2022 journal article

Fine scale hydrologic modelling of bioretention using DRAINMOD-urban: Verifying performance across multiple systems

JOURNAL OF HYDROLOGY, 614.

By: G. Diab*, J. Hathaway *, W. Lisenbee*, R. Brown & W. Hunt n

co-author countries: United States of America πŸ‡ΊπŸ‡Έ
author keywords: Bioretention; DRAINMOD; Green infrastructure; Hydrology; Modeling
Source: Web Of Science
Added: November 28, 2022

Urbanization causes fundamental shifts in hydrologic partitioning within watersheds, leading to excess runoff being quickly routed to nearby conveyances. This leads to a host of concerns, from flooding to water quality impairments. To combat these effects, bioretention systems are implemented to restore more natural hydrology in the urban environment. To better understand and predict the effectiveness of these interventions, there is a need for reliable hydrology models to assess the performance of bioretention cells prior to installation. DRAINMOD-Urban was recently developed to produce hydrographs with a high temporal resolution, showing substantial promise during initial testing. Unfortunately, the dataset originally used for testing was limited, having minimal occasions of overflow and only consisting of one bioretention location. To achieve a more robust analysis of the model, DRAINMOD-Urban was evaluated using two years of monitoring data for four bioretention cells in North Carolina. The modeled bioretention cells had variable media depths, surface storage volumes, site conditions, and propensity for overflow. DRAINMOD-Urban model parameters were calibrated for a Nash-Sutcliff efficiency (NSE) from 0.14 to 0.60 for drainage and from 0.49 to 0.89 for overflow across the sites using six months of monitoring data. Model validation confirmed these results, producing drainage and overflow hydrographs with accurate timing, duration, and a range of NSEs from 0.19 to 0.60 and from 0.49 to 0.81, respectively, across the four sites. Model performance varied across sites; high drainage and overflow rates are well predicted compared to extended low rates caused by clogging issues or small storms. This study highlights the potential of DRAINMOD-Urban in modeling bioretention hydrology at a fine temporal scale under varying design configurations.