Introduction of an index for drought evaluation using principle components analysis

Document Type : Scientific - Research


1 Department of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, Iran

2 Department of Agroecology, Environmental Sciences Research Institute, Shahid Beheshti University, Iran

3 Department of Remote sensing and GIS, Shahid Beheshti University, Tehran, Iran


Isfahan province is located in the center of Iran and has arid and semi-arid climate. In recent years, water shortage has increased in this region and has affected crop production. Wheat is one of the most important crops of the province. In the present research, an index (DEI) has been developed for drought evaluation using long term climatic data through application of principle components analysis (PCA). The counties of the province were classified and evaluated according to drought intensity. In addition to DEI for quantifying drought, Aridity index (AI) was also calculated at different time scales in each county. The climatic and grain yield data were collected from the Iranian Meteorological Organization and Isfahan Agricultural Organization, respectively. In order to remove the positive effects of genetic improvement and progress in agronomic management on long-term wheat grain yield, double exponential smoothing technique was used. According to DEI, Isfahan, Shahreza, Golpaygan and Natanz had semi-arid climate and Ardestan, Khoorobiabanak, Kashan and Naein could be classified as arid, while according to AI studied counties had arid climate. AI had the greatest amount only in Golpaygan while DEI had the greatest value in Isfahan, Shahreza, Golpaygan, Kashan and Natanz. PCA results showed that maximum temperature (coefficient of 3.51) followed by mean wind speed (coefficient of 2.27) were the main climatic variable influencing counties weather. Calculated drought indices showed poor correlation with wheat yield, indicating that other meteorological indices should still be examined to capture wheat yield variability in this province.


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