Premium
Assessing spatiotemporal variation of drought in China and its impact on agriculture during 1982–2011 by using PDSI indices and agriculture drought survey data
Author(s) -
Yan Hao,
Wang ShaoQiang,
Wang JunBang,
Lu HouQuan,
Guo AnHong,
Zhu ZaiChun,
Myneni Ranga B.,
Shugart Herman H.
Publication year - 2016
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2015jd024285
Subject(s) - agriculture , china , climate change , climatology , geography , environmental science , relative humidity , physical geography , meteorology , ecology , biology , archaeology , geology
Inspired by concerns of the effects of a warming climate, drought variation and its impacts have gained much attention in China. Arguments about China's drought persist and little work has utilized agricultural drought survey area to evaluate the impact of natural drought on agriculture. Based on a newly revised self‐calibrating Palmer Drought Severity Index (PDSI) model driven with air‐relative‐humidity‐based two‐source (ARTS) E 0 (PDSI ARTS ; Yan et al., 2014), spatial and temporal variations of drought were analyzed for 1982–2011 in China, which indicates that there was nonsignificant change of drought over this interval but with an extreme drought event happened in 2000–2001. However, using air temperature ( T a )‐based Thornthwaite potential evaporation ( E P_Th ) and Penman‐Monteith potential evaporation ( E P_PM ) to drive the PDSI model, their corresponding PDSI Th and PDSI PM all gave a significant drying trend for 1982–2011. This suggests that PDSI model was sensitive to E P parameterization in China. Annual drought‐covered area from agriculture survey was initially adopted to evaluate impact of PDSI drought on agriculture in China during 1982–2011. The results indicate that PDSI ARTS drought area (defined as PDSI ARTS < −0.5) correlated well with the agriculture drought‐covered area and PDSI ARTS successfully detected the extreme agriculture drought in 2000–2001 during 1982–2011, i.e., climate factors dominated the interannual changes of agriculture drought area, while PDSI Th and PDSI PM drought areas had no relationship with the agriculture drought‐covered area and overestimated the uptrend of agriculture drought This study highlights the importance of coupling PDSI with drought survey data in evaluating the impact of natural drought on agriculture.