Variation Characteristics and Trend Prediction of Runoff in the Upper and Middle Yellow River with Different Frequencies

JIA Hao; MU Xingmin; ZHAO Guangju; GAO Peng; SUN Wenyi

doi:10.13870/j.cnki.stbcxb.2020.06.009

您当前的位置：

首页 >

文章列表页 >

Variation Characteristics and Trend Prediction of Runoff in the Upper and Middle Yellow River with Different Frequencies

更新时间：2025-03-12

- Variation Characteristics and Trend Prediction of Runoff in the Upper and Middle Yellow River with Different Frequencies
- Vol. 34, Issue 6, Pages: 60-64(2020)
- 作者机构：
  
  1. 西北农林科技大学黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌,712100
  2. 中国科学院水利部水土保持研究所, 陕西杨凌,712100
- 作者简介：
- 基金信息：
- DOI：10.13870/j.cnki.stbcxb.2020.06.009
  CLC： TV882.1
- Published：2020
- 稿件说明：
移动端阅览
JIA Hao, MU Xingmin, ZHAO Guangju, et al. Variation Characteristics and Trend Prediction of Runoff in the Upper and Middle Yellow River with Different Frequencies[J]. 2020, 34(6): 60-64.
DOI：

JIA Hao, MU Xingmin, ZHAO Guangju, et al. Variation Characteristics and Trend Prediction of Runoff in the Upper and Middle Yellow River with Different Frequencies[J]. 2020, 34(6): 60-64. DOI： 10.13870/j.cnki.stbcxb.2020.06.009.

摘要

水资源是影响黄河流域高质量发展的战略资源，在人类活动及气候作用影响下，黄河上中游径流发生极大的变化，因此研究黄河径流变化特点及其预测对水资源的合理开发和分配调控具有重要生产意义。对黄河潼关水文站实测1950—2018年径流量进行分析，通过M—K等方法分析了黄河上中游区径流量变化特征，并预测未来20年不同频率径流量变化趋势。结果表明：黄河上中游1950—2018年径流量呈极显著性减少趋势；黄河潼关水文站径流变化突变点位于1985年，减少趋势较之前显著增加；通过优化后的GM （1，1）模型对5%及95%频率径流量进行预测，表明未来20年的径流量变化为113.38~210.35亿m3，并持续减少趋于稳定；该优化模型对黄河潼关水文数据有较好的模拟结果，适用于频率优化后低递减水文长序列的预测。

Abstract

Water resources are strategic resources that affect the high-quality development of the Yellow River Basin. Under the influence of human activities and climate

the runoff in the upper and middle reaches of the Yellow River has undergone changes greatly. Therefore

the variation characteristics of the runoff in the Yellow River and their prediction have great importance on the rational development

allocation and regulation of water resources. This study used the runoff data measured from 1950 to 2018 at the Tongguan station of the Yellow River to analyze the characteristics of runoff changes in the upper and middle reaches of the Yellow River by M-K and other methods. The change trends of runoff at different frequencies in the next 20 years were also predicted. The results showed that the runoff in the upper and middle reaches of the Yellow River decreased significantly from 1950 to 2018; the runoff changing point of the Tongguan station of the Yellow River was located in 1985

and the decreasing trend was significantly higher than before; through the optimized GM (1

1) model

5% and 95% frequency runoff predictions indicated that the runoff change in the next 20 years would be 113.38 to 210.35 billion m3

and it would continue to decrease and stabilize; this optimized model had good simulation results for the Tongguan hydrological data of the Yellow River and was suitable for frequency optimized prediction of long sequences of low decreasing hydrology.

关键词

Keywords

references

穆兴民.黄土高原生态水文研究[M].北京:中国林业出版社,2001.

陈霁巍,穆兴民.黄河断流的态势、成因与科学对策[J].自然资源学报,2000,15(1):31-35.

赵广举,穆兴民,田鹏,等.近60年黄河中游水沙变化趋势及其影响因素分析[J].资源科学,2012,34(6):1070-1078.

Gao P, Mu X M, Wang F, et al. Changes in stream flow and sediment discharge and the response to human activities in the middle reaches of the Yellow River[J].Hydrology and Earth System Sciences,2011,15:1-10.

穆兴民,李靖,王飞.黄河天然径流量年际变化过程分析[J].干旱区资源与环境,2003,17(2):1-5.

李二辉,穆兴民,赵广举.1919-2010年黄河上中游区径流量变化分析[J].水科学进展,2014,25(2):155-163.

黄土高原科学数据中心. http://loess.qeodata.cn/

Lin L Y. An introduction to grey systems:Foundations, methodology and applications[M].Grove City ⅡGSS Academic Publisher,1988:1-101.

Kisi O, Ay M. Comparison of Mann-Kendall and innovative trend method for water quality parameters of Kizilirmak River, Turkey[J].Journal of Hydrology,2014,513:362-375.

Zhao G J, Li E H, Mu X M, et al. Changing trends and regime shift of streamflow in the Yellow River basin[J].Stochastic Environmental Research and Risk Assessment,2015,29(5):1331-1343.

宋小燕.松花江流域水沙演变及其对人类活动的响应[D].北京:中国科学院研究生院(教育部水土保持与生态环境研究中心),2010.

高鹏.黄河中游水沙变化及其对人类活动的响应[D].北京:中国科学院研究生院(教育部水土保持与生态环境研究中心),2010.

Gao P, Geissen V, Ritsema C J. Impact of climate change and anthropogenic activities on stream flow and sediment discharge in the Wei River basin, China[J].Hydrology and Earth Systemences,2012,17(3):961-972.

Pettitt A N. A non-parametric approach to the change-point problem[J].Journal of the Royal Statistical Society. Series C (Applied Statistics),1979,28(2):126-135.

赵娟.基于VAR模型的典型流域水沙变化及其对降水与水土保持措施的动态响应[D].陕西杨凌:西北农林科技大学,2019.

代昌龙,代稳.频率曲线在荆江三口输沙量计算中的应用[J].水利科技与经济,2017,23(4):24-27.

宋松柏.水文频率计算研究面临的挑战与建议[J].水利与建筑工程学报,2019,17(2):15-21.

邓聚龙.社会经济灰色系统的理论与方法[J].中国社会科学,1984(6):48-61.

邓聚龙.本征性灰色系统的主要方法[J].系统工程理论与实践,1986(1):48-53.

傅立.灰色系统理论及其应用[M].北京:科学技术文献出版社,1992.

刘思峰,杨英杰,吴利丰.灰色系统理论及其应用[M].北京:科学出版社,2014.

贾得海,曾建初.灰色系统理论GM(1,1)预测模型的应用[J].昆明理工大学学报(自然科学版),2013,38(6):115-120.

罗党,刘思峰,党耀国.灰色模型GM(1,1)优化[J].中国工程科学,2003,5(8):50-53.

王正新,党耀国,刘思峰.GM(1,1)模型时间响应函数的一种优化方法//2006年灰色系统理论及其应用学术会议论文集.北京:中国优选法统筹法与经济数学研究会,2006:344-349.

胡大红.参数和背景值同时优化的GM(1,1)模型[J].湖北文理学院学报,2013,34(11):18-21.

Zhou P, Wei Y. The data processing method based on a kind of new GM (1, 1) model// Proceeding of 2007 IEEE International Conference on Grey Systems and Intelligent Services. Nanjin: IEEE, 2007(11):18-20.

张善余,程胜余.洪涝灾害的灰色预测[J].水文,2000,20(2):23-25.

Views

1505

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

No data

Related Author

No data

Related Institution

No data

⁰