Drought spatiotemporal variations assessment is an efficient method for implementing drought mitigation strategies and reducing its negative impacts. In this study, the spatiotemporal pattern of short to long-term droughts was assessed for an area with different climates. 31 stations located in Iran were considered and the Standardized Precipitation Index (SPI) series with timescales of 3, 6, and 12 months were calculated during the 1951-2016 period. A hybrid methodology namely Maximal Overlap Discrete Wavelet Transform (MODWT) was applied to obtain the SPIs time-frequency properties and multiscale zoning was done via K-means clustering approach. The energy amounts of decomposed subseries via the MODWT were used as inputs for K-means approach. 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 north parts where the lowest values of drought duration were obtained. 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 mean SPI, drought severity, and drought peak, whereas an inverse relationship was obtained for longer term drought. It was found that with increasing the degree of SPI, the similarity of the stations of each cluster increased too and the homogeneity of stations for the SPI-12 was slightly higher than the SPI-3 and -6.