Model Library

Stormwater Treatment and Analysis INtegration (SUSTAIN)

Model name: Stormwater Treatment and Analysis INtegration (SUSTAIN)

Developed by: U.S. Environmental Protection Agency (EPA) (Last update: 2014)

Model type: Distributed, deterministic, process-based, hydrologic and water quality modeling, decision support system for watersheds and urban streams.

Computational requirements: Microsoft Excel 2003 or later versions are required.

Software requirements: GIS (required): ESRI's ArcGIS 9.3 and the Spatial Analyst extension

Link to download model

Capabilities and Limitations:

Capabilities

  • It has a modular design;
  • SUSTAIN evaluates BMP effectiveness, cost-efficiency, and optimal placement, type, and size (U.S. EPA, n.d.);
  • Its BMP Optimization module uses scatter search and NSGA-II algorithms to identify cost-effective solutions based on user criteria (U.S. EPA, n.d.).

Limitations

  • It is no longer developed or supported by EPA (U.S. EPA, n.d.);
  • SUSTAIN's macro-scale simulation-optimization is time-consuming, with computational costs rising exponentially with more candidate LIDs and sites (Dong et al., 2020);
  • Simplified BMP geometries and outlet controls need assumptions; outlet control structures can only be represented as a single circular and weir, and existing complex detention pond geometries cannot be modeled (Herrera Environmental Consultants, Inc., 2013);
  • Dissolved concentrations are assumed proportional to total concentrations, and no pollutant removal is assumed for permeable pavement runoff to surface water (Herrera Environmental Consultants, Inc., 2013);
  • The aggregate BMP template supports only one BMP type per sub-catchment unit (Herrera Environmental Consultants, Inc., 2013);
  • Model memory limits simulations up to about 7 years at 15-minute intervals; longer periods cause crashes (Herrera Environmental Consultants, Inc., 2013);
  • The simulation time series significantly influences the optimized solution (Herrera Environmental Consultants, Inc., 2013).

Model Inputs and Outputs:

Inputs

Topography data, LULC data, Soil data, Meteorological data, Hydrological data, Water quality data, BMPs data, Conveyance system information, Economic data, Optimization and decision criteria

Outputs

  • Time-series simulation of hydrological and water quality parameters.
  • It generates geospatial outputs for BMP performance metrics, cost-effectiveness analyses, BMP placement and optimization results for user-defined criteria.

Examples:

References

Gallo, E., Bell, C., Mika, K., Gold, M., & Hogue, T. S. (2020). Stormwater management options and decision-making in urbanized watersheds of Los Angeles, California. Journal of Sustainable Water in the Built Environment, 6(2), 04020003. https://doi.org/10.1061/JSWBAY.0000905

Qiu, S., Yin, H., Deng, J., & Li, M. (2020). Cost-effectiveness analysis of green–gray stormwater control measures for non-point source pollution. International Journal of Environmental Research and Public Health, 17(3), 998. https://doi.org/10.3390/ijerph17030998

Objectives

The objectives of the study were to identify key characteristics contributing to water quality impairment, analyze the efficacy of specific BMPs for regulatory compliance, investigate variability in achieving water quality compliance across watersheds, and consider benefits and tradeoffs in BMP selection for optimal stormwater management plans.

The objectives of the study were: (1) create a SUSTAIN model of the study area to examine the ability of coupled green-gray SCMs to control non-point source pollution; (2) compare the cost-effectiveness of three different stormwater control scenarios under the same pollution reduction target; and (3) investigate the ability of coupled green-gray SCMs to control non-point source pollution during high-intensity rainfall events.