Parameterizing Haverkamp Model From the Steady-State of Numerically Generated Infiltration: Influence of Algorithms for Steady-State Selection

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Özet

BEST (Beerkan Estimation of Soil Transfer parameters) methods of soil hydraulic characterisation are widely applied for estimating sorptivity, S, and saturated hydraulic conductivity, Ks. Calculating these properties requires choosing the β and γ parameters of the Haverkamp infiltration model. These parameters can be obtained from numerically simulated three-dimensional (3D) infiltration runs reaching steady-state. This investigation tested dependence of the estimated β and γ parameters on the algorithm for steady-state selection using simulated 3D cumulative infiltrations for different soils and initial conditions. Two algorithms used the original simulation outputs and included using (i) a threshold defining steadiness (T-algorithm) and (ii) the last four data points, yielding a reference value of steady-state infiltration rate (R-algorithm). A third algorithm, similar to the R-algorithm, was applied to previously re-sampled infiltration data at fixed time intervals (RR-algorithm). The intercept, bs, of the straight line fitted to the data describing steady-state on the cumulative infiltration plot depended on the applied algorithm more than the slope of this line. Consequently, β varied with the applied algorithm more than γ. The RR-algorithm, yielding 0.62 ≤ β ≤ 1.99 and 0.74 ≤ γ ≤ 0.98, was preferred since it mediated between advantages and disadvantages of T- and R-algorithms. The influence of the choice of proper values for β and γ on the estimates of S and Ks was evaluated using BEST. Using the default values of β (0.6) and γ (0.75) yielded accurate estimates of S but not of Ks. Soil dependent β and γ values should be used in this case. A check of the reliability of the estimates of bs can be made by a sequential analysis of the cumulative infiltration data. Future developments include considering sources differing in size and establishing if the suggested β and γ values apply in general to the available BEST algorithms.

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dc.contributor.authorAutovino, Dario
dc.contributor.authorBagarello, Vincenzo
dc.contributor.authorIovino, Massimo
dc.contributor.authorLassabatere, Laurent
dc.contributor.authorYilmaz, Deniz
dc.date.accessioned2026-10-28T14:54:28.276610947Z
dc.date.available2026-10-28T14:54:28.276610947Z
dc.date.issued2024
dc.description.abstractBEST (Beerkan Estimation of Soil Transfer parameters) methods of soil hydraulic characterisation are widely applied for estimating sorptivity, S, and saturated hydraulic conductivity, Ks. Calculating these properties requires choosing the β and γ parameters of the Haverkamp infiltration model. These parameters can be obtained from numerically simulated three-dimensional (3D) infiltration runs reaching steady-state. This investigation tested dependence of the estimated β and γ parameters on the algorithm for steady-state selection using simulated 3D cumulative infiltrations for different soils and initial conditions. Two algorithms used the original simulation outputs and included using (i) a threshold defining steadiness (T-algorithm) and (ii) the last four data points, yielding a reference value of steady-state infiltration rate (R-algorithm). A third algorithm, similar to the R-algorithm, was applied to previously re-sampled infiltration data at fixed time intervals (RR-algorithm). The intercept, bs, of the straight line fitted to the data describing steady-state on the cumulative infiltration plot depended on the applied algorithm more than the slope of this line. Consequently, β varied with the applied algorithm more than γ. The RR-algorithm, yielding 0.62 ≤ β ≤ 1.99 and 0.74 ≤ γ ≤ 0.98, was preferred since it mediated between advantages and disadvantages of T- and R-algorithms. The influence of the choice of proper values for β and γ on the estimates of S and Ks was evaluated using BEST. Using the default values of β (0.6) and γ (0.75) yielded accurate estimates of S but not of Ks. Soil dependent β and γ values should be used in this case. A check of the reliability of the estimates of bs can be made by a sequential analysis of the cumulative infiltration data. Future developments include considering sources differing in size and establishing if the suggested β and γ values apply in general to the available BEST algorithms.
dc.description.sponsorshipEuropean Union Next-GenerationEU
dc.description.sponsorshipEuropean Union Next‐GenerationEU
dc.description.sponsorshipNRRP, (1243 2/8/2022, PE0000005)
dc.identifier.articlenumbere15330
dc.identifier.doi10.1002/hyp.15330
dc.identifier.eissn1099-1085
dc.identifier.issn0885-6087
dc.identifier.issue11
dc.identifier.scopus2-s2.0-85208795485
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/1677
dc.identifier.volume38
dc.identifier.wosWOS:001368735000001
dc.language.isoen
dc.publisherJohn Wiley and Sons Ltd
dc.relation.ispartofHydrological Processes
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectanalytical infiltration models
dc.subjectBEST methods of soil hydraulic characterization
dc.subjectnumerically simulated infiltration
dc.subjectsaturated soil hydraulic conductivity
dc.subjectsorptivity
dc.subject.otherDigital elevation model
dc.subject.otherAnalytical infiltration model
dc.subject.otherBeerkan estimation of soil transfer parameter method of soil hydraulic characterization
dc.subject.otherHydraulic characterization
dc.subject.otherInfiltration models
dc.subject.otherNumerically simulated infiltration
dc.subject.otherParameter methods
dc.subject.otherSaturated soil hydraulic conductivities
dc.subject.otherSoil hydraulics
dc.subject.otherSoil transfers
dc.subject.otherSorptivity
dc.subject.otherTransfer parameters
dc.subject.otheralgorithm
dc.subject.otheranalytical framework
dc.subject.othercomputer simulation
dc.subject.otherhydraulic conductivity
dc.subject.otherhydraulics
dc.subject.otherinfiltration
dc.subject.othernumerical model
dc.subject.otherparameterization
dc.subject.othersaturated medium
dc.titleParameterizing Haverkamp Model From the Steady-State of Numerically Generated Infiltration: Influence of Algorithms for Steady-State Selection
dc.typeArticle
rdl.citation.openalex2
rdl.citation.scopus2
rdl.oa.statushybrid
rdl.oa.statusclosed
rdl.oa.urlhttps://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/hyp.15330
rdl.scopus.quartileQ1
rdl.source.indexSCOPUS
rdl.source.indexWOS