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.     

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.     

Development and parameterization of an infiltration model accounting for water depth and rainfall intensity

Experimental work has clearly shown that the effective hydraulic conductivity (K_e) or effective infiltration rate (f_e) on the local scale of a plot cannot be considered as constant but are dependent on water depth and rainfall intensity because non‐random microtopography‐related variations in hydraulic conductivity occur. Rainfall–runoff models generally do not account for this: models assume that excess water is uniformly spread over the soil surface and within‐plot variations are neglected. In the present study, we propose a model that is based on the concepts of microtopography‐related water depth‐dependent infiltration and partial contributing area. Expressions for the plot scale K_e and f_e were developed that depend on rainfall intensity and runon from upslope (and thus on water depth). To calibrate and validate the model, steady state infiltration experiments were conducted on maize fields on silt loam soils in Belgium, with different stages and combinations of rainfall intensity and inflow, simulating rainfall and runon. Water depth–discharge and depth–inundation relationships were established and used to estimate the effect of inundation on K_e. Although inflow‐only experiments were found to be unsuitable for calibration, the model was successfully calibrated and validated with the rainfall simulation data and combined rainfall–runon data (R²: 0.43–0.91). Calibrated and validated with steady state infiltration experiments, the model was combined with the Green–Ampt infiltration equation and can be applied within a two‐dimensional distributed rainfall–runoff model. The effect of water depth–dependency and rainfall intensity on infiltration was illustrated for a hillslope. Copyright © 2012 John Wiley & Sons, Ltd.     

Occurrence of water ponding on soil surfaces depending on infiltration rates on Mongolian rangeland

The occurrence of water ponding on soil surfaces during and after heavy rainfall produces surface run‐off or surface water accumulation in low‐lying areas, which might reduce the water supply to soils and result in a reduction of the soil water that plants can use, especially in arid climates. On Mongolian rangeland, we observed ponded water on the surface of a specific soil condition subjected to a heavy rainfall of 30 mm/hr. By contrast, ponded water was not observed for the same type of soil where livestock grazing had been removed for 6–8 years via a fence or for nearby soil containing less clay. We measured the infiltration rate (the saturated hydraulic conductivity of the surface soil, K_s) of the three sites by applying ponded water on the soil surface (an intake rate test). The results showed that K_s in the rangeland was lower than the rainfall intensity in the site where water ponded on the soil surface; however, K_s of the soil inside of the fence has recovered to 3 times that of the soil outside of the fence to exceed the rainfall intensity. Heavy rainfall that exceeds the infiltration rate occurs several times a year at the livestock grazing site where we observed ponded water. Slight water repellency of the soil reduces rain infiltration to increase the possibility of surface ponding for the soil.     

In situ measurements of soil saturated hydraulic conductivity: Assessment of reliability through rainfall–runoff experiments

The saturated hydraulic conductivity, K_s, is a soil property that has a key role in the partitioning of rainfall into surface runoff and infiltration. The commonly used instruments and methods for in situ measurements of K_s have frequently provided conflicting results. Comparison of K_s estimates obtained by three classical devices—namely, the double ring infiltrometer (DRI), the Guelph version of the constant‐head well permeameter (GUELPH‐CHP) and the CSIRO version of the tension permeameter (CSIRO‐TP) is presented. A distinguishing feature in this study is the use of steady deep flow rates, obtained from controlled rainfall–runoff experiments, as benchmark values of K_s at local and field‐plot scales, thereby enabling an assessment of these methods in reliably reproducing repeatable values and in their capability of determining plot‐scale variation of K_s. We find that the DRI grossly overestimates K_s, the GUELPH‐CHP gives conflicting estimates of K_s with substantial overestimation in laboratory experiments and underestimation at the plot scale, whereas the CSIRO‐TP yields average K_s values with significant errors of 24% in the plot scale experiment and 66% in laboratory experiments. Although the DRI would likely yield a better estimate of the nature of variability than the GUELPH‐CHP and CSIRO‐TP, a separate calibration may be warranted to correct for the overestimation of K_s values. The reasons for such discrepancies within and between the measurement methods are not yet fully understood and serve as motivation for future work to better characterize the uncertainty associated with individual measurements of K_s using these methods and the characterization of field scale variability from multiple local measurements.     

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, K_s. BEST yielded water retention values statistically similar to those obtained in the laboratory and K_s 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 K_s, 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 K_s 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.     

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.     

Estimating field‐saturated soil hydraulic conductivity by a simplified Beerkan infiltration experiment

Field‐saturated soil hydraulic conductivity, K_fs, is highly variable. Therefore, interpreting and simulating hydrological processes, such as rainfall excess generation, need a large number of K_fs data even at the plot scale. Simple and reasonably rapid experiments should be carried out in the field. In this investigation, a simple infiltration experiment with a ring inserted shortly into the soil and the estimation of the so‐called α* parameter allowed to obtain an approximate measurement of K_fs. The theoretical approach was tested with reference to 149 sampling points established on Burundian soils. The estimated K_fs with the value of first approximation of α* for most agricultural field soils (α* = 0.012 mm^?1) differed by a practically negligible maximum factor of two from the saturated conductivity obtained by the complete Beerkan Estimation of Soil Transfer parameters (BEST) procedure for soil hydraulic characterization. The measured infiltration curve contained the necessary information to obtain a site‐specific prediction of α*. The empirically derived α* relationship gave similar results for K_fs (mean = 0.085 mm s^?1; coefficient of variation (CV) = 71%) to those obtained with BEST (mean = 0.086 mm s^?1; CV = 67%), and it was also successfully tested with reference to a few Sicilian sampling points, since it yielded a mean and a CV of K_fs (0.0094 mm s^?1 and 102%, respectively) close to the values obtained with BEST (mean = 0.0092 mm s^?1; CV = 113%). The developed method appears attractive due to the extreme simplicity of the experiment. Copyright © 2012 John Wiley & Sons, Ltd.     

A modified multiple tension upward infiltration method to estimate the soil hydraulic properties

Determination of saturated hydraulic conductivity, K_s, and the shape parameters α and n of the water retention curve, θ(h), is of paramount importance to characterize the water flow in the vadose zone. This work presents a modified upward infiltration method to estimate K_s, α and n from numerical inverse analysis of the measured cumulative upward infiltration (CUI) at multiple constant tension lower boundary conditions. Using the HYDRUS‐2D software, a theoretical analysis on a synthetic loam soil under different soil tensions (0, 0–10, 0–50 and 0–100 cm), with and without an overpressure step of 10 cm high from the top boundary condition at the end of the upward infiltration process, was performed to check the uniqueness and the accuracy of the solutions. Using a tension sorptivimeter device, the method was validated in a laboratory experiment on five different soils: a coarse and a fine sand, and a 1‐mm sieved loam, clay loam and silt‐gypseous soils. The estimated α and n parameters were compared to the corresponding values measured with the TDR‐pressure cell method. The theoretical analysis demonstrates that K_s and θ(h) can be simultaneously estimated from measured upward cumulative infiltration when high (>50 cm) soil tensions are initially applied at the lower boundary. Alternatively, satisfactory results can be also obtained when medium tensions (<50 cm) and the K_s calculated from the overpressure step at the end of the experiment are considered. A consistent relationship was found between the α (R² = 0.86, p < 0.02) and n (R² = 0.97, p < 0.001) values measured with the TDR‐pressure cell and the corresponding values estimated with the tension sorptivimeter. The error between the α (in logarithm scale) and n values estimated with the inverse analysis and the corresponding values measured with pressure chamber were 3.1 and 6.1%, respectively. Copyright © 2016 John Wiley & Sons, Ltd.     

An approach to analysing plot scale infiltration and runoff responses to rainfall of fluctuating intensity

Simulated rainfall of fluctuating intensity was applied to runoff plots on bare dryland soils in order to explore a new method for analysing the non‐steady‐state responses of infiltration and overland flow. The rainfall events all averaged 10 mm/h but included intensity bursts of up to 70 mm/h and lasting 5–15 min, as well as periods of low intensity and intermittency of up to 25 min. Results were compared with traditional steady‐state estimates of infiltrability made under simulated rainfall sustained at a fixed intensity of 10 mm/h. Mean event infiltration rate averaged 13.6% higher under fluctuating intensities, while runoff ratios averaged only 63% of those seen under constant intensity. In order to understand the changing soil infiltrability, up to three affine Horton infiltration equations were fitted to segments of each experiment. All equations had the same final infiltrability f_c, but adjusted values for coefficients f₀ (initial infiltrability) and K_f (exponential decay constant) were fitted for periods of rainfall that followed significant hiatuses in rainfall, during which subsurface redistribution allowed near‐surface soil suction to recover. According to the fitted Horton equations, soil infiltrability recovered by up 10–24 mm/h during intra‐event rainfall hiatuses of 15 to 20‐min duration, contributing to higher overall event infiltration rates and to reduced runoff ratios. The recovery of infiltrability also reduced the size of runoff peaks following periods of low intensity rainfall, compared with the predictions based on single Horton infiltration equations, and in some cases, no runoff at all was recorded from late intensity peaks. The principal finding of this study is that, using a set of affine equations, the intra‐event time variation of soil infiltrability can be tracked through multiple intensity bursts and hiatuses, despite the lack of steady‐state conditions. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

Simplified modelling of areal average infiltration at the hillslope scale

Two models for estimating expected areal‐average infiltration rate, ī, at the hillslope scale are presented. The first relies upon the condition of a negligible infiltration of surface water running downslope (run‐on process) into a previous heterogeneous soil. It is an adapted version of an earlier semi‐analytical model. The second incorporates the run‐on process and is based on a lumped approach that uses an effective saturated hydraulic conductivity. This latter was parameterized in terms of the main characteristics of rainfall and soil. Both the models were tested by comparison with the results carried out by Monte‐Carlo simulations over different soil types. It was found that the first model simulated ī with maximum errors in magnitude typically less than 10%. The second model provided similar errors in the total volume of overland flow, and the rising limb of the hydrograph experienced a distortion. Lastly, satisfactory results were obtained by comparing the model without run‐on with an empirical approach particularly accurate for fine‐textured soils. Copyright © 2002 John Wiley & Sons, Ltd.     

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.     

Analytical solutions of infiltration process under ponding irrigation

The objective of this paper is to simulate the progress of the soil water content distribution in the soil profile with a water table at the bottom of the soil profile during ponding irrigation. This simulation can be done by solving the two‐dimensional Richards's equation for the assimilation of the advancing water jet, which uses the conditions of the two exponential functional forms k = k_s e^αψ and θ = θ_r + (θ_s − θ_r) e^αψ to represent the hydraulic conductivity and volumetric water content, with ψ the pressure as the third variable. We assume that the ground surface becomes ponded and saturated as soon as the water flux passes the dry ground surface. By the technique of transformation, the analytical solution of these two‐dimensional Richards' equations has enabled figures of volumetric water content distribution to be obtained in successive time periods after irrigation. For the example of loam soil, it can simulate the variation of volumetric water content during and after irrigation in the soil profile. The analytical solutions of this paper reflect the real situation simulated, and can be applied to verify those complicated solutions from other analytical models. Copyright © 2005 John Wiley & Sons, Ltd.     

Prediction of rainfall‐induced shallow landslides in the Loess Plateau,Yan'an,China, using the TRIGRS model

In this work, a transient rainfall infiltration and grid‐based regional slope‐stability model (TRIGRS) was implemented in a case study of Yan'an City, Northwest China. In this area, widespread shallow landslides were triggered by the 12 July 2013 exceptional rainstorm event. A high‐resolution DEM, soil parameters from in‐situ and laboratory measurements, water table depths, the maximum depth of precipitation infiltration and rain‐gauge‐corrected precipitation of the event, were used as inputs in the TRIGRS model. Shallow landslides triggered on the same day were used to evaluate the modeling results. The summarized results are as follows: (i) The characteristics and distribution of thirty‐five shallow landslides triggered by the 12 July 2013 rainfall event were identified in the study area and all were classified as shallow landslides with the maximum depth, area and volume less than 3 m, 200 m² and 1000 m³, respectively, (ii) Four intermediate factor of safety (F_S) maps were generated using the TRIGRS model to represent the scenarios 6, 12, 18 and 24 hours after the storm event. The area with F_S < 1 increased with the rainfall duration. The percentage of the area with F_S < 1 was 0.2%, 3.3%, 3.8% and 5.1% for the four stages, respectively. Twenty‐four hours after the rainstorm, TRIGRS predicted that 1255 grid cells failed, which is consistent with the field data. (iii) TRIGRS generated more satisfactory results at a given precipitation threshold than SINMAP, which is ideal for landslide hazard zoning for land‐use planning at the regional scale. Comparison results showed that TRIGRS is more useful for landslide prediction for a certain precipitation threshold, also in the regional scale. (iv) Analysis of the responses of loess slope prone to slope failure after different precipitation scenarios revealed that loess slopes are particularly sensitive to extended periods of heavy precipitation. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparative assessment of two distributed watershed models with application to a small watershed

Distributed watershed models are beneficial tools for the assessment of management practices on runoff and water‐induced erosion. This paper evaluates, by application to an experimental watershed, two promising distributed watershed‐scale sediment models in detail: the Kinematic Runoff and Erosion (KINEROS‐2) model and the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. The physics behind each model are to some extent similar, though they have different watershed conceptualizations. KINEROS‐2 was calibrated using three rainfall events and validated over four separate rainfall events. Parameters estimated by this calibration process were adapted to GSSHA. With these parameters, GSSHA generated larger and retarded flow hydrographs. A 30% reduction in both plane and channel roughness in GSSHA along with the assumption of Green‐Ampt conductivity K_G‐A = K_s, where K_s is the saturated conductivity, resulted in almost identical hydrographs. Sediment parameters not common in both models were calibrated independently of KINEROS‐2. A comparative discussion of simulation results is presented. Even though GSSHA's flow component slightly overperformed KINEROS‐2, the latter outperformed GSSHA in simulations for sediment transport. In spite of the fact that KINEROS‐2 is not geared toward continuous‐time simulations, simulations performed with both models over a 1 month period generated comparable results. Copyright © 2006 John Wiley & Sons, Ltd.     

Alternative analysis of transient infiltration experiment to estimate soil water repellency

The repellency index (RI) defined as the adjusted ratio between soil‐ethanol, S_e, and soil‐water, S_w, sorptivities estimated from minidisk infiltrometer experiments has been used instead of the widely used water drop penetration time and molarity of ethanol drop tests to assess soil water repellency. However, sorptivity calculated by the usual early‐time infiltration equation may be overestimated as the effects of gravity and lateral capillary are neglected. With the aim to establish the best applicative procedure to assess RI, different approaches to estimate S_e and S_w were compared that make use of both the early‐time infiltration equation (namely, the 1 min, S1, and the short‐time linearization approaches), and the two‐term axisymmetric infiltration equation, valid for early to intermediate times (namely, the cumulative linearization and differentiated linearization approaches). The dataset included 85 minidisk infiltrometer tests conducted in three sites in Italy and Spain under different vegetation habitats (forest of Pinus pinaster and Pinus halepensis, burned pine forest, and annual grasses), soil horizons (organic and mineral), postfire treatments, and initial soil water contents. The S1 approach was inapplicable in 42% of experiments as water infiltration did not start in the first minute. The short‐time linearization approach yielded a systematic overestimation of S_e and S_w that resulted in an overestimation of RI by a factor of 1.57 and 1.23 as compared with the cumulative linearization and differentiated linearization approaches. A new repellency index, RI_s, was proposed as the ratio between the slopes of the linearized data for the wettable and hydrophobic stages obtained by a single water infiltration test. For the experimental conditions considered, RI_s was significantly correlated with RI and WDPT. Compared with RI, RI_s includes information on both soil sorptivity and hydraulic conductivity and, therefore, it can be considered more physically linked to the hydrological processes affected by soil water repellency.     

Synthesis of soil‐hydraulic properties and infiltration timescales in wildfire‐affected soils

We collected soil‐hydraulic property data from the literature for wildfire‐affected soils, ash, and unburned soils. These data were used to calculate metrics and timescales of hydrologic response related to infiltration and surface runoff generation. Sorptivity (S) and wetting front potential (Ψ_f) were significantly different (lower) in burned soils compared with unburned soils, whereas field‐saturated hydraulic conductivity (K_fs) was not significantly different. The magnitude and duration of the influence of capillarity during infiltration was greatly reduced in burned soils, causing faster ponding times in response to rainfall. Ash had large values of S and K_fs but moderate values of Ψ_f, compared with unburned and burned soils, indicating ash has long ponding times in response to rainfall. The ratio of S²/K_fs was nearly constant (~100 mm) for unburned soils but more variable in burned soils, suggesting that unburned soils have a balance between gravity and capillarity contributions to infiltration that may depend on soil organic matter, whereas in burned soils the gravity contribution to infiltration is greater. Changes in S and K_fs in burned soils act synergistically to reduce infiltration and accelerate and amplify surface runoff generation. Synthesis of these findings identifies three key areas for future research. First, short timescales of capillary influences on infiltration indicate the need for better measurements of infiltration at times less than 1 min to accurately characterize S in burned soils. Second, using parameter values, such as Ψ_f, from unburned areas could produce substantial errors in hydrologic modeling when used without adjustment for wildfire effects, causing parameter compensation and resulting underestimation of K_fs. Third, more thorough measurement campaigns that capture soil‐structural changes, organic matter impacts, quantitative water repellency trends, and soil‐water content along with soil‐hydraulic properties could drive the development of better techniques for numerically simulating infiltration in burned areas.     

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.