Abstract
Drought monitoring is very important for water resource planning due to the impact of climate change on the frequency of drought events. The objective of this study was to evaluate the spatiotemporal characteristics of drought in Iran. Spatial and temporal distributions of drought severity were assessed using the well-accepted standardized reconnaissance drought index (RDIst) in seasonal and annual scales in 40 synoptic meteorological stations of Iran during the years 1967–2014. Parametric and nonparametric statistical tests were further used for trend assessments. According to the results of RDIst on an annual time scale, the trends of drought were positive in 87.5% of the stations. The results of seasonal RDIst also indicated that the trends of drought in winter (92.5%), spring (82.5%), summer (37.5%), and fall (67.5%) were upward. In sequence series of all seasons, 90% of all stations had a negative trend in the value of their calculated RDIst over time, which means an upward trend in drought over time. Our findings demonstrated an upward trend in drought over the study period. In 45% of the studied stations, winter had the most significant positive trend at all time scales. The results also showed that a moderate drought covered the highest portion of the study area. Generally, a positive trend was observed in coverage of extreme, severe, and moderate drought. However, a negative trend was evident in the coverage of extreme, severe, and moderate wet conditions during the time. It is suggested that the spatiotemporal distribution of the RDIst trend can be used to identify drought and mitigate its impacts in Iran.
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Thanks to the Meteorological Organization of Iran for providing the data needed in this research.
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The participation of Samira Bazrkar and Abdol Rassoul Zarei includes the data collection, analyzing the results and writing the article, and the participation of Mehdi Bahrami includes writing the article and help to analyzing the results.
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Bahrami, M., Bazrkar, S. & Zarei, A.R. Spatiotemporal investigation of drought pattern in Iran via statistical analysis and GIS technique. Theor Appl Climatol 143, 1113–1128 (2021). https://doi.org/10.1007/s00704-020-03480-1
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DOI: https://doi.org/10.1007/s00704-020-03480-1