (MENA) region as well as in dryland regions facing drought hazards.
