REAL-TIME GROUNDWATER VISUALIZATION TECHNOLOGY

Regional groundwater flow patterns in a karstic aquifer in St. Louis Park, Minnesota were completely obscured by the hydraulic stress of municipal water supply wells. Draw downs in the pumping wells are commonly 80 to 100 feet or more. The complex pumping schedules in the day to day operations of all the surrounding municipal well fields confused the interpretation of mass water level measurements. Furthermore, models that were based on average pumping rates and average aquifer parameters were unable to predict actual groundwater flow directions.

An accurate picture of the groundwater flow regime was obtained using telemetered data and a patented technology called Aqua TrueVue that integrates off-the-shelf software to better visualize actual flow patterns. Aqua TrueVue is a graphical user interface (GUI) to a database that enables scientists and engineers to efficiently analyze and visualize many types of data. Aqua TrueVue interfaces directly with sensors for temperature, pH, conductivity, and other parameter-specific probes.

Wells in St. Louis Park, Edina and adjacent locations were equipped with pressure transducers set to record water levels at fifteen-minute intervals. Much of this equipment was already installed as part of municipal Supervisory Control And Data Acquisition (SCADA) systems. We found that the SCADA water level data were generally underutilized by some of the users, and that users sometimes had difficulty accessing their water level and well pumping data.

Once a complete data set was obtained for all of the wells of interest, visualizations of the water surface were created in Aqua TrueVue. The resulting groundwater flow patterns were created in planar view to compare with well capture areas, well head protection areas, and groundwater particle tracking simulations. Another feature of the data analysis capability of Aqua TrueVue is that many of the pumping changes produce excellent drawdown or recovery data with which to analyze aquifer parameters. Thus, refined inputs to predictive modeling are able to be generated.