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首页> 外文期刊>Journal of Geophysical Research, D. Atmospheres: JGR >Assessing spatiotemporal variation of drought in China and its impact on agriculture during 1982–2011 by using PDSI indices and agriculture drought survey data
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Assessing spatiotemporal variation of drought in China and its impact on agriculture during 1982–2011 by using PDSI indices and agriculture drought survey data

机译：利用PDSI指数和农业干旱调查数据评价1982-2011年中国干旱的时空变化及其对农业的影响。

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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.
机译：受对气候变暖影响的担忧启发，干旱变化及其影响在中国引起了广泛关注。关于中国干旱的争论仍然存在，很少有工作利用农业干旱调查区来评估自然干旱对农业的影响。基于新修订的基于空气相对湿度的两源（ARTS）E_0驱动的自校正帕尔默干旱严重程度指数（PDSI）模型（PDSI_（ARTS）; Yan等人，2014），时空变化对中国1982-2011年的干旱变化进行了分析，这表明在这段时间内干旱没有明显变化，但在2000-2001年发生了极端干旱事件。但是，使用基于气温（T_a）的Thornthwaite势能蒸发量（E_（P_Th））和Penman-Monteith势能蒸发量（E_（P_PM））来驱动PDSI模型，它们相应的PDSI_（Th）和PDSI_（PM）都给出了1982年至2011年的明显干燥趋势。这表明PDSI模型对中国的E_P参数化敏感。最初采用了农业调查中的年度干旱覆盖面积来评估1982-2011年间PDSI干旱对中国农业的影响。结果表明，PDSI_（ARTS）干旱区（定义为PDSI_（ARTS）<-0.5）与农业干旱覆盖区具有良好的相关性，PDSI_（ARTS）在1982-2011年成功检测到2000-2001年的极端农业干旱，即，气候因素主导了农业干旱区的年际变化，而PDSI_（Th）和PDSI_（PM）干旱区与农业干旱覆盖区没有关系，并且高估了农业干旱的上升趋势。用干旱调查数据评估自然干旱对农业的影响。

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