摘要
为解决南水北调中线工程冰期输水能力受限问题,根据输水明渠线性、单向流动的特点,建立基于初始断面水温-沿程气温链的冬季水温回归预测模型,根据2018—2021年冰期的水温气象资料,模拟分析中线工程京石段水温变化过程,并用2017—2018年度冰期的实测数据进行检验。结果表明:回归模型的拟合优度(R2)值最小为0.957,最大为0.991;各组模型检验的确定性系数(DC)值均能达到0.90;预见期从1日至5日,均方根误差(RMSE)值分别为0.05、0.11、0.15、0.14、0.22;平均绝对误差(MAE)值分别为0.17、0.25、0.28、0.28、0.37,均随预见期递增,符合模型的残差累积规律。模型选择的水温变量T_(w_(n,i))和气温变量T_(a_(n,x))对被解释变量T_(w_((n+1),i+1))具有较好解释性,预测值和观测值的拟合度优良。
As a strategic infrastructure project to solve the uneven distribution of water resources in China,the middle route of South-to-North Water Transfer Project was increasingly dependent in Beijing,Tianjin and other water receiving areas due to its good quality and stable water supply.In winter,the water temperature of the open channel gradually decreased with the air temperature,and there was ice in the canal north of Anyang.When the water temperature dropped below 0.5℃,a large number of ice crystals began to form.In order to prevent ice jam,the safe water delivery flow under the ice sheet was only 31.6%~47.6% of the design flow.There was a huge contradiction between the increasing water demand in north China and the declining water delivery capacity of the project in ice period.Ice condition prediction was an important means to solve the safe operation of water conveyance in the ice period of the project,meet the control requirements of water level and flow under various complex operating conditions,and ensure the safe and efficient operation of the middle route of South-to-North Water Transfer Project.Water temperature prediction model was the most important sub model in ice condition prediction.The occurrence and evolution process of ice condition was closely related to water temperature factors.According to the characteristics of linear,unidirectional and sequential flow in open channel,a calculation model based on initial section water temperature along the temperature chain was established.Based on the data of meteorological and water temperature during the ice period in 2019,2020 and 2021,five groups of 15 regression parameter models of water temperature prediction in the prediction period of 1-5 days in the 217.5 km canal section from Hutuo River Siphon outlet sluice(K 980+263)to the North Juma River culvert inlet sluice(K 1197+773)at the northernmost end of the main canal were established.Based on the analysis and sorting of the field measurement data of water transmission in winter since the first water supply of the whole line of the project,according to the statistical data of North Juma River canal segment from 2015 to 2022,the freezing of ice carapace only accounted for 14%of the whole ice period.The minimum value of R^(2) in regression models was 0.957 and the maximum value was 0.991.Using the data of 2018 for prediction test,the DC values of each group of model test could reach 0.90.Taking the North Juma River station as the prediction section,the RMSE values of 1-5 day forecast period were 0.05,0.11,0.15,0.14 and 0.22 respectively,and the MAE values were 0.17,0.25,0.28,0.28 and 0.37 respectively,which increased regularly with the growth of the forecast period.The water transmission dispatching mode in winter had a lot of room to optimize.Water temperature could be used as the judgment basis for the initiation and development of ice condition.Water temperature T_(w_(n,i))and air temperature T_(a_(n,x))had a good interpretation to the water temperature T_(w_((n+1),i+1)),and the predicted value and the observed value was matched well.The method to establish the model had a certain practical value.
作者
李程喜
段文刚
马啸
黄明海
LI Chengxi;DUAN Wengang;MA Xiao;HUANG Minghai(Changjiang River Scientific Research Institute of Changjiang Water Resources Commission,Wuhan 430102,China;Construction Administration Bureau of the Middle Route of South-to-North Water Transfer Project,Beijing 100038,China)
出处
《南水北调与水利科技（中英文）》
CAS
CSCD
北大核心
2023年第2期352-361,共10页
South-to-North Water Transfers and Water Science & Technology
基金
南水北调中线冬季输水能力提升关键技术研究项目(CKSK2019707/SL)
南水北调中线干线工程冰期输水冰情原型观测项目(CKSK2020168/SL)。
关键词
南水北调中线
水温
预测
冰情
回归模型
middle route of South-to-North Water Transfer
water temperature
prediction
ice condition
regression model
