Abstract: Groundwater is one of the key factors in underground engineering design, which is related to the stability and structural safety of geotechnical engineering. The large amount of measured data information of groundwater level during operation reflects the operation state and project environment faithfully. So it is very important to evaluate the groundwater distribution and engineering operation security based on these in-site measured data. In this paper, a mathematical model of quantitative analysis of monitoring data is established, and the regression fitting method is used to obtain groundwater distribution and its main influencing factors. Taking the Tianhuangping I pumped storage power station as an example, this paper analyzes and evaluates the groundwater distribution and its seepage influence factors in the project area by using the 20-years operation measured data. The study results in this paper are useful for the analysis of measured data, the distribution and change of groundwater, seepage control effect evaluation, repair plan establishment and operation management.

Key words: underground engineering, mountain ground water level, mathematical statistics, seepage flow, influencing factors

摘要： 地下水是地下工程设计考虑的关键因素之一，直接关系到岩土工程的稳定性及结构安全。工程运行期大量地下水位实测数据信息，如实反映了工程运行状态和周围环境，对地下水分析评估和工程安全性评估十分重要。通过建立监测数据定量分析数学统计模型，对大量长序列实测数据采用回归拟合方法，获得地下水分布及其主要影响因素。以天荒坪一级抽水蓄能电站为例，利用运行20年以来的实测数据，对工程区域地下水分布及其渗流影响因素进行了分析评价。研究成果对工程实测数据分析、地下水分布、防渗效果评价、运行管理等有重要参考意义。

关键词: 地下工程, 山体地下水位, 数学统计, 渗流, 影响因子