基于GAMLSS 模型的宜昌站年径流序列趋势分析

doi:10.11821/xb201211007

地理学报 ›› 2012, Vol. 67 ›› Issue (11): 1505-1514.doi: 10.11821/xb201211007

基于GAMLSS 模型的宜昌站年径流序列趋势分析

江聪, 熊立华

武汉大学水资源与水电工程科学国家重点实验室, 武汉430072

收稿日期:2012-07-24 修回日期:2012-08-15 出版日期:2012-11-20 发布日期:2012-11-20
作者简介:江聪(1989-),男,河北宁晋人,硕士研究生,主要从事水文水资源方面的研究。E-mail:jc1207@whu.edu.cn
基金资助:
国家自然科学基金重大项目(51190094); 国家自然科学基金项目(51079098)

Trend Analysis for the Annual Discharge Series of the Yangtze River at the Yichang Hydrological Station Based on GAMLSS

JIANG Cong, XIONG Lihua

State Key Laboratory of Water Resources and Hydropower Engineering Sciences, Wuhan University, Wuhan 430072, China

Received:2012-07-24 Revised:2012-08-15 Online:2012-11-20 Published:2012-11-20
Supported by:
Major Program of the National Natural Science Foundation of China, No.51190094; National Natural Science Foundation of China, No.51079098

摘要/Abstract

摘要： 在变化环境下, 研究非一致性水文序列的变化趋势具有重要意义。常规的趋势分析方法一般只能分析水文序列均值的线性趋势。本文引入GAMLSS模型对宜昌站1882-2009 年间的年平均流量序列和年最小月流量序列分别进行趋势分析, 将序列的趋势分析从均值扩展至均方差(或变差系数)、偏态系数等其他统计参数。研究发现宜昌站年平均流量序列的均值有明显线性减少的趋势, 而宜昌站年最小月流量序列线性趋势不明显。在此基础上, 建立基于多项式回归的GAMLSS模型, 结果表明宜昌站年最小月流量序列并非平稳序列, 其均值表现为非线性的趋势变化, 偏态系数呈现线性的趋势变化。

关键词: 趋势分析, 年径流量, 时变统计参数, 长江, GAMLSS模型

Abstract: It is very important to study the trends of the inconsistent hydrological series under the changing environments. The conventional methods of trend analysis can only be used to analyze the linear trends of the mean value of hydrological series. In this paper, GAMLSS is introduced to analyze the trends in both the annual average discharge series and the annual minimum monthly discharge series of the Yangtze River at the Yichang hydrological station. GAMLSS can detect not only the time variation of the mean value of the discharge series, but also the time variation of other statistical parameters, such as standard deviation (or coefficient of variation) and coefficient of skew. Model results indicate that the mean of the annual mean discharge series decreases linearly with time, and the annual minimum monthly discharge series do not show any significant linear trend of decrease or increase.

Key words: trend analysis, annual discharge, GAMLSS, time-varying statistical parameters, Yangtze River

江聪, 熊立华. 基于GAMLSS 模型的宜昌站年径流序列趋势分析[J]. 地理学报, 2012, 67(11): 1505-1514.

JIANG Cong, XIONG Lihua. Trend Analysis for the Annual Discharge Series of the Yangtze River at the Yichang Hydrological Station Based on GAMLSS[J]. Acta Geographica Sinica, 2012, 67(11): 1505-1514.

参考文献

[1] Xie Ping, Chen Guangcai, Lei Hongfu et al. Hydrological alteration diagnosis system. Journal of HydroelectricEngineering, 2010, 29(1): 85-91. [谢平, 陈广才, 雷红富等. 水文变异诊断系统. 水力发电学报, 2010, 29(1): 85-91.]

[2] Qiu Linjing, Zheng Fenli, Yi Runsheng. Trend analysis of precipitation and streamflow during 1952-2008 in YanheRiver basin. Journal of Soil and Water Conservation, 2011, 25(3): 49-53. [邱临静, 郑粉莉, 尹润生. 1952-2008 年延河流域降水与径流的变化趋势分析. 水土保持学报, 2011, 25(3): 49-53.]

[3] Cao Jianting, Qin Dahe, Luo Yong et al. Discharge changes of the Yangtze River in source area during 1956-2000.Advance in Water Science, 2007, 18(1): 29-33. [曹建廷, 秦大河, 罗勇等. 长江源区1956-2000 年径流量变化分析. 水科学进展, 2007, 18(1): 29-33.]

[4] Xie Ping, Chen Guangcai, Lei Hongfu. The assessment method of water resources based on trend analysis of changing.Journal of Hydroelectric Engineering,, 2009, 28(2): 14-19. [谢平, 陈广才, 雷红富. 变化环境下基于趋势分析的水资源评价方法. 水力发电学报, 2009, 28(2): 14-19.]

[5] Xiong Lihua, Guo Shenglian. Trend test and change-point detection for the annual discharge series of the Yangtze Riverat the Yichang hydrological station. Hydrological Sciences Journal, 2004, 49(1): 99-112.

[6] Xu Jijun, Yang Dawen. Long-term trend test for precipitation and runoff in Yangtze basin. Yangtze River, 2006, 37(9):63-69. [许继军, 杨大文. 长江流域降水量和径流量长期变化趋势检验. 人民长江, 2006, 37(9): 63-69.]

[7] Qin Nianxiu, Jiang Tong, Xu Chongyu. Trends and abruption analysis on the discharge in the Yangtze basin. Resourcesand Environment in the Yangtze Basin, 2005, 14(5): 589-594. [秦年秀, 姜彤, 许崇育. 长江流域径流趋势变化及突变分析. 长江流域资源与环境, 2005, 14(5): 589-594.]

[8] Wang Wensheng, Ding Jing, Jin Juliang. Stochastic Hydrology. 2nd ed. Beijing: China Conservancy and HydropowerPress, 1997: 33-34. [王文圣, 丁晶, 金菊良. 随机水文学. 2 版. 北京: 中国水利水电出版社, 1997: 33-34.]

[9] Rigby R A, Stasinopoulos D M. Generalized additive models for location scale and shape. Journal of the RoyalStatistical Society, 2005, 54(3): 507-554.

[10] Liu Hao, Chen Langnan. Non-parametric and non-linear analysis of stock liquidity with high frequency data in Chinaon GAMLSS model. Journal of Shanxi Finance and Economics University, 2011, 33(4): 25-33. [刘昊, 陈浪南. 基于GAMLSS模型的高频流动性指标分布特征. 山西财经大学学报, 2011, 33(4): 25-33.]

[11] Yan Kai, Wang Qian, Yao Hua et al. Establishment of blood pressure reference centiles modeled by sex, age andheight percentiles in children and adolescents aged 7-17 in Xinjiang by GAMLSS program. Chinese Journal ofEvidence-based Pediatrics, 2011, 6(5): 343-348. [严恺, 王倩, 姚华等. 应用GAMLSS构建基于性别、年龄、身高的新疆7-17 儿童青少年血压参考标准. 中国循证儿科杂志, 2011, 6(5): 343-348.]

[12] Hernandez F J, Hare J A. Evaluating diel, ontogenetic and environmental effects on larval fish vertical distributionusing generalized additive models for location, scale and shape. Fisheries Oceanography, 2009, 18(4): 224-236.

[13] Gabriele V, James A S, Francesco S. Nonstationary modeling of a long record of rainfall and temperature over Rome. Advances in Water Resources, 2010, 33: 1256-1267.

[14] Gabriele V, James A S, Francesco S et al. Flood frequency analysis for nonstationary annual peak records in an urbandrainage basin. Advances in Water Resources, 2009, 32: 1255-1266.

[15] Rigby B. A flexible regression approach using GAMLSS in R. University of Lancaster, November 13, 2009.

[16] Filliben J J. The probability plot correlation coefficient test for normality. Technometrics. 1975, 17(1): 111-117.

[17] Huang Guoru, Chen Yongqin, Xie Hehai. Low flow frequency analysis in Dongjiang basin. Journal of TsinghuaUniversity: Sci & Tech, 2005, 45(12): 1633-1635. [黄国如, 陈永勤, 解河海. 东江流域枯水径流的频率分析. 清华大学学报: 自然科学版, 2005, 45(12): 1633-1635.]

[18] Feng Guozhang, Wang Shuangyin. A study of the characteristics of the low flows of rivers. Journal of NaturalResources, 1995, 10(2): 127-135. [冯国章, 王双银. 河流枯水流量特征研究. 自然资源学报, 1995, 10(2): 127-135.]

[19] Xue Yi, Chen Liping. Statistical Modeling and R Software. Beijing: Tsinghua University Press, 2006: 142-143. [薛毅,陈立萍. 统计建模与R软件. 北京: 清华大学出版社, 2006: 142-143.]

[20] Zhan Daojiang, Ye Shouze. Engineering Hydrology: 3rd ed. Beijing: China Conservancy and Hydropower Press, 2000:176-179. [詹道江, 叶守泽. 工程水文学. 3 版. 北京: 中国水利水电出版社, 2000: 176-179.]

基于GAMLSS 模型的宜昌站年径流序列趋势分析

Trend Analysis for the Annual Discharge Series of the Yangtze River at the Yichang Hydrological Station Based on GAMLSS

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