Responses of Seasonal Indicators to Extreme Droughts in Southwest China

Remote Sensing - Tập 12 Số 5 - Trang 818
Peiyu Lai1,2,3, Miao Zhang4, Zhongxi Ge1,2,3, Binfei Hao1,2,3, Zengjing Song1,2,3, Huang Jing1,2,3, Mingguo Ma1,2,3, Hong Yang1,5, Xujun Han1,2,3
1Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
2Southwest University, School of Geographical Sciences, Chongqing Jinfo Mountain Field Scientific Observation and Research Station for Karst Ecosystem, Ministry of Education, Chongqing 400715, China
3State Cultivation Base of Eco-agriculture for Southwest Mountainous Land, Southwest University, Chongqing, 400715, China
4Northwest Land and Resources Research Center, Shaanxi Normal University, Xi'an, 710119, China
5Department of Geography and Environmental Science, University of Reading, Whiteknights, Reading, RG6 6AB, UK

Tóm tắt

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.

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Remote Sensing

Tập 12 Số 5

818

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