Calibration and validation of a general infiltration model

A general infiltration model proposed by Singh and Yu (1990) was calibrated and validated using a split sampling approach for 191 sets of infiltration data observed in the states of Minnesota and Georgia in the USA. Of the five model parameters, f_c (the final infiltration rate), S_o (the available storage space) and exponent ‘n’ were found to be more predictable than the other two parameters: m (exponent) and a (proportionality factor). A critical examination of the general model revealed that it is related to the Soil Conservation Service (1956) curve number (SCS‐CN) method and its parameter S_o is equivalent to the potential maximum retention of the SCS‐CN method and is, in turn, found to be a function of soil sorptivity and hydraulic conductivity. The general model was found to describe infiltration rate with time varying curve number. Copyright © 1999 John Wiley & Sons, Ltd.     

Matching hydrologic response to measured effective hydraulic conductivity

The objective of this study was to test the practicability of defining hydrologic response units as combinations of soil, land use and topography for modelling infiltration at the hillslope and catchment scales. In an experimental catchment in the East African Highlands (Kwalei, Tanzania), three methods of measuring infiltration were compared for their ability to capture the spatial variability of effective hydraulic conductivity: the constant head (CH) method; the tension infiltration (TI) method; and the mini‐rainfall simulation (RS) method. The three methods yielded different probability distributions of effective hydraulic conductivity and suggested different types of hydrologic response units. Independently from these measurements, the occurrence of infiltration‐excess overland flow was monitored over an area of 6 ha by means of overland flow detectors. The observed pattern of overland flow occurrence did not match any of the patterns suggested by the infiltration measurements. Instead, clusters of spots with overland flow were practically independent from field borders. Geostatistical analysis of the overland flow confirmed the absence of spatial correlation for distances over 40 m. The RS method yielded the pattern closest to the observations, probably because the method simulated better the processes that trigger infiltration‐excess overland flow, i.e. soil sealing and infiltration through macroporosity. The RS hydrologic response unit correlated significantly with observed overland flow frequency. However, the location of clusters and ‘hot spots’ of overland flow remained largely unexplained by land use, soil and topographic variables. It is concluded that using such landscape variables to define hydrologic units may create artificial boundaries that do no correspond to physical realities, especially if the stochastic component within hydrologic units is neglected. Copyright © 2005 John Wiley & Sons, Ltd.     

Effects of eastern redcedar encroachment on soil hydraulic properties along Oklahoma's grassland‐forest ecotone

In north‐central Oklahoma eastern redcedar (Juniperus virginiana), encroachment into grassland is widespread and is suspected of reducing streamflow, but the effects of this encroachment on soil hydraulic properties are unknown. This knowledge gap creates uncertainty in understanding the hydrologic effects of eastern redcedar encroachment and obstructs fact‐based management of encroached systems. The objective of this study was to quantify the effects of eastern redcedar encroachment into tallgrass prairie on soil hydraulic properties. Leaf litter depth, soil organic matter, soil water repellency, soil water content, sorptivity, and unsaturated hydraulic conductivity were measured near Stillwater, OK, along 12 radial transects from eastern redcedar trunks to the center of the grassy intercanopy space. Eastern redcedar encroachment in the second half of the 20th century caused the accumulation of 3 cm of hydrophobic leaf litter near the trunks of eastern redcedar trees. This leaf litter was associated with increased soil organic matter in the upper 6 cm of soil under eastern redcedar trees (5.96% by mass) relative to the grass‐dominated intercanopy area (3.99% by mass). Water repellency was more prevalent under eastern redcedar than under grass, and sorptivity under eastern redcedar was 0.10 mm s^?1/2, one seventh the sorptivity under adjacent prairie grasses (0.68 mm s^?1/2). Median unsaturated hydraulic conductivity under grass was 2.52 cm h^?1, four times greater than under eastern redcedar canopies (0.57 cm h^?1). Lower sorptivity and unsaturated hydraulic conductivity would tend to decrease infiltration and increase runoff, but other factors such as rainfall interception by the eastern redcedar canopy and litter layer, and preferential flow induced by hydrophobicity must be examined before the effects of encroachment on streamflow can be predicted. Copyright © 2011 John Wiley & Sons, Ltd.     

Sources of inherent infiltration variability in postwildfire soils

An automated disc infiltrometer was developed to improve the measurements of soil hydraulic properties (saturated hydraulic conductivity and sorptivity) of soils affected by wildfire. Guidelines are given for interpreting curves showing cumulative infiltration as a function of time measured by the autodisc. The autodisc was used to measure the variability of these soil hydraulic properties in three different sample sets: (a) a reference soil consisting of a nonrepellent, uniform, fine sand; (b) soils with the same soil textural classification derived from the same bedrock geology but having different initial burn severities; and (c) soils from different bedrock geology but having the same burn severity. The autodisc infiltrometer had greater sampling rates and volume resolution when compared with the visual minidisc infiltrometer from previous studies. There was no statistical difference in the mean values measured using the autodisc and visual minidisc, but the variability of the autodisc measurements was significantly less than the visual minidisc for a given set of samples. The greatest variability of soil hydraulic properties in reference samples with uniform particle size was attributed to different pore geometries (coefficient of variation [COV] = 0.28–0.34). Unburned field samples (same soil type) with heterogeneous particle sizes had greater variability (COV = 0.57–0.78) than the reference samples. However, this basic variability decreased or remained constant in these field samples as burn severity increased. Additional sources of variability (COV = 0.53–1.99) were attributed to multiple layers resulting from ash or sediment deposition. Results indicate that resolving differences in soil hydraulic properties from different sites requires more than the common 10 random samples because of the multiple sources of variability.     

ESTIMATING INFILTRATION PARAMETERS FROM BASIC SOIL PROPERTIES

Infiltration data were collected on two rectangular grids with 25 sampling points each. Both experimental grids were located in tropical rain forest (Guyana), the first in an Arenosol area and the second in a Ferralsol field. Four different infiltration models were evaluated based on their performance in describing the infiltration data. The model parameters were estimated using non-linear optimization techniques. The infiltration behaviour in the Ferralsol was equally well described by the equations of Philip, Green–Ampt, Kostiakov and Horton. For the Arenosol, the equations of Philip, Green–Ampt and Horton were significantly better than the Kostiakov model. Basic soil properties such as textural composition (percentage sand, silt and clay), organic carbon content, dry bulk density, porosity, initial soil water content and root content were also determined for each sampling point of the two grids. The fitted infiltration parameters were then estimated based on other soil properties using multiple regression. Prior to the regression analysis, all predictor variables were transformed to normality. The regression analysis was performed using two information levels. The first information level contained only three texture fractions for the Ferralsol (sand, silt and clay) and four fractions for the Arenosol (coarse, medium and fine sand, and silt and clay). At the first information level the regression models explained up to 60% of the variability of some of the infiltration parameters for the Ferralsol field plot. At the second information level the complete textural analysis was used (nine fractions for the Ferralsol and six for the Arenosol). At the second information level a principal components analysis (PCA) was performed prior to the regression analysis to overcome the problem of multicollinearity among the predictor variables. Regression analysis was then carried out using the orthogonally transformed soil properties as the independent variables. Results for the Ferralsol data show that the parameters of the Green–Ampt and Kostiakov model were estimated relatively accurately (maximum R² = 0.76). For the Arenosol, use of the second information level together with PCA produced regression models with an R² value ranging from 0.38 to 0.68. For the Ferralsol, most of the variance was explained by the root content and organic matter content. In the Arenosol plot, the fractions medium and fine sand explained most of the observed variance.     

SMALL-SCALE SPATIAL STRUCTURE OF SHALLOW SNOWCOVERS

The results of a field study of the small-scale spatial structure of the depth of shallow seasonal snowcovers in prairie and arctic environments are presented. It is shown that the spatial distribution of snow depth is fractal at small scales, becoming random at scales beyond some limiting length. This is due to the autocorrelation of depth at small sampling distances. The transition of fractal to random behaviour is indexed by a ‘cutoff length’, which is defined by the intersection of the ‘fractal’ slope and horizontal tangent of a logarithmic plot of the standard deviation of depth versus sampling distance. The magnitude of the cutoff length is related to the degree of macroscopic variability of the underlying topography. An increase in length due to the effects of macroscopic topographic variability on snowcover accumulation is confirmed by de-trending field measurements. The de-trended data shown a cutoff length for wheat stubble and fallow surfaces of approximately 30 m, which is consistent with the distance determined from measurements on ‘flat’ fields. The implications of the transition of snow depth from fractal to random structure on the scales of snow sampling and modelling are presented. The cutoff length may provide a statistic for stratifying shallow snowcovers, by linking snowcover properties to the underlying topography.     

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.     

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.     

Infiltration and runoff generation processes in fire‐affected soils

Post‐wildfire runoff was investigated by combining field measurements and modelling of infiltration into fire‐affected soils to predict time‐to‐start of runoff and peak runoff rate at the plot scale (1 m²). Time series of soil‐water content, rainfall and runoff were measured on a hillslope burned by the 2010 Fourmile Canyon Fire west of Boulder, Colorado during cyclonic and convective rainstorms in the spring and summer of 2011. Some of the field measurements and measured soil physical properties were used to calibrate a one‐dimensional post‐wildfire numerical model, which was then used as a ‘virtual instrument’ to provide estimates of the saturated hydraulic conductivity and high‐resolution (1 mm) estimates of the soil‐water profile and water fluxes within the unsaturated zone. Field and model estimates of the wetting‐front depth indicated that post‐wildfire infiltration was on average confined to shallow depths less than 30 mm. Model estimates of the effective saturated hydraulic conductivity, K_s, near the soil surface ranged from 0.1 to 5.2 mm h^?1. Because of the relatively small values of K_s, the time‐to‐start of runoff (measured from the start of rainfall), t_p, was found to depend only on the initial soil‐water saturation deficit (predicted by the model) and a measured characteristic of the rainfall profile (referred to as the average rainfall acceleration, equal to the initial rate of change in rainfall intensity). An analytical model was developed from the combined results and explained 92–97% of the variance of t_p, and the numerical infiltration model explained 74–91% of the variance of the peak runoff rates. These results are from one burned site, but they strongly suggest that t_p in fire‐affected soils (which often have low values of K_s) is probably controlled more by the storm profile and the initial soil‐water saturation deficit than by soil hydraulic properties. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.     

Infiltration into frozen soil: From core‐scale dynamics to hillslope‐scale connectivity

Infiltration into frozen soil is a key hydrological process in cold regions. Although the mechanisms behind point‐scale infiltration into frozen soil are relatively well understood, questions remain about upscaling point‐scale results to estimate hillslope‐scale run‐off generation. Here, we tackle this question by combining laboratory, field, and modelling experiments. Six large (0.30‐m diameter by 0.35‐m deep) soil cores were extracted from an experimental hillslope on the Canadian Prairies. In the laboratory, we measured run‐off and infiltration rates of the cores for two antecedent moisture conditions under snowmelt rates and diurnal freeze–thaw conditions observed on the same hillslope. We combined the infiltration data with spatially variable data from the hillslope, to parameterise a surface run‐off redistribution model. We used the model to determine how spatial patterns of soil water content, snowpack water equivalent (SWE), and snowmelt rates affect the spatial variability of infiltration and hydrological connectivity over frozen soil. Our experiments showed that antecedent moisture conditions of the frozen soil affected infiltration rates by limiting the initial soil storage capacity and infiltration front penetration depth. However, shallow depths of infiltration and refreezing created saturated conditions at the surface for dry and wet antecedent conditions, resulting in similar final infiltration rates (0.3 mm hr^?1). On the hillslope‐scale, the spatial variability of snowmelt rates controlled the development of hydrological connectivity during the 2014 spring melt, whereas SWE and antecedent soil moisture were unimportant. Geostatistical analysis showed that this was because SWE variability and antecedent moisture variability occurred at distances shorter than that of topographic variability, whereas melt variability occurred at distances longer than that of topographic variability. The importance of spatial controls will shift for differing locations and winter conditions. Overall, our results suggest that run‐off connectivity is determined by (a) a pre‐fill phase, during which a thin surface soil layer wets up, refreezes, and saturates, before infiltration excess run‐off is generated and (b) a subsequent fill‐and‐spill phase on the surface that drives hillslope‐scale run‐off.     

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.     

Pattern analysis of dune‐field parameters

As a basic form of pattern analysis, the parameters of dune spacing, defect density, crest orientation and crest length are measured from remote images and treated statistically for dunes at White Sands in New Mexico, the Algodones in California, the Agneitir in Mauritania, and the Namib in Namibia. Statistical populations are identified from frequency plots of dune spacing and crest length, field‐scale calculations of defect density, and rose diagrams of crest orientation. Single populations characterize simple dune fields (White Sands), whereas multiple populations characterize compound/complex dunes (Algodones, Namib), and complex dune fields (Agneitir). As time increases, dune fields show an increase in dune spacing and crest length, a decrease in defect density, more tightly clustered crest orientation, and a reduction in the variance associated with measurements of these parameters. The results are consistent with models of dune fields as self‐organizing complex systems in which a characteristic pattern emerges as a function of constructional time. Because pattern evolution is a function of time, it may be possible to use pattern analysis to augment current methods of age determination. Statistically defined populations can be used in geomorphic backstripping to unstack generations of simple patterns that give rise to complex patterns, and to reconstruct each generation in terms of construction time and palaeo‐wind regime. Copyright © 2006 John Wiley & Sons, Ltd.     

Dune deformation in a multi‐directional wind regime: White Sands Dune Field,New Mexico

As with most dune fields, the White Sands Dune Field in New Mexico forms in a wind regime that is not unimodal. In this study, crescentic dune shape change (deformation) with migration at White Sands was explored in a time series of five LiDAR‐derived digital elevation models (DEMs) and compared to a record of wind direction and speed during the same period. For the study period of June 2007 to June 2010, 244 sand‐transporting wind events occurred and define a dominant wind mode from the SW and lesser modes from the NNW and SSE. Based upon difference maps and tracing of dune brinklines, overall dune behavior consists of crest‐normal migration to the NE, but also along‐crest migration of dune sinuosity and stoss superimposed dunes to the SE. The SW winds are transverse to dune orientations and cause most forward migration. The NNW winds cause along‐crest migration of dune sinuosity and stoss bedforms, as well as SE migration of NE‐trending dune terminations. The SSE winds cause ephemeral dune deformation, especially crestal slipface reversals. The dunes deform with migration because of differences in dune‐segment size, and differences in the lee‐face deposition rate as a function of the incidence angle between the wind direction and the local brinkline orientation. Each wind event deforms dune shape, this new shape then serves as the boundary condition for the next wind event. Shared incidence‐angle control on dune deformation and lee‐face stratification types allows for an idealized model for White Sands dunes. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparison of the effects of litter covering and incorporation on infiltration and soil erosion under simulated rainfall

Plant litter can either cover on soil surface or be incorporated into top-soil layer in natural ecosystems. Their effects on infiltration and soil erosion are likely quite different. This study was performed to compare the effects of litter covering on soil surface and being incorporated into top-soil layer on infiltration and soil erosion under simulated rainfall. Four litter types (needle-leaf, broad-leaf, brush, and herb) were collected from fields and applied to cover on soil surface or to be incorporated into top-soil layer (5 cm) at the same rate (0.2 kg/m²). The simulated rainfalls (40 and 80 mm/hr) were run at two slope angles (10° and 20°). The results showed that the mean infiltration rate of litter covering treatment was 1.4 times as great as that of litter incorporated. Litter covering enhanced infiltration via protecting surface from soil sealing. Whereas, litter incorporation affected infiltration by its water repellency. Soil erosion of litter incorporated treatment was 5.4 times as large as that of litter covered treatment, which was attributed to the changes in surface litter coverage and soil erosion resistance. Litter type affected soil erosion through the variations in litter coverage and litter morphology. For litter covering treatment, litter coverage can explain the major variance of soil loss on the slopes. Whereas, for litter incorporated treatment, both the influences of litter coverage and litter length on soil erosion resistance were considered necessary to well explain the variance of soil loss. The results also showed that the benefits of litter to control soil erosion declined with rainfall intensity and slope gradient for both covering and incorporated treatments. The results of this study are helpful to understand the mechanisms of litter influencing hydrological and erosion processes on hillslopes.     

Sampling variance of a T-year flood estimated by curve-fitting

The sampling variance of a T-year flood when estimated using a curve-fitting method results from the errors in hydrologic observations, plotting positions, and model-fitting. This paper develops a method to quantify the contribution of plotting positions to the sampling variance of the T-year flood magnitude. Application of the method to 150 flood-flow data sets of 41 rivers in the People's Republic of China show that the errors due to plotting positions contribute more to the sampling variance than others.     

Random variation of fabric eigenvalues: implications for the use of a‐axis fabric data to differentiate till facies†

Fabric ‘shape’, based on the relative values of three eigenvalues calculated from fabric data, has been used to differentiate sediment facies and infer deformation histories. The eigenvalues are based on samples drawn from parent populations, and as such are subject to statistical variance due to sampling effects. In this paper, the degree of statistical variance in fabric data for two types of subglacial till from Breidamerkurjøkull, Iceland, is investigated using ‘bootstrapping’ techniques, in which empirical ‘confidence regions’ are built up by repeated resampling of the original data. The experiments show that, for each till type, the observed between‐sample variability in the fabrics lies within the boundaries associated with random variations, indicating that the observed range of fabric shapes within each till type is likely to be entirely the product of sampling effects. Differences in fabric shape between till types are generally greater than that associated with random variations, indicating that their fabric shape characteristics, as measured by eigenvalues, are significantly different. Nevertheless, the results suggest that great care should be exercised when using a‐axis fabric data to differentiate sedimentary facies, or to infer subtle differences in physical processes or conditions. Copyright © 2001 John Wiley & ­Sons, Ltd.     

Modelling to analyse the impacts of animal treading effects on soil infiltration

Animal treading can change soil physical properties, and thus is an important factor in hydrological modelling. We investigated the impacts of animal treading on infiltration by using a series of rainfall simulation experiments at Whatawhata Research Center, Waikato, New Zealand. The study identified significant variables for estimating soil steady‐state infiltration at a micro‐site (0·5 m²) and fitted the Green and Ampt equation by modifying or including variables for soil and water parameters and animal activities on grazing paddocks. A regression function for estimating steady‐state infiltration rate was created for each of four scenarios: between tracks (inter‐track), track, easy slope with ash soil, and easy slope with clay soil. Significant variables included the number of days after treading, antecedent soil moisture, field capacity, percentage of bare ground, bulk density, and the high degree of soil damage (damage not compacted). Regression models explained more than 71% of the variance in steady‐state infiltration for three scenarios, but only 53% for the easy slope with clay soil. The remodified Green and Ampt equation provided satisfactory estimation of infiltration for all scenarios (accuracy > 80%), and thus enables us to use the modified model for Waikato hill country pastures of different topography, soil physical condition, season and grazing management. Copyright © 2006 John Wiley & Sons, Ltd.     

Effects of frozen soil and snow cover on cold‐season soil water dynamics in Tokachi,Japan

Despite the potential impact of winter soil water movements in cold regions, relatively few field studies have investigated cold‐season hydrological processes that occur before spring‐onset of snowmelt infiltration. The contribution of soil water fluxes in winter to the annual water balance was evaluated over 5 years of field observations at an agricultural field in Tokachi, Hokkaido, Japan. In two of the winters, soil frost reached a maximum depth of 0·2 m (‘frozen’ winters), whereas soil frost was mostly absent during the remaining three winters (‘unfrozen’ winters). Significant infiltration of winter snowmelt water, to a depth exceeding 1·0 m, occurred during both frozen and unfrozen winters. Such infiltration ranged between 126 and 255 mm, representing 28–51% of total annual soil water fluxes. During frozen winters, a substantial quantity of water (ca 40 mm) was drawn from deeper layers into the 0–0·2 m topsoil layer when this froze. Under such conditions, the progression and regression of the freezing front, regulated by the thickness of snow cover, controlled the quantity of soil water flux below the frozen layer. During unfrozen winters, 13–62 mm of water infiltrated to a depth of 0·2 m, before the spring snowmelt. These results indicate the importance of correctly evaluating winter soil water movement in cold regions. Copyright © 2010 John Wiley & Sons, Ltd.