Joint modeling of drought and dust hazards using copula- based model over Iran from 1988 to 2018

Abstract

This study aims to employ joint modeling for drought and dust hazards. Long-term monthly precipitation and temperature were used to calculate drought characteristics based on the standardized precipitation- evapotranspiration index. Three-hourly horizontal visibility and wind erosion event codes were also obtained to detect dust events. The results of drought hazard assessment indicated that about 52% of the total area of Iran was affected by moderate hazard. Other classes of drought hazard i.e., severe, low, and very severe, covered approximately 24, 18, and 6%, respectively. The assessment of dust hazard was conducted by weighting the frequency of dust events based on the horizontal visibility. The findings on dust hazard showed that approximately 18% of the total area of Iran was affected by the more intense hazard, which covered the southeastern sectors. Bivariate copulas were considered for joint modeling of drought and dust hazards. The copulas of Student’s t, Gaussian, Gumbel, and others were applied to construct a joint model. Bivariate assessment of drought and dust hazard illustrated that the eastern part of Iran, which covers around 47% of the country, exposed at greater hazard than other parts. The copula-based conditional probability was also obtained to quantify the probability of dust occurrence under different drought hazard levels. The conditional probability values showed that by intensification of drought conditions the probability of dust hazard increased. In addition the frequency of dust occurrences increased when the region faced very severe droughts. Generally, the prolonged and severe droughts were identified as the most important reasons for the increased hazard of dust and drought in the study region. This study results indicated that the joint risk of drought and dust hazard along with vulnerability factors, can be used for possible mitigation of the risks of these natural hazards. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.