Abstract: In view of the lag effect and the nonlinear characteristics of the influence of upstream water level and rainfall on the uplift pressure of concrete gravity dam, a monitoring model of the concrete gravity dam considering the nonlinear environmental influence is established. The influential process is regarded as a normal distribution process and the lagging days and influential days are optimized by improved quantum genetic algorithm to raise the fitting and forecasting accuracy. Finally, a concrete gravity dam is taken as an example and the corresponding uplift pressure series of the measuring point A6-UP-01 are fitted and predicted with the proposed method. Through comparison between measured data and predicted data, the proposed method is verified superior to the traditional statistic model and it is of scientific and practical application value.

Key words: concrete gravity dam, uplift pressure, hysteresis effect, traditional statistical model, classified quantum genetic algorithm