自然资源学报 ›› 2015, Vol. 30 ›› Issue (10): 1735-1749.doi: 10.11849/zrzyxb.2015.10.012

• 资源评价 • 上一篇    下一篇

气候变化背景下贵州省农作物生长期干旱时空变化规律

陈学凯1, 雷宏军1, *, 徐建新1, 黄鑫1, 张泽中1, 胡娟萍1, 商崇菊2, 杨静2   

  1. 1. 华北水利水电大学 水利学院,郑州 450045;
    2. 贵州省水利科学研究院,贵阳 550002
  • 收稿日期:2014-10-29 修回日期:2015-03-16 出版日期:2015-10-15 发布日期:2015-10-15
  • 通讯作者: *通信作者简介:雷宏军(1975- ),男,湖北大冶人,副教授,博士后,主要从事节水灌溉及区域水资源高效利用研究。E-mail: hj_lei2002@163.com
  • 作者简介:陈学凯(1990- ),男,河北唐山人,硕士研究生,主要研究区域水资源高效利用方向研究。 E-mail: cxkkaixuan@163.com
  • 基金资助:
    水利部公益性行业科研专项(201301039); 贵州省水利厅科技专项经费项目(KT201313); 国家自然科学基金项目(41271236); 河南省科技攻关计划项目(142102110058,142102310290); 华北水利水电大学青年科技创新人才项目(70459); 华北水利水电大学创新计划项目(HSCX2004059)

Spatial and Temporal Distribution Characteristics of Drought during Crop Growth Period in Guizhou Province from Climate Change Perspectives

CHEN Xue-kai1, LEI Hong-jun1, XU Jian-xin1, HUANG Xin1, ZHANG Ze-zhong1, HU Juan-ping1, SHANG Chong-ju2, YANG Jing2   

  1. 1. School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450045, China;
    2. Water Resources Research Institute of Guizhou Province, Guiyang 550002, China
  • Received:2014-10-29 Revised:2015-03-16 Online:2015-10-15 Published:2015-10-15

摘要: 以干旱高发区贵州省为研究对象,利用贵州省19个站点1960—2013年气象日值资料,考虑气象干旱累积效应及当地秋收农作物生长时期需水要求,验证了秋收作物生育期内标准降水蒸散指数(Sep-SPEI-6)与粮食减产量之间的相关性。基于Sep-SPEI-6指数采用Mann-Kendall法、滑动t检验、Morlet小波周期分析以及Hurst指数等方法分析了贵州省干旱时空变化特征。结果表明:① Sep-SPEI-6与贵州省及各州、市粮食减产量呈极显著负相关性。② 在1991、2001年前后贵州省气候发生了突变。③ 与第一阶段(1960—1991年)相比,第二阶段(1992—2001年)干旱发生频率和影响范围均减少了10.59%;较第二阶段,第三阶段(2002—2013年)分别增加了23.67%和24.74%;与前两阶段相比,第三阶段的干旱历时与强度增加显著。④ Sep-SPEI-6时间序列存在明显的周期性振荡特征,以22 a为第1主周期。⑤ 各站点Sep-SPEI-6的Hurst数值均大于0.5,说明其变化具有较好的持续性。⑥ 干旱易发区呈现由东向西的转移趋势。⑦ 农作物生长期内日降水>1 mm天数和日照总时数是影响农作物生长期干旱的主要气象因素。研究成果为贵州省抗旱减灾措施的制定提供了理论依据。

Abstract: Guizhou is an important agriculture area locating in the southwest of China with maize and rice as its main food crops. Food security here is of great importance to maintain the stability of the minorities. However, droughts have frequently taken place recently, and resulted in big reductions in the crop yield. Under the circumstance of global climate change, therefore, the understanding of the temporal and spatial characteristics of drought and its relation with the climate mutation is of necessity for drought prevention and mitigation. We collected the daily meteorological data of 19 stations in Guizhou Province during 1960-2013. In consideration of the accumulated drought effect and the water requirement of autumn crops, the standard Precipitation-Evaporation index at six-month time scale between April and September (Sep-SPEI-6) was calculated. The correlation analysis between Sep-SPEI-6 and the crop yield reduction was tested. By use of multiple methods, i.e., Mann-Kendall, sliding t-test, Morlet wavelet cycle analysis and Hurst index, the spatial and temporal variation of drought were analyzed. Some results were obtained as bellow. Sep-SPEI-6 in Guizhou Province and the 9 cities showed a significant negative correlation with the annual crop yield reduction. The climate mutation occurred twice around year 1991 and year 2001. Compared with that in the first phase between 1960 and 1991, the occurring frequency and extent of droughts in the second stage between 1992 and 2001 decreased 10.59%. Compared with that in the second stage, the occurring frequency and extent of droughts increased 23.67% and 24.74% respectively in the third phase between 2002 and 2013. In contrast to the former two stages, the third one had significantly increased duration and intensity of drought. There was an obvious periodic oscillation in time series of Sep-SPEI-6, and 22 years was the first primary period. The Hurst index of Sep-SPEI-6 at different stations were all greater than 0.5, suggesting a better continuity in the Sep-SPEI-6 variation. The high drought frequency region tended to move to the west. The days of precipitation greater than 1 mm and the accumulative sunshine hours during the crop growth were both found the main factors affecting the meteorological drought in Guizhou Province. These results are fundamental to the decision of drought mitigation measures.

中图分类号: 

  • P429