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应用生态学报 ›› 2021, Vol. 32 ›› Issue (9): 3277-3287.doi: 10.13287/j.1001-9332.202109.017

• 研究论文 • 上一篇    下一篇

鄱阳湖流域极端降水时空分布和非平稳性特征

雷享勇1, 高路1,2,3*, 马苗苗4,5, 党皓飞6, 高建芸6   

  1. 1福建师范大学地理研究所, 福州 350007;
    2福建省陆地灾害监测评估工程技术研究中心, 福州 350007;
    3湿润亚热带山地生态国家重点实验室培育基地, 福州 350007;
    4中国水利水电科学研究院, 北京 100038;
    5水利部防洪抗旱减灾工程技术研究中心, 北京 100038;
    6福建省灾害天气重点实验室, 福州 350001
  • 收稿日期:2021-03-17 接受日期:2021-06-11 出版日期:2021-09-15 发布日期:2022-03-15
  • 通讯作者: * E-mail: l.gao@foxmail.com
  • 作者简介:雷享勇, 男, 1997年生, 硕士研究生。主要从事水文气象与生态安全研究。E-mail: xiangyonglei@163.com
  • 基金资助:
    国家重点研发计划项目(2018YFE0206400)、福建省科技厅省属公益类科研专项(2019R1002-3)、福建省灾害天气重点实验室开放课题(2020KFKT01)和福建省高校杰出青年科研人才培育计划项目资助

Temporal-spatial and non-stationarity characteristics of extreme precipitation in the Poyang Lake Basin, China

LEI Xiang-yong1, GAO Lu1,2,3*, MA Miao-miao4,5, DANG Hao-fei6, GAO Jian-yun6   

  1. 1Institude of Geography, Fujian Normal University, Fuzhou 350007, China;
    2Fujian Provincial Engineering Research Center for Monitoring and Accessing Terrestrial Disasters, Fuzhou 350007, China;
    3Cultivation Base of State Key Laboratory of Subtropical Mountain Ecology, Fuzhou 350007, China;
    4China Institute of Water Resources and Hydropower Research, Beijing 100038, China;
    5Research Center on Flood and Drought Disaster Reduction of the Ministry of Water Resources, Beijing 100038, China;
    6Fujian Key Laboratory of Severe Weather, Fuzhou 350001, China
  • Received:2021-03-17 Accepted:2021-06-11 Online:2021-09-15 Published:2022-03-15
  • Contact: * E-mail: l.gao@foxmail.com
  • Supported by:
    National Key Research and Development Program of China (2018YFE0206400), the Scientific Project from Fujian Provincial Department of Science and Technology (2019R1002-3), the Scientific Project from Fujian Key Laboratory of Severe Weather (2020KFKT01) and the Outstanding Young Scientific Research Talents Cultivation Program of Fujian Province.

摘要: 全球变暖背景下的极端天气气候事件显著增加。本研究基于PreWhitening Mann-Kendall(PWMK)、极点对称模态分解法和广义可加模型,利用鄱阳湖流域1959—2019年16个国家级气象站点的逐日降水数据,从极端降水的强度、频率和持续性3个维度系统检测和分析流域极端降水的时空分布和非平稳性特征。结果表明: 研究期间,鄱阳湖流域极端降水强度和频率呈显著增加趋势,持续性呈下降趋势,极端降水整体表现出强度大、频率高、持续时间短的特点;极端降水存在明显的汛期和非汛期时间分异规律,汛期极端降水集中在流域北部和中部,而非汛期多集中于中部,子流域中信江流域降水量增加趋势最显著,达到2.10 mm·a-1;汛期极端降水的持续时间越长,强度和范围越小,非汛期极端降水则相反;鄱阳湖流域的极端降水强度和频率以平稳性特征为主,持续性表现出非平稳性特征。随着鄱阳湖流域极端降水量的不断增加,其可能引发的灾害风险将进一步增大。

关键词: 鄱阳湖流域, 极端降水, 非平稳, 时空分布, 灾害风险

Abstract: Extreme weather/climate events increased significantly because of global warming. Based on daily records from 16 meteorological stations in the Poyang Lake Basin (PLB) from 1959 to 2019, we comprehensively investigated the temporal-spatial and non-stationarity characteristics of extreme precipitation from three dimensions (intensity, frequency and duration) using PreWhite-ning Mann-Kendall (PWMK), extreme-point symmetric mode decomposition method (ESMD) and the generalized additive models for location, scale and shape (GAMLSS). The results showed that the intensity and frequency of extreme precipitation increased significantly in the PLB, while the duration of extreme precipitation decreased from 1959 to 2019. The extreme precipitation had features of high intensity, high frequency, and short duration in the PLB. There was a clear distinction between flood season and non-flood season for extreme precipitation. Extreme precipitation was concentrated in the northern and central PLB during the flood season and in the central PLB during the non-flood season. The increasing trend of extreme precipitation amount was 2.10 mm·a-1 in the Xinjiang basin, which had the largest increment over the PLB. In the flood season, the extreme precipitation had longer duration but weaker intensity and smaller range, contrasting with the status during the non-flood season. The intensity and frequency of extreme precipitation showed stationarity characteristics in the PLB. However, the duration of extreme precipitation showed non-stationarity characteristics. With the continuous increase of extreme precipitation amount, the risk of related disasters would increase.

Key words: Poyang Lake Basin, extreme precipitation, non-stationary, temporal-spatial variation, disaster risk