Drought Trend Analysis Using Standardized Precipitation Evapotranspiration Index in Cold-Climate Regions

This study aimed to conduct a drought trend analysis using the standardized precipitation evapotranspiration index (SPEI) in two mountainous and cold-climate regions in Iran and the United States (US). The Mann–Kendall test was employed to assess the trend in the Upper Colorado River Basin (UCRB) in the US and Lorestan province. The results reveal a predominantly decreasing trend in drought occurrences across Lorestan, especially in southern and southwestern areas with lower elevations. In contrast, the UCRB showed a positive trend, indicating a wet period. The western parts of the UCRB were predominantly affected by droughts. Among the stations, the Khorram Abad station exhibited the most statistically significant trend at the 99% confidence level (Z > 2.57). A temporal trend analysis of droughts revealed more positive and negative abrupt changes in the UCRB than in Lorestan. This indicates a higher degree of small-scale variability in the UCRB compared to Lorestan. This study indicates that factors such as elevation, land use changes, and proximity to water sources may contribute to the observed variations in drought trends. Additionally, the findings highlight that rising temperatures have a significantly greater impact on drought severity than reductions in precipitation. This study provides a temperature-responsive method for drought assessments, supporting the development of adaptive strategies that address snowmelt variability, seasonal water availability, and shifting drought patterns in cold regions.

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Publication Details

Journal
Atmosphere
Published
2025-04-21
DOI
https://doi.org/10.3390/atmos16040482
Citations
6
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
6.63
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article

Drought Trend Analysis Using Standardized Precipitation Evapotranspiration Index in Cold-Climate Regions

Saeid Eslamian, Mohammad Hadi Bazrkar, Yaser Sabzevari, Abhiram Siva Prasad Pamula
6 citations
Atmosphere
Climate variability and models
6.63
article

Drought Trend Analysis Using Standardized Precipitation Evapotranspiration Index in Cold-Climate Regions

Saeid Eslamian, Mohammad Hadi Bazrkar, Yaser Sabzevari, Abhiram Siva Prasad Pamula
article en
6 citations

Abstract

This study aimed to conduct a drought trend analysis using the standardized precipitation evapotranspiration index (SPEI) in two mountainous and cold-climate regions in Iran and the United States (US). The Mann–Kendall test was employed to assess the trend in the Upper Colorado River Basin (UCRB) in the US and Lorestan province. The results reveal a predominantly decreasing trend in drought occurrences across Lorestan, especially in southern and southwestern areas with lower elevations. In contrast, the UCRB showed a positive trend, indicating a wet period. The western parts of the UCRB were predominantly affected by droughts. Among the stations, the Khorram Abad station exhibited the most statistically significant trend at the 99% confidence level (Z > 2.57). A temporal trend analysis of droughts revealed more positive and negative abrupt changes in the UCRB than in Lorestan. This indicates a higher degree of small-scale variability in the UCRB compared to Lorestan. This study indicates that factors such as elevation, land use changes, and proximity to water sources may contribute to the observed variations in drought trends. Additionally, the findings highlight that rising temperatures have a significantly greater impact on drought severity than reductions in precipitation. This study provides a temperature-responsive method for drought assessments, supporting the development of adaptive strategies that address snowmelt variability, seasonal water availability, and shifting drought patterns in cold regions.

AtmosphereVol. 16(4)
Marquette University (US), Isfahan University of Technology (IR), Slovak Academy of Sciences (SK), Temple College (US), Institute of Hydrology of the Slovak Academy of Sciences (SK)
Openalex Percentile: Top 3%
Climate variability and models
6.63
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