Dam monitoring data analysis methods: A literature review

Abstract

Dam monitoring usually involves environmental variables (e.g., the water level and temperature) and effect variables (deformation, cracking, seepage, etc.). The associated monitoring data can reflect the trends in these variables over time and are important information for managers to understand the operational status of a dam. Therefore, research on monitoring data analysis methods is very important for monitoring dam safety. Dam monitoring data analysis methods can be divided into monitoring model, monitoring index, and abnormal value detection methods. A monitoring model takes environment variables as independent variables and effect variables as dependent variables. By studying the interactions among variables, the trends of effect variables can be learned for monitoring and prediction. A monitoring index is established to denote warning or extreme value considering the previous changes in effect variables to determine whether future changes are safe. Abnormal value detection is also an important method of finding abnormal changes in the dam state. This paper summarizes the principles, research progress, deficiencies, and development trends of these three types of monitoring data analysis methods. This review promotes research in the field of dam safety monitoring.