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It is vital to understand long-term drought variability and its causes for better water resource management in precipitation deficit regions. In order to assess the characteristics and potential risk of drought in Qinghai Province (as a typical arid and semi-arid area in China), the temporal trends of precipitation and temperature data (daily records from 1961 to 2006) of 44 stations across this province were firstly detected using the Mann-Kendall trend test. The self-calibrating Palmer drought severity index (PDSI), rotated empirical orthogonal function (REOF), and continuous wavelet transform (CWT) were used to further evaluate and investigate spatial patterns, temporal variations and periodicities of dryness/wetness conditions in Qinghai. The results show that: (1) A significant increasing trend in annual mean temperature can be detected in most parts of Qinghai over the last five decades, especially in Qaidam Basin. A non-significant downward trend in annual precipitation can be found in the eastern and southeastern regions of the province; (2) Four dominantly geographical sub-climate regions of dryness/wetness conditions were identified - the source region (Tuotuo River) of the Yangtze River, Qaidam Basin, the Qilian Mountains area, and the eastern agricultural area; (3) With respect to temporal variations of dryness/wetness conditions in each sub-region, only the source region (Tuotuo River) of the Yangtze River indicates a long-term wet tendency over the past 46 years; (4) A 3-5-year significant (at 95% confidence level) periodical oscillation can be detected in the PDSI series of the source region of the Yangtze River and 5-7-year and 8-10-year periods exist in Qaidam Basin. However, periodical features in the Qilian Mountains and eastern agricultural area are not statistically noticeable. The results of this study will be beneficial for water resource management, forecasting, and preparations for potential drought hazards in Qinghai Province and also be a valuable reference for other arid and semi-arid areas. (C) 2013 Elsevier B.V. All rights reserved.