Spatiotemporal Analysis of Droughts Over Different Climate Regions Using Hybrid Clustering Method

Kiyoumars Roushangar (), Roghayeh Ghasempour and Vahid Nourani
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Kiyoumars Roushangar: University of Tabriz
Roghayeh Ghasempour: University of Tabriz
Vahid Nourani: University of Tabriz

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2022, vol. 36, issue 2, No 3, 473-488

Abstract: Abstract Assessment of spatiotemporal variations of drought is an efficient method for implementing drought mitigation strategies and reducing its negative impacts. This study aimed to assess the spatiotemporal pattern of short- to long-term droughts for an area with different climates. Therefore, 31 stations located in Iran were selected and the Standardized Precipitation Index (SPI) series with timescales of 3, 6, and 12 months were computed during the 1951-2016 period. A hybrid methodology including Maximal Overlap Discrete Wavelet Transform (MODWT) and K-means methods was used for obtaining the SPIs time-frequency properties and multiscale zoning of the area. The energy amounts of the decomposed subseries via the MODWT were applied as inputs for K-means. Also, the statistics in drought features (i.e. drought duration, severity, and peak) were assessed and the results showed that shorter term droughts (i.e. SPI-3 and -6) were more frequent and severe in the northern parts where the lowest values were obtained for drought duration. It was observed that the regions with more droughts frequency had the highest energy values. For shorter term droughts a direct relationship was obtained between the energy values and the mean SPIs, drought severity, and drought peak, whereas an inverse relationship was obtained for longer term drought. It was found that increasing the degree of SPI led to more similarity between the stations of each cluster. Also, the homogeneity of stations for the SPI-12 was slightly higher than the SPI-3 and -6.

Keywords: Different climate; Drought features; Homogeneity; MODWT; Spatiotemporal analysis (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s11269-021-02974-5

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