Investigation of the groundwater effect on slow-motion landslides by using dynamic Kalman filtering method with GPS: Koyulhisar town center

Authors : Kemal Özgür Hastaoğlu

Pages : 1033-1046

Doi:10.3906/yer-1210-10

View : 22 | Download : 7

Publication Date : 9999-12-31

Article Type : Makaleler

Abstract :The monitoring and analysis of natural disasters and their systems is crucially important in minimizing loss of life and property. In recent years, various methods of measurement and analysis have been employed to monitor and analyze landslides and their mechanisms. The Global Positioning System (GPS) is one of the methods used to monitor landslides. The consideration of external forces causing movement is essential when interpreting movement obtained by GPS. This paper describes a large motion in the Koyulhisar town center obtained from one GPS point. Twelve GPS points were set up in the Koyulhisar landslide region; 6 periods of GPS measurements were performed. The resultant data were processed using Bernese V5.0 software and coordinate information related to the points was obtained. In this study, the relationship between large motion and external forces was mathematically determined in a different way from previous studies. The coordinate information was first analyzed using the kinematic Kalman filtering technique and time-dependent speed and acceleration values for the points were determined. Data from the points at which significant displacements were observed were then analyzed using the dynamic Kalman filtering technique and the relationship between significant movements and temperature was modeled. Finally, the dynamic and kinematic model results were compared; it was observed that the displacements predicted by the dynamic model were more consistent with real values. It is concluded that accuracy in developing prediction models for deformations in landslides would be improved by using a dynamic deformation model containing either forces causing deformations or functions of quantities related to these forces.
Keywords : Key words: Landslide monitoring, dynamic Kalman filtering, GPS