Document Type : Original Article
Authors
1 PhD Student of Irrigation and Drainage, Department of Water Engineering, Faculty of Agriculture, University of Torbat Heydariyeh, Torbat Heydariyeh, Iran
2 Assistant Professor, Department of Water Engineering, Faculty of Agriculture, University of Torbat Heydariyeh, Torbat Heydariyeh, Iran.
Abstract
The study of trends in climatic components reflects the occurrence of climate change impacts and is considered the most crucial part of climate change studies. Accordingly, this study aims to evaluate the annual trends of climatic variables, including mean temperature and precipitation, at four synoptic stations, in Semnan Province during the 2000–2022. The daily data were collected from the meteorological organization, and preprocessing procedures, such as outlier and missing values handling, were performed, and daily data were aggregated to annual scales. An auto correlation test was then performed prior to trend analysis. To conduct the annual trend analysis, two nonparametric tests, the Mann–Kendall and the Spearman tests, were incorporated. The results of the autocorrelation tests indicated that major climate variables are time-independent, and the minimum and mean temperatures in Garmsar, and rainfall in Damghan and Mayamey, exhibit significant autocorrelation. Although, the trend in many of climate variables in not significant statistically, the maximum and minimum increasing of temperature was recorded in Garmsar and Mayamey. While, the maximum and minimum decreasing of rainfall was observed in Semnan and Damghan. The applicability of both MKT and SPT tests suggests that the MKT is more reliable and applicable due to its greater interpretability, sensitivity to autocorrelation, and ability to estimate trend slope. Furthermore, the spatial-temporal examination of trends revealed that the increasing trend of temperature in more possible (stronger) than that of rainfall. Also, the variability of rainfall and temperature in the western regions of Semnan provinces is higher than in other regions.
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