Real-Time Analysis of Moisture and Flow Data to Describe Wet Weather Response in a Permeable Pavement Parking Lot

The authors have used the CANARY event detection software for the purposes of detecting and identifying system response to rainfall in a permeable pavement stormwater best management practice that is installed in an academic parking lot in Cincinnati, OH. The results show that the software, originally designed for water quality detection in drinking water systems, proved adept at identifying a change in both underdrain flow and subsurface moisture in response to precipitation. Flow was measured as level in a 1-inch Parshall flume. Moisture was measured using four transmission line oscillation water content reflectometers placed in the aggregate media beneath interlocking concrete pavers. Of 21 storms greater than 2.5 mm of precipitation, all 21 were detected using CANARY software when evaluating flow detection. Nineteen of the 21 were detected using CANARY software to process the moisture signals. Additional event detections were generated from sensor device failures and maintenance activity.