4.6 Article

Drought monitoring in Yunnan Province based on a TRMM precipitation product

Journal

NATURAL HAZARDS
Volume 104, Issue 3, Pages 2369-2387

Publisher

SPRINGER
DOI: 10.1007/s11069-020-04276-2

Keywords

TRMM; Drought; GWR; Pa; TRCI; Yunnan Province

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) for Innovation on Remote Sensing Education and Learning [586037-EPP-1-2017-1-HU-EPPKA2-CBHE-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 Middle-aged 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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Yunnan Province is a region with frequent droughts; thus, drought monitoring research is important for implementing active and effective measures to mitigate drought and scientifically guide agricultural production. In this study, the Tropical Rainfall Measuring Mission (TRMM 3B43) remote sensing-based product is used as the data source, and a geographically weighted regression (GWR) model, normalized difference vegetation index (NDVI) data and gross primary productivity (GPP) are used as independent variables. The TRMM 3B43 data are downscaled to 1 km spatial resolution to obtain two downscaled precipitation models (GWR_NDVI and GWR_GPP). The precipitation anomaly percentage (Pa) index and the tropical rainfall condition index (TRCI) are used to evaluate the drought situation in Yunnan Province from 2009 to 2018, and the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) are used to verify the Pa and TRCI. The results show the following: (1) With anR(2)as high as 0.8821 and BIAS close to zero, the TRMM 3B43 monthly precipitation is significantly correlated with the measured precipitation. The GWR_NDVI data increase theR(2)at the monthly scale by 0.0114; the GWR_NDVI data show greater improvements from spring and winter than from summer and autumn; and theR(2)of the GWR_NDVI data for some sites are slightly reduced. TheR(2)of GWR_GPP data is smaller than that of the TRMM data and GWR_NDVI data at all timescales. (2) Drought occurs every month from 2009 to 2018; it decreases from November to February of the following year and is generally alleviated from March to April; and the incidence of drought from 2009 to 2014 is generally higher than that from 2015 to 2018. The Pa and TRCI show strong correlations with the SPI and SPEI and thus can be used to effectively monitor drought events in Yunnan, although the degree of drought assessed by the Pa and TRCI differs. (3) The spatial distribution of precipitation in Yunnan Province shows little precipitation in the north and east but abundant precipitation in the south and west. Precipitation is mainly concentrated from May to October, with the most abundant precipitation occurring in July.

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