4.4 Article

Comprehensive drought monitoring in Yunnan Province, China using multisource remote sensing data

Journal

JOURNAL OF MOUNTAIN SCIENCE
Volume 18, Issue 6, Pages 1537-1549

Publisher

SCIENCE PRESS
DOI: 10.1007/s11629-020-6333-7

Keywords

Multisource data; Comprehensive drought index (CDI); Standardized precipitation index (SPI); Standardized precipitation evapotranspiration index (SPEI); Temperature vegetation dryness index (TVDI); Yunnan Province; China

Funding

  1. Multi government International Science and Technology Innovation Cooperation Key Project of the National Key Research and Development Program of China [2018YFE0184300]
  2. Erasmus+ Capacity Building in Higher Education of the Education, Audiovisual and Culture Executive Agency (EACEA) [586037-EPP-1-2017-1-HU-EPPKA2CBHE-JP]
  3. National Natural Science Foundation of China [41561048]
  4. Technical Methods and Empirical Study on Ecological Assets Measurement in County Level of Yunnan Province [ZDZZD201506]
  5. Young and Middleaged Academic and Technical Leaders Reserve Talents Training Program of Yunnan Province [2008PY056]
  6. Program for Innovative Research Team (in Science and Technology) at the University of Yunnan Province, IRTSTYN

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Development of drought monitoring techniques is crucial for understanding and mitigating droughts. This study in Yunnan Province used various data sources to calculate different indices and constructed comprehensive drought monitoring models using PCA and AHP. The results indicated that CDI is a strong indicator of drought and the drought situation in Yunnan Province showed consistent spatiotemporal changes from 2009 to 2018.
Development of drought monitoring techniques is important for understanding and mitigating droughts and for rational agricultural management. This study used data from multiple sources, including MOD13A3, TRMM 3B43, and SRTMDEM, for Yunnan Province, China from 2009 to 2018 to calculate the tropical rainfall condition index (TRCI), vegetation condition index (VCI), temperature condition index (TCI), and elevation factors. Principal component analysis (PCA) and analytic hierarchy process (AHP) were used to construct comprehensive drought monitoring models for Yunnan Province. The reliability of the models was verified, following which the drought situation in Yunnan Province for the past ten years was analysed. The results showed that: (1) The comprehensive drought index (CDI) had a high correlation with the standardized precipitation index, standardized precipitation evapotranspiration index, temperature vegetation dryness index, and CLDAS (China Meteorological Administration land data assimilation system), indicating that the CDI was a strong indicator of drought through meteorological, remote sensing and soil moisture monitoring. (2) The droughts from 2009 to 2018 showed generally consistent spatiotemporal changes. Droughts occurred in most parts of the province, with an average drought frequency of 29% and four drought-prone centres. (3) Monthly drought coverage during 2009 to 2014 exceeded that over 2015 to 2018. January had the largest average drought coverage over the study period (61.92%). Droughts at most stations during the remaining months except for October exhibited a weakening trend (slope > 0). The CDI provides a novel approach for drought monitoring in areas with complex terrain such as Yunnan Province.

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