长江科学院院报 ›› 2023, Vol. 40 ›› Issue (4): 44-50.DOI: 10.11988/ckyyb.20211383

• 水资源 • 上一篇    下一篇

变化环境下气候因素对赣江径流的影响

韩会明1, 孙军红1, 简鸿福1, 朱龙辉1, 胡闽2   

  1. 1.江西省水利科学研究院,南昌 330029;
    2.江西省鄱阳湖水利枢纽建设办公室,南昌 330009
  • 收稿日期:2021-12-22 修回日期:2022-02-18 出版日期:2023-04-01 发布日期:2023-04-01
  • 作者简介:韩会明(1994-),男,陕西商洛人,助理工程师,硕士,研究方向为水文水资源。E-mail: 947348703@qq.com
  • 基金资助:
    江西省水利厅科技项目(201921YBKT07,202223YBKT05,202223YBKT16,202224ZDKT06)

Influence of Climate Factors on Runoff in Ganjiang River under Changing Environment

HAN Hui-ming1, SUN Jun-hong1, JIAN Hong-fu1, ZHU Long-hui1, HU Min2   

  1. 1. Jiangxi Academy of Water Science and Engineering,Nanchang 330029, China;
    2. Poyang Lake Hydro Project Construction Office of Jiangxi Province, Nanchang 330009, China
  • Received:2021-12-22 Revised:2022-02-18 Published:2023-04-01 Online:2023-04-01

摘要: 为探究变化环境下赣江流域水文极端事件季节性变化的新特征,基于赣江流域1960—2018年气象水文数据,引入Copula函数和条件概率分布建立径流与气候因素之间的概率依存关系,分析季节性径流与气候因素之间的相关性和敏感性,以及不同气候情景下水文极端事件发生的概率特征及变化。结果表明:赣江流域春季径流和降水量均呈减少趋势,其他季节呈增多趋势;对数正态分布、威布尔分布、伽玛分布和广义极值分布对气象水文要素拟合效果良好,气象要素与径流的最优Copula函数以Frank-Copula函数为主;径流与降水量、相对湿度和水汽压呈正相关,与潜在蒸散量、日照时长呈负相关,且春夏冬对降水量最敏感,秋季对日照时长最敏感;降水量从中值降至低值时,径流特枯事件发生概率平均增多16.6%,由中值增至高值时,洪水发生概率平均增多13.6%。

关键词: 径流, 气候因素, 水文极端事件, Copula函数, 条件概率, 赣江

Abstract: The purpose of this paper is to explore the new characteristics of seasonal changes of extreme hydrological events in the Ganjiang River Basin under changing circumstances. We used hydrometeorological data from 1960 to 2018 in the basin and established the probability dependence between runoff and climatic factors using Copula function and conditional probability distribution. We analyzed the correlation and sensitivity between seasonal runoff and climatic factors, as well as the probability characteristics and changes of extreme hydrological events under different climate scenarios. Our results show that runoff and precipitation in the Ganjiang River Basin decrease in spring while increase in other seasons. Climatic hydrological elements can be well fitted by logarithimic normal distribution, Weibull distribution, gama distribution, and generalized extreme value distribution. Frank-Copula function is the optimal Copula function for meteorological elements and runoff. Runoff is positively correlated with precipitation, relative humidity, and water vapor pressure, while negatively with potential evapotranspiration and sunshine duration. Runoff is most sensitive to precipitation in spring, summer, and winter, and most sensitive to sunshine duration in autumn. When precipitation decreases from median value to low value, the probability of extremely dry runoff events increases by an average of 16.6%; when precipitation increases from median value to high value, the probability of flood occurrence increases by an average of 13.6%.

Key words: runoff, climatic factors, extreme hydrological event, Copula function, conditional probability;Ganjiang River

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