The main core of SWAP, as stated before, consists of the solution of the governing flow equation for water movement in soils. The solution is determined by initial and boundary conditions, as well as by soil properties. All the conditions and properties need to be supplied by the user; those are not hard-coded in SWAP. Only universal constants or scientifically accepted parameter values have been coded hard in the source code. Technical calibration of internal parameters is not operational (this will only occur internally when new routines will be implemented). In summary, technical calibration is not implemented, because:
- state-of-the-art theory;
- state-of-the-art solutions; e.g. both the soil water movement and soil temperature problems are posted as matrix-vector problems, and for one-dimensional situations these matrix-vector problems can be solved mathematically by using the well-known tri-diagonal solver (e.g., (Press et al. 1992));
- non-trivial code (e.g. mass balance computations: change in storage = input-output);
- universal constants should not be calibrated (e.g. the von Karman constant (= 0.41) as used in the Penman-Monteith subroutine PenMon);
- some constants have been imposed constant in code based on literature (e.g. thermal properties of soil components; see parameter definitions in subroutine DeVries (temperature.f90) and Table 9.1 of the manual).
Most model variables are model input variables, which allows the user to calibrate, validate, verify or check for plausibility whether the outcome matches observations.
Several papers have been published in the scientific literature where SWAP was compared against other models, against analytical solutions and/or against available data: for example, Eitzinger et al. (2004), Vanderborght et al. (2005) (see also comment by Groenendijk et al. (2006)), Bonfante et al. (2010), Hack-ten Broeke et al. (2013), Groenendijk et al (2014), and Kroes et al. (2015).
SWAP can be combined with optimization algorithms as PEST (Doherty 2025) to perform sensitivity analysis or automatic calibration. For instance, the SWAP-PEST combination has been used by Van Dam (2000), De Wit et al. (2024) and De Melo et al. (2025).
Bonfante, A., A. Basile, M. Acutis, et al. 2010.
“SWAP, CropSyst and MACRO Comparison in Two Contrasting Soils Cropped with Maize in Northern Italy.” Journal Article.
Agricultural Water Management 97: 1051–62.
https://doi.org/10.1016/j.agwat.2010.02.010.
De Melo, M. L. A., Q. de Jong van Lier, M. Heinen, J. C. van Dam, and F. R. Marin. 2025.
“Mechanistic Modeling of Root Water Uptake in Tropical Agriculture: A Sensitivity Analysis of Drought Stress Dynamics.” Journal Article.
Plant and Soil 514: 1143–65.
https://doi.org/10.1007/s11104-025-07452-0.
De Wit, J. A., M. H. J. van Huijgevoort, J. C. van Dam, et al. 2024.
“Hydrological Consequences of Controlled Drainage with Subirrigation.” Journal Article.
Journal of Hydrology 628.
https://doi.org/10.1016/j.jhydrol.2023.130432.
Doherty, J. 2025.
Calibration and Uncertainty Analysis for Complex Environmental Models. Second Edition. Book. Watermark Numerical Computing, Brisbane, Australia.
https://pesthomepage.org/pest-book.
Eitzinger, J., M. Trnka, J. Hösch, Z. Žalud, and M. Dubrovský. 2004.
“Comparison of CERES, WOFOST and SWAP Models in Simulating Soil Water Content During Growing Season Under Different Soil Conditions.” Journal Article.
Ecological Modelling 171: 223–46.
https://doi.org/10.1016/j.ecolmodel.2003.08.012.
Groenendijk, P., M. Heinen, G. Klammler, et al. 2014.
“Performance Assessment of Nitrate Leaching Models for Highly Vulnerable Soils Used in Low-Input Farming Based on Lysimeter Data.” Journal Article.
Science of the Total Environment 499: 463–80.
https://doi.org/10.1016/j.scitotenv.2014.07.002.
Groenendijk, P., J. G. Kroes, and J. C. van Dam. 2006.
“Comments on ‘“a Set of Analytical Benchmarks to Test Numerical Models of Flow and Transport in Soils”’.” Journal Article.
Vadose Zone Journal 5: 126–27.
https://doi.org/10.2136/vzj2005.0077L.
Hack-ten Broeke, M., J. Kroes, R. Hendriks, R. Bartholomeus, J. van Bakel, and I. Hoving. 2013.
Actualisatie Schadefuncties Voor de Landbouw, Tussenfase 2a: Plausibiliteitstoets SWAP En Enkele Verkennende Berekeningen. Rapport 2013-37. Book. STOWA, Amersfoort.
https://edepot.wur.nl/286135.
Kroes, J., R. Bartholomeus, J. van Dam, et al. 2015.
Waterwijzer Landbouw, Fase 2. Modellering van Het Bodem-Water-Plantsysteem Met Het Gekoppelde Instrumentarium SWAP-WOFOST. Rapport 2015-16. Book. STOWA, Amersfoort.
https://www.stowa.nl/sites/default/files/assets/PUBLICATIES/Publicaties%202015/STOWA%202015-16.pdf.
Press, W. H., S. A. Teukolsky, and W. T. Vetterling. 1992. Numerical Recipes in Fortran 77. The Art of Scientific Computing, Second Edition. Book. Cambridge University Press.
Van Dam, J. C. 2000. Field Scale Water Flow and Solute Transport. SWAP Model Concepts, Parameter Estimation and Case Studies. PhD Thesis. Book. Wageningen University, Wageningen, The Netherlands.
Vanderborght, J., R. Kasteel, M. Herbst, et al. 2005.
“A Set of Analytical Benchmarks to Test Numerical Models of Flow and Transport in Soils.” Journal Article.
Vadose Zone Journal 4: 206–21.
https://doi.org/10.2113/4.1.206.