Zhang Gengxi, Su Xiaoling, Hao Lina, Wu Haijiang. Response of vegetation to drought based on NDVI and scPDSI data sets from 1982 to 2015 across China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(20): 145-151. DOI: 10.11975/j.issn.1002-6819.2019.20.018
    Citation: Zhang Gengxi, Su Xiaoling, Hao Lina, Wu Haijiang. Response of vegetation to drought based on NDVI and scPDSI data sets from 1982 to 2015 across China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2019, 35(20): 145-151. DOI: 10.11975/j.issn.1002-6819.2019.20.018

    Response of vegetation to drought based on NDVI and scPDSI data sets from 1982 to 2015 across China

    • Drought is a natural hazard caused by long-term precipitation deficiency and high evaporation resulted from high temperature, which is among the most common disasters around the world. In recent decades, with the intensification of climate change and human activities, drought occurrence is becoming more frequent in China, causing negative impacts on agricultural production, ecological environment and social economy. Therefore, it is significant to explore the impact of drought on vegetation for agricultural production and healthy development of ecological systems. In this paper, the response and sensitivity of vegetation to drought in different climatic zones in China were analyzed, and the effects of different climatic factors, including water balance (precipitation-potential evapotranspiration), annual precipitation, mean temperature and sunshine hours, on the relationship between different vegetation types including forestland, grassland and cultivated land and drought were explored, so as to reveal the response mechanism of ecological vegetation to drought from a macro perspective. Using the self-calibrating Palmer drought severity index (scPDSI) and normalized difference vegetation index (NDVI) data for the period of 1982-2015, the response rule and sensitivity of different types of vegetation to drought were analyzed by applying time-delay correlation method, and the influence of various climate factors on the relationship between vegetation and drought was analyzed by applying linear regression method. The results of the research showed that in northwest China, Inner Mongolia, north China plain and southern Qinghai-Tibet plateau, the correlation of shorter lag time scPDSI (1-3 months) and NDVI was close (Rmax>0.4), which indicated that vegetation growth was more sensitive to drought in these regions and that vegetation biomass were influenced mainly by the spatiotemporal characteristics of the water availability. In the humid areas of south China, including the middle and lower reaches of the Yangtze River and the Pearl River basin, the precipitation is abundant so that the correlation between NDVI and scPDSI was negative, and the response of vegetation was not sensitive to drought. The growth of vegetation is mainly controlled by energy factors such as temperature and sunshine hours. The relationship between vegetation and drought was significantly affected by the average annual water balance, precipitation, sunshine hours and temperature, among which the annual water balance was the main water controlling factor (R2=0.45). It can be concluded that the change of water availability was the key factor behind the change of vegetation vigor. Sunshine hours were the main energy controlling factor. When average annual temperature was less than 5℃, the effect of temperature on the correlation between scPDSI and NDVI was also significant. The sensitive areas of drought impact on vegetation were mainly in the northern arid regions, while the southern humid areas had strong resilience and resilience to drought. The sensitivity of different types of vegetation to drought varied greatly, and the order of sensitivity is grassland >forestland>cultivated land. The results can provide a scientific basis for the evaluation of the impact of drought on ecological vegetation in different regions of China, and thus help to guide agricultural and environmental production, protect vulnerable ecosystems and provide implications for sustainable socioeconomic development.
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