Abstract
Drought is expected to increase in frequency and severity due to global warming, and its impacts on vegetation are typically extensively evaluated with climatic drought indices, such as multi-scalar Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the covariation between the SPEIs of various time scales and the anomalies of the normalized difference vegetation index (NDVI), from which the vegetation type-related optimal time scales were retrieved. The results indicated that the optimal time scales of needle-leaved forest, broadleaf forest and shrubland were between 10 and 12 months, which were considerably longer than the grassland, meadow and cultivated vegetation ones (2 to 4 months). When the optimal vegetation type-related time scales were used, the SPEI could better reflect the vegetation’s responses to water conditions, with the correlation coefficients between SPEIs and NDVI anomalies increased by 5.88% to 28.4%. We investigated the spatio-temporal characteristics of drought and quantified the different responses of vegetation growth to drought during the growing season (April–October). The results revealed that the frequency of drought has increased in the 21st century with the drying trend occurring in most of China. These results are useful for ecological assessments and adapting management steps to mitigate the impact of drought on vegetation. They are helpful to employ water resources more efficiently and reduce potential damage to human health caused by water shortages.
Highlights
Drought is a complex natural hazard that affects water resources, natural ecosystems, agriculture, and society more frequently than any other natural disaster [1,2,3]
When the Standardized Precipitation Evapotranspiration Index (SPEI) of a specific meteorological station was less than −1, it was regarded as the drought
The regression models between the NDVIanomaly and the SPEI with both the SPEI-12 and the optimal time scale (SPEIopt) for various vegetation types are compared, and the results show that the relationship between the NDVIanomaly and the SPEIopt has better linear trends, as the R2 increased by
Summary
Drought is a complex natural hazard that affects water resources, natural ecosystems, agriculture, and society more frequently than any other natural disaster [1,2,3]. Over 900 million people worldwide were affected by drought during the period of 1999 to 2010 [4]. Drought has occurred in most places of the world, including wet and humid regions [5,6], and it is expected to increase in frequency and severity due to decreasing precipitation and increasing evapotranspiration driven by global warming [7,8,9,10]. In China, drought has become one of the most severe natural disasters [6], and the affected area has increased in the past 50 years [11]. Serious drought events occur frequently in China, especially in Yunnan Province [12,13]. The most widely used method is to propose a climatic drought index, which is simple to use to reflect the fluctuation of water conditions [14,15,16]
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