Effects of initial soil water content and saturated hydraulic conductivity variability on small watershed runoff simulation using LISEM

Abstract

Soil water content (θ) and saturated hydraulic conductivity (K_s) vary in space. The objective of this study was to examine the effects of initial soil water content (θ_i) and K_s variability on runoff simulations using the LImburg Soil Erosion Model (LISEM) in a small watershed in the Chinese Loess Plateau, based on model parameters derived from intensive measurements. The results showed that the total discharge (TD) and peak discharge (PD) were underestimated when the variability of θ_i and K_s was partially considered or completely ignored compared with those when the variability was fully considered. Time to peak (TP) was less affected by the spatial variability compared to TD and PD. Except for TP in some cases, significant differences were found in all hydrological variables (TD, PD and TP) between the cases in which spatial variability of θ_i or K_s was fully considered and those in which spatial variability was partially considered or completely ignored. Furthermore, runoff simulations were affected more strongly by K_s variability than by θ_i variability. The degree of spatial variability influences on runoff simulations was related to the rainfall pattern and θ_i. Greater rainfall depth and instantaneous rainfall intensity corresponded to a smaller influence of the spatial variability. Stronger effects of the θ_i variability on runoff simulation were found in wetter soils, while stronger effects of the K_s variability were found in drier soils. For accurate runoff simulation, the θ_i variability can be completely ignored in cases of a 1-h duration storm with a return period greater than 10 years, while K_s variability should be fully considered even in the case of a 1-h duration storm with a return period of 20 years.

Editor D. Koutsoyiannis; Associate editor A. Fiori     

Variation in soil saturated hydraulic conductivity along the hillslope of collapsing granite gullies

Saturated hydraulic conductivity (K_s) affects the soil hydrological process and is influenced by many factors that exhibit strong spatial variations. To accurately measure K_s and its scale, spatial variability and relationship with collapsing gullies, we analysed four double-ring infiltrometer diameters in three soil layers during in situ experiments designed to measure K_s in two typical collapsing gullies (three slope sites) in Tongcheng County of China. The results showed that K_s increased with increasing inner ring diameter, but no significant difference existed between inner diameters of 30 and 40 cm. The K_s in red soil layers was higher than that in sandy soil layers, the transition layers had the lowest values. K_s also varied with slope position, gradually decreasing with distance from the gully head. The suggestion is that the spatial variation in K_s is affected not only by the intrinsic soil properties but also by the interaction with the collapsing gully.     

Incorporating spatially heterogeneous infiltration capacity into hydrologic models with applications for simulating post‐wildfire debris flow initiation

Soils in post‐wildfire environments are often characterized by a low infiltration capacity with a high degree of spatial heterogeneity relative to unburned areas. Debris flows are frequently initiated by run‐off in recently burned steeplands, making it critical to develop and test methods for incorporating spatial variability in infiltration capacity into hydrologic models. We use Monte Carlo simulations of run‐off generation over a soil with a spatially heterogenous saturated hydraulic conductivity (K_s) to derive an expression for an aerially averaged saturated hydraulic conductivity ( ) that depends on the rainfall rate, the statistical properties of K_s, and the spatial correlation length scale associated with K_s. The proposed method for determining is tested by simulating run‐off on synthetic topography over a wide range of spatial scales. Results provide a simplified expression for an effective saturated hydraulic conductivity that can be used to relate a distribution of small‐scale K_s measurements to infiltration and run‐off generation over larger spatial scales. Finally, we use a hydrologic model based on to simulate run‐off and debris flow initiation at a recently burned catchment in the Santa Ana Mountains, CA, USA, and compare results to those obtained using an infiltration model based on the Soil Conservation Service Curve Number.     

Statistical analysis of the effects on overland flow of spatial variability in soil hydraulic conductivity / Analyse statistique des effets de la variabilité spatiale de la conductivité hydraulique du sol sur l'écoulement de surface

Abstract

The effects of spatial variation of the saturated hydraulic conductivity (K _s ) of the soil on the variation of overland flow were tested by analysing 2000 synthetic rainfall—runoff events, all generated from real, observed rainfall events but with runoff modelled by a two-dimensional distributed model using different spatially variable K _s fields in a small (12 ha) agricultural catchment. The purpose is to determine the influence of spatial variation in K _s on runoff generation. The statistical measures used to describe the variation in the generated K _s were its coefficient of variation and correlation length. Both of these had two levels of typical values obtained from field measurements in other studies. The storms were analysed at a general event level, first using simple graphical and statistical methods and then using analysis of variance (ANOVA). The observed scale of the spatial variation of K _s does cause statistically significant variation in overland flow. The graphical analysis showed that the first flow peak in a multi-event storm had the largest variation and that differences were greater in the rising part of the hydrograph than in its recession. The greatest variation in overland flow was produced by the combination of the greater coefficient of variation and the longer correlation lengths. The smallest variation in overland flow was produced by the combination of the smaller coefficient of variation and the shorter correlation lengths. ANOVA showed that the coefficient of variation and correlation length alone did not explain all the variation of the total flow. ANOVA was not very useful due to the many restrictive assumptions that were not satisfied by the nature of the data and therefore analysis methods with less restrictive assumptions need to be tested.     

Two-Dimensional Probabilistic Infiltration Analysis in a Hillslope Using First-Order Moment Approach

A first-order moment analysis method is introduced to evaluate the pore-water pressure variability within a hillslope due to spatial variability in saturated hydraulic conductivity (K_s) during rainfall. The influences of the variance of the natural logarithm of K_s(ln K_s), spatial structure anisotropy of ln K_s, and normalized vertical infiltration flux (q) on the evaluations of the pore-water pressure uncertainty are investigated. Results indicate different responses of pressure head variability in the unsaturated region and the saturated region. In the unsaturated region, a larger variance of ln K_s, a higher spatial structure anisotropy, and a smaller q lead to a larger variability in pressure head, while in the saturated region, the variability in pressure head increases with the increase of variance of ln K_s, the decrease of spatial structure anisotropy, or the increase of q. These variables have great impacts on the range of fluctuation of the phreatic surface within the hillslope. The influences of these three variables on the variance of pressure head within the saturated region are greater than those within the unsaturated region, and the variance of ln K_s has the greatest impact. These results yield useful insight into the effects of heterogeneity on pressure head and uncertainty associated with predicted flow field.     

Runoff modelling at two field slopes: use of in situ measurements of air permeability to characterize spatial variability of saturated hydraulic conductivity

The time required at a field site to obtain a few measurements of saturated hydraulic conductivity (K_s) will allow for many measurements of soil air permeability (k_a). This study investigates if k_a measured in situ (k_{a, in situ}) can be a substitute for measurement of K_s in relation to infiltration and surface runoff modelling. Measurements of k_{a, in situ} were carried out in two small agricultural catchments. A spatial correlation of the log‐transformed values existed having a range of approximately 100 m. A predictive relationship between K_s and k_a measured on 100‐cm³ soil samples in the laboratory was derived for one of the field slopes and showed good agreement with an earlier suggested predictive K_s–k_a relationship. In situ measurements of K_s and k_a suggested that the predictive relationships also could be used at larger scale. The K_s–k_a relationships together with the k_{a, in situ} data were applied in a distributed surface runoff (DSR) model, simulating a high‐intensity rainfall event. The DSR simulation results were highly dependent on whether the geometric average of k_{a, in situ} or kriged values of k_{a, in situ} was used as model input. When increasing the resolution of K_s in the DSR model, a limit of 30–40 m was found for both field slopes. Below this limit, the simulated runoff and hydrograph peaks were independent of resolution scale. If only a few randomly chosen values of K_s were used to represent the spatial variation within the field slope, very large deviations in repeated DSR simulation results were obtained, both with respect to peak height and hydrograph shape. In contrast, when using many predicted K_s values based on a K_s–k_a relationship and measured k_{a, in situ} data, the DSR model generally captured the correct hydrograph shape although simulations were sensitive to the chosen K_s–k_a relationship. As massive measurement efforts normally will be required to obtain a satisfactory representation of the spatial variability in K_s, the use of k_{a, in situ} to assess spatial variability in K_s appears a promising alternative. Copyright © 2004 John Wiley & Sons, Ltd.     

Seasonal variations in infiltrability of moss‐dominated biocrusts on aeolian sand and loess soil in the Chinese Loess Plateau

Biocrust effects on soil infiltration have attracted increasing attention in dryland ecosystems, but their seasonal variations in infiltrability have not yet been well understood. On the Chinese Loess Plateau, soil infiltrability indicated by saturated hydraulic conductivity (K_s) of biocrusts and bare soil, both on aeolian sand and loess soil, was determined by disc infiltrometer in late spring (SPR), midsummer (SUM), and early fall (FAL). Then their correlations with soil biological and physiochemical properties and water repellency index (RI) were analysed. The results showed that the biocrusts significantly decreased K_s both on sand during SPR, SUM, and FAL (by 43%, 66%, and 35%, respectively; P < .05) and on loess (by 42%, 92%, and 10%, respectively; P <.05). As compared with the bare soil, the decreased K_s in the biocrusted surfaces was mostly attributed to the microorganism biomass and also to the increasing content of fine particles and organic matter. Most importantly, both the biocrusts and bare soil exhibited significant (F ≥ 11.89, P ≤ .003) seasonal variations in K_s, but their patterns were quite different. Specifically, the K_s of bare soil gradually decreased from SPR to SUM (32% and 42% for sand and loess, respectively) and FAL (29% and 39%); the K_s of biocrusts also decreased from SPR to SUM (59% and 92%) but then increased in FAL (36% and 588%). Whereas the seasonal variations in K_s of the biocrusts were closely correlated with the seasonal variations in RI, the RI values were not high enough to point at hydrophobicity. Instead of that, the seasonal variations of K_s were principally explained by the changes in the crust biomass and possibly by the microbial exopolysaccharides. We conclude that the biocrusts significantly decreased soil infiltrability and exhibited a different seasonal variation pattern, which should be carefully considered in future analyses of hydropedological processes.     

Rock physics analysis for time-lapse seismic at Schiehallion Field, North Sea

Rock physics analysis plays a vital role in time‐lapse seismic interpretation because it provides the link between changes in rock and fluid properties and the resulting seismic data response. In this case study of the Schiehallion Field, we discuss a number of issues that commonly arise in rock physics analyses for time‐lapse studies. We show that:

• 1 Logarithmic fits of dry bulk (K_dry) and shear (G_dry) moduli vs. effective pressure (P_eff) are superior to polynomial fits.
• 2 2D surface fits of K_dry and G_dry over porosity (φ) and effective pressure using all the core data simultaneously are more useful and accurate than separate 1D fits over φ and P_eff for each individual core.
• 3 One average set (facies) of K_dry(φ, P_eff) and G_dry(φ, P_eff) can be chosen to represent adequately the entire Schiehallion reservoir.
• 4 Saturated velocities and densities modelled by fluid substitution of K_dry(φ, P_eff), G_dry(φ, P_eff) and the dry bulk density ρ_dry(φ) compare favourably with well‐log velocities and densities.
• 5 P‐ and S‐wave impedance values resulting from fluid substitution of K_dry(φ, P_eff), G_dry(φ, P_eff) and ρ_dry(φ) show that the largest impedance changes occur for high porosities and low effective pressures.
• 6 Uncertainties in K_dry(φ, P_eff) and G_dry(φ, P_eff) derived for individual cores can be used to generate error surfaces for these moduli that represent bounds for quantifying uncertainties in seismic modelling or pressure–saturation inversion.

     

Persistence of road runoff generation in a logged catchment in Peninsular Malaysia

Measurements of saturated hydraulic conductivity (K_s) and diagnostic model simulations show that all types of logging road/trail in the 14·4 ha Bukit Tarek Experimental Catchment 3 (BTEC3) generate substantial Horton overland flow (HOF) during most storms, regardless of design and level of trafficking. Near‐surface K_s(0–0·05 m) on the main logging road, skid trails and newly constructed logging terraces was less than 1, 2 and 34 mm h^?1, respectively. Near‐surface K_s on an abandoned skid trail in an adjacent basin was higher (62 mm h^?1), owing to the development of a thin organic‐rich layer on the running surface over the past 40 years. Saturated hydraulic conductivity measured at 0·25 m below the surface of all roads was not different (all <6 mm h^?1) and corresponded to the K_s of the adjacent hillslope subsoil, as most roads were excavated into the regolith more than 0·5–1 m. After 40 years, only limited recovery in near‐surface K_s occurred on the abandoned skid trail. This road generated HOF after the storage capacity of the upper near‐surface layer was exceeded during events larger than about 20 mm. Thus, excavation into low‐K_s substrate had a greater influence on the persistence of surface runoff production than did surface compaction by machinery during construction and subsequent use during logging operations. Overland flow on BTEC3 roads was also augmented by the interception of shallow subsurface flow traveling along the soil–saprolite/bedrock interface and return flow emerging from the cutbank through shallow biogenic pipes. The most feasible strategy for reducing long‐term road‐related impacts in BTEC3 is limiting the depth of excavation and designing a more efficient road network, including minimizing the length and connectivity of roads and skid trails. Copyright © 2007 John Wiley & Sons, Ltd.     

Geomorphic controls on the physical and hydrologic properties of soils in a valley floor

The distribution of soil hydraulic and physical properties strongly influences runoff processes in landscapes. Although much work has been done to quantify and predict the properties of hillslope soils, far less is known about the distribution of soil properties in valley floors. A technique that links the estimation and distribution of soil hydraulic properties in valleys, with easily identified geomorphic features, was developed along a 2 km length of a valley at Brooks Creek in New South Wales, Australia. Soil physical and hydraulic property data were collected across a set of floodplain and fan features within the valley and analysed statistically to determine if soil properties varied significantly between geomorphic features and stratigraphic layers. The results show that the depth‐averaged saturated hydraulic conductivity, K_s, of the soil varies significantly with landform: fan units have K_g values that are twice that of floodplains and colluvial toeslope deposits have K_s values four times higher than floodplains. Given the notorious variability of K_s values in space, the strong statistical separation of soil properties by landform, backed up by strong separation of soil particle size by landform, suggests a way forward in understanding the distribution of soil properties in valleys and their influence on catchment hydrology. Copyright © 2000 John Wiley & Sons, Ltd.     

Evaluation of crystallization temperatures of mineral paragenesis in consolidated crust and uppermost mantle from explosion seismology data

In terms of the general endogeneous evolution of the lithosphere, the continental crystalline crust and the uppermost mantle, formed by regional metamorphic and magmatic processes, show mineral paragenesis stratification, expressed by a regular mineral sequence. The continuous macrolayering of mineral paragenesis through lithospheric depth profile is caused by phase transformations and variations in composition of complex natural systems, and affects the vertical distribution of seismic velocities,V _p,V _s, and other physical parameters.To evaluate palaeotemperatures (crystallization temperatures of mineral paragenesis), consistentV _pandV _s (Z) velocity models for the consolidated crust of two regionally separated areas of different geological structures — Precambrian shield (Voronezh Massif) and a young fold-mountain structure in the central part of the Transasian orogeneous belt (Himalaya) — are used as starting data.The velocity models are recalculated into (Z) and (Z) profiles (Z) being the seismic parameter. (Z) the Debye temperature). These, according to Debye theory, allow the determination of variations in entropy, thermodynamic and temperature gradients at the time of crustal generation.For the two regions chosen, palaeotemperature distributions are eventually calculated for the depth intervals given by velocity profiles. Crystallization temperatures calculated from seismic data show good agrrement with the values obtained from mineralogical thermobarometry.     

A bootstrap calculation of confidence regions for proportions of sediment contributed by different source areas in a ‘fingerprinting’ model

When ‘fingerprinting’ is used to identify what proportions P_s (s = 1, …, g) of suspended sediment come from g different source areas, measures of the uncertainties in estimates of the P_s are also required. These uncertainties are influenced by two kinds of correlation whose effects are rarely recognized in the literature. These are (i) correlation between the estimated P_s because they must add to 1 and (ii) correlation between the geochemical tracers measured in sediment samples. This paper uses bootstrap procedures to identify joint confidence regions for the estimated proportions [responding to correlation of type (i)] and to explore alternatives to the ‘standard’ least‐squares criterion used to estimate the proportions when tracer measurements are correlated [correlation of type (ii)]. Using a limited dataset with three sediment source areas for illustration (g = 3), results were obtained from 5000 bootstrap samples, using two criteria (standard and generalized least squares, GLS) with two inequality constraints: (a) 0 ≤ P_s ≤ 1, where P_s is the fraction of suspended sediment contributed by the s‐th source area (s = 1, 2, 3) and (b) 0 < P_s < 1, which, the paper argues, better represents reality. Approximate 95% confidence regions for the P_s, given by the two criteria and two inequality constraints, were compared. Using inequality constraint (a), the confidence region given by the GLS criterion was slightly smaller than that given by the standard; using constraint (b), the two confidence regions' boundaries were almost identical, suggesting that the effects of correlations between tracers were not large for the dataset used. For both criteria, the scatter amongst estimated proportions P_s obtained by bootstrapping was large, raising issues concerning the efficiency of sampling and the allocation of sampling effort, both in source areas and in transported suspended sediment. The results suggest that apparently small differences in the constraints applied to the proportions P_s can give quite different numerical results. Copyright © 2014 John Wiley & Sons, Ltd.     

A semi-analytical model of expected areal-average infiltration under spatial heterogeneity of rainfall and soil saturated hydraulic conductivity

A semi-analytical model for the estimate of expected areal-average infiltration rate at hillslope scale is presented. It accounts for spatial heterogeneity of the saturated hydraulic conductivity, K_s, and rainfall rate, r. The K_s field is characterized by a lognormal probability density function while the rainfall rate r is represented by a uniform distribution between two extreme values. The model formulation relies upon the use of cumulative infiltration as the independent variable which is then expressed as a function of an expected time for use in practical applications. The solution is applicable for those ranges of r and K_s that allow for neglecting the infiltration of surface water running downslope into pervious soils (run-on process). The model was tested by comparisons with Monte Carlo simulations carried out for a variety of coefficients of variation of r and K_s over a clay loam soil and a sandy loam soil. The model was found to be very reliable both with coupled spatial variability of r and K_s and when only one variable is characterized by spatial heterogeneity while the other is uniform.     

Upward infiltration–evaporation method to estimate soil hydraulic properties

Determination of saturated hydraulic conductivity, K_s, and the van Genuchten water retention curve θ(h) parameters is crucial in evaluating unsaturated soil water flow. The aim of this work is to present a method to estimate K_s, α and n from numerical analysis of an upward infiltration process at saturation (Cap0), with (Cap0 + h) and without (Cap0) an overpressure step (h) at the end of the wetting phase, followed by an evaporation process (Evap). The HYDRUS model as well as a brute-force search method were used for theoretical loam soil parameter estimation. The uniqueness and the accuracy of solutions from the response surfaces, K_s–n, α–n and K_s–α, were evaluated for different scenarios. Numerical experiments showed that only the Cap0 + Evap and Cap0 + h + Evap scenarios were univocally able to estimate the hydraulic properties. The method gave reliable results in sand, loam and clay-loam soils.     

抚仙湖秋、冬季光衰减特征及其与有色可溶性有机物的关系

为了研究抚仙湖紫外辐射(UVR)和光合有效辐射(PAR)衰减的时空特征及其与有色可溶性有机物(CDOM)、悬浮物(SS)、浮游植物(叶绿素a表征)等因子的关系,于2014年10月(秋季)、2015年1月(冬季)开展现场调查,结果显示:秋季不同波长(段)的漫射衰减系数Kd(305)、Kd(340)和Kd(PAR)分别为1.27±0.12、0.68±0.11和0.32±0.13 m-1,冬季分别为1.13±0.10、0.63±0.07和0.36±0.07 m-1;秋季CDOM的不同波长吸收系数ag(254)、ag(305)和ag(340)分别为4.09±0.26、1.18±0.09和0.57±0.05 m-1,冬季分别为2.95±0.24、0.61±0.11和0.11±0.07 m-1,秋季ag(254)、ag(305)和ag(340)显著高于冬季;秋季Kd(305)显著大于冬季,这与秋季(雨季)较高的CDOM丰度、浮游植物生物量(及SS浓度)有关.秋季ag(305)/Kd(305)、ag(340)/Kd(340)均显著高于冬季;秋季及秋冬季整体而言,ag(254)与Kd(305)、Kd(340)呈显著正相关,各多元逐步回归方程中均包含ag(254),说明CDOM吸收对UVR的衰减有重要贡献.空间差异方面,秋季北部的ag(254)、Kd(305)和Kd(340)显著高于南部,冬季南北部无明显差异,或与雨旱季北岸河流输入的CDOM和SS的情况有关.此外,浮游植物对UV-B衰减的影响和SS(与CDOM的交互作用)对UV-A衰减的影响更在于季节变化方面,而影响UVR、PAR衰减的各因子的相对贡献有待进一步量化.     

Application of a conceptual method for separating runoff components in daily hydrographs in Kimakia forest catchments,Kenya

This paper highlights the use of a conceptual method for separating runoff components in daily hydrographs, contrary to the traditionally used graphical method of separation. In the conceptual method, the components, viz. surface flow, interflow and baseflow, are regarded as high, medium and low frequency signals and their separation is done using the principle of a recursive digital filter commonly used in signal analysis and processing. It requires estimates of the direct runoff (β_d) and surface runoff (β_s) filter parameters which are obtained by a least‐squares procedure involving baseflow and interflow indices based on graphical and recursive digital filter estimation techniques. The method thus circumvents the subjective element associated with the graphical procedure of hydrograph separation, in which case the eye approximation and/or one's skill at plotting is the prime basis for the whole analysis. The analysis based on three forest catchments in Kimakia, Kenya, East Africa, revealed that β_d=K_b and β_s=K_i , where K_b and K_i are the baseflow and interflow recession constants. Copyright © 1999 John Wiley & Sons, Ltd.     

Variability of tree transpiration across three zones in a southeastern U.S. Piedmont watershed

Quantifying the spatial variability of species-specific tree transpiration across hillslopes is important for estimating watershed-scale evapotranspiration (ET) and predicting spatial drought effects on vegetation. The objectives of this study are to (1) assess sap flux density (J_s) and tree-level transpiration (T_s) across three contrasting zones a (riparian buffer, mid-hillslope and upland-hillslope, (2) determine how species-specific J_s responds to vapour pressure deficit (VPD) and (3) estimate watershed-level transpiration (T_w) using T_s derived from each zone. During 2015 and 2016, we measured J_s in eight tree species in the three topographic zones in a small 12-ha forested watershed in the Piedmont region of central North Carolina. In the dry year of 2015, loblolly pine (Pinus taeda), Virginia pine (Pinus virginiana) and sweetgum (Liquidambar styraciflua) J_s rates were significantly higher in the riparian buffer when compared to the other two zones. In contrast, J_s rates in tulip poplar (Liriodendron tulipifera) and red maple (Acer rubrum) were significantly lower in the buffer than in the mid-hillslope. Daily T_s varied by zone and ranged from 10 to 93 L/day in the dry year and from 9 to 122 L/day in the wet year (2016). J_s responded nonlinearly to VPD in all species and zones. Annual T_w was 447, 377 and 340 mm based on scaled-J_s data for the buffer, mid-hillslope and upland-hillslope, respectively. We conclude that large spatial variability in J_s and scaled T_w was driven by differences in soil moisture at each zone and forest composition. Consequently, spatial heterogeneity of vegetation and soil moisture must be considered when accurately quantifying watershed level ET.     

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.