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Intelligent Dam and Levee Monitoring


The Colorado School of Mines SmartGeo Smart Dam Team research goals are to develop the technology needed to change traditional earth dams and levees into intelligent earth dams and levees. Intelligent earth dams and levees are structures that monitor their condition or “health” and adapt to improve their performance. Using wireless sensing and monitoring, intelligent earth dams and levees will assess early onset of internal erosion and other damage due to aging or extreme loading, and will advance 4D (space and time) monitoring systems that fuse together geophysical, geotechnical and sensing data.

To successfully achieve these goals, this NSF-funded IGERT team at Colorado School of Mines is developing a wireless sensor network (WSN) that uses geophysical sensing techniques to continuously assess the subsurface condition of dams and levees. Planned WSN sensing techniques include passive and active seismic and self potential. Remote sensing data techniques and geographic information systems will be integrated with the WSN data to enhance knowledge discovery. This team of six graduate trainees and associates have combined their interdisciplinary knowledge from Geology, Geophysics, Civil Engineering, and Computer Science and have both developed unique test hardware and begun both laboratory and field experimentation.

In the laboratory, the team has begun experiments to investigate a scale model dam to determine whether they can detect the initiation/early stages of internal erosion. Initially, they want to determine what size anomalies (e.g. due to construction, animal or human action, sinkholes, etc.) these geophysical techniques can discern and the sensitivity of the different measurement methods. They are also exploring what conditions are required to induce internal erosion, specifically focusing on the effects of head, porosity, and the introduction of anomalies. They will use time-lapse monitoring to study what internal erosion looks like as it initiates and other instrumentation to measure flow rate, upstream head level, outlet turbidity, acoustic emissions (passive seismic), and self potential. Because these measuring techniques generate significant data, trainees are actively researching various methods to extract meaningful information from 4D noisy geophysical data, to advance visualization techniques that characterize earth dam and levee conditions, and are pursuing advances in artificial intelligence techniques and machine learning for wireless sensors and networks.

For field testing, trainees in collaboration with Dr. Chuck Odon from Earth Science Systems have designed and built a wireless, precision data acquisition system that supports long-term in-situ geophysical measurements for monitoring structural health of dams and levees. The hardware, currently in its second revision, supports high sampling frequencies and large amounts of in-network data using geophysical inspection techniques like self potential, resistivity, and seismic measurements. Figure 1 shows a picture of the current wireless geophysical hardware (mote).

In Spring, 2011, the research team obtained permission from Colorado’s Chief Engineer of the Dam Safety Program and the Denver Water Management Department to do field research at Long Lakes Dams in Arvada, Colorado. After obtaining this permission, the team worked with CSM professor, Dr. Andre Revil and his Ground Water Geophysics class and completed initial on-site characterization of DC resistivity tomography and self potential potential. Two lines were collected that allowed trainees and students to clearly see the aquifer made by the impermeable Pierre Shale. The data from this testing will be used to assess groundwater flow and will be used to create a hydro and geophysics integrated flow model. The site will be used for future testing of the geophysical sensing mote hardware. Figure 2 Shows the Lower Long Lake Dam and some of the testing that was done.

In the future, the research team hopes to deploy long-term geophysical networks of the wireless geophysical mote hardware. Before this can happen, laboratory research needs to define the limitations and advantages of various measuring techniques. The computer science trainees must improve their in-network geolocation algorithm refinement that includes applying temperature and humidity correction factors and a system to more accurately define distance estimates for better location estimates.

Address Goals

After hurricane Katrina, the safety and monitoring of levees and dams gained global attention. It also highlighted some of the weaknesses in US policy of monitoring and analyzing levees and dams. The advanced instrumentation being developed by the SmartGeo Smart Dam research team could help both alleviate tragedies and provide leaders with better tools for policy and safety decisions. The technology developed by the research team aims to both sense and monitor levees and dams “health” in order to assess early onset of internal erosion and other damage due to aging or extreme loading. These experimental tools will advance the frontiers of knowledge of 4D (space and time) monitoring systems by fusing together geophysical, geotechnical, and remote sensing technologies.

Trainees participating in the SmartGeo Smart Dam Research have gained a unique experience in teamwork not normally associated with a PhD dissertation. Besides completing their individual PhD dissertation work, these students have experienced the importance of teamwork and the value of interdisciplinary knowledge sharing. Working together, they are researching, designing, and building a unique set of tools that could not be made by any one individual. Through their policy research, they are learning that technology alone is not enough. As technical experts, they need to understand how to influence governmental policy in order for their technology to be implemented. They are truly being formed into the leaders of the future.

This teams’ successful integration and advanced research quality was highlighted at the CSM Graduate Student 2011 Research Fair. Over 150 Colorado School of Mines graduate students competed in a poster contest, including all members of the SmartGeo SmartDam Team. Although each student presented his or her individual research, all students work focused on the theme of their SmartGeo SmartDam research. Kerri Stone, one of the Computer Science SmartGeo Trainees, was awarded best Math and Computer Science poster for her presentation on “IMAGINE: Intelligent Monitoring and Geophysical INspection of Embankment dams.” Scott Ikard, a SmartGeo Geophysics Trainee, was awarded best Geophysics poster for his presentation of “Time-lapse Geophysical Monitoring for Hydraulic Assessments of Embankment Dams and Levees: Detecting and Monitoring Internal Erosion.” Finally, Ben Lowry, a Geology SmartGeo SmartDam Trainee, won 3rd Overall Best Poster for his presentation of “Construction of a Three Dimensional Subsurface Framework Model and Geospatial Infrastructure of the Muddy Creek Landslide Complex, Gunnison County, Colorado.”

It was felt that the interdisciplinary integration of the teams work into each student’s individual research helped make both the individual student and the team successful. Trainee and team research success isn’t the only measure of the success of the program and the team. The SmartGeo IGERT program is also recognized as a successful program outside of the IGERT. Dr. Kevin Moore, the Intern Engineering Division Director at Colorado School of Mines, made the following comment about the SmartGeo IGERT program. “I wish all programs on campus were such that there was a cohort system and an entry course like SYGN 550 and nicely managed seminars like SmartGeo.” Dr. Thomas Boyd, Dean of Graduate Studies at Colorado School of Mines, stated “I think we could argue that the activities [of SmartGeo] were one of the fundamental impetuses for the institution to create the Center for Professional Education. Activities done under the auspices of the IGERT have been used as a model for the Center (info about the center found at” Only through interdisciplinary technology transfer, and understanding policy roadblocks will implementation of technologies like those being developed by the SmartGeo SmartDam team be possible. Their progress is a reflection of the success of the SmarDam team and an inspiration for other trainees and faculty.