Mapping dust risk under heterogenous vulnerability to dust: The combination of spatial modelling and questionnaire survey

Abstract

Dust storms are natural events that remove and relocate surface soil, damage vegetation crops, and disrupt many other aspects of the earth's terrestrial ecosystem. Despite the importance of the risk assessment of dust hazards, vulnerability modeling of them is very limited. For this reason, this study provides a conceptual model based on Structural Equation Modeling and the Finite Mixture Partial Least Squares (FIMIX-PLS) approach using interviews and questions for vulnerability modeling of dust in Ahvaz County, Khuzestan province, Iran. Key model drivers included Resilience Actions, Natural-Physical effects, Economic Influence, and Social Influence. The Aerosol Optical Depth (AOD) product of MODIS/Terra was used to develop a dust hazard map. MODIS/Terra performance was evaluated using observed PM10 data from Ahvaz County air pollution monitoring stations. Land use mapping was used for spatial detection of agricultural land affected by the intensity of the AOD map in the previous step. The vulnerability model fitting results showed that the model had acceptable validity (SRMR = 0.013). Results showed that approximately 25 % of agricultural lands are at high and very high dust hazard risk. Based on modeling results, natural-physical variables affect about 89 % and 97 % of social and economic drivers, respectively. Conversely, social influences significantly negatively affect dust storm resilience resulting in agricultural vulnerability. Based on results from the integrated model, strengthening farmers' resilience strategies against dust hazards requires additional research and attention.