December 22, 2024
Zohre Ebrahimi-Khusfi

Zohre Ebrahimi-Khusfi

Academic rank: Associate professor
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Education: PhD. in dedesertification
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Research

Title
Investigation of the relationship between dust storm index, climatic parameters, and normalized difference vegetation index using the ridge regression method in arid regions of Central Iran
Type Article
Keywords
Dry lands; Iran; meteorological data; remote sensing; wind erosion
Researchers Zohre Ebrahimi-Khusfi, Fatemeh Roostii, mohsen ebrahimi khusfi, somayeh naghavi

Abstract

Wind erosion is a serious environmental issue caused by the interaction between various climatic and terrestrial factors. Using the ridge regression (RR) method, the present study aimed to investigate the relationship between these parameters and dust storm index (DSI) in arid regions of Central Iran during 2000–2014. The removal area of soil particles in the dustiest season was further detected via sand and dust roses. The results showed that the highest activity of wind erosion occurred in spring (DSI > 1). The RR analysis indicated that only the air temperature changes had a significant positive effect on DSI variations during the first period (b ¼ þ0.38; p < .05). For the second period, decreased precipitation and increased wind velocity were identified as the most important factors influencing the DSI variations. The estimated regression coefficients concerning precipitation and wind speed at 95% confidence level were (1.02) and (þ0.51), respectively. Based on the R2 value, 27% of the DSI changes could be explained by the air temperature variations in the first period. However, approximately 50% of the DSI variations were explained by the rainfall and wind speed changes in the second period. These results illustrate the effective application of RR to elucidate the relationship of climatic and terrestrial factors with DSI. It was further observed that the removal area of soil particles in the northeastern, southeastern, and western parts of Central Iran was easterly, northerly, and westerly, respectively.