融雪洪水跳跃变异对其参数估计不确定性影响分析

doi:10.7522/j.issn.1000-0240.2018.0110

冰川冻土 ›› 2018, Vol. 40 ›› Issue (5): 1004-1015.doi: 10.7522/j.issn.1000-0240.2018.0110

融雪洪水跳跃变异对其参数估计不确定性影响分析

陈伏龙^1,2, 张婷², 冯平², 何新林¹, 李绍飞³, 龙爱华^1,4

1. 石河子大学水利建筑工程学院, 新疆石河子 832000;
2. 天津大学水利工程仿真与安全国家重点实验室, 天津 300072;
3. 天津农学院水利工程学院, 天津 300384;
4. 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室, 北京 100038

收稿日期:2018-06-11 修回日期:2018-08-06 出版日期:2018-10-25 发布日期:2018-12-10
通讯作者: 张婷,E-mail:zhangting_hydro@tju.edu.cn. E-mail:zhangting_hydro@tju.edu.cn
作者简介:陈伏龙(1978-),男,湖南人,副教授,2017年在天津大学获博士学位,从事水文学及水资源问题的研究.E-mail:cfl103@shzu.edu.cn
基金资助:
国家自然科学基金项目（51769029）；国家重点研发计划项目（2017YFC0404301）；水利工程仿真与安全国家重点实验室开放基金项目（HESS-1405）；天津市科委应用基础与前沿技术重点项目（15JCZDJC41400）资助

Impacts of jump up components on the uncertainties of parameters estimation in snowmelt flood sequences

CHEN Fulong^1,2, ZHANG Ting², FENG Ping², HE Xinlin¹, LI Shaofei³, LONG Aihua^1,4

1. College of Water Conservancy & Architectural Engineering, Shihezi University, Shihezi 832000, Xinjiang, China;
2. State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China;
3. Department of Hydraulic Engineering, Tianjin Agriculture University, Tianjin 300384, China;
4. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China

Received:2018-06-11 Revised:2018-08-06 Online:2018-10-25 Published:2018-12-10

摘要/Abstract

摘要： 利用Pettitt非参数检验法和Mann-Kendall非参数趋势检验法，分析年最大洪峰流量序列的非一致性，确定序列的变异形式，采用“分解-合成”理论对其进行一致性修正，得到过去、现状两种条件下年最大洪峰流量序列，根据贝叶斯理论对序列一致性修正前后参数不确定性进行估计，并对其预报区间优良性进行评价。研究结果表明：年最大洪峰流量序列变异点发生在1993年，序列整体上升趋势不显著，在1957-1993年子序列呈显著下降趋势，而1994-2006年子序列变化趋势不显著，跳跃变异为序列主要变异形式；给出了实测、还原及还现序列参数后验分布估计值及95%置信区间，将其结合优化适线法进行P-Ⅲ型频率分析，得到修正前后设计频率年最大洪峰流量预报区间估计值；还原、还现序列与实测序列相比，预报区间覆盖率均提高24%，平均带宽分别减少39.59%、23.17%，平均偏移幅度分别减少28.45%、11.39%。通过对非一致性年最大洪峰流量序列还原/还现计算，可减小参数估计不确定性对其计算产生的影响，从而提高预报区间的可靠性。

关键词: 融雪洪水, 跳跃变异, 贝叶斯理论, 参数估计, 不确定性

Abstract: Pettitt test and Mann-Kendall test were used to analyze the inconsistency of the annual maximum flood peak discharge sequence of the Ken Swart reservoir, and determine the variant form of the sequence. The consistent correction was conducted based on the theory of decomposition-synthesis, then the annual maximum peak discharge sequences under the conditions of past and present were obtained. Bayesian theory was used to estimate the uncertainty of the parameters of the sequences before and after the consistency correction, and evaluate its prediction intervals. The results showed that the change point of the annual maximum peak discharge sequence occurred in 1993, whereas the overall upward trend of the sequence was not significant. Specifically, the sub-sequence from 1957 to 1993 was significantly decreased, but that from 1994 to 2006 was not significant. And jumping variation was the main variant form. The posteriori distribution estimate and the 95% confidence interval of the parameters of the measured and modified sequences under both the past and present conditions were given. Then combined with the optimized fitting method of P-Ⅲ distribution frequency analysis, the prediction interval estimate of the design flood peak discharge before and after modification were obtained. Compared with the measured sequence, the prediction interval coverage of the modified sequences both increased by 24%, while the average bandwidth decreased by 39.59% and 23.17%, and the average migration amplitude decreased by 28.45% and 11.39% respectively. Therefore, modifying the annual maximum peak discharge under the past and present conditions can reduce the effect of the parameter uncertainty on calculation, and thus improve the reliability of the prediction interval.

Key words: snowmelt flood, jump variation, bayesian theory, parameter estimation, uncertainty

中图分类号:

P331.1

陈伏龙, 张婷, 冯平, 何新林, 李绍飞, 龙爱华. 融雪洪水跳跃变异对其参数估计不确定性影响分析[J]. 冰川冻土, 2018, 40(5): 1004-1015.

CHEN Fulong, ZHANG Ting, FENG Ping, HE Xinlin, LI Shaofei, LONG Aihua. Impacts of jump up components on the uncertainties of parameters estimation in snowmelt flood sequences[J]. Journal of Glaciology and Geocryology, 2018, 40(5): 1004-1015.

参考文献

[1] Guo Shenglian, Liu Zhangjun, Xiong Lihua. Advances and assessment on design flood estimation methods[J]. Journal of Hydraulic Engineering, 2016, 47(3):302-314.[郭生练, 刘章君, 熊立华. 设计洪水计算方法研究进展与评价[J]. 水利学报, 2016, 47(3):302-314.]
[2] Yang Hui, Song Songbai. Application of high-order L-moments to parameter estimation of Pearson Type Ⅲ distribution[J]. Journal of Hydroelectric Engineering, 2017, 36(1):42-49.[杨惠, 宋松柏. 高阶线性矩在P-Ⅲ分布参数计算中的应用[J]. 水力发电学报, 2017, 36(1):42-49.]
[3] Wang Yintang, Li Lingjie, Hu Qingfang, et al. Nonstationary hydrologic frequency analysis method considering local trends[J]. Advances in Water Science, 2017, 28(3):406-414.[王银堂, 李伶杰, 胡庆芳, 等. 考虑局部趋势的非一致性水文频率分析方法[J]. 水科学进展, 2017, 28(3):406-414.]
[4] Beven K, Binley A. The future of distributed models:model calibration and uncertainty prediction[J]. Hydrological Processes, 1992, 6(3):279-298.
[5] Beven K, Smith P, Freer J. Comment on "hydrological forecasting uncertainty assessment:incoherence of the GLUE methodology" by Pietro Mantovan and Ezio Todini[J]. Journal of Hydrology, 2007, 338(3):315-318.
[6] Wei Xiaojing, Xiong Lihua, Wan Min, et al. Application of Markov Chain Monte Carlo method based modified generalized likelihood uncertainty estimation to hydrological models[J]. Journal of Hydraulic Engineering, 2009, 40(4):464-473.[卫晓婧, 熊立华, 万民, 等. 融合马尔科夫链-蒙特卡洛算法的改进通用似然不确定性估计方法在流域水文模型中的应用[J]. 水利学报, 2009, 40(4):464-473.]
[7] Lin K R, Qiang Z, Chen X H. An evaluation of impacts of DEM resolution and parameter correlation on TOPMODEL modeling uncertainty[J]. Journal of Hydrology, 2010, 395(3/4):370-383.
[8] Li Z L, Shao Q X, Xu Z X, et al. Analysis of parameter uncertainty in semi-distributed hydrological models using bootstrap method:a case study of SWAT model applied to Yingluoxia watershed in northwest China[J]. Journal of Hydrology, 2010, 385(1):76-83.
[9] Bouph K, Sourinphomy K. Rainfall-Runoff Simulation using Remote Sensing and GIS Tool (SWAT Model):a case study:Xebanghieng basin in Lao PDR[J]. Journal of Natural Sciences Research, 2015:98-109.
[10] Shang Xiaosan, Wang Zhenlong Wang Dong. Uncertainty analysis of parameters estimation in hydrologic frequency analysis based on bayesian method:a case study of P-Ⅲ distribution[J]. Journal of Basic Science and Engineering, 2011, 19(4):554-564.[尚晓三, 王振龙, 王栋. 基于贝叶斯理论的水文频率参数估计不确定性分析——以P-Ⅲ型分布为例[J]. 应用基础与工程科学学报, 2011, 19(4):554-564.]
[11] Feng Ping, Huang Kai. A study about the impacts of non-stationary characteristic on the uncertainties of parameters estimation in hydrological series[J]. Journal of Hydraulic Engineering, 2015, 46(10):1145-1154.[冯平, 黄凯. 水文序列非一致性对其参数估计不确定性影响研究[J]. 水利学报, 2015, 46(10):1145-1154.]
[12] Chen Yaning, Li Zhi, Fan Yuting, et al. Research progress on the impact of climate change on water resources in the arid region of Northwest China[J]. Acta Geographica Sinica, 2014, 69(9):1295-1304.[陈亚宁, 李稚, 范煜婷, 等. 西北干旱区气候变化对水文水资源影响研究进展[J]. 地理学报, 2014, 69(9):1295-1304.]
[13] Xiang Yanyun, Wang Zhicheng, Zhang Hui, et al. Study of snowmelt runoff simulation in arid regions:progress and prospect[J]. Journal of Glaciology and Geocryology, 2017, 39(4):892-901.[向燕芸, 王志成, 张辉, 等. 干旱区融雪径流模拟的研究进展与展望[J]. 冰川冻土, 2017, 39(4):892-901.]
[14] Abulemite Abullikemu, Chen Chunyan, Yusup Abdulla, et al. Temporal and spatial distribution characteristics of snowmelt flood in Xinjiang from 2001 to 2012[J]. Journal of Glaciology and Geocryology, 2015, 37(1):226-232.[阿不力米提江·阿布力克木, 陈春艳, 玉素甫·阿不都拉, 等. 2001-2012年新疆融雪型洪水时空分布特征[J]. 冰川冻土, 2015, 37(1):226-232.]
[15] Pettitt A N. A non-parametric approach to the change-point problem[J]. Applied Statistics, 1979, 28(2):126-135.
[16] Villarini G, Serinaldi F, Smith J A, et al. On the stationarity of annual flood peaks in the continental United States during the 20th century[J]. Water Resources Research, 2009, 45:W08417.
[17] Mann H B. Non-parametric test against trend[J]. Econometic, 1945, 13(3):245-259.
[18] Kendall M G. Rank correlation methods[M]. London:Charles Griffin, 1975.
[19] Zhang Danwu, Cong Zhentao, Ni Guangheng. Comparison of three Mann-Kendall methods based on the China's meteorological data[J]. Advances in Water Science, 2013, 24(4):490-496.[章诞武, 丛振涛, 倪广恒. 基于中国气象资料的趋势检验方法对比分析[J]. 水科学进展, 2013, 24(4):490-496.]
[20] Xie Ping, Chen Guangcai, Lei Hongfu, et al. Hydrological alteration diagnosis[J]. Journal of Hydroelectric Engineering, 2010, 29(1):85-91.[谢平, 陈广才, 雷红富, 等. 水文变异诊断系统[J]. 水力发电学报, 2010, 29(1):85-91.]
[21] Xie Ping, Chen Guangcai, Xia Jun. Hydrological frequency calculation principle of inconsistent annual runoff series under changing environment[J]. Engineering Journal of Wuhan University, 2005, 38(6):6-9.[谢平, 陈广才, 夏军. 变化环境下非一致性年径流序列的水文频率计算原理[J]. 武汉大学学报(工学版), 2005, 38(6):6-9.]
[22] Ding Jing, Deng Yuren. Random hydrology[M]. Chengdu:Chengdu University of Science and Technology Press, 1988.[丁晶, 邓育仁. 随机水文学[M]. 成都:成都科技大学出版社, 1988.]
[23] Bao Zhenxin, Liu Jiufu, Zhang Jianyun. Study on stochastic simulation annual maximum peak discharge of P-Ⅲ distribution based on the Quasi-Monte Carlo Method[J]. Journal of China Hydrology, 2009, 29(6):33-36.[鲍振鑫, 刘九夫, 张建云. 年最大洪峰流量的P-Ⅲ型分布拟蒙特卡罗随机模拟研究[J]. 水文, 2009, 29(6):33-36.]
[24] Romy R, Alexandra M. A joint model for rainfall-runoff:the case of Rio Grande basin[J]. Journal of Hydrology, 2008:189-200.
[25] Xiong L H, Wan M, Wei X J, et al. Indices for assessing the prediction bounds of hydrological models and application by generalized likelihood uncertainty estimation[J]. Hydrological Science Journal, 2009, 54(5):852-871.

融雪洪水跳跃变异对其参数估计不确定性影响分析

Impacts of jump up components on the uncertainties of parameters estimation in snowmelt flood sequences

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 9

Metrics

本文评价

推荐阅读 7

[1]	冯畅, 毛德华, 周慧, 曹艳敏, 胡光伟. 气候与土地利用变化对涟水流域径流的影响[J]. 冰川冻土, 2017, 39(2): 395-406.
[2]	张伟, 王根绪, 周剑, 刘光生, 王一博. 基于CoupModel的青藏高原多年冻土区土壤水热过程模拟[J]. 冰川冻土, 2012, 34(5): 1099-1109.
[3]	李传金, 任贾文, 秦大河, 效存德, 侯书贵, 丁明虎. 火山活动的气候影响及其冰芯记录研究进展[J]. 冰川冻土, 2012, 34(4): 863-876.
[4]	龙银平, 张耀南, 赵国辉, 严鹏, 李其江, 李润杰. SWAT模型水文过程模拟的数据不确定性分析——以青海湖布哈河流域为例[J]. 冰川冻土, 2012, 34(3): 660-667.
[5]	田园, 张雪芹, 孙瑞. 基于多源、多时相遥感影像的高原湖泊提取及其不确定性——以西藏羊卓雍错流域为例[J]. 冰川冻土, 2012, 34(3): 563-572.
[6]	孔彦龙;庞忠和. 高寒流域同位素径流分割研究进展[J]. 冰川冻土, 2010, 32(3): 619-625.
[7]	刘金涛, 张佳宝. 前期土壤含水量对水文模拟不确定性影响分析[J]. 冰川冻土, 2006, 28(4): 519-525.
[8]	胡国华, 夏军. 基于灰色概率的非突发性环境风险度量化方法[J]. 冰川冻土, 2002, 24(4): 433-437.
[9]	徐中民, 张志强, 苏志勇, 程国栋. 恢复额济纳旗生态系统的总经济价值——条件估值非参数估计方法的应用[J]. 冰川冻土, 2002, 24(2): 160-167.