基于贝叶斯网络的塔里木河流域丰枯遭遇分析
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摘要
本文利用贝叶斯网络对塔里木河流域三源流和塔里木干流的年径流量进行分析研究,通过建立丰枯遭遇的风险管理模型,直观地描述了三源流与干流年径流量的丰枯组合关系,并利用贝叶斯网络的反向推理功能,以后验知识为输入,推求未来干流流量的丰枯遭遇受三源流流量的影响。结果表明:当三源流均为枯水时,干流的枯水概率上升为50%;仿真分析可为塔里木河干流丰枯遭遇预测及采取适当的调水措施提供理论依据。
Based on Bayesian Network, this paper analyzes and studies the annual runoff of the three headwaters and the main stream of Tarim River. By establishing a risk management model of wetness-dryness encountering, it delicately describes the combination of wetness anddrynessof the three headwaters and the annual runoff of the main stream. Using the reverse reasoning function of Bayesian Network, and taking posterior knowledge as input, it can be deduced that the future mainstream flowaffected by the three source flows. The results show when the three streams are dry, the dry probability of the main stream rises to 50%. The simulation analysis can provide a theoretical basis for the prediction of wetness-drynessencountering in the mainstream of Tarim River and the adoption of appropriate water diversion measures.
Based on Bayesian Network, this paper analyzes and studies the annual runoff of the three headwaters and the main stream of Tarim River. By establishing a risk management model of wetness-dryness encountering, it delicately describes the combination of wetness anddrynessof the three headwaters and the annual runoff of the main stream. Using the reverse reasoning function of Bayesian Network, and taking posterior knowledge as input, it can be deduced that the future mainstream flowaffected by the three source flows. The results show when the three streams are dry, the dry probability of the main stream rises to 50%. The simulation analysis can provide a theoretical basis for the prediction of wetness-drynessencountering in the mainstream of Tarim River and the adoption of appropriate water diversion measures.
引文
[1] 周建方,张迅炜,唐椿炎.基于贝叶斯网络的沙河集水库大坝风险分析[J].河海大学学报(自然科学版),2012,40(3):287-293.
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[3] 康玲,何小聪,熊其玲.基于贝叶斯网络理论的南水北调中线工程水源区与受水区降水丰枯遭遇风险分析[J].水利学报,2010,41(8):908-913.
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[5] H.VAN de Vyver.Bayesian estimation of rainfall intensity-duration -frequency relationships[J].Journal of Hydrology,2015:1451-1463.
[6] MURPHY K P.A brief introduction to graphical models and bayesian networks[J].Borgelt Net,1998.
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[8] REN J.An offshore risk analysis method using fuzzy bayesian network[J].Journal of Offshore Mechanics and Arctic Engineering,2009,131(4):1101-1112.
[9] SINGH V P,Zhang L.Bivariate Flood Frequency Analysis Using the Copula Method[J].Journal of Hydrologic Engineering,2016,11(2):150-164.
[10] 徐海量.流域水文过程与生态环境演变的耦合关系—以塔里木河流域为例[D].新疆:新疆农业大学,2005.
[2] 林鹏智,陈宇.基于贝叶斯网络的梯级水库群漫坝风险分析[J].工程科学与技术,2018,50(3):46-53.
[3] 康玲,何小聪,熊其玲.基于贝叶斯网络理论的南水北调中线工程水源区与受水区降水丰枯遭遇风险分析[J].水利学报,2010,41(8):908-913.
[4] O’CONNELL D R H Nonparametric Bayesian flood frequency estimation[J].Journal of Hydrology,2005,313(S1-2):79-96.
[5] H.VAN de Vyver.Bayesian estimation of rainfall intensity-duration -frequency relationships[J].Journal of Hydrology,2015:1451-1463.
[6] MURPHY K P.A brief introduction to graphical models and bayesian networks[J].Borgelt Net,1998.
[7] 李典庆,鄢丽丽,邵东国.基于贝叶斯网络的土石坝可靠性分析[J].武汉大学学报(工学版),2007(6):24-29.
[8] REN J.An offshore risk analysis method using fuzzy bayesian network[J].Journal of Offshore Mechanics and Arctic Engineering,2009,131(4):1101-1112.
[9] SINGH V P,Zhang L.Bivariate Flood Frequency Analysis Using the Copula Method[J].Journal of Hydrologic Engineering,2016,11(2):150-164.
[10] 徐海量.流域水文过程与生态环境演变的耦合关系—以塔里木河流域为例[D].新疆:新疆农业大学,2005.