长江科学院院报 ›› 2024, Vol. 41 ›› Issue (4): 46-54.DOI: 10.11988/ckyyb.20221523

• 水资源 • 上一篇    下一篇

叶尔羌河源流区洪水极值事件联合概率分析

司涵, 何英, 徐慧敏, 卢潇悦   

  1. 新疆农业大学 水利与土木工程学院,乌鲁木齐 830052
  • 收稿日期:2022-11-14 修回日期:2023-02-20 出版日期:2024-04-01 发布日期:2024-04-11
  • 通讯作者: 何 英(1982-),女,新疆乌鲁木齐人,副教授,博士,硕士生导师,主要从事水文水资源的教学与研究工作。E-mail:xjheying@126.com
  • 作者简介:司 涵(1998-),女,甘肃金昌人,助理工程师,硕士,研究方向为干旱区水文模拟与水资源高效利用。E-mail:1659213537@qq.com
  • 基金资助:
    新疆维吾尔自治区高校科研计划自然科学青年项目(XJEDU2021Y023)

Joint Probability Analysis of Extreme Flood Events in the Source Flow Area of Yarkant River

SI Han, HE Ying, XU Hui-min, LU Xiao-yue   

  1. College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China
  • Received:2022-11-14 Revised:2023-02-20 Online:2024-04-01 Published:2024-04-11

摘要: 以叶尔羌河流域源区为例,选取塔什库尔干气象站的气温数据和库鲁克栏杆站的洪水资料,基于Copula函数对洪峰流量和1、3、7 d洪水总量的概率分布特征进行分析,结合小波相干分析进一步探讨气候因子变化与洪水极值事件的关系。结果表明:两变量的同现重现期>单变量重现期>两变量的联合重现期,联合重现期和同现重现期随着洪峰流量和洪量的增大而变长,相应洪水极值事件发生概率降低;夏季日平均气温和洪峰流量序列在年代际尺度上具有高相干性,夏季日平均气温先于洪峰流量0.13~0.31周期变化;基于Copula函数建立1957—2010年夏季日平均气温与洪峰之间的二维统计模型,单变量重现期越长,所对应两变量的联合重现期与同现重现期之间相差越大;随着夏季日平均气温的升高,不同重现期洪水发生的可能性均增大。研究成果可对该地区的洪水风险管理和水资源适应性对策提供重要的科学价值和技术支撑。

关键词: 洪水极值, 气候因子, 重现期, Copula函数, 小波相干, 频率分析, 叶尔羌河源流区

Abstract: Based on temperature data from Tashkurgan meteorological station and flood data from Kulukelangan station, we investigated the probability distribution characteristics of flood peak discharge and 1 d, 3 d, and 7 d total flood volume of Yarkant River by using Copula functions. Additionally, we explored the relationship between climate factor variations and extreme flood events through wavelet coherence analysis. Our findings indicate that the co-occurrence return period of two variables surpasses the single variable return period, which, in turn, exceeds the joint return period of two variables. Both the joint return period and the co-occurrence return period increase with the continuous rises in peak flow and flood volume, leading to a decreasing likelihood of corresponding extreme flood events. We also found a high coherence between summer daily average temperature and flood peak discharge series on an interdecadal scale. The summer daily average temperature tends to change 0.13-0.31 cycles prior to the occurrence of flood peak flow. By using Copula functions, we established a two-dimensional statistical model between summer daily average temperature and flood peak spanning from 1957 to 2010. Notably, as the return period of a single variable increases, the disparity between joint return period and co-occurrence return period of the corresponding two variables widens. As summer daily average temperature rises, the likelihood of floods in different return periods also increases. These research outcomes carry significant scientific value and offer technical support for the flood risk management and adaptive measures in the Yarkant River Basin.

Key words: extreme value of flood, climatic factors, return period, Copula function, Wavelet coherence, probability analysis, source flow area of the Yarkant River

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