2024 journal article
Calibration and validation of DRAINMOD to predict long-term permeable pavement hydrology
JOURNAL OF HYDROLOGY, 637.
author keywords: Pervious pavement; Porous pavement; Low impact development; Long-term model; Continuous simulation; Modeling
open access via doi.org (publisher)
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2. Zero Hunger
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Added: June 24, 2024
The hydrologic performance of permeable pavement varies widely due to underlying soil type, drainage configuration, contributing drainage area, surface infiltration rate, and aggregate depth. A long-term hydrologic model is needed to better understand the influence of these design variables on surface runoff, drainage, exfiltration, and evaporation from permeable pavement systems. Most permeable pavement models have not been calibrated with field monitored data, are usually unable to accurately model internal water storage (IWS) zones, and do not account for evaporation from the aggregate profile. Because permeable pavement employs drainage and exfiltration as primary hydrologic mechanisms, it was hypothesized that DRAINMOD, a model shown to accurately simulate bioretention hydrology, could be calibrated to predict the hydrologic response from permeable pavements. Hydrologic data were collected from two permeable pavement applications in North Carolina (Boone and Durham) and two permeable pavement applications in Ohio (Perkins Township and Willoughby Hills) to calibrate and test the model. The specific permeable pavements applications varied widely in aggregate depth, drainage configuration, underlying soil type, and contributing drainage area. Nash-Sutcliffe Efficiencies for drainage ranged from 0.77 to 0.95 during calibration and validation of all sites. Nash-Sutcliffe Efficiencies for exfiltration/evaporation ranged from 0.55 to 0.97 for Boone and Perkins Township, but prediction of exfiltration/evaporation volumes on an event basis was poor for the remaining two sites due to low exfiltration rates (less than 0.20 mm/hr). Despite this, the cumulative volume of exfiltration/evaporation was predicted to within 1–9 % of what was measured during monitoring. Modeled and monitored surface runoff from the Willoughby Hills application (8 % of the water balance) was equivalent. The model predicted the percentage of drainage, surface runoff, and exfiltration/evaporation to within 2 % of what was monitored/estimated at each site, suggesting long-term modeling of permeable pavement hydrology with DRAINMOD is viable.