Model Library

Soil and Water Assessment Tool Plus (SWAT+)

Model name: Soil and Water Assessment Tool Plus (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 software (required): ArcSWAT, QSWAT, Mapwindow, AVSwat-X, GRASS; Calibration tool: SWAT-CUP

Link to download model

Capabilities and Limitations:

Capabilities

  • Newly completely revised and more flexible version of the SWAT model;
  • More flexible spatial representation of interactions and processes within a watershed;
  • Simulating up to continental scale without requiring excessive data and calibration;
  • More realistic simulation of landscape position, overland routing, and floodplain processes than SWAT;
  • Facilitation of SWAT-MODFLOW linkage;
  • Better tracking of modified parameters than SWAT;
  • Data files can be maintained as databases, including management schedules and operations;
  • It can simulate sediment and nutrient load reductions by management practices;
  • Unlimited number of crops growing at the same time.

Limitations

  • Limited number of studies using SWAT+ to assess the hydrological impacts of climate change (Pulighe et al., 2021);
  • SWAT+ retains the groundwater flow simulation limitations identified in SWAT, including assumptions like steady flow conditions, independent treatment of aquifers, and uniform aquifer properties (Sánchez-Gómez et al., 2024; Bailey et al., 2022);
  • It does not simulate stream-to-aquifer seepage, with groundwater head solely influenced by recharge and discharge (Bailey et al., 2022);
  • SWAT+ Toolbox v. 0.7.6 offers limited capabilities for conducting sensitivity analysis on parameters related to the nitrogen cycle (Yulianti et al., 2024);
  • Simplifying model parameters for wet and dry periods may lead to variations in simulation performance. (Yulianti 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

Singh, S., Hwang, S., Arnold, J. G., & Bhattarai, R. (2023). Evaluation of agricultural BMPs’ impact on water quality and crop production using SWAT+ model. Agriculture, 13(8), 1484. https://doi.org/10.3390/agriculture13081484

Bihonegn, B. G., & Awoke, A. G. (2023). Evaluating the impact of land use and land cover changes on sediment yield dynamics in the upper Awash basin, Ethiopia: The case of Koka reservoir. Heliyon, 9, e23049. https://doi.org/10.1016/j.heliyon.2023.e23049

 

Objectives

This study focused on evaluating the effects of combined management practices on riverine nitrate loads and crop production on the watershed scale and sought to identify the effectiveness of these management practices.

The objectives of the study were: (1) to assess the impact of land use land cover changes on sediment yield dynamics in the upper Koka Dam watershed using the 2000, 2005, 2010 and 2015 LULC maps; (2) to estimate the mean annual sediment yield loading to the Koka reservoir; (3) to evaluate the spatial and temporal variability of sediment yield and identify the erosion prone area.