Model Library

Soil and Water Assessment Tool (SWAT)

Model name: Soil and Water Assessment Tool (SWAT)

Developed by: U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS) and Texas A&M scientists (Last update: 2023)

Model type: Quasi-dynamic, semi-distributed, deterministic, process-based, ecohydrological small watershed to river basin-scale model

Computational requirements: 32-bit and 64-bit Windows, Linux, approx. 2–5 GB for software installation and input data, Ensure compatibility with other software components.

Software requirements: GIS (required): ArcSWAT, QSWAT, Mapwindow, AVSwat-X, GRASS;

Calibration tool: SWAT-CUP

Link to download model

Capabilities and Limitations:

Capabilities

  • Most common-used watershed model;
  • Comprehensive environmental modeling software;
  • Handling large watersheds with complex hydrology;
  • Simulating up to continental scale without requiring excessive data and calibration;
  • It can simulate sediment and nutrient load reductions by management practices;
  • Supported by extensive documentation.

Limitations

  • Low prediction accuracy in simulating areas with serious snow cover (Costa et al., 2019);
  • It does not incorporate bacterial growth (Cho et al., 2020) and metals reactions (Zouiten et al., 2013);
  • Not well-suited to simulate sub-daily events and seasonal dynamics of sediment load delivery at a small catchment outlet (Rhomad et al., 2023);
  • Low temporal resolution (Duku et al., 2015; Akoko et al., 2021);
  • Require numerous input data (Akoko et al., 2021);
  • SWAT was not designed to model heterogeneous mountain basins (Fontaine et al., 2002);
  • It simplifies the cross-section of natural channels and rivers to be a trapezoid or rectangular (Borah et al., 2019);
  • Lack of baseflow maintenance during low flow periods (Sánchez-Gómez et al., 2024).

Model Inputs and Outputs:

Inputs

  • Required: Topography data, LULC data, Soil data, Meteorological data, Hydrological data, Water quality data, Management data.
  • Optional: Stream network, Soil moisture, Climate statistics, Crop data, Pesticides, Waterbody management, Aquifer data, Floodplain.

Outputs

  • Reports of time-series simulations of hydrological and water quality loadings in watershed(s).
  • Soil moisture, crop yields, and irrigation simulations.
  • Reservoir storage, channel flow simulations.

Examples:

References

Rath, S., Zamora-Re, M., Graham, W., Dukes, M., & Kaplan, D. (2021). Quantifying nitrate leaching to groundwater from a corn-peanut rotation under a variety of irrigation and nutrient management practices in the Suwannee River Basin, Florida. Agricultural Water Management, 246, 106634. https://doi.org/10.1016/j.agwat.2020.106634

Abimbola, O., Mittelstet, A., Messer, T., Berry, E., & van Griensven, A. (2021). Modeling and prioritizing interventions using pollution hotspots for reducing nutrients, atrazine, and E. coli concentrations in a watershed. Sustainability, 13(1), 103. https://doi.org/10.3390/su13010103

Objectives

The objectives of the study were: (1) Calibrate SWAT using observations from a three-year irrigation and N fertilizer rate management experiment for a corn peanut rotation conducted in Live Oak, Florida (Zamora et al., 2018, 2020); (2) evaluate the long-term effects of the experimental irrigation and fertilization treatments on annual yield, N uptake, irrigation applied, and NO₃-N leaching using calibrated parameters over a 39-year (1980–2018) historic weather record; (3) estimate the effect of planting a rye cover crop on NO₃-N leaching, irrigation water use, and yield in corn-peanut rotations.

The objectives of the study were: (1) simulate BMPs proposed by the Nebraska Department of Environment and Energy (NDEE) within target sub-watersheds to determine reductions in pollutant loads and (2) determine if water-quality standards are met at the watershed outlet.