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应用生态学报 ›› 2018, Vol. 29 ›› Issue (4): 1071-1078.doi: 10.13287/j.1001-9332.201804.013

• 水文变异与非一致性专栏 • 上一篇    下一篇

基于信息熵的我国日降水量随机性和时空差异性

李鑫鑫1,2, 桑燕芳1,3*, 谢平4, 刘昌明1   

  1. 1中国科学院地理科学与资源研究所陆地水循环与地表过程重点实验室, 北京 100101;
    2中国科学院大学, 北京 101407;
    3南京水利科学研究院水文水资源与水利工程科学国家重点实验室, 南京 210029;
    4武汉大学水资源与水电工程科学国家重点实验室, 武汉 430072;
  • 收稿日期:2017-06-18 出版日期:2018-04-18 发布日期:2018-04-18
  • 通讯作者: * E-mail: sangyf@igsnrr.ac.cn
  • 作者简介:李鑫鑫,女,1993年生,硕士研究生.主要从事水文系统变异诊断与模拟研究. E-mail: inslixin@163.com
  • 基金资助:

    本文由国家自然科学基金项目(91647110,91547205,41330529)、中国科学院地理科学与资源研究所 “秉维”优秀青年人才计划项目、中国科学院青年创新促进会项目(2017074)和水文水资源与水利工程科学国家重点实验室开放研究基金项目(2015491811)资助

Stochastic characteristics of daily precipitation and its spatiotemporal difference over China based on information entropy

LI Xin-xin1,2, SANG Yan-fang1,3*, XIE Ping4, LIU Chang-ming1   

  1. 1Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    2University of Chinese Academy of Sciences, Beijing 101407, China;
    3State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing Hydraulic Research Institute, Nanjing 210029, China;
    4State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China;
  • Received:2017-06-18 Online:2018-04-18 Published:2018-04-18
  • Contact: * E-mail: sangyf@igsnrr.ac.cn
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (91647110, 91547205, 41330529), the “Bingwei” Excellent Talents from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, the Youth Innovation Promotion Association of Chinese Academy of Sciences (2017074) and the Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (2015491811).

摘要: 我国日降水过程呈现明显的随机性与时空差异性,如何准确认识其时空变化规律对洪涝灾害防治等实际工作的影响具有重要意义.本文基于1961—2013年全国520个气象站点的日降水数据,选用信息熵指标研究我国日降水量的随机性.结果表明: 研究期间,我国东南地区日降水量的随机性大于西北地区,且不同等级日降水量随机性的空间分布存在差异,小雨(降雨量0.1~10 mm,P0)等级日降水量随机性较大,差异不明显,中雨(10~25 mm,P10)、大雨(25~50 mm,P25)等级日降水量随机性最大,差异明显,暴雨及以上(≥50 mm,P50)等级日降水量随机性最小,差异最明显.整体上,日降水的信息熵值呈上升趋势,表明全球气候变化下我国大部分地区日降水量的随机性增大,尤其表现为极端暴雨发生的频次明显增大.日降水信息熵的空间分布及其变化趋势可以很好地综合反映我国日降水量随机性的空间分布格局,可为洪涝灾害防治、农业规划布局、生态环境规划等提供科学依据.

关键词: 日降水, 随机性, 信息熵, 时空差异性, 中国, 洪涝灾害

Abstract: Daily precipitation process in China showed obvious randomness and spatiotemporal variation. It is important to accurately understand the influence of precipitation changes on control of flood and waterlogging disaster. Using the daily precipitation data measured at 520 stations in China during 1961-2013, we quantified the stochastic characteristics of daily precipitation over China based on the index of information entropy. Results showed that the randomness of daily precipitation in the southeast region were larger than that in the northwest region. Moreover, the spatial distribution of stochastic characteristics of precipitation was different at various grades. Stochastic characteri-stics of P0(precipitation at 0.1-10 mm) was large, but the spatial variation was not obvious. The stochastic characteristics of P10(precipitation at 10-25 mm) and P25(precipitation at 25-50 mm) were the largest and their spatial difference was obvious. P50(precipitation ≥50 mm) had the smallest stochastic characteristics and the most obviously spatial difference. Generally, the entropy values of precipitation obviously increased over the last five decades, indicating more significantly stochastic characteristics of precipitation (especially the obvious increase of heavy precipitation events) in most region over China under the scenarios of global climate change. Given that the spatial distribution and long-term trend of entropy values of daily precipitation could reflect thespatial distribution of stochastic characteristics of precipitation, our results could provide scientific basis for the control of flood and waterlogging disaster, the layout of agricultural planning, and the planning of ecological environment.

Key words: flood disaster, temporal-spatial difference, China., information entropy, stochastic characteristics, daily precipitation