Beerkan Estimation of Soil Transfer parameters (BEST) across soils and scales

Angulo-Jaramillo, Rafaël; Bagarello, Vincenzo; Prima, Simone Di; Gosset, A.; Iovino, Massimo; Lassabatère, Laurent

doi:10.1016/j.jhydrol.2019.06.007

Cited by 59 publications

(54 citation statements)

References 95 publications

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“…Each of these sites is further divided into three blocks (i.e., upslope, U, midslope, M, and downslope, D). For a detailed description of the field sites, the reader may refer to our previous work [13]. In brief, for a given plot, three undisturbed soil cores (5 cm in height and 5 cm in diameter) were collected at the 0-5 cm depth.…”

Section: Field Sites and Soil Samplingmentioning

confidence: 99%

“…For further descriptions of the MDI, details of measurements and calculations of hydraulic conductivity see Decagon Devices Inc. (Washington, DC, USA) [28]. The saturated soil hydraulic conductivity, Ks (mm h −1 ), was measured with ponding infiltration experiments of the Beerkan type [13]. At each plot, we performed seven Beerkan tests, for a total of 126 experiments.…”

Section: Unsaturated and Saturated Soil Hydraulic Conductivity Measurmentioning

confidence: 99%

“…The equilibration time, ts (s), namely the duration of the transient phase of the infiltration process, was estimated according to the suggested criterion by Bagarello et al [30] for analyzing cumulative infiltration data. More specifically, the ts value was determined as the first value for which: The saturated soil hydraulic conductivity, K s (mm h −1 ), was measured with ponding infiltration experiments of the Beerkan type [13]. At each plot, we performed seven Beerkan tests, for a total of 126 experiments.…”

Section: Unsaturated and Saturated Soil Hydraulic Conductivity Measurmentioning

confidence: 99%

“…We estimated K s by the Simplified method based on the near Steady-state phase of a Beerkan Infiltration run (SSBI), recently proposed by Bagarello et al [32]. This method estimates K s through an infiltration experiment of the Beerkan type [13] and an estimate of the macroscopic capillary length, λ c (mm), expressing the relative importance of the capillary over gravity forces during water movement in unsaturated soil [33][34][35]. Firstly, the experimental steady-state infiltration rate, i s (mm h −1 ), is estimated by linear regression analysis of the last data points of the cumulative infiltration, I (mm), versus time, t (h), plot, describing the near steady-state condition.…”

Section: Estimating the Saturated Soil Hydraulic Conductivity K Smentioning

confidence: 99%

“…During the last years, many infiltration methods and devices have been developed to determine soil hydraulic properties [10]. Among them, the Beerkan method [11] is becoming very popular in soil science because it constitutes a simple and an inexpensive way to determine the saturated soil hydraulic conductivity, K s , in the field [12,13]. On the other hand, the mini-disk infiltrometer (MDI) is a routinely used method for measuring infiltration rates under negative pressure head in the field.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Assessing Water Infiltration and Soil Water Repellency in Brazilian Atlantic Forest Soils

et al. 2020

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This study presents the results of the soil hydraulic characterization performed under three land covers, namely pasture, 9-year-old restored forest, and remnant forest, in the Brazilian Atlantic Forest. Two types of infiltration tests were performed, namely tension (Mini-Disk Infiltrometer, MDI) and ponding (Beerkan) tests. MDI and Beerkan tests provided complementary information, highlighting a clear increase of the hydraulic conductivity, especially at the remnant forest plots, when moving from near-saturated to saturated conditions. In addition, measuring the unsaturated soil hydraulic conductivity with different water pressure heads allowed the estimation of the macroscopic capillary length in the field. This approach, in conjunction with Beerkan measurements, allowed the design better estimates of the saturated soil hydraulic conductivity under challenging field conditions, such as soil water repellency (SWR). This research also reports, for the first time, evidence of SWR in the Atlantic Forest, which affected the early stage of the infiltration process with more frequency in the remnant forest.

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Section: Field Sites and Soil Samplingmentioning

confidence: 99%

Section: Unsaturated and Saturated Soil Hydraulic Conductivity Measurmentioning

confidence: 99%

Section: Unsaturated and Saturated Soil Hydraulic Conductivity Measurmentioning

confidence: 99%

Section: Estimating the Saturated Soil Hydraulic Conductivity K Smentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Assessing Water Infiltration and Soil Water Repellency in Brazilian Atlantic Forest Soils

et al. 2020

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

Autovino,

Bagarello,

Iovino

et al. 2024

Hydrological Processes

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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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Improved Beerkan run methodology to assess water impact effects on infiltration and hydraulic properties of a loam soil under conventional‐ and no‐tillage

Castellini

Prima

Iovino

et al. 2021

Soil Science Soc of Amer J

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Beerkan infiltration experiments with three water pouring heights (low, L = 3 cm; intermediate, M = 100 cm; high, H = 200 cm) were performed on both a no‐tilled (NT) and a conventionally tilled (CT) bare loam soil to determine the surface soil hydraulic properties by the BEST‐steady algorithm. Saturated soil hydraulic conductivity, Ks, significantly and monotonically decreased from the L to the H runs (from 236 to 37 mm h‒1) and lower Ks values were detected under CT (163–23 mm h‒1) than NT (346–51 mm h‒1) for each water pouring height. For both soil management practices, the gravitational potential energy, Ep, of the water used for the infiltration runs, explained most of the variance in the mean Ks values. According to the fitted relationships, an increase of Ep from 50 to 3,327 J m‒2 determined a Ks decrease by a factor of 9.5 in the CT soil and 6.3 in the NT soil. The CT soil was 2.1 and 3.3 times less conductive than the NT soil with the lowest and the highest energy, respectively. The water retention scale parameter, hg, only varied between non‐perturbing (L) and perturbing (M, H) runs because |hg| increased from 55 to 93–100 mm. Therefore, water impact can greatly influence hydrodynamic properties of the upper soil layer regardless of the management practice. The tested infiltration methodology looks promising to mimic effects of relatively high energy rainfall events and to determine the hydraulic properties of the exposed soil layer under different management practices.

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Beerkan Estimation of Soil Transfer parameters (BEST) across soils and scales

Cited by 59 publications

References 95 publications

Assessing Water Infiltration and Soil Water Repellency in Brazilian Atlantic Forest Soils

Assessing Water Infiltration and Soil Water Repellency in Brazilian Atlantic Forest Soils

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

Improved Beerkan run methodology to assess water impact effects on infiltration and hydraulic properties of a loam soil under conventional‐ and no‐tillage

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