Adaptive Management to Improve Deicing Operations
Lawrence Baker, Research Professor, Bioproducts and Biosystems Engineering
- Bruce Wilson, Professor, Bioproducts and Biosystems Engineering
Project Summary:The goal of this research is to find ways to further reduce the use of deicing salts by linking automatically collected data from salting trucks to automatically collected water quality data. This has required development of a new type of "meltwater sampler" to measure flows entering catch basins, which have been used for nearly a full winter. The study has also examined historical data from the Nine Mile Creek Watershed District (2004-2015) and found that the largest daily chloride loadings were in late spring and summer, not winter. Preliminary analysis of data for the study's first field sampling season showed that the novel meltwater sampler worked. One interesting finding is that much of the seasonal chloride loading occurred over a week-long period. If this pattern persists, mitigation efforts might focus on these "disproportionate" events to decrease annual loadings. The study's outcomes would take adaptive management (AM) for deicing operations to a new level that would achieve both traffic mobility goals and water quality goals (lower chloride, Cl). Researchers are communicating this information throughout the state with a web-based AM tool (e.g., a simple spreadsheet tool) and documentation, an online video presentation, and presentation of findings at several professional conferences.
- Start date: 06/2017
- Project Status: Active
- Research Area: Environment and Energy
- Topics: Snow and ice control