JOURNAL OF NATURAL RESOURCES ›› 2020, Vol. 35 ›› Issue (10): 2553-2568.doi: 10.31497/zrzyxb.20201019

• Regular Articles • Previous Articles    

Establishment of comprehensive drought monitoring model based on downscaling TRMM and MODIS data

YU Hao-zhe1,2,3, LI Li-juan2, LI Jiu-yi2   

  1. 1. School of History Culture and Tourism, Shaanxi University of Technology, Hanzhong 723000, Shaanxi, China;
    2. Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    3. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2019-06-27 Revised:2019-11-24 Online:2020-10-28 Published:2020-12-28

Abstract: The Beijing-Tianjin-Hebei region is one of the main producing areas of high-quality winter wheat in China, but drought disasters frequently occur in this region under the influence of global warming. Accurate monitoring of drought in the Beijing-Tianjin-Hebei region can not only provide scientific guidance for regional agricultural production, but also play an important strategic role in guaranteeing national food security. Therefore, in this study, drought-causing factors such as precipitation, vegetation growth, soil moisture gain and loss were considered comprehensively. Firstly, the GWR (Geographical Weighted Regression) model was used to downscale TRMM (Tropical Rainfall Measuring Mission) 3B43 data, and the Precipitation Condition Index (PCI) with a 1-km resolution was obtained. Combining MODIS (Moderate-Resolution Imaging Spectroradiometer) data, the Vegetation Condition Index (VCI), Temperature Condition Index (TCI) were obtained. Finally, a comprehensive drought index (CDI) was constructed based on the multiple regression model to achieve spatial and temporal monitoring and evaluation. The results show that: (1) The annual and monthly data of the 1-km spatial resolution TRMM based on the GWR model and proportion coefficient method have been greatly improved in spatial resolution compared with the original TRMM data, and the accuracy of the data has also passed the test, which shows that the downscaling analysis improves the description ability of TRMM data to the spatial and temporal characteristics of precipitation in the study area. (2) The results of the monitoring model are basically consistent with the drought process. The correlation coefficient (R value) between CDI and Standard Precipitation Index (SPI) was 0.45-0.85, and the correlation coefficient between CDI and drought area of crops ranged from -0.81 to -0.86, and all of them passed the very significant test of P<0.01, and the R value was greater than 0.6 between the CDI and standardized unit yield of crop (P<0.05), which indicated that the comprehensive drought monitoring model constructed by this research was applicable in the Beijing-Tianjin-Hebei region.

Key words: TRMM, statistical downscaling, multi-source remote sensing data, comprehensive drought monitoring model, Beijing-Tianjin-Hebei region