Dam safety systems are systems monitoring the state of dams used for hydropower or other purposes, as well as external physical threats to them, and issuing emergency warnings at various degrees of automation. This includes the use of differential GPS and SAR remote sensing to monitor the risks imposed by landslides and subsidence. For large dams seismographs are used to detect reservoir-induced seismicity that could threaten the stability of the dam. The output of these systems can provide warning to the local population ahead of a potential collapse.
The dam monitoring system of Enel green Power in Riolunato Dam, controls all important parameters of the dam. Optical and physical alignment systems are installed for control any movement of the land under and around the dam. The dam monitoring system checks the level of the water because this creates different pressures on the dam also in relation at temperature of the water and the temperature of the air. All these parameters are controlled and compared with the deformation and stress applied on the structure of the dam, measured with extensimeter, pendulum, reverse pendulum, piezometer, etc. The dam monitoring system continuously store and analyze all the dam parameters, creating 5 typologies if alarms. For each level of alarm the dam monitoring system set different levels of risk that involve specific reaction, like reduction of the level of the water in the lake and communication at the network of all dam control system. When the level of risk increase, the monitoring system activate alarms for close some road or bridge, and eventually alerted people living in some village. All data are continuously sent from the dam monitoring system at the network dam control system were specialist engineers take decision about eventually emergency situations. The Riolunato dam monitoring local system software is developed from AuCo Solutions. In the 80s and 90s, Enel fostered also the development of a family of expert systems for dam safety management, based on the application of artificial intelligence techniques to the real-time interpretation of monitoring data gathered by automatic acquisition systems. From the project DAMSAFE, several instances of a decision support system named MISTRAL were derived, which were installed on the Pieve di Cadore Dam owned by Enel, but also on other dams managed by other companies, such as Ridracoli Dam, Cancano, Fusino, Valgrosina, and San Giacomo. Some of these systems are still operating after more than twenty years.
Dam safety systems became a focus of multi-agency regulations during the U.S. Army Corps of Engineers construction of large flood control and hydro-electric power generation projects. To help benchmark proven practices, the Association of State Dam Safety Officials formed a national non-profit organization of state and federal dam safety regulators, dam owners and operators, engineering consultants, manufacturers and suppliers, academia, contractors and others interested in dams safety. More recently public safety concerns were addressed by the Indian Dams Safety Act of 1992 during hearings before the Select Committee on Indian Affairs, United States Senate, 102nd Congress, second session, on S. 2617. The purpose was to provide for the maintenance of dams located on Indian lands in New Mexico by the Bureau of Indian Affairs through contracts with the Indian tribes. The ASDSO Conference Proceedings paper by Gary R. Holtzhausen describes the effective use of tiltmeters with remote sensing to provide reliable low-cost early warning of impending structural failures. The ASDSO Conference Proceedings paper by Barry K. Meyers describes two case studies using failure modes analysis together with a variety of automated instrumentation to provide early warnings at White River Project owned by Puget Sound Energy as well as a case study of the Silver Creek Dam near Silverton OR.
