Uncertainties in DRAINMOD predictions of subsurface drain flow for an Indiana silt loam using the GLUE methodology

Good modelling practice requires the incorporation of uncertainty analysis into hydrologic/water quality models. The generalized likelihood uncertainty estimation procedure was used to evaluate the uncertainty in DRAINMOD predictions of daily, monthly, and yearly subsurface drain flow. A variance‐based sensitivity analysis technique, the extended Fourier amplitude sensitivity test, was used to identify the main sources of prediction uncertainty. The analysis was conducted for the experimental drainage field at the Southeast Purdue Agricultural Center in Indiana. Six years of data were used and the uncertainties in eight model parameters were considered to analyse how uncertainties in input parameters propagate to model outputs. The width of 90% confidence interval bands of drain flow ranged from 0 to 0·6 cm day^?1 for daily predictions, from 0 to 3·1 cm month^?1 for the monthly predictions, and from 7·6 to 12·4 cm year^?1 for yearly predictions. Annual drain flow predicted by DRAINMOD fell well within the 90% confidence bounds. Model results were most sensitive to the vertical saturated hydraulic conductivity of the restrictive layer and the lateral hydraulic conductivity of the deepest soil layer, followed by the lateral hydraulic conductivity of the top soil layer and surface micro‐storage. Parameter interactions also contributed to the prediction uncertainty. Copyright © 2006 John Wiley & Sons, Ltd.     

Influence of antecedent soil moisture on hydraulic conductivity in a series of texture‐contrast soils

Antecedent soil moisture significantly influenced the hydraulic conductivity of the A1, A2e and B21 horizons in a series of strong texture‐contrast soils. Tension infiltration at six supply potentials demonstrated that in the A1 horizon, hydraulic conductivity was significantly lower in the ‘wet’ treatment than in the ‘dry’ treatment. However in the A2e horizon, micropore and mesopore hydraulic conductivity was lower in the ‘dry’ treatment than the ‘wet’ treatment, which was attributed to the precipitation of soluble amorphous silica. In the B21 horizon, desiccation of vertic clays resulted in the formation of shrinkage cracks which significantly increased near‐saturated hydraulic conductivity and prevented the development of subsurface lateral flow in the ‘dry’ treatment. In the ‘wet’ treatment, the difference between the hydraulic conductivity of the A1 and B21 horizons was reduced; however, lateral flow still occurred in the A1 horizon due to difficulty displacing existing soil water further down the soil profile. Results demonstrate the need to account for temporal variation in soil porosity and hydraulic conductivity in soil‐water model conceptualisation and parameterisation. Copyright © 2011 John Wiley & Sons, Ltd.     

Effects of Vegetation Restoration on Soil Physical Properties in the Wind–Water Erosion Region of the Northern Loess Plateau of China

In the northern Loess Plateau that has been severely affected by wind–water erosion, shifts from arable land to forest or grasslands have been promoted since 1998, using both native and introduced vegetation. However, there is little knowledge of the ecological consequences and effectiveness of the vegetation restoration in the region. Therefore, relationships between watershed‐scale soil physical properties and plant recovery processes were analyzed. The results show that soil physical properties such as bulk density, hydraulic conductivity, mean weight diameter, and the stability of >1 mm macro‐aggregates have been significantly ameliorated in the 0–20 cm soil layer under secondary natural grasslands. In contrast, re‐vegetation with introduced species such as Caragana korshinskii or Medicago sativa had adversely affected the soil physical properties, probably due to the deterioration of soil water conditions and lower organic matter inputs resulting from severe erosion. Reductions in bulk density and increases in saturated hydraulic conductivity could be used as indicators of soil structure amelioration since they are closely related to most other measured properties. Practical considerations for future re‐vegetation projects are suggested, particularly that native species with lower water consumption rates than the introduced species should be used to avoid further soil degradation.     

Sensitivity of soil parameters in unsaturated zone modelling and the relation between effective,laboratory and in situ estimates

Simulation of soil moisture content requires effective soil hydraulic parameters that are valid at the modelling scale. This study investigates how these parameters can be estimated by inverse modelling using soil moisture measurements at 25 locations at three different depths (at the surface, at 30 and 60 cm depth) on an 80 by 20 m hillslope. The study presents two global sensitivity analyses to investigate the sensitivity in simulated soil moisture content of the different hydraulic parameters used in a one‐dimensional unsaturated zone model based on Richards' equation. For estimation of the effective parameters the shuffled complex evolution algorithm is applied. These estimated parameters are compared to their measured laboratory and in situ equivalents. Soil hydraulic functions were estimated in the laboratory on 100 cm³ undisturbed soil cores collected at 115 locations situated in two horizons in three profile pits along the hillslope. Furthermore, in situ field saturated hydraulic conductivity was estimated at 120 locations using single‐ring pressure infiltrometer measurements. The sensitivity analysis of 13 soil physical parameters (saturated hydraulic conductivity (K_s), saturated moisture content (θ_s), residual moisture content (θ_r), inverse of the air‐entry value (α), van Genuchten shape parameter (n), Averjanov shape parameter (N) for both horizons, and depth (d) from surface to B horizon) in a two‐layer single column model showed that the parameter N is the least sensitive parameter. K_s of both horizons, θ_s of the A horizon and d were found to be the most sensitive parameters. Distributions over all locations of the effective parameters and the distributions of the estimated soil physical parameters from the undisturbed soil samples and the single‐ring pressure infiltrometer estimates were found significantly different at a 5% level for all parameters except for α of the A horizon and K_s and θ_s of the B horizon. Different reasons are discussed to explain these large differences. Copyright © 2004 John Wiley & Sons, Ltd.     

Sensitivity analysis of EUROSEM using Monte Carlo simulation I: hydrological,soil and vegetation parameters

Knowledge about model uncertainty is essential for erosion modelling and provides important information when it comes to parameterizing models. In this paper a sensitivity analysis of the European soil erosion model (EUROSEM) is carried out using Monte Carlo simulation, suitable for complex non‐linear models, using time‐dependent driving variables. The analysis revealed some important characteristics of the model. The variability of the static output parameters was generally high, with the hydrologic parameters being the most important ones, especially saturated hydraulic conductivity and net capillary drive followed by the percentage basal area for the hydrological and vegetation parameters and detachability and cohesion for the soil erosion parameters. Overall, sensitivity to vegetation parameters was insignificant. The coefficient of variation for the sedigraph was higher than for the hydrograph, especially from the beginning of the rainstorm and up to the peak, and may explain difficulties encountered when trying to match simulated hydrographs and sedigraphs with observed ones. The findings from this Monte Carlo simulation calls for improved within‐storm modelling of erosion processes in EUROSEM. Information about model uncertainty will be incorporated in a new EUROSEM user interface. Copyright © 2000 John Wiley & Sons, Ltd.     

Effects of experimental uncertainty on the calculation of hillslope flow paths

Measurement uncertainty is a key hindrance to the quantification of water fluxes at all scales of investigation. Predictions of soil‐water flux rely on accurate or representative measurements of hydraulic gradients and field‐state hydraulic conductivity. We quantified the potential magnitude of errors associated with the parameters and variables used directly and indirectly within the Darcy – Buckingham soil‐water‐flux equation. These potential errors were applied to a field hydrometric data set collected from a forested hillslope in central Singapore, and their effect on flow pathway predictions was assessed. Potential errors in the hydraulic gradient calculations were small, approximately one order of magnitude less than the absolute magnitude of the hydraulic gradients. However, errors associated with field‐state hydraulic conductivity derivation were very large. Borehole (Guelph permeameter) and core‐based (Talsma ring permeameter) techniques were used to measure field‐saturated hydraulic conductivity. Measurements using these two approaches differed by up to 3\9 orders of magnitude, with the difference becoming increasingly marked within the B horizon. The sensitivity of the shape of the predicted unsaturated hydraulic conductivity curve to ±5% moisture content error on the moisture release curve was also assessed. Applied moisture release curve error resulted in hydraulic conductivity predictions of less than ±0\2 orders of magnitude deviation from the apparent conductivity. The flow pathways derived from the borehole saturated hydraulic conductivity approach suggested a dominant near‐surface flow pathway, whereas pathways calculated from the core‐based measurements indicated vertical percolation to depth. Direct tracer evidence supported the latter flow pathway, although tracer velocities were approximately two orders of magnitude smaller than the Darcy predictions. We conclude that saturated hydraulic conductivity is the critical hillslope hydrological parameter, and there is an urgent need to address the issues regarding its measurement further. Copyright © 2000 John Wiley & Sons, Ltd.     

Influence of basin characteristics on baseflow and stormflow chemistry in the Great Smoky Mountains National Park,USA

Relationships between stream chemistry and elevation, area, Anakeesta geology, soil properties, and dominant vegetation were evaluated to identify the influence of basin characteristics on baseflow and stormflow chemistry in eight streams of the Great Smoky Mountains National Park. Statistical analyses were employed to determine differences between baseflow and stormflow chemistry, and relate basin‐scale factors governing local chemical processes to stream chemistry. Following precipitation events, stream pH was reduced and aluminium concentrations increased, while the response of acid neutralizing capacity (ANC), nitrate, sulfate, and base cations varied. Several basin characteristics were highly correlated with each other, demonstrating the interrelatedness of topographical, geological, soil, and vegetative parameters. These interrelated basin factors uniquely influenced acidification response in these streams. Streams in higher‐elevation basins (>975 m) had significantly lower pH, ANC, sodium, and silicon and higher nitrate concentrations (p < 0.05). Streams in smaller basins (<10 km²) had significantly lower nitrate, sodium, magnesium, silicon, and base cation concentrations. In stormflow, streams in basins with Anakeesta geology (>10%) had significantly lower pH and sodium concentrations, and higher aluminium concentrations. Chemical and physical soil characteristics and dominant overstory vegetation in basins were more strongly correlated with baseflow and stormflow chemical constituents than topographical and geological basin factors. Saturated hydraulic conductivity, of all the soil parameters, was most related to concentrations of stormflow constituents. Basins with higher average hydraulic conductivities were associated with lower stream pH, ANC, and base cation concentrations, and higher nitrate and sulfate concentrations. These results emphasize the importance of soil and geological properties influencing stream chemistry and promote the prioritization of management strategies for aquatic resources. Copyright © 2012 John Wiley & Sons, Ltd.     

Studies on changes in extreme flood peaks resulting from land-use changes need to consider roughness variations

ABSTRACT

The impacts of changes in forest coverage on extreme floods have drawn much attention globally. This study quantifies the sensitivity of flood peaks to forest coverage and roughness changes. With this objective, a framework is first introduced that includes a variance-based sensitivity analysis approach and a water and energy budget-based distributed hydrological model with a vegetation module. The influence of forest coverage changes is simulated by altering land-use types that are based on physical parameters. A variance decomposition approach is used to quantify the contribution of influential factors, i.e. event size, forest coverage and roughness changes, to extreme flood peak variations. The results in a medium-sized river basin show forest coverage changes have little influence: variations in canopy interception, ground surface water retention, soil moisture and groundwater table resulting from changing forest coverage did not alter flood peaks considerably. In contrast, it is found that flood peaks are more sensitive to roughness variations.     

Evaluation of the hydrology of the IBIS land surface model in a semi‐arid catchment

This paper evaluates the Integrated BIosphere Simulator (IBIS) land surface model using daily soil moisture data over a 3‐year period (2005–2007) at a semi‐arid site in southeastern Australia, the Stanley catchment, using the Monte Carlo generalized likelihood uncertainty estimation (GLUE) approach. The model was satisfactorily calibrated for both the surface 30 cm and full profile 90 cm. However, full‐profile calibration was not as good as that for the surface, which results from some deficiencies in the evapotranspiration component in IBIS. Relatively small differences in simulated soil moisture were associated with large discrepancies in the predictions of surface runoff, drainage and evapotranspiration. We conclude that while land surface schemes may be effective at simulating heat fluxes, they may be ineffective for prediction of hydrology unless the soil moisture is accurately estimated. Sensitivity analyses indicated that the soil moisture simulations were most sensitive to soil parameters, and the wilting point was the most identifiable parameter. Significant interactions existed between three soils parameters: porosity, saturated hydraulic conductivity and Campbell ‘b’ exponent, so they could not be identified independent of each other. There were no significant differences in parameter sensitivity and interaction for different hydroclimatic years. Even though the data record contained a very dry year and another year with a very large rainfall event, this indicated that the soil model could be calibrated without the data needing to explore the extreme range of dry and wet conditions. IBIS was much less sensitive to vegetation parameters. The leaf area index (LAI) could affect the mean of daily soil moisture time series when LAI < 1, while the variance of the soil moisture time series was sensitive to LAI > 1. IBIS was insensitive to the Jackson rooting parameter, suggesting that the effect of the rooting depth distribution on predictions of hydrology was insignificant. Copyright © 2014 John Wiley & Sons, Ltd.     

Revegetation impacts on runoff generation processes in a typical loess catchment

Since 1999, large-scale ecosystem restoration has been implemented in the Loess Plateau, effectively increasing regional vegetation coverage. Vegetation restoration has significantly elevated the saturated hydraulic conductivity (Ks) of the near-surface soil layers and increased the vertical heterogeneity of the Ks profile. Many studies have examined the change of runoff due to revegetation, yet the impacts of Ks profile on the soil moisture distribution and runoff generation processes were less explored. In this study, numerical simulations were conducted to investigate how changes in the Ks profile caused by vegetation restoration influenced the hydrological responses at event scale. The numerical simulation results show that the increase of surface Ks caused by vegetation restoration can effectively reduce runoff at event scale. Moreover, the enhancement of vertical heterogeneity of Ks profiles can significantly change the vertical profile of soil water content, prompting more water to percolate into the deep soil layer. When rainfall exceeds a threshold, the accumulation of soil water above the relatively less permeable layer can cause short-term saturation in shallow soil layers, resulting in a transient perched water table. As a result, after the vegetation restoration in the Loess Plateau, though Horton overland flow is still the main runoff generation mechanism, there is a possibility of the emergence of Dunne overland flow under the high vegetation coverage (e.g., NDVI larger than 0.5). This emergence of new runoff generation mechanism, saturation excess runoff, in the Loess Plateau due to the vegetation restoration could provide scientific guidance for water and sediment movement, soil and water conservation practices, and desertification control in the Loess Plateau.     

Comparing hydraulic properties of different forest floors

The forest floor plays an important role in runoff rate, soil erosion and soil infiltration capacity by protecting mineral soils from the direct impact of falling raindrops. Forest floor consists of different kinds of litter with different hydraulic properties. In this study, the inverse method was used to estimate the hydraulic properties of three kinds of forest floor (broad‐leaved, needle‐leaved and mixed‐stand) at three replications in a completely random design. Forest floor samples were collected from the Gilan Province, Iran. The samples were piled up to make long columns 40.88 cm high with an inner diameter of 18.1 cm. Artificial rainfall experiments were conducted on top of the columns, and free drainage from the bottom of the columns was measured in the laboratory. Saturated hydraulic conductivity (K_s), saturated water content and water retention curve parameters (van Genuchten equation) were estimated by the inverse method. The results showed that the K_s of needle‐leaved samples differed significantly (p < 0.05) from those of broad‐leaved and mixed‐stand samples, whereas the latter two did not differ in this regard. No significant differences emerged in the water retention function parameters of van Genuchten (θ_r, β and α) in the three forest floor samples. The saturated water content of mixed‐stand samples was significantly different (p < 0.05) from that of broad‐leaved and needle‐leaved treatments with the latter two samples showing no significant difference. The good agreement between simulated and observed free drainage for all forest floor samples in the validation period indicates that the estimated hydraulic properties efficiently characterize the unsaturated water flow in the forest floor. Copyright © 2013 John Wiley & Sons, Ltd.     

Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

Abstract

The accuracy of six combined methods formed by three commonly-used soil hydraulic functions and two methods to determine soil hydraulic parameters based on a soil hydraulic parameter look-up table and soil pedotransfer functions was examined for simulating soil moisture. A novel data analysis and modelling approach was used that eliminated the effects of evapotranspiration so that specific sources of error among the six combined methods could be identified and quantified. By comparing simulated and observed soil moisture at six sites of the USDA Soil Climate Analysis Network, we identified the optimal soil hydraulic functions and parameters for predicting soil moisture. Through sensitivity tests, we also showed that adjusting only the soil saturated hydraulic conductivity, K_s , is insufficient for representing important effects of macropores on soil hydraulic conductivity. Our analysis illustrates that, in general, soil hydraulic conductivity is less sensitive to K_s than to the soil pore-size distribution parameter.

Editor D. Koutsoyiannis; Associate editor D. Hughes

Citation Pan, F., McKane, R.B. and Stieglitz, M., 2012. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture. Hydrological Sciences Journal, 57 (4), 723–737.     

Experimental study on the hydrological performance of green roofs in the application of novel biochar

Biochar has the potential to be a soil amendment in green roofs owing to its water retention, nutrient supply, and carbon sequestration application. The combined effects of biochar and vegetated soil on hydraulic performance (e.g., saturated hydraulic conductivity, retention and detention, and runoff delay) are the crucial factor for the application of the novel biochar in green roofs. Recent studies investigated soil water potential (i.e., suction) either on vegetated soil or on biochar-amended soil but rarely focused on their integrated application. With the purpose of investigating the hydraulic performance of green roofs in the application of biochar, the combined effect of biochar and vegetated soil on hydrological processes was explored. Artificial rainfall experiments were conducted on the four types of experimental soil columns, including natural soil, biochar-amended soil, vegetated natural soil, and vegetated biochar-amended soil. The surface ponding, bottom drainage and the volumetric water content were measured during the rainfall test. Simulation method by using HYDRUS-1D was adopted for estimating hydraulic parameters and developing modelling analysis. The results indicated that the saturated hydraulic conductivity of vegetated soil columns were higher than bare soil columns. The addition of biochar decreased the saturated hydraulic conductivity, and the magnitude of decrease was much significant in the case of vegetated soil. The influence of vegetation on permeability is more prominent than biochar. The vegetated biochar-amended soil has the highest retention and detention capacity, and shows a preferable runoff delay effect under heavy rain among the four soil columns. The results from the present study help to understand the hydrological processes in the green roof in the application of biochar, and imply that biochar can be an alternative soil amendment to improve the hydraulic performance.     

Impact of land use on the hydraulic properties of the topsoil in a small French catchment

The hydraulic properties of the topsoil control the partition of rainfall into infiltration and runoff at the soil surface. They must be characterized for distributed hydrological modelling. This study presents the results of a field campaign documenting topsoil hydraulic properties in a small French suburban catchment (7 km²) located near Lyon, France. Two types of infiltration tests were performed: single ring infiltration tests under positive head and tension‐disk infiltration using a mini‐disk. Both categories were processed using the BEST—Beerkan Estimation of Soil Transfer parameters—method to derive parameters describing the retention and hydraulic conductivity curves. Dry bulk density and particle size data were also sampled. Almost all the topsoils were found to belong to the sandy loam soil class. No significant differences in hydraulic properties were found in terms of pedologic units, but the results showed a high impact of land use on these properties. The lowest dry bulk density values were obtained in forested soils with the highest organic matter content. Permanent pasture soils showed intermediate values, whereas the highest values were encountered in cultivated lands. For saturated hydraulic conductivity, the highest values were found in broad‐leaved forests and small woods. The complementary use of tension‐disk and positive head infiltration tests highlighted a sharp increase of hydraulic conductivity between near saturation and saturated conditions, attributed to macroporosity effect. The ratio of median saturated hydraulic conductivity to median hydraulic conductivity at a pressure of − 20 mm of water was about 50. The study suggests that soil texture, such as used in most pedo‐transfer functions, might not be sufficient to properly map the variability of soil hydraulic properties. Land use information should be considered in the parameterizations of topsoil within hydrological models to better represent in situ conditions, as illustrated in the paper. Copyright © 2010 John Wiley & Sons, Ltd.     

Inverse upscaling of hydraulic parameters during constant flux infiltration using borehole radar

Modeling unsaturated flow in porous media requires constitutive relations that describe the soil water retention and soil hydraulic conductivity as a function of either potential or water content. Often, the hydraulic parameters that describe these relations are directly measured on small soil cores, and many cores are needed to upscale to the entire heterogeneous flow field. An alternative to the forward upscaling method using small samples are inverse upscaling methods that incorporate soft data from geophysical measurements observed directly on the larger flow field. In this paper, we demonstrate that the hydraulic parameters can be obtained from cross borehole ground penetrating radar by measuring the first arrival travel time of electromagnetic waves (represented by raypaths) from stationary antennae during a constant flux infiltration experiment. The formulation and coupling of the hydrological and geophysical models rely on a constant velocity wetting front that causes critical refraction at the edge of the front as it passes by the antennae. During this critical refraction period, the slope of the first arrival data can be used to calculate (1) the wetting velocity and (2) the hydraulic conductivity of the wet (or saturated) soil. If the soil is undersaturated during infiltration, then an estimate of the saturated water content is needed before calculating the saturated hydraulic conductivity. The hydraulic conductivity value is then used in a nonlinear global optimization scheme to estimate the remaining two parameters of a Broadbridge and White soil.     

Year‐round estimation of soil moisture content using temporally variable soil hydraulic parameters

Soil moisture plays a key role in the hydrological cycle as it controls the flux of water between soil, vegetation, and atmosphere. This study is focused on a year‐round estimation of soil moisture in a forested mountain area using the bucket model approach. For this purpose, three different soil moisture models are utilised. The procedure is based on splitting the whole year into two complement periods (dormant and vegetation). Model parameters are allowed to vary between the two periods and also from year to year in the calibration procedure. Consequently, two sets of average model parameters corresponding to dormant and vegetation seasons are proposed. The process of splitting is strongly supported by the experimental data, and it enables us to variate saturated hydraulic conductivity and pore‐size characterisation. The use of the two different parameter sets significantly enhances the simulation of two (Teuling and Troch model and soil water balance model‐green–ampt [SWBM‐GA]) out of three models in the 6‐year period from 2009 to 2014. For these two models, the overall Nash‐Sutcliffe coefficient increased from 0.64 to 0.79 and from 0.55 to 0.80. The third model (the Laio approach) proved to be insensitive to parameter changes due to its insufficient drainage prediction. The variability of the warm and cold parameter sets between particular years is more pronounced in the warm periods. The cold periods exhibited approximately similar character during all 6 years.     

Determination of soil hydrophysical characteristics in the Ivankovo Reservoir watershed

The capillary-sorption potential and the unsaturated hydraulic conductivity of soils as functions of soil water content are derived for forest, meadow, and agricultural ecosystems of the Ivankovo Reservoir watershed. The parameters of van Genuchten-Mualem equations were determined for the same soils based on data on soil particle size distribution and density. Computer code HYDRUS-1D and the obtained data were used to calculate the values of field capacity of soils in forest, meadow, and agricultural ecosystems in the drainage basin of the Ivankovo Reservoir.     

Sensitivity of nitrate concentration-discharge patterns to soil nitrate distribution and drainage properties in the vertical dimension

We propose a conceptual model that examines the ‘variable source area’ (VSA) and ‘nitrate flushing’ hypothesis in the vertical direction, and use this approach to explain nitrate concentration–discharge relationships in a semi-arid watershed. We use an eco-hydrology simulation model (RHESSys) to show that small changes in the vertical distribution of nitrate mass and their interaction with soil hydraulic conductivity can result in abrupt changes in the nitrate concentration–discharge relationship. We show that the estimated concentration–discharge relationship is sensitive to the parameters governing soil vertical nitrate distribution and soil hydraulic conductivity, at both patch scale and watershed scale, where lateral redistribution of water and nitrate is also accounted for. Given heterogeneity in nitrogen inputs, uptake processes, soil drainage and storage processes, substantial variation in parameters that describe rate of changes in vertical distribution of soil nitrate and hydraulic properties is likely both within and between watersheds. Thus, we argue that vertical ‘variable source area’ processes may be as important as lateral VSA in determining concentration discharge relationships.     

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

The 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.