[1]董家根,胡义明,罗俐雅*,等.误差异分布概率预报模型在运河站洪水预报中的应用研究[J].江苏水利,2020,(08):15-19.
　DONG Jiagen,HU Yiming,LUO Liya*,et al.Application of forecast model of error differential distribution probability in flood forecasting of Yunhe Station[J].JIANGSU WATER RESOURCES,2020,(08):15-19.
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误差异分布概率预报模型在运河站洪水预报中的应用研究()
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《江苏水利》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2020年08期
页码:
15-19
栏目:
水文水资源
出版日期:
2020-09-04

文章信息/Info

Title:
Application of forecast model of error differential distribution probability in flood forecasting of Yunhe Station
文章编号:
1007-7839(2020)08-0015-05
作者:
董家根1;  胡义明2;  罗俐雅1*;  梁忠民2
1.江苏省水文水资源勘测局, 江苏 南京 210029; 2.河海大学水文水资源学院, 江苏 南京 210098
Author(s):
DONG Jiagen1;  HU Yiming2;  LUO Liya1*;  LIANG Zhongmin2
1.Jiangsu Hydrology and Water Resources Survey Bureau, Nanjing 210029, China; 2.College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
关键词:
洪水概率;  误差异分布;  预报倾向值;  预报区间
Keywords:
flood probability;  error differential distribution;  forecast tendency value;  forecast interval
分类号:
TV124
文献标志码:
B
摘要:
分析运河站不同流量量级下洪水预报误差的规律特征,发现不同量级下洪水预报误差的均值和标准差存在显著差异,构建了预报误差的均值和标准差与流量大小间的分段线性关系。在此基础上,采用误差异分布概率预报模型推求了不同量级洪水条件下,以流量预报值为条件的“真实”流量的条件概率分布函数。据此流量预报条件分布函数,可获得流量的预报倾向值(50%概率对应的分位点,即中位数)和任一置信水平下的流量预报区间。运河站的应用结果表明,基于误差异分布概率预报模型提供的预报倾向值的精度整体要优于初始确定性预报结果,同时也提供了90%置信水平下的预报区间成果,丰富了运河站的洪水预报信息。
Abstract:
It's founded that there were significant differences in the mean value and standard deviation of the flood forecasting errors under different orders of magnitude by analyzing the regular characteristics of the flood forecast errors under different flow levels at Yunhe Station, and the piece-wise linear relationship between the mean value and standard deviation of the flood forecasting errors and the flow was constructed. On this basis, the conditional probability distribution function of "real" flow under flood conditions with flow forecast value as the condition was deduced by using forecast model of error differential distribution probability. Based on the distribution function of flow forecast conditions, the forecast tendency value(the point corresponding to 50% probability, namely the median)and the forecast interval of flow at any confidence level could be obtained. The application results of Yunhe Stations showed that the accuracy of forecast tendency value based on the probability model of false difference distribution was better than the initial deterministic prediction results, and the prediction interval results under 90% confidence level were also provided, which enriched the flood prediction information of Yunhe Station.

参考文献/References:

[1] 梁忠民, 蒋晓蕾, 钱名开, 等. 考虑误差异分布的洪水概率预报方法研究[J]. 水力发电学报, 2017, 36(4):18-25.
[2] KAVETSKI D, KUCZERA G, FRANKS S W. Bayesian analysis of input uncertainty in hydrological modeling:2. Application[J]. Water Resources Research, 2006, 42(3):W03407.
[3] AJAMI N K, DUAN Q, SOROOSHIAN S. An integrated hydrologic Bayesian multimodel combination framework:Confronting input, parameter, and model structural uncertainty in hydrologic prediction[J]. Water Resources Research, 2007, 43(1).
[4] KRZYSZTOFOWICZ R. Bayesian Theory of Probabilistic Forecasting Via Deterministic Hydrologic Model[J]. Water Resources Research, 1999, 35(9):2739-2750.
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备注/Memo

备注/Memo:
收稿日期:2020-06-10
基金项目:江苏省水利科技项目(2017008)
作者简介:董家根(1962—),男,高级工程师,本科,研究方向为水文学及水资源。
通信作者:罗俐雅(1978—),女,高级工程师,硕士,研究方向为水文学及水资源。E-mail:516174631@qq.com
更新日期/Last Update: 2020-08-20