院报 ›› 2024, Vol. 41 ›› Issue (6): 69-75.DOI: 10.11988/ckyyb.20231214

• 水灾害 • 上一篇    下一篇

赣江流域水文干旱事件重现期计算方法

郭娜1, 洪兴骏2, 江聪3   

  1. 1.武汉理工大学 资源与环境工程学院,武汉 430070;
    2.长江勘测规划设计研究有限责任公司,武汉 430010;
    3.中国地质大学(武汉) 环境学院,武汉 430074
  • 收稿日期:2023-11-07 修回日期:2024-01-05 出版日期:2024-06-01 发布日期:2024-06-03
  • 通讯作者: 洪兴骏(1989-),男,广东丰顺人,高级工程师,博士,主要从事水文水资源方面的研究。E-mail:hongxingjun@cjwsjy.com.cn
  • 作者简介:郭 娜(1989-),女,辽宁灯塔人,讲师,博士研究生,主要从事水环境工程方面的研究。E-mail: 11978@whut.edu.cn
  • 基金资助:
    国家自然科学基金项目(51809243);水资源与水电工程科学国家重点实验室(武汉大学)开放研究基金项目(2018SWG03);江西省鄱阳湖水资源与环境重点实验室开放研究基金项目(2020GPSYS06)

Estimation of Hydrological Drought Return Period Based on Annual Runoff Statistical Characteristics: A Case Study of Ganjiang River Basin

GUO Na1, HONG Xing-jun2, JIANG Cong3   

  1. 1. School of Resources and Environmental Engineering, Wuhan University of Technology, Wuhan 430070, China;
    2. Changjiang Survey, Planning, Design and Research Co., Ltd., Wuhan 430010, China;
    3. School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
  • Received:2023-11-07 Revised:2024-01-05 Online:2024-06-01 Published:2024-06-03

摘要: 针对以径流相对亏缺状态表征的水文干旱事件,采用3种常用的概率分布函数Log-normal、Gamma和Normal,拟合了赣江外洲站实测年径流资料;利用外洲站年径流的统计特征,推导了干旱历时和干旱强度2种典型干旱特征变量的理论概率分布函数的参数;计算了期望间隔时间定义下干旱历时内累积干旱强度达到某一阈值的干旱事件的重现期,并采用Monte Carlo随机模拟技术进行了验证。结果表明:根据年径流统计信息解析推求水文干旱事件的重现期,具有较强的统计基础和可信的精度,能够一定程度克服依靠有限观测水文序列进行干旱事件重现期推断的样本偏差,可为定量评估流域干旱风险,支撑流域水安全保障提供新的思路。

关键词: 水文干旱, 重现期, 计算方法, 年径流, 赣江流域

Abstract: To address the challenge of estimating the return level of hydrological drought events due to the limited sample size of drought events that can be obtained from measured streamflow data, we applied three commonly utilized annual runoff probability distribution functions,namely, Log-normal, Gamma, and Normal,to measured runoff data obtained from the Waizhou station on the Ganjiang River. Theoretical probability distribution functions (PDFs) for drought characteristics, including duration and severity, were derived using statistical properties of annual runoff. The return period, defined as the mean interarrival time of drought events surpassing a certain severity threshold, was computed and validated through Monte Carlo simulation. Results demonstrate that deriving return periods of hydrological drought events using PDFs of drought duration and severity establishes a robust statistical basis with credible accuracy. The proposed method partially mitigates sample bias in estimating drought return periods based on limited observed hydrological series, offering a novel approach to assessing future drought risk.

Key words: hydrological drought, return period, calculation method, annual runoff, Ganjiang River basin

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