Beerkan Estimation Of Soil Transfer Parameters Research Articles

Using Beerkan Procedure to Estimate Hydraulic Soil Properties under Long Term Agroecosystems Experiments

The BEST (Beerkan Estimation of Soil Transfer parameters) method was used to compare the hydraulic properties of the soils in two Long-term Agroecosystem Experiments (LTAEs) located at the FIELDLAB experimental site of the University of Perugia (central Italy). The LTAE “NewSmoca” consists of a biennial maize-durum wheat crop rotation under integrated low-input cropping systems with (i) inversion soil tillage (INT) or (ii) no-tillage (INT+) and (iii) under an organic cropping system with inversion soil tillage (ORG). ORG and INT+ involve the use of autumn-sown cover crops (before the maize cycle). Pure stand durum wheat was grown in INT and INT+, while a faba bean–wheat temporary intercropping was implemented in ORG. The LTAE “Crop Rotation” consists of different crop rotations and residue management, a continuous soft winter wheat and biennial rotations of soft winter wheat with maize or faba bean. Each rotation is combined with two modes of crop residue management: removal or burial. For INT+, despite the high-bulk density (>1.50 g/cm3), we found that conductivity, sorptivity and available water are comparable to those of INT, probably due to a more structured and efficient micropore system. ORG soils show the highest conductivity, sorptivity and available water content values, probably due to the recent spring tillage occurring in the wheat inter-row with the faba bean incorporation into the soil. For LTAE Rotation, the residue burial seems to influence the capacity-based indicators positively. However, the differences in the removal treatment are minor, and this could be due to the inversion soil tillage, which limits the progressive accumulation of organic matter.

Hydraulic characterization of earthworm macropore surfaces using miniaturized infiltration data

Water repellency related to organic matter (OM) of coatings along the earthworm burrows (EB) walls can facilitate preferential flow due to limiting the water exchange with the soil matrix. The objectives of this work were (i) to characterize the hydraulic behavior of EB wall and the surrounding matrix using a miniaturized infiltrometer; (ii) to compare standard infiltration analyses with BEST-WR algorithm; and (iii) to determine the local spatial distribution of water repellency at the EB wall surface in relation to that of the OM composition. Infiltration experiments were carried out on intact sample surfaces, including the EB wall and the surrounding matrix. Soil samples were collected from Bt and C horizons in a characteristic Haplic Luvisol. Hydraulic conductivity (K) at different water pressure heads (h) and water and ethanol sorptivity (Sw and Se, respectively), water repellency index (RI) and water repellency cessation time (WRCT) were determined from infiltration data. The adapted Beerkan Estimation of Soil Transfer parameters (BEST) algorithm for water-repellent soils (BEST-WR) was used for analysing infiltration data. The potential water repellency index (PWRI), relating C-H with CO functional groups in OM, was determined at the same locations using diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy. Lower values of K and Sw in the coatings as compared to the soil matrix were found related to higher PWI values. Water repellency was also reflected in the shape of the cumulative infiltration curves and in the RI-values. The latter were significantly higher for EB as compared to matrix surfaces. The fittings provided by the BEST-WR algorithm characterizing the hydraulic properties of the macropore surfaces were comparable to those obtained with standard method. The tested methods could help to improve the estimation of parameters for macropore-matrix mass exchange in two-domain models.

Seasonal and Soil Use Dependent Variability of Physical and Hydraulic Properties: An Assessment under Minimum Tillage and No-Tillage in a Long-Term Experiment in Southern Italy

Defining the optimal sampling time across the growing season is crucial to standardize sampling protocols for soil physical status monitoring and to achieve comparable results under different experimental conditions and on different sites. In this study, the seasonal variability of soil physical and hydraulic properties under two conservative soil management strategies, minimum tillage and no-tillage, was evaluated in a long-term field experiment. On two sampling dates, autumn 2021 and summer 2022, soil bulk density (BD) and volumetric soil water content at the time of the experiments (θi) were measured in each experimental unit and Beerkan infiltration experiments were performed. The soil water retention curve and the hydraulic conductivity function were then estimated using the Beerkan estimation of soil transfer parameters (BEST) methodology. In this way, the saturated hydraulic conductivity (Ks) and a set of capacitive indicators—plant available water capacity (PAWC), soil macroporosity (PMAC), air capacity (AC) and relative field capacity (RFC)—were obtained. Results underlined the role of soil moisture conditions as a main factor affecting variability in soil physical properties. Different soil moisture under autumn and summer samplings significantly affected BD (1.0093 and 1.1905 g cm−3, respectively, in autumn and summer) and Ks (0.0431 and 0.0492 mm s−1). Relationships observed between BEST-derived variables, such as PMAC (or AC) and RFC, and measured variables, such as BD, showed consistent results, with increases in PMAC to BD decreases. However, a comparison of capacity-based indicators obtained by BEST with those obtained from measured soil water retention curves, in a previous year but under comparable soil conditions, highlighted some discrepancies. This finding drives the focus towards the need to use more robust datasets deriving from experimental measurements or from coupling information obtained from measured and estimated data. Finally, this study provided further evidence that, in the long-term field experiment investigated, the two soil management systems allowed keeping the values of key soil physical quality indicators, such as bulk density and saturated hydraulic conductivity, within the optimal or near- optimal reference ranges.

Investigating the Spatial Structure of Soil Hydraulic Properties in a Long-Term Field Experiment Using the BEST Methodology

Understanding the spatial structure of soil properties at field scale and introducing this information into appropriate data analysis methods can help in detecting the effects of different soil management practices and in supporting precision agriculture applications. The objectives of this study were: (i) assessing the spatial structure of soil physical and hydraulic properties in a long-term field experiment; (ii) defining a set of spatial indicators for gaining an integrated view of the studied system. In seventy-two georeferenced locations, soil bulk density (BD), initial volumetric soil water content (θi) and cumulative infiltration curve as function of the time (I(t)) were measured. The soil water retention curve (θ(h)) and the hydraulic conductivity function (K(h)) were then estimated using the Beerkan Estimation of Soil Transfer parameters (BEST) methodology. The volumetric soil water contents at soil matrix (h = −10 cm), field capacity (h = −100 cm) and wilting point (h = −15,300 cm) were considered. In addition, a set of capacitive indicators—plant available water capacity (PAWCe), soil macroporosity (PMACe), air capacity (ACe) and relative field capacity (RFCe)—were computed. The data were first analyzed for overall spatial dependence and then processed through variography for structural analysis and subsequent spatial interpolation. Cross-correlation analysis allowed for assessing the spatial relationships between selected physical and hydraulic properties. On average, optimal soil physical quality conditions were recorded; only PMACe values were indicative of non-optimal conditions, whereas mean values of all the other indicators (BD, Ks, PAWCe, ACe, RFCe) fell within optimal ranges. The exponential model was found to be the best function to describe the spatial variability of all the considered variables, except ACe. A good spatial dependence was found for most of the investigated variables and only BD, ACe and Ks showed a moderate autocorrelation. Ks was confirmed to be characterized by a relatively high spatial variability, and thus, to require a more intensive spatial sampling. An inverse spatial cross-correlation was observed between BD and Ks up to a distance of 10 m; significant cross-correlations were also recorded between Ks and PMACe and ACe. This result seems to suggest the possibility to use these soil physical quality indicators as covariates in predictive multivariate approaches.

Run duration effects on the hydrodynamic properties of a loam soil estimated by steady-state infiltration methods

Steady-state methods for the analysis of single-ring infiltration data are commonly applied. However, the duration of an infiltrometer experiment is often established quite subjectively based on the assumption that in general infiltration stabilizes rather quickly in the field. For a loam soil, the effect of the duration of a beerkan run on sorptivity, S, and saturated hydraulic conductivity, Ks, was tested by using the BEST (Beerkan Estimation of Soil Transfer parameters)-steady method and SSBI (Steady version of the Simplified method based on a Beerkan Infiltration run) method for data analysis. The standard experiment, based on a total of 15 water volumes each establishing an initial ponding depth of ~0.01 m (on average, 0.32 hours of infiltration), yielded approximately two and >100 times higher S and Ks values, respectively, than a long run (117 water volumes or 8.1 hours). Stabilization was faster for S (approximately in 3 hours) than Ks (6 hours). Similar Ks values were obtained with BEST-steady (192-261 mm/h) and the SSBI method (177-184 mm/h) for the standard run but not for the long-duration run (1.5-2.1 and 20-21 mm/h, respectively). This discrepancy was due to the fact that more information on the infiltration process is used by BEST-steady (total duration, total infiltrated water, steady-state infiltration rate) than the SSBI method (only the latter variable). In conclusion, Ks estimates are very sensitive to the used water volume for the run. The run duration should not only depend on the attainment of near steadiness, but also on the possibility of capturing the soil hydraulic behaviour in a representative situation for the hydrological process under study. In the near future, the possibility of using the hydrodynamic soil properties determined with the tested methodology to simulate rainfall effects on soil structure should be investigated.

Estimating the Soil Hydraulic Functions of Some Olive Orchards: Soil Management Implications for Water Saving in Soils of Salento Peninsula (Southern Italy)

Saving water resources in agriculture is a topic of current research in Mediterranean environments, and rational soil management can allow such purposes. The Beerkan Estimation of Soil Transfer parameters (BEST) procedure was applied in five olive orchards of Salento peninsula (southern Italy) to estimate the soil physical and hydraulic properties under alternative soil management (i.e., no-tillage (NT) and minimum tillage (MT)), and to quantify the impact of soil management on soil water conservation. Results highlighted the soundness of BEST predictions since they provided consistent results in terms of soil functions or capacitive-based soil indicators when (i) the entire data set was grouped by homogeneous classes of texture, bulk density, and capillarity of the soil, (ii) the predictions were compared with the corresponding water retention measures independently obtained in lab, and (iii) some correlations of literature were checked. BEST was applied to establish a comparison at Neviano (NE) and Sternatia (ST) sites. The two neighboring NT soils compared at NE showed substantial discrepancies in soil texture (i.e., sandy loam (NE-SL) or clay (NE-C)). This marked difference in soil texture could determine a worsening of the relative field capacity at the NE-SL site (relative field capacity, RFC < 0.6), as compared to NE-C where RFC was optimal. The current soil management determined a similar effect (RFC < 0.6) at Sternatia (ST-MT vs. ST-NT), but the worsening in soil properties, due to soil tillage, must be considered substantially transient, as progressive improvement is expected with the restoration of the soil structure. The results of this work suggest that strategic MT can be a viable solution to manage the soil of Salento olive orchards.

A general Beerkan Estimation of Soil Transfer parameters method predicting hydraulic parameters of any unimodal water retention and hydraulic conductivity curves: Application to the Kosugi soil hydraulic model without using particle size distribution data

Soil hydraulic characterization is crucial to describe the retention and transport of water in soil, but current methodologies limit its spatial applicability. This paper presents a cost-effective general Beerkan Estimation of Soil Transfer parameters (BEST) methodology using single ring infiltration experiments to derive soil hydraulic parameters for any unimodal water retention and hydraulic conductivity functions. The proposed method relies on the BEST approach. The novelty lies in the use of Kosugi hydraulic parameters without need for textural information. In addition, the method uses a quasi-exact formulation that is valid for all times, which avoids the use of approximate expansions and related inaccuracy. The new BEST methods were tested against numerically generated data for several contrasting synthetic soils, and the results show that these methods provide consistent hydraulic functions close to the target functions. The new BEST method is accurate and can use any water retention and hydraulic conductivity functions.

Modelling Soil Water Dynamics from Soil Hydraulic Parameters Estimated by an Alternative Method in a Tropical Experimental Basin

Knowledge about soil moisture dynamics and their relation with rainfall, evapotranspiration, and soil physical properties is fundamental for understanding the hydrological processes in a region. Given the difficulties of measurement and the scarcity of surface soil moisture data in some places such as Northeast Brazil, modelling has become a robust tool to overcome such limitations. This study investigated the dynamics of soil water content in two plots in the Gameleira Experimental River Basin, Northeast Brazil. For this, Time Domain Reflectometry (TDR) probes and Hydrus-1D for modelling one-dimensional flow were used in two stages: with hydraulic parameters estimated with the Beerkan Estimation of Soil Transfer Parameters (BEST) method and optimized by inverse modelling. The results showed that the soil water content in the plots is strongly influenced by rainfall, with the greatest variability in the dry–wet–dry transition periods. The modelling results were considered satisfactory with the data estimated by the BEST method (Root Mean Square Errors, RMSE = 0.023 and 0.022 and coefficients of determination, R2 = 0.72 and 0.81) and after the optimization (RMSE = 0.012 and 0.020 and R2 = 0.83 and 0.72). The performance analysis of the simulations provided strong indications of the efficiency of parameters estimated by BEST to predict the soil moisture variability in the studied river basin without the need for calibration or complex numerical approaches.

Hydrodynamic Characterization of Sustainable Urban Drainage Systems (SuDS) by Using Beerkan Infiltration Experiments

Stormwater management techniques in urban areas, such as sustainable urban drainage systems (SuDS), are designed to manage rainwater through an infiltration process. In order to determine the infiltration capacities of different SuDS and to identify their unsaturated hydraulic properties, measurements with the Beerkan method (i.e., single ring infiltration tests) were carried out on four types of common infiltration structures in an urban zone of Lyon (France): A drainage ditch with an underlying storage structure, a parking lot with a waterproof pavement that transfers runoff water toward the ditch, a vegetated hollow core slab, and an embankment of a grass-covered garden that was used as a reference for rainwater infiltration capacity. The novelty of this study lies in the use of three Beerkan estimation of soil transfer parameters (BEST) algorithms: BEST-slope, BEST-intercept, and BEST-steady to analyze infiltration data. The BEST methods are based on the analysis of the infiltration rate from transient to steady-state flow. They allow the determination of both shape and scale parameters of the soil water retention curve h(θ) and the hydraulic conductivity curve K(θ). The three BEST methods are efficient and simple for hydraulic characterization of SuDS. The study of the hydrodynamic behavior of the four structures revealed the infiltration inefficiency of some of them. Their average infiltration rates are considerably lower than the reference infiltration rain garden. The results confirmed the impact of some physical conditions, such as pore structure modification due to invasive vegetation colonization and the presence of soil organic matter, on soil hydrodynamic behavior degradation.

Using Beerkan experiments to estimate hydraulic conductivity of a crusted loamy soil in a Mediterranean vineyard

Abstract In bare soils of semi-arid areas, surface crusting is a rather common phenomenon due to the impact of raindrops. Water infiltration measurements under ponding conditions are becoming largely applied techniques for an approximate characterization of crusted soils. In this study, the impact of crusting on soil hydraulic conductivity was assessed in a Mediterranean vineyard (western Sicily, Italy) under conventional tillage. The BEST (Beerkan Estimation of Soil Transfer parameters) algorithm was applied to the infiltration data to obtain the hydraulic conductivity of crusted and uncrusted soils. Soil hydraulic conductivity was found to vary during the year and also spatially (i.e., rows vs. inter-rows) due to crusting, tillage and vegetation cover. A 55 mm rainfall event resulted in a decrease of the saturated soil hydraulic conductivity, Ks , by a factor of 1.6 in the inter-row areas, due to the formation of a crusted layer at the surface. The same rainfall event did not determine a Ks reduction in the row areas (i.e., Ks decreased by a non-significant factor of 1.05) because the vegetation cover intercepted the raindrops and therefore prevented alteration of the soil surface. The developed ring insertion methodology on crusted soil, implying pre-moistening through the periphery of the sampled surface, together with the very small insertion depth of the ring (0.01 m), prevented visible fractures. Consequently, Beerkan tests carried out along and between the vine-rows and data analysis by the BEST algorithm allowed to assess crusting-dependent reductions in hydraulic conductivity with extemporaneous measurements alone. The reliability of the tested technique was also confirmed by the results of the numerical simulation of the infiltration process in a crusted soil. Testing the Beerkan infiltration run in other crusted soils and establishing comparisons with other experimental methodologies appear advisable to increase confidence on the reliability of the method that seems suitable for simple characterization of crusted soils.

Beerkan multi-runs for characterizing water infiltration and spatial variability of soil hydraulic properties across scales

ABSTRACTA method is presented for characterizing the spatial variability of water infiltration and soil hydraulic properties at the transect and field scales. The method involves monitoring a set of 10 Beerkan runs distributed over a 1-m length of soil, and running BEST (Beerkan estimation of soil transfer parameters) methods to derive hydraulic parameters. The Beerkan multi-runs (BMR) method provides a significant amount of data at the transect scale, allowing the determination of correlations between water infiltration variables and hydraulic parameters, and the detection of specific runs affected by preferential flow or water repellence. The realization of several BMRs at several transects on the same site allows comparison of the variation between locations (spatial variability at the field scale) and at the transect scale (spatial variability at the metre scale), using analysis of variance. From the results, we determined the spatial variability of water infiltration and hydraulic parameters as well as its characteristic scale (transect versus field).

An assessment of the BEST procedure to estimate the soil water retention curve: A comparison with the evaporation method

The Beerkan Estimation of Soil Transfer parameters (BEST) procedure is an attractive, easy, robust, and inexpensive way for a complete soil hydraulic characterization but testing the ability of this procedure to estimate the water retention curve is necessary as relatively little information is available in the literature. In this investigation the soil water retention curve was predicted for four differently textured soils by applying three existing BEST algorithms (i.e., slope, intercept and steady) and the results compared with those measured by the standard Wind evaporation method. A sensitivity analysis of the infiltration constants, β and γ, was also carried out and their impact on the estimated retention curve scale parameter, hg, was evaluated. BEST-slope underestimated the soil water retention for three of the four soils under consideration, providing relatively low root mean squared differences between estimated and measured data (0.0261 cm3cm−3 ≤ RMSD ≤0.0483 cm3cm−3). For one site (PAL, sandy-loam soil), BEST-steady provided the lowest RMSD value (0.0893 cm3cm−3) among the considered algorithms, but the water retention was systematically overestimated as a consequence of a relatively higher difference between field and lab saturated soil water contents. A specific calibration performed for β and γ highlighted that: i) the water retention estimations by BEST-slope were more sensitive to β than those obtained by BEST-intercept and BEST-steady; ii) with the exception of PAL soil, the lowest RMSD values were obtained with BEST-slope. Estimation of the soil water retention curve was not significantly worse when reference values of infiltration constants (β = 0.6 and γ = 0.75) were used as detected by negligible differences in RMSDs as compared to calibrated β and γ. Therefore, it was concluded that the BEST-slope algorithm yielded predictions of water retention closer to the laboratory estimated ones than the alternative BEST algorithms (i.e. BEST-intercept and -steady). For these algorithms, the less accurate estimates of the water retention data were attributed to hg overestimations due to the independence of the retention curve scale parameter from γ.

Comparing Different Methods to Determine Soil Physical Quality in a Mediterranean Forest and Pasture Land

Core Ideas Optimal values of soil physical quality indicators are still approximate. Sampling soils with minimal anthropic pressures will improve soil physical quality assessment. Capacity‐based indicators yielded plausible results in a near natural area in Sicily. Field methods appears a possible alternative to laboratory techniques to assess soil physical quality. Simultaneous characterization of forest and soil parameters is recommended. Soil physical quality (SPQ) can be assessed by different experimental methodologies and criteria and the optimal/critical values or ranges for SPQ indicators are still approximate. Sampling soils with minimal anthropic pressures should allow improvements in SPQ assessment. Different experimental methodologies and criteria were applied to sample a Mediterranean oak forest (Quercus ilex L.) and pasture land, in Sicily, with a varying degree of anthropic disturbance. Soil water retention was determined in the laboratory and the field, using the BEST (Beerkan Estimation of Soil Transfer parameters) procedure of soil hydraulic characterization. Capacity‐based indicators, the S index, and location and shape parameters of the pore volume distribution function were calculated for assessing SPQ. With the laboratory data, only the criterion using the capacity‐based indicators suggested that SPQ increased as external pressures decreased. Therefore, this criterion appeared to be more reliable than the other tested criteria in the sampled environment. The field method was more prone to suggest good conditions and less able to signal differences between plots as compared with the laboratory method. A forest soil with a good SPQ has an ability to store and provide water to plant roots similar to, but it is more aerated than, a good agricultural soil. Developing BEST for SPQ assessment is advisable since parameters descriptive of the soil water transport properties can be collected with a single experiment. Simultaneous characterization of dendrometric and soil parameters at other sites is recommended to explore the relationships between SPQ indicators and characteristics of the forest cover.

Use of BEST Procedure to Assess Soil Physical Quality in the Baratz Lake Catchment (Sardinia, Italy)

Core Ideas Soil physical quality (SPQ) of four areas with Mediterranean vegetation was evaluated. BEST procedure was tested to evaluate SPQ and detect signs of soil degradation. Independently measured indicators of SPQ were compared with those derived by BEST. BEST reproduced plausible SPQ evaluation. BEST is a promising technique to simply detect land degradation in natural environments. Conversion of Mediterranean maquis and/or natural forest into agro‐pastoral lands is a cause of soil degradation in many Mediterranean areas. Indicators of soil physical quality (SPQ) quantitatively linked to soil hydraulic properties are a valuable tool to assess the effect of land use changes. In this investigation, the Beerkan Estimation of Soil Transfer parameters (BEST) procedure for soil hydraulic characterization was used to estimate SPQ indicators. Four areas of the Baratz Lake watershed, Sardinia, Italy, characterized by both typical natural vegetation (holm oak [Quercus ilex L.] forest and high maquis) and degraded vegetation (grassland established after fire or clearing of the maquis) were considered. The SPQ was assessed by either independently measured soil physical attributes, like soil bulk density, organic C content, saturated hydraulic conductivity, and sorptivity, and “capacitive” and “dynamic” indicators calculated from the water retention curve estimated by the BEST procedure. Measured and estimated SPQ indicators unanimously showed that clearing of the maquis caused a severe deterioration of SPQ associated with soil compaction, organic matter loss, and decrease of macropore volume and soil aeration capacity as well as reduced water circulation. A different and unexpected result was obtained for the fire‐affected area, where the SPQ was comparable to that of the neighboring oak forest area. We deduced that vegetation restoration after fire passage contributed to maintain a high organic matter content and to mitigate rain compaction effects. We concluded that SPQ indicators derived by applying the BEST procedure are suitable to detect land degradation in the natural environments studied.

Testing infiltration run effects on the estimated water transmission properties of a sandy-loam soil

Testing factors influencing determination of soil water transmission properties by an infiltrometer method helps better interpretation of the collected data and allows the development of appropriate sampling strategies for the intended use of the data. These factors include the soil water content at the start of the experiment, the height from which water is poured onto the soil surface, and the duration of the infiltration run. A sandy-loam soil was sampled with the BEST (Beerkan Estimation of Soil Transfer parameters) procedure of soil hydraulic characterization and two heights of pouring of water (0.03 and 1.5m) under three different initial soil water content, θi (0.12≤θi≤0.20m3m−3), conditions. According to the BEST guidelines, relatively short infiltration runs (average run duration ≤1.5h, depending on both the date and the height from which water was poured) were carried out. However, three long infiltration runs (10h) were also carried out when θi was of 0.075m3m−3. The saturated soil hydraulic conductivity, Ks, and the soil water sorptivity, S, were estimated for each infiltration run with the BEST-steady algorithm. The mean values of Ks varied with the height of pouring of water and θi from 13 to 496mmh−1, and a low height from which water was poured yielded 13 to 27 times higher Ks means than a high height, depending on θi. An inverse relationship between Ks and θi was clearer with the low height of pouring of water than the high one. The mean saturated hydraulic conductivity obtained with the long runs (15mmh−1) was close to the means of Ks obtained with the high and shorter runs (13–19mmh−1, depending on θi). The means of S varied from 35 to 126mmh−0.5, with the low runs yielding 2.3 to 2.8 times higher means than the high runs. The high sorptivity obtained with the long runs (160mmh−0.5) was in line with the low initial soil water content. In conclusion, the water application procedure and the duration of the infiltration run can have a noticeable effect on the estimated soil water transmission properties. Long duration runs or runs carried out with a high height of pouring of water appear more appropriate than short duration runs with a low height of pouring of water to obtain data usable to explain surface runoff generation phenomena during intense rainfall events, especially when the soil is relatively dry at the time of sampling. In the future, the effects of both the height from which water is poured and the run duration on the water transmission properties measured with BEST should be tested for different initial soil water conditions in other soils. The usability of the height from which water is poured onto the soil surface as a parameter to mimic high intensity rain should also be investigated specifically.

Determining hydraulic properties of a loam soil by alternative infiltrometer techniques

Testing infiltrometer techniques to determine soil hydraulic properties is necessary for specific soils. For a loam soil, the water retention and hydraulic conductivity predicted by the BEST (Beerkan Estimation of Soil Transfer parameters) procedure of soil hydraulic characterization was compared with data collected by more standard laboratory and field techniques. Six infiltrometer techniques were also compared in terms of saturated soil hydraulic conductivity, Ks. BEST yielded water retention values statistically similar to those obtained in the laboratory and Ks values practically coinciding with those determined in the field with the pressure infiltrometer (PI). The unsaturated soil hydraulic conductivity measured with the tension infiltrometer (TI) was reproduced satisfactorily by BEST only close to saturation. BEST, the PI, one-potential experiments with both the TI and the mini disk infiltrometer (MDI), the simplified falling head (SFH) technique and the bottomless bucket (BB) method yielded statistically similar estimates of Ks, differing at the most by a factor of three. Smaller values were obtained with longer and more soil-disturbing infiltration runs. Any of the tested infiltration techniques appears usable to obtain the order of magnitude of Ks at the field site, but the BEST, BB and PI data appear more appropriate to characterize the soil at some stage during a rainfall event. Additional investigations on both similar and different soils would allow development of more general procedures to apply infiltrometer techniques for soil hydraulic characterization. Copyright © 2015 John Wiley & Sons, Ltd.

Estimation of soil hydraulic properties and their uncertainty through the Beerkan infiltration experiment

AbstractThe Beerkan method based on in situ single‐ring water infiltration experiments along with the relevant specific Beerkan estimation of soil transfer parameters (BEST) algorithm is attractive for simple soil hydraulic characterization. However, the BEST algorithm may lead to erroneous or null values for the saturated hydraulic conductivity and sorptivity especially when there are only few infiltration data points under the transient flow state, either for sandy soil or soils in wet conditions. This study developed an alternative algorithm for analysis of the Beerkan infiltration experiment referred to as BEST‐generalized likelihood uncertainty estimation (GLUE). The proposed method estimates the scale parameters of van Genuchten water retention and Brooks–Corey hydraulic conductivity functions through the GLUE methodology. The GLUE method is a Bayesian Monte Carlo parameter estimation technique that makes use of a likelihood function to measure the goodness‐of‐fit between modelled and observed data. The results showed that using a combination of three different likelihood measurements based on observed transient flow, steady‐state flow and experimental steady‐state infiltration rate made the BEST‐GLUE procedure capable of performing an efficient inverse analysis of Beerkan infiltration experiments. Therefore, it is more applicable for a wider range of soils with contrasting texture, structure, and initial and saturated water content. Copyright © 2015 John Wiley & Sons, Ltd.

An assessment of the Beerkan method for determining the hydraulic properties of a sandy loam soil

Establishing the ability of the Beerkan Estimation of Soil Transfer parameters (BEST) procedure to reproduce soil properties is necessary for specific soil types. In this investigation, the BEST predictions for a sandy loam soil were compared with water retention data obtained by a standard laboratory method and with the saturated soil hydraulic conductivity, Ks, obtained by both the Wu et al. (1999) method, applied to the BEST infiltration data, and the Simplified Falling Head (SFH) technique. When the original BEST-slope algorithm with the infiltration constants fixed at β=1.9 and γ=0.79 was applied, the agreement between the predicted and the measured retention data was satisfactory in terms of similarity of the means and correlation and coincidence between the regression and identity lines. The prediction of Ks at a sampling point differed by not more than a factor of two from the Ks value obtained by the Wu et al. (1999) method. The SFH technique yielded Ks values approximately five times higher than those of BEST, probably because soil disturbance during water application, swelling and air entrapment phenomena had a lower impact on the measured infiltration data with the former technique. In conclusion, BEST is a promising approach for easily characterizing a soil, but its method of application should be adapted to the particular situation under consideration. Additional investigations carried out on different soils would allow development of more general procedures for applying BEST.

Comparing Alternative Algorithms to Analyze the Beerkan Infiltration Experiment

The increasing interest in the Beerkan Estimation of Soil Transfer parameters (BEST) procedure of soil hydraulic characterization justifies an assessment of alternative methods to analyze infiltration data. The BEST-slope and BEST-intercept algorithms allow estimation of soil sorptivity, S, and saturated soil hydraulic conductivity, Ks, using the transient part of the experimental infiltration curve and the slope and the intercept, respectively, of the linear portion of this curve. With reference to 401 runs performed in Sicily (Italy) and Burundi, this investigation showed that these two algorithms differed by the number of successful runs (positive S and Ks values), with BEST-intercept yielding a higher success percentage (93%) than BEST-slope (66%) at the expense of a poorer performance in terms of data representation by the infiltration model. On average, the two algorithms yielded S values differing by 3.3% and Ks values differing by a factor of 3.1. High discrepancies between two alternative Ks estimates, that is, by even more than two orders of magnitude, were occasionally detected at individual sampling points. The BEST-steady algorithm developed in this investigation, using steady-state cumulative infiltration data, was closer to BEST-intercept (individual S and Ks values differing at the most by 17% and a factor of 1.5, respectively) than to BEST-slope (differences by 22% for S and a factor of 186 for Ks). Data should initially be analyzed with BEST-slope and an attempt to apply BEST-intercept should be made only if the former algorithm fails in giving physically plausible S and Ks values. BEST-steady is an alternative algorithm to be considered in practice for a variety of reasons, including a success percentage of 100%, a simplified calculation of S and Ks, and the possibility to adjust the run duration directly in the field.

A test of the Beerkan Estimation of Soil Transfer parameters (BEST) procedure

The Beerkan Estimation of Soil Transfer parameters (BEST) procedure is attractive for a simple soil hydraulic characterization but testing the ability of this procedure to estimate soil properties is necessary. The BEST predictions were compared with soil water retention and hydraulic conductivity data measured in the laboratory and the field, respectively, at ten Sicilian field sites. Provided that BEST yielded physically possible scale parameters of the soil characteristic curves in most of the four replicated infiltration runs at a site, the measured water retention was satisfactorily predicted (i.e., not statistically significant differences between measurements and predictions, significant correlation between the data, regression line not significantly different from the identity one) when i) the infiltration run was relatively short (11 applied volumes of water); ii) the n shape parameter of the water retention curve was estimated on the basis of the measured sand and clay content of the soil; and iii) the saturated soil water content, θs, was set equal to 93% of the porosity. Possible field saturated soil hydraulic conductivity values were also obtained, although some trace of soil disturbance by the infiltration run was detected. The predicted unsaturated soil hydraulic conductivity was higher than the measured one, probably because the unimodal hydraulic conductivity function used in BEST does not reproduce the changes in the pore system of a real soil in the pressure head range close to saturation. It was concluded that BEST is promising to simply yield a reasonably reliable soil hydraulic characterization. An improved description of the unsaturated hydraulic conductivity function is desirable.