Chinese Journal of Agrometeorology ›› 2016, Vol. 37 ›› Issue (05): 587-599.doi: 10.3969/j.issn.1000-6362.2016.05.011

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Variation of Drought Characteristics and its Agricultural Exposure in North China Plain

CHEN Jing,LIU Hong-bin,WANG Yan-jun,WANG An-qian,SU Bu-da,JU Hui   

  1. 1.Collaboration Innovation Center on Forecast and Evaluation of Meteorological Disasters/School of Geography & Remote Sensing, Nanjing University of Information Science &Technology, Nanjing 210044, China;2.National Climate Center, Beijing 100081;3.Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Science, Beijing 100081
  • Received:2016-02-29 Online:2016-10-20 Published:2016-10-12

Abstract: Based on the observed monthly precipitation data of 52 meteorological stations for 1961-2014 and the projected data of regional climate model COSMO-CLM (CCLM), the standardized precipitation index (SPI) and the Intensity-Area-Duration method (IAD method) were used to analyze the characteristics and spatial-temporal distribution of the drought events in the past (1961-2014) and future (2016-2050) under RCP scenarios(RCP2.6,4.5,8.5 ). And the evolution of agricultural land exposure to these drought events in 2016-2050 was estimated by applying the land use data in 2000. Results showed that: (1) from 1961 to 2014, the spatial distribution of drought center migrated from south to north in the North China Plain. (2)The unprecedented drought events are projected to occur in all three RCP scenarios in 2016-2050,and probably happens more frequently in RCP2.6 than other scenarios. (3) Under RCP2.6 and 4.5 scenarios, the exposure of agricultural land to drought is expected to raise, and that of RCP4.5 scenario increases comparatively faster. While, the trend of agriculture land exposure might decrease under RCP8.5 scenario for 2016-2050. The peak value of agricultural exposure under three RCP scenarios will occur in the late 2040s, the early 2040s, and the mid-2020s, respectively.

Key words: Intensity-Area-Duration method, Regional climate model CCLM, RCP scenarios, Agriculture land, Exposure