Drought occurs more frequently in the context of climate change and threatens water security worldwide. An appropriate fitting distribution is crucial for accurately identifying drought using drought indices. Here, seven two‐parameter distributions (Gamma, Gumbel, Logistic, Log–Logistic, Log‐normal, Normal, and Weibull) and four distributions (general logistic, generalized extreme value, Normal, and Pearson Type III) are applied to calculate the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI), respectively, to choose the most appropriate fit for the 541 stations in China. The results show that, in most cases, Gamma and general logistic were the best distributions for SPI and SPEI, respectively. Nevertheless, we noted that Pearson Type III and generalized extreme value also fit the SPEI series well, indicating the importance of distribution fitting assessment for various regions. The annual and seasonal drought evolutions across China were clarified, with drought decreasing significantly in western Northwest China (annually and each season), northern North China (spring and winter), the Tibetan Plateau (spring), and the lower reaches of the Yangtze River (winter) and increasing mainly in South China (spring) and western South China (summer and autumn). The intensity, duration and severity of light, moderate, and severe drought were also detected; the results suggest that drought in China is mainly concentrated around the changes in light and moderate drought. Additionally, we assessed the sensitivity of drought evolution to various meteorological variables. The most sensitive variable in South China, North China and the Tibetan Plateau is precipitation, followed by wind speed, temperature, relative humidity, and sunshine duration; in Northwest China, the order is wind speed, precipitation, temperature, relative humidity, and sunshine duration. Furthermore, the correlation results also indicate that the drought evolution is affected by the multivariate ENSO index, while the influencing characteristics are different in various seasons and regions. The results in this paper contribute to drought mitigation and the effective utilization of water resources in China.

Drought evolutions in the arid region of northwestern China from 1960 to 2010 were analyzed based on the standardized precipitation index (SPI), the standardized precipitation‐evapotranspiration index (SPEI), and the self‐calibrated Palmer drought severity index (SC‐PDSI). All three forms of drought indices were significantly correlated with each other. No statistically significant differences were found for the severity of drought, as assessed by both the SPI and SPEI. The SC‐PDSI was generally an index representing water deficits at a medium period. For the entire geographical area of study, wet conditions dominated during 1987–2010, whereas persistent drought conditions occurred from 1960 to 1986.

Temporal and spatial changes in vegetation and their influencing factors are of great significance for the assessment of climate change and sustainable development of ecosystems. This study applied the Asymmetric Gaussians (AG) fitting method, Mann-Kendall test, and correlation analysis to the Global Inventory Monitoring and Modeling System (GIMMS) third-generation Normalized Difference Vegetation Index and gridded climate and drought data for 1982–2015. The temporal and spatial changes to NDVI for natural grassland and forest during the growing season were analyzed. Relationships among NDVI, climate change, and droughts were also analyzed to reveal the influence of vegetation change. The results showed that: (1) Land use/cover change (LUCC) in China was mainly represented by increases in agricultural land (Agrl) and urban and rural land (Uril), and decreases in unutilized land (Bald), grassland, forest, and permanent glacier and snow (Snga). The increase in agricultural land was mainly distributed in the western northwest arid area (WNW) and northern North China (NNC), whereas regions with severe human activities such as southern South China (SNC), western South China (WSC), and eastern South China (ESC) showed significant decreases in agricultural land due to conversion to urban and rural land. (2) The start of the growing season (SOS) was advanced in WNW, SNC, WSC, and ESC, and the end of growing season (EOS) was delayed in WNW, NNC, and SNC. The growing season length (GSL) of natural vegetation in China has been extended by eight days over the last 34 years. However, the phenology of the Qinghai-Tibet Plateau (TP) was opposite to that of the other regions and the GSL showed an insignificant decreasing trend. (3) The NDVI increased significantly, particularly in the SNC, WSC, ESC, and the grassland of the WNW. Precipitation was found to mainly control the growth of vegetation in the arid and semi-arid regions of northwest China (WNW and ENW), and precipitation had a much greater impact on grassland than on forests. Temperature had an impact on the growth of vegetation throughout China, particularly in SNC, ESC, and WSC. (4) The Standardized Precipitation Evapotranspiration Index (SPEI) showed a downward trend, indicating an aridification trend in China, particularly in ENW, NNC, and WNW. Similar to precipitation, the main areas affected by drought were WNW and ENW and grassland was found to be more sensitive to drought than forest. The results of this study are of great significance for predicting the response of ecosystem productivity to climate change under future climate change scenarios.