Spatial-Temporal Variation of Drought in China from 1982 to 2010 Based on a modified Temperature Vegetation Drought Index (mTVDI)

Zhao, Shuang; Cong, Dianmin; He, Kexun; Hong, Yang; Qin, Zhihao

doi:10.1038/s41598-017-17810-3

Cited by 69 publications

(46 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The positive relationship occurred in cold seasons but negative relationship appeared in warm seasons [32]. Other studies researched drought by monitoring LST and NDVI [34]. For example, an increasing trend of aridity was found in arid and semi-arid areas of Southern Europe by monitoring LST and NDVI via Harmonic Analysis of Time Series software from 1982 to 1999 [31].…”

Section: Introductionmentioning

confidence: 99%

Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016

Song

Qiu

et al. 2018

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Land surface temperature (LST) is an important parameter to evaluate environmental changes. In this paper, time series analysis was conducted to estimate the interannual variations in global LST from 2001 to 2016 based on moderate resolution imaging spectroradiometer (MODIS) LST, and normalized difference vegetation index (NDVI) products and fine particulate matter (PM2.5) data from the Atmospheric Composition Analysis Group. The results showed that LST, seasonally integrated normalized difference vegetation index (SINDVI), and PM2.5 increased by 0.17 K, 0.04, and 1.02 μg/m3 in the period of 2001–2016, respectively. During the past 16 years, LST showed an increasing trend in most areas, with two peaks of 1.58 K and 1.85 K at 72°N and 48°S, respectively. Marked warming also appeared in the Arctic. On the contrary, remarkable decrease in LST occurred in Antarctic. In most parts of the world, LST was affected by the variation in vegetation cover and air pollutant, which can be detected by the satellite. In the Northern Hemisphere, positive relations between SINDVI and LST were found; however, in the Southern Hemisphere, negative correlations were detected. The impact of PM2.5 on LST was more complex. On the whole, LST increased with a small increase in PM2.5 concentrations but decreased with a marked increase in PM2.5. The study provides insights on the complex relationship between vegetation cover, air pollution, and land surface temperature.

show abstract

Section: Introductionmentioning

confidence: 99%

Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016

Song

Qiu

et al. 2018

Remote Sensing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Drought indices play an important role in identifying and quantifying drought and are recognized as the best approach for obtaining a measure of relative wetness or dryness [19][20][21]. The commonly used drought indices include the Palmer Drought Severity Index (PDSI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Precipitation Index (SPI), the Vegetation Health Index (VHI) and the Temperature Vegetation Drought Index (TDVI) [11,[21][22][23][24][25]. With the advantage of taking account of the cumulative effect of moisture supply and demand, PDSI has been widely used in drought studies all over the world [26].…”

Section: Introductionmentioning

confidence: 99%

Responses of Seasonal Indicators to Extreme Droughts in Southwest China

Lai

Zhang

et al. 2020

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Significant impact of extreme droughts on human society and ecosystem has occurred in many places of the world, for example, Southwest China (SWC). Considerable research concentrated on analyzing causes and effects of droughts in SWC, but few studies have examined seasonal indicators, such as variations of surface water and vegetation phenology. With the ongoing satellite missions, more and more earth observation data become available to environmental studies. Exploring the responses of seasonal indicators from satellite data to drought is helpful for the future drought forecast and management. This study analyzed the seasonal responses of surface water and vegetation phenology to drought in SWC using the multi-source data including Seasonal Water Area (SWA), Permanent Water Area (PWA), Start of Season (SOS), End of Season (EOS), Length of Season (LOS), precipitation, temperature, solar radiation, evapotranspiration, the Palmer Drought Severity Index (PDSI), the Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), Gross Primary Productivity (GPP) and data from water conservancy construction. The results showed that SWA and LOS effectively revealed the development and recovery of droughts. There were two obvious drought periods from 2000 to 2017. In the first period (from August 2003 to June 2007), SWA decreased by 11.81% and LOS shortened by 5 days. They reduced by 21.04% and 9 days respectively in the second period (from September 2009 to June 2014), which indicated that there are more severe droughts in the second period. The SOS during two drought periods delayed by 3~6 days in spring, while the EOS advanced 1~3 days in autumn. All of PDSI, SWA and LOS could reflect the period of droughts in SWC, but the LOS and PDSI were very sensitive to the meteorological events, such as precipitation and temperature, while the SWA performed a more stable reaction to drought and could be a good indicator for the drought periodicity. This made it possible for using SWA in drought forecast because of the strong correlation between SWA and drought. Our results improved the understanding of seasonal responses to extreme droughts in SWC, which will be helpful to the drought monitoring and mitigation for different seasons in this ecologically fragile region.

show abstract

“…Predicting future drought trends has received much attention in recent years, which is important for long-term water use planning and developing adaptation strategies to reduce climate risk [15][16][17][18][19]. However, most current work focuses on the analysis of specific regions (e.g., southwest China [20], eastern China [21], northwest China [22], and Loess Plateau [23]) rather than the whole China.…”

Section: Introductionmentioning

confidence: 99%

Drought Trend Analysis Based on the Standardized Precipitation–Evapotranspiration Index Using NASA’s Earth Exchange Global Daily Downscaled Projections, High Spatial Resolution Coupled Model Intercomparison Project Phase 5 Projections, and Assessment of Potential Impacts on China’s Crop Yield in the 21st Century

Guo

Yang

et al. 2019

Water

View full text Add to dashboard Cite

Drought is among the costliest natural disasters on both ecosystems and agroeconomics in China. However, most previous studies have used coarse resolution data or simply stopped short of investigating drought projection and its impact on crop yield. Motivated by the newly released higher-resolution climate projection dataset and the crucial need to assess the impact of climate change on agricultural production, the overarching goal of this study was to systematically and comprehensively predict future droughts at unprecedented resolutions over China as a whole. rather than region-specific projections, and then to further investigate its impact on crop yield by innovatively using a soil water deficit drought index. Methodologically, the drought projections were quantified from very high resolution climate data and further predicted impacts on crop yield over China using the standardized precipitation–evapotranspiration index (SPEI) at a relatively high (25 km) spatial resolution from NASA’s Earth Exchange Global Daily Downscaled Projections (NEX-GDDP). The results showed that (1) overall, China is projected to experience a significant decrease in SPEI (−0.15/decade under RCP (representative concentration pathway) 4.5; −0.14/decade under RCP8.5). Seasonally, the decreasing rate of SPEI is projected to be largest in winter (−0.2/decade and −0.31/decade) and the least in summer (−0.08/decade and −0.10/decade) under respective RCPs. (2) Regionally, winter/spring will get drier, especially at high latitudes/altitudes (North China and Tibetan plateau), and summer/autumn will get wetter in southern China. (3) Both the frequency and duration for medium and severe drought are projected to decrease, while extreme drought, particularly in high latitudes/altitudes, is projected to increase. (4) The percentage of the potential crop production affected by drought would increase to 36% (47%) by 2100 under RCP4.5 (RCP8.5). Especially, the ratio impacted by extreme drought is projected to increase over time and with much worse magnitude under RCP8.5; thus, adaptive crop policies are expected to address such a risk.

show abstract

Spatial-Temporal Variation of Drought in China from 1982 to 2010 Based on a modified Temperature Vegetation Drought Index (mTVDI)

Cited by 69 publications

References 45 publications

Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016

Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016

Responses of Seasonal Indicators to Extreme Droughts in Southwest China

Contact Info

Product

Resources

About