Dam Movement Modeling by Using Multiple Linear Regression and Arima Models
Structural health monitoring of the large infrastructural objects (high buildings, bridges, tunnels, dams, etc.) is in the domain of civil and geodetic engineers who use different methods and instruments for this task. Dam movement is influenced by various factors among which the most important are: thermal variations, hydrostatic pressure and dam ageing. This research investigates influence of thermal variations on dam crest movement by using statistical methods: autoregressive integrated moving average (ARIMA) and multiple linear regression. Dam crest movement data is obtained by using optical alignement method on the concrete gravity dam HP Salakovac. In the first part of this research correlation between dam crest movement and concrete temperature is determined, the second part deals with short term concrete temperature prediction and in the final part of this research previously fitted statistical models are used for dam movement prediction. The results showed that proposed model based on statistical methods can provide quality prediction of dam crest movement.