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Cited by 3,450Hydrology and Watershed Management StudiesSoil Moisture and Remote SensingEnvironmental Monitoring and Data Management

SWAT: Model Use, Calibration, and Validation

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J. G. Arnold, D. N. Moriasi, P. W. Gassman, K. C. Abbaspour, M. J. White, R. Srinivasan, C. Santhi, R. D. Harmel +4 more·2012·Transactions of the ASABE
DOI 10.13031/2013.42256
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Abstract

SWAT (Soil and Water Assessment Tool) is a comprehensive, semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. Several calibration techniques have been developed for SWAT, including manual calibration procedures and automated procedures using the shuffled complex evolution method and other common methods. In addition, SWAT-CUP was recently developed and provides a decision-making framework that incorporates a semi-automated approach (SUFI2) using both manual and automated calibration and incorporating sensitivity and uncertainty analysis. In SWAT-CUP, users can manually adjust parameters and ranges iteratively between autocalibration runs. Parameter sensitivity analysis helps focus the calibration and uncertainty analysis and is used to provide statistics for goodness-of-fit. The user interaction or manual component of the SWAT-CUP calibration forces the user to obtain a better understanding of the overall hydrologic processes (e.g., baseflow ratios, ET, sediment sources and sinks, crop yields, and nutrient balances) and of parameter sensitivity. It is important for future calibration developments to spatially account for hydrologic processes; improve model run time efficiency; include the impact of uncertainty in the conceptual model, model parameters, and measured variables used in calibration; and assist users in checking for model errors. When calibrating a physically based model like SWAT, it is important to remember that all model input parameters must be kept within a realistic uncertainty range and that no automatic procedure can substitute for actual physical knowledge of the watershed.

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Cited by

Sorted by citations

Authors
Arnold, J. G., Moriasi, D. N., Gassman, P. W., Abbaspour, K. C., White, M. J., Srinivasan, R., Santhi, C., Harmel, R. D., van Griensven, A., Liew, M. W. V., Kannan, N., & Jha, M. K.
Affiliations
  • United States Department of Agriculture (US)
  • Iowa State University (US)
  • Swiss Federal Institute of Aquatic Science and Technology (CH)
  • Texas A&M University (US)
  • IHE Delft Institute for Water Education (NL)
  • North Carolina Agricultural and Technical State University (US)
ORCID
Venue
Transactions of the ASABE
Publisher
American Society of Agricultural and Biological Engineers (ASABE)
Published
2012
Volume
55
Issue
4
Pages
1491-1508
ISSN
  • 2151-0032 (ISSN-L)
  • 2151-0040
DOI
10.13031/2013.42256
OpenAlex
W2059646894
Cited by
3,450
References
3
Citations by year
2026: 313 · 2025: 346 · 2024: 370 · 2023: 368 · 2022: 390 · 2021: 328 · 2020: 332 · 2019: 250 · 2018: 258 · 2017: 184 · 2016: 145 · 2015: 92 · 2014: 51 · 2013: 19 · 2012: 1
FWCI
47.34
Type
journal article
Language
en
Open access
Locations
  • Transactions of the ASABE (publishedVersion)
  • Lincoln (University of Nebraska) (submittedVersion)
  • DORA Eawag (Swiss Federal Institute of Aquatic Science and Technology (Eawag)) (submittedVersion)
Topics
  • Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
  • Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
  • Physical Sciences › Earth and Planetary Sciences › Geology › Environmental Monitoring and Data Management
Keywords
SWAT model, model calibration, model validation, SWAT-CUP, shuffled complex evolution, parameter sensitivity analysis, uncertainty analysis, watershed modeling, hydrological modeling, model parameterization

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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