Metropolis-Hastings Markov Chain Monte Carlo Approach to Simulate van Genuchten Model Parameters for Soil Water Retention Curve
نویسندگان
چکیده
The soil water retention curve (SWRC) is essential for assessing flow and solute transport in unsaturated media. van Genuchten (VG) model widely used to describe the SWRC; however, estimation of its effective hydraulic parameters often prone error, especially when data exist only a limited range matric potential. We developed Metropolis-Hastings algorithm Markov chain Monte Carlo (MH-MCMC) approach using R estimate VG parameters, which produces numerical joint posterior distribution including fully-quantified uncertainties. When were obtained complete content (SWC) (i.e., from saturation oven dryness), MH-MCMC returned similar accuracy as non-linear curve-fitting program RETC (RETention Curve), but avoiding non-convergence issues. 5 SWC measured at potential around −60, −100, −200, −500, −15,000 cm, was more robust than program. performance are generally good (R2 > 0.95) all 8 soils, whereas underperformed coarse-textured soils. obtain 1871 soils National Cooperative Soil Characterization dataset with potentials −60 −100 −330 cm; results showed that simulated by highly consistent corresponding Altogether, our new solving coverage compared procedures, making it an alternative traditional solvers. code can be found GitHub repository.
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ژورنال
عنوان ژورنال: Water
سال: 2022
ISSN: ['2073-4441']
DOI: https://doi.org/10.3390/w14121968