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Modeling Hydrologic Performance of Permeable Pavement with DRAINMOD in North Carolina and Ohio
Variations in the hydrologic performance of permeable pavement can be due to several factors including gravel storage depth, drainage configuration, surface infiltration rate, and underlying soil type. A long-term hydrologic model is needed to better understand the influence of these factors on surface runoff, drainage, and exfiltration from permeable pavement systems. DRAINMOD is a widely accepted agricultural drainage model that can predict water table level, drainage, infiltration, and evapotranspiration continuously over long records of time. Past research has shown that DRAINMOD can be calibrated to accurately predict the hydrology of bioretention areas. Given that water movement through a permeable pavement cell is similar to a bioretention area, it is hypothesized that the model could also be calibrated to predict the hydrologic response from permeable pavement. Both stormwater control measures (SCMs) employ infiltration as the primary mechanism for peak flow attenuation and exfiltration for volume reduction. Drainage configurations for both SCMs are also analogous to the required DRAINMOD inputs. This study investigates the application of DRAINMOD to predict permeable pavement hydrology for a variety of different drainage configurations and underlying soil types. Three sites in North Carolina and one site in Ohio were monitored for rainfall, drainage outflow, and internal water level for a period of 9 to 12 months. The four sites have varying drainage configurations and underlying soils to represent a wide variety of permeable pavement applications. The model was calibrated for a period of 4 to 6 months at each site and validated for an additional 4 to 6 months. Results comparing the field-monitored and modeled volumes of drainage, surface runoff, and exfiltration/ET will be presented for each site. Preliminary results at the Boone, NC, site indicate success in predicting drainage volumes, with Nash-Sutcliffe efficiencies of 0.97 during the calibration period and 0.85 during the validation period. How the DRAINMOD outputs can be extended to predict the annual average water balance for varying drainage configurations and underlying soil types will also be discussed.
Modeling Hydrologic Performance of Permeable Pavement with DRAINMOD in North Carolina and Ohio
Variations in the hydrologic performance of permeable pavement can be due to several factors including gravel storage depth, drainage configuration, surface infiltration rate, and underlying soil type. A long-term hydrologic model is needed to better understand the influence of these factors on surface runoff, drainage, and exfiltration from permeable pavement systems. DRAINMOD is a widely accepted agricultural drainage model that can predict water table level, drainage, infiltration, and evapotranspiration continuously over long records of time. Past research has shown that DRAINMOD can be calibrated to accurately predict the hydrology of bioretention areas. Given that water movement through a permeable pavement cell is similar to a bioretention area, it is hypothesized that the model could also be calibrated to predict the hydrologic response from permeable pavement. Both stormwater control measures (SCMs) employ infiltration as the primary mechanism for peak flow attenuation and exfiltration for volume reduction. Drainage configurations for both SCMs are also analogous to the required DRAINMOD inputs. This study investigates the application of DRAINMOD to predict permeable pavement hydrology for a variety of different drainage configurations and underlying soil types. Three sites in North Carolina and one site in Ohio were monitored for rainfall, drainage outflow, and internal water level for a period of 9 to 12 months. The four sites have varying drainage configurations and underlying soils to represent a wide variety of permeable pavement applications. The model was calibrated for a period of 4 to 6 months at each site and validated for an additional 4 to 6 months. Results comparing the field-monitored and modeled volumes of drainage, surface runoff, and exfiltration/ET will be presented for each site. Preliminary results at the Boone, NC, site indicate success in predicting drainage volumes, with Nash-Sutcliffe efficiencies of 0.97 during the calibration period and 0.85 during the validation period. How the DRAINMOD outputs can be extended to predict the annual average water balance for varying drainage configurations and underlying soil types will also be discussed.
Modeling Hydrologic Performance of Permeable Pavement with DRAINMOD in North Carolina and Ohio
Smolek, A. P. (author) / Hunt, W. F. (author) / Winston, R. J. (author)
World Environmental and Water Resources Congress 2014 ; 2014 ; Portland, Oregon
2014-05-29
Conference paper
Electronic Resource
English
Modeling Hydrologic Performance of Permeable Pavement with DRAINMOD in North Carolina and Ohio
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