Drainage area characterization for evaluating green infrastructure using the Storm Water Management Model

Area of Science:

• Environmental Engineering
• Hydrology
• Urban Planning

Background:

• Urban stormwater runoff is significantly influenced by catchment characteristics.
• Current stormwater management models' accuracy depends on how catchment areas are spatially represented.
• Existing methods may not adequately capture the nuances of runoff processes, especially for green infrastructure.

Purpose of the Study:

• To propose and demonstrate a novel spatial discretization method for urban stormwater modeling.
• To improve the representation of runoff processes, particularly for green infrastructure performance assessment.
• To validate the method using the Storm Water Management Model (SWMM) in a real-world watershed.

Main Methods:

• Developed a discretization approach distinguishing directly connected impervious area, total impervious area, and pervious buffers.
• Applied the method to the Shayler Crossing watershed using a highly resolved spatial database.
• Evaluated six different spatial representations with synthetic storms to select an optimal scheme balancing complexity and accuracy.

Main Results:

• The balanced discretization approach, separating impervious and pervious areas, showed strong performance at the watershed scale (Nash-Sutcliffe coefficient = 0.852, R² = 0.871) with minimal calibration.
• The model successfully accommodated the distribution of runoff contributions from different spatial components and flow pathways.
• Hydrograph separation revealed relative contributions from various land cover types and subsurface sources, offering insights into green infrastructure effectiveness.

Conclusions:

• The proposed spatial discretization method enhances the accuracy of stormwater runoff simulation, particularly for evaluating green infrastructure.
• This approach allows for more informed planning and design of urban stormwater management strategies.
• The method is adaptable for large watersheds with appropriate land cover categorization and GIS support.