基于长期水位记录概率建模的堤内承压水位预测

    Prediction of confined water level inside levee based on probability modeling of long-term water level record

    • 摘要: 为了给设计基准期T内建筑工程的抗浮设防水位取值提供依据,依托北江大堤周边一住宅工程的长期地下水位观测记录及堤外水文资料,以承压水位为研究对象,利用经验分布法与极大值分布法实现观测记录的概率建模,外推T内承压水位最大值的密度函数,从而实现承压水远期最高水位的预测。研究结果表明:在概率模型与反演法/数值法所得的百年一遇承压水位关联时,50 a重现期承压水位标准值分别为10.32 m(经验分布法) 和10.26 m(极大值分布法); 在概率模型仅通过观测记录建立时,50 a重现期承压水位标准值为9.96 m(极大值分布法)。根据标准值以及观测记录分析成果,提出了施工期与使用期抗浮设防水位的取值方法,同时为校准荷载分项系数和组合值系数提供了荷载统计参数。该方法以荷载概率建模作为切入点,解决了抗浮设计的关键问题,可为可靠度分析的应用和优化提供依据,且具有较强的兼容性和可操作性。

       

      Abstract: In order to provide a basis for determining the anti-floating fortification water level of buildings within the design reference period T, this study takes the confined water level as the research object, based on long-term groundwater level observation records of a residential project near the Beijiang Embankment and the river hydrological data, the empirical distribution method and the maximum value distribution method were employed to conduct probabilistic modeling of the observation records. The density function of the maximum confined water level within the reference period T was extrapolated to predict the long-term maximum confined water level. The results indicate that when the probability model is related to the confined water level results of 100-year return period obtained from the inversion method/numerical method, the standard values of the confined water level of 50-year return period are 10.32 m (using the empirical distribution method) and 10.26 m (using the maximum value distribution method). When the probability model is established solely based on observation records, the standard value of the confined water level of 50-year return period is 9.96 m (using the maximum value distribution method). Based on the standard values and the analysis results of the observation records, a method for determining the anti-floating fortification water level of the residential project during the construction period and the service period was proposed. Additionally, load statistical parameters were provided for the calibration of the load partial coefficient and the combined value coefficient. By taking probabilistic load modeling as a breakthrough, we solve key problems in anti-floating design and providing a basis for the application and optimization of reliability analysis. The technical method demonstrates strong compatibility and operability.

       

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