Location: Agroclimate and Hydraulics Research UnitTitle: Development of a low-cost sensor network for real time monitoring of earthen dams
|Shelton, Colton - Kade|
|FUKA, DANIEL - Virginia Tech|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 4/7/2022
Publication Date: 7/18/2022
Citation: Wise, J.L., Hunt, S., Shelton, C.K., Fuka, D., Buser, M.D. 2022. Development of a low-cost sensor network for real time monitoring of earthen dams. In proceedings: American Society of Agricultural and Biological Engineers Annual International Meeting, Houston, Texas, July 17-20, 2022. Abstract.
Technical Abstract: More than half of the nearly 12,000 USDA sponsored watershed dams have surpassed their 50-year planned service life. Age, land use changes, extreme weather events, deterioration, and sedimentation filling flood pools increase the risk for dam incidents or failure to occur. Commercial models for potential dam incidents or failures are available, but these models often have inherent assumptions assuming static conditions. Improvements to these models require historic and real-time data. Commercial weather and dam monitoring sensors are available, but their cost can be burdensome, especially if implemented at thousands of dam sites across the country. Scientists at the USDA Agricultural Research Service (ARS) Hydraulic Engineering Research Unit (HERU) in Stillwater, Oklahoma in collaboration with ARS’ Partnerships for Data Innovations and Virginia Tech University are leading a pilot program focused on developing low-cost sensors for real time monitoring of earthen dams. Low-cost global positioning systems (GPS) and meteorological stations (e.g., precipitation, temperature, relative humidity, pressure, wind speed, soil moisture) have been developed and are being tested against commercially available sensors. The outcome of this research will be low-cost sensor networks for data collection and sharing through ARS Agricultural Collaborative Research Outcome System (AgCROS). Data will be used to develop new cloud-based hydrologic and hydraulic models and decision support tools for a vast array of end-users (e.g., policy makers, design engineers, dam operators and owners, etc.).