基于混沌理论的汉江上游安康站1950—2014年逐月降水量特征

doi:10.11988/ckyyb.20210007

院报 ›› 2021, Vol. 38 ›› Issue (7): 137-142.DOI: 10.11988/ckyyb.20210007

• 长江技术经济学会2020年学术年会暨长江治理与保护科技创新高端论坛专栏 • 上一篇下一篇

基于混沌理论的汉江上游安康站1950—2014年逐月降水量特征

赵自阳^1,2, 王红瑞^1,2, 赵岩^1,2, 胡立堂^1,3, 刘海军^1,2

1.北京师范大学水科学研究院,北京 100875;
2.北京师范大学城市水循环与海绵城市技术北京市重点实验室,北京 100875;
3.北京师范大学地下水污染控制与修复教育部工程研究中心,北京 100875

收稿日期:2021-01-04 修回日期:2021-03-31 出版日期:2021-07-01 发布日期:2021-07-08
通讯作者: 王红瑞(1963- ),男,河南新乡人,教授,博士,博士生导师,研究方向为水文学及资源。E-mail: henrywang@bnu.edu.cn
作者简介:赵自阳(1991- ),男,河南洛阳人,博士研究生,主要从事水资源系统分析研究。E-mail: zyzhao@mail.bnu.edu.cn
基金资助:
国家重点研发计划项目(2018YFC0407900)

Analysis of Monthly Precipitation Characteristics of Ankang Station in Upper Hanjiang River from 1950 to 2014 Based on Chaos Theory

ZHAO Zi-yang^1,2, WANG Hong-rui^1,2, ZHAO Yan^1,2, HU Li-tang^1,3, LIU Hai-jun^1,2

1. College of Water Science, Beijing Normal University, Beijing 100875, China;
2. Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing Normal University, Beijing 100875, China;
3. Engineering Research Center of Groundwater Pollution Control and Remediation of Ministry of Education, Beijing Normal University, Beijing 100875, China

Received:2021-01-04 Revised:2021-03-31 Online:2021-07-01 Published:2021-07-08

摘要/Abstract

摘要： 通过对安康站1950—2014年逐月降水量的趋势进行分析,发现其降水存在周期变化。基于自相关函数法、C-C关联积分法来确定安康站降水的非线性系统的延迟时间、嵌入维数后,对降水序列进行了相空间重构,并利用G-P关联维法以及最大Lyapunov指数法进行混沌特征识别。结果显示:采用G-P关联维算法分析安康站1950—2014年降水时间序列并不能得到其存在混沌特性的结果,但最大Lyapunov指数法显示其存在混沌性;基于现有780个月份降水数据,可预报的最大时间长度为7个月。研究结果可为当地和下游地区的径流预报提供科学支撑。

关键词: 降水量特征, 混沌理论, C-C法, G-P关联维法, 预报时间尺度, 汉江上游安康站

Abstract: By analyzing the monthly precipitation trend of Ankang Station from 1950 to 2014, we found that the precipitation at Ankang changes periodically. Having determined the delay time and embedded dimension of the nonlinear system of precipitation at Ankang using autocorrelation function method and C-C correlation integral method, we reconstructed the phase space of the precipitation series, and identified the chaotic characteristics of precipitation by using the G-P correlation dimension method and the maximum Lyapunov exponent method. Results reveal that the G-P correlation dimension algorithm indicates no chaos, while the maximum Lyapunov exponent method suggests chaos. With the existing 780 monthly precipitation data, we can forecast up to seven months of precipitation. The research finding offers scientific support for the runoff forecast in Hanjiang River and its downstream areas.

Key words: precipitation characteristics, chaos theory, C-C method, G-P correlation dimension, forecast time scale, Ankang Station in upper Hanjiang River

中图分类号:

TV213

赵自阳, 王红瑞, 赵岩, 胡立堂, 刘海军. 基于混沌理论的汉江上游安康站1950—2014年逐月降水量特征[J]. 院报, 2021, 38(7): 137-142.

ZHAO Zi-yang, WANG Hong-rui, ZHAO Yan, HU Li-tang, LIU Hai-jun. Analysis of Monthly Precipitation Characteristics of Ankang Station in Upper Hanjiang River from 1950 to 2014 Based on Chaos Theory[J]. Journal of Yangtze River Scientific Research Institute, 2021, 38(7): 137-142.

基于混沌理论的汉江上游安康站1950—2014年逐月降水量特征

Analysis of Monthly Precipitation Characteristics of Ankang Station in Upper Hanjiang River from 1950 to 2014 Based on Chaos Theory

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