Geostatistical analysis of soil hydrologic properties in a field plot

A 91-m transect was set up in an irrigated field near Las Cruces, New Mexico to obtain soil water tension and water content data to investigate their spatial variability. A total of 455 sampling points were monitored along a grid consisting of 91 stations placed 1 m apart by 5 depths per station (at 0.3, 0.6, 0.9, 1.2 and 1.5 m below the surface). Post-irrigation tension and wetness measurements were recorded over 45 days at 11 time periods. Soil water tension was measured with tensiometers using a hand-held pressure transducer. A neutron probe was used to obtain volumetric water content. Using the observed wetness and tension data, unsaturated hydraulic conductivity values were derived (using a cubic spline function to estimate the gradient), and an exponential model was used to fit the calculated conductivity-tension curves to obtain hydraulic conductivity parameter values. The spatial and temporal variability of wetness, tension, saturated hydraulic conductivity and pore-size distribution parameters, and texture at the 0.3-m depth were examined using geostatistical techniques.The exponential model was found to inadequately describe the hydraulic conductivity/tension relationship for the full range of tension, particularly in the tension range near saturation. The derived values of the saturated hydraulic conductivity parameter were much greater than expected and do not correspond to reasonable saturated hydraulic conductivity values.All of the soil parameters studied exhibited large spatial variability horizontally and vertically in the field. Ranges of dependence determined from semivariogram analysis over the 44-day drainage period are 3–32 m for wetness, 6–34 m for soil water tension, 5–35 m for natural log of saturated hydraulic conductivity parameters, 5–11 m for pore-size distribution parameter, and 8–24 m for percent sand, silt and clay at the 0.3 m depth. An alternate hole-effect model is suggested to describe the texture semivariograms.It was determined that the variance of volumetric water content generally increased at each depth over the measured time periods, which is consistent with certain past field studies and a stochastic analysis of unsaturated flow in heterogeneous soils. Future research is recommended relating soil texture to soil hydrologic parameters with the goal of predicting soil behavior with less extensive sampling schemes.     

Darcian preferential water flow and solute transport through bimodal porous systems: Experiments and modelling

Soils often exhibit a variety of small-scale heterogeneities such as inter-aggregate pores and voids which partition flow into separate regions. In this paper a methodological approach is discussed for characterizing the hydrological behaviour of a heterogeneous clayey–sandy soil in the presence of structural inter-aggregate pores. For the clay soil examined, it was demonstrated that, coupling the transfer function approach for analyzing BTCs and water retention data obtained with different methods from laboratory studies captures the bimodal geometry of the porous system along with the related existence of fast and slow flow paths. To be effectively and reliably applied this approach requires that the predominant effects of the soil hydrological behaviour near saturation be supported by accurate experimental data of both breakthrough curves (BTCs) and hydraulic functions for high water content values. This would allow the separation of flow phases and hence accurate identification of the processes and related parameters.     

A multimedia environmental model of chemical distribution: fate, transport, and uncertainty analysis

This paper presented a framework for analysis of chemical concentration in the environment and evaluation of variance propagation within the model. This framework was illustrated through a case study of selected organic compounds of benzo[alpha]pyrene (BAP) and hexachlorobenzene (HCB) in the Great Lakes region. A multimedia environmental fate model was applied to perform stochastic simulations of chemical concentrations in various media. Both uncertainty in chemical properties and variability in hydrometeorological parameters were included in the Monte Carlo simulation, resulting in a distribution of concentrations in each medium. Parameters of compartmental dimensions, densities, emissions, and background concentrations were assumed to be constant in this study. The predicted concentrations in air, surface water and sediment were compared to reported data for validation purpose. Based on rank correlations, a sensitivity analysis was conducted to determine the influence of individual input parameters on the output variance for concentration in each environmental medium and for the basin-wide total mass inventory. Results of model validation indicated that the model predictions were in reasonable agreement with spatial distribution patterns, among the five lake basins, of reported data in the literature. For the chemical and environmental parameters given in this study, parameters associated to air-ground partitioning (such as moisture in surface soil, vapor pressure, and deposition velocity) and chemical distribution in soil solid (such as organic carbon partition coefficient and organic carbon content in root-zone soil) were targeted to reduce the uncertainty in basin-wide mass inventory. This results of sensitivity analysis in this study also indicated that the model sensitivity to an input parameter might be affected by the magnitudes of input parameters defined by the parameter settings in the simulation scenario. Therefore, uncertainty and sensitivity analyses for environmental fate models was suggested to be conducted after the model output was validated based on an appropriate input parameter settings.     

A multi-flowpath model for the interpretation of immiscible displacement experiments in heterogeneous soil columns

This work focuses on the phenomenon of the immiscible two-phase flow of water and oil in saturated heterogeneous soil columns. The goal is to develop a fast and reliable method for quantifying soil heterogeneities for incorporation into the relevant capillary pressure and relative permeability functions. Such data are commonly used as input data in simulators of contaminant transport in the subsurface. Rate-controlled drainage experiments are performed on undisturbed soil columns and the transient response of the axial distribution of water saturation is determined from electrical measurements. The transient responses of the axial distribution of water saturation and total pressure drop are fitted with the multi-flowpath model (MFPM) where the pore space is regarded as a system of parallel paths of different permeability. The MFPM enables us to quantify soil heterogeneity at two scales: the micro-scale parameters describe on average the effects of pore network heterogeneities on the two-phase flow pattern; the macro-scale parameters indicate the variability of permeability at the scale of interconnected pore networks. The capillary pressure curve is consistent with that measured with mercury intrusion porosimetry over the low pressure range. The oil relative permeability increases sharply at a very low oil saturation (< 10^− 3) and tends to a high end value. The water relative permeability decreases abruptly at a low oil saturation (~ 0.1), whereas the irreducible wetting phase saturation is quite high. The foregoing characteristics of the two-phase flow properties are associated with critical (preferential) flowpaths that comprise a very small percentage of the total pore volume, control the overall hydraulic conductivity, and are consistent with the very broad range of pore-length scales usually probed in soil porous matrix.     

Investigation of hydrogeologic processes in a dipping layer structure: 1. The flow barrier effect

Numerical simulations of a field experiment were performed in order to study the processes contributing to lateral diversion of water flow in the unsaturated zone. The experimental site is a glacial delta with dipping layers of alternating finer and coarser sand. Model soil physical parameters for each of the stratigraphic layers were estimated from soil grain size distributions. Anisotropy of the hydraulic conductivity within the layers was critical in order to reproduce the flow pattern observed in the experiment. Capillary and hydraulic barriers were of minor importance for the observed lateral diversion.     

Impact of varying soil structure on transport processes in different diagnostic horizons of three soil types

When soil structure varies in different soil types and the horizons of these soil types, it has a significant impact on water flow and contaminant transport in soils. This paper focuses on the effect of soil structure variations on the transport of pesticides in the soil above the water table. Transport of a pesticide (chlorotoluron) initially applied on soil columns taken from various horizons of three different soil types (Haplic Luvisol, Greyic Phaeozem and Haplic Cambisol) was studied using two scenarios of ponding infiltration. The highest infiltration rate and pesticide mobility were observed for the Bt₁ horizon of Haplic Luvisol that exhibited a well-developed prismatic structure. The lowest infiltration rate was measured for the Bw horizon of Haplic Cambisol, which had a poorly developed soil structure and a low fraction of large capillary pores and gravitational pores. Water infiltration rates were reduced during the experiments by a soil structure breakdown, swelling of clay and/or air entrapped in soil samples. The largest soil structure breakdown and infiltration decrease was observed for the Ap horizon of Haplic Luvisol due to the low aggregate stability of the initially well-aggregated soil. Single-porosity and dual-permeability (with matrix and macropore domains) flow models in HYDRUS-1D were used to estimate soil hydraulic parameters via numerical inversion using data from the first infiltration experiment. A fraction of the macropore domain in the dual-permeability model was estimated using the micro-morphological images. Final soil hydraulic parameters determined using the single-porosity and dual-permeability models were subsequently used to optimize solute transport parameters. To improve numerical inversion results, the two-site sorption model was also applied. Although structural changes observed during the experiment affected water flow and solute transport, the dual-permeability model together with the two-site sorption model proved to be able to approximate experimental data.     

Concentration statistics for mixing-controlled reactive transport in random heterogeneous media

Uncertainty in the distribution of hydraulic parameters leads to uncertainty in flow and reactive transport. Traditional stochastic analysis of solute transport in heterogeneous media has focused on the ensemble mean of conservative-tracer concentration. Studies in the past years have shown that the mean concentration often is associated with a high variance. Because the range of possible concentration values is bounded, a high variance implies high probability weights on the extreme values. In certain cases of mixing-controlled reactive transport, concentrations of conservative tracers, denoted mixing ratios, can be mapped to those of constituents that react with each other upon mixing. This facilitates mapping entire statistical distributions from mixing ratios to reactive-constituent concentrations. In perturbative approximations, only the mean and variance of the mixing-ratio distribution are used. We demonstrate that the second-order perturbative approximation leads to erroneous or even physically impossible estimates of mean reactive-constituent concentrations when the variance of the mixing ratio is high and the relationship between the mixing ratio and the reactive-constituent concentrations strongly deviates from a quadratic function. The latter might be the case in biokinetic reactions or in equilibrium reactions with small equilibrium constant in comparison to the range of reactive-constituent concentrations. When only the mean and variance of the mixing ratio is known, we recommend assuming a distribution that meets the known bounds of the mixing ratio, such as the beta distribution, and mapping the assumed distribution of the mixing ratio to the distributions of the reactive constituents.     

Kinematic wave approximation to solute transport along preferred flow paths in soils

A routing procedure is introduced which accounts for the loss of a conservative solute tracer from preferred paths during macropore flow. Water flow is treated as a series of kinematic waves from which the tracer is lost due to mixing previously stored soil water, and an expression for solute loss is added to a previously developed model. The model parameters are estimated through experiments at three different input rates applied to a column of a macroporous forest soil.The results of seven experimental runs indicate that solute losses are consistently highest at the early stages of infiltration and drainage flow. An empirical relationship is proposed which links the frequency distribution of the flow parameter with that for solute loss from the preferred path during transient water flow and solute transport.     

Description of hydrogeologic heterogeneity and evaluation of radionuclide transport at an underground nuclear test

Realistic models of contaminant transport in groundwater demand detailed characterization of the spatial distribution of subsurface hydraulic properties, while at the same time programmatic constraints may limit collection of pertinent hydraulic data. Fortunately, alternate forms of data can be used to improve characterization of spatial variability. We utilize a methodology that augments sparse hydraulic information (hard data) with more widely available hydrogeologic information to generate equiprobable maps of hydrogeologic properties that incorporate patterns of connected permeable zones. Geophysical and lithologic logs are used to identify hydrogeologic categories and to condition stochastic simulations using Sequential Indicator Simulation (SIS). The resulting maps are populated with hydraulic conductivity values using field data and Sequential Gaussian Simulation (SGS). Maps of subsurface hydrogeologic heterogeneity are generated for the purpose of examining groundwater flow and transport processes at the Faultless underground nuclear test, Central Nevada Test Area (CNTA), through large-scale, three-dimensional numerical modeling. The maps provide the basis for simulation of groundwater flow, while transport of radionuclides from the nuclear cavity is modeled using particle tracking methods. Sensitivity analyses focus on model parameters that are most likely to reduce the long travel times observed in the base case. The methods employed in this study have improved our understanding of the spatial distribution of preferential flowpaths at this site and provided the critical foundation on which to build models of groundwater flow and transport. The results emphasize that the impacts of uncertainty in hydraulic and chemical parameters are dependent on the radioactive decay of specific species, with rapid decay magnifying the effects of parameters that change travel time.     

Using stochastic risk assessment in setting information priorities for managing dioxin impact from a municipal waste incinerator

The objectives of this study were to assess site-specific carcinogenic risk of incinerator-emitted dioxins in a manner reflecting pollutant transfer across multimedia and multi-pathways. The study used site-specific environmental and exposure information and combined the Monte Carlo method with multimedia modeling to produce probability distributions of risk estimates. The risk estimates were further categorized by contaminated environmental media and exposure pathways that are experienced by human receptors in order to pinpoint significant sources of risk. Rank correlation coefficients were also calculated along with the Monte Carlo sampling to identify key factors that influenced estimation of risk. The results showed that ingestion accounted for more than 90% of the total risk and that risk control on ingestion of eggs, aboveground vegetables, and poultry should receive priority. It was also found that variation of parameters with variability accounted for around 35% of the total risk variance, while uncertainty contributed to the remaining 65%. Intake rates of aboveground vegetables, eggs, and poultry were the key parameters with the largest contribution to variance. In addition, sufficient sampling and analysis of dioxin contents in eggs, aboveground vegetables, poultry, soil, and fruit should be performed to improve risk estimation because the variation in concentrations in these media accounted for the largest overall risk variance. Finally, focus should be placed on reduction of uncertainty associated with the risk estimation through ingestion of aboveground vegetables, eggs, poultry, fruit, and soil because the risk estimates associated with these exposure pathways had the largest variance.     

Long-term effects of soil heterogeneity on cadmium behaviour in soil

A deterministic model for long-term behaviour of contaminants in the rootzone is developed that includes sorption, leaching, and plant uptake. The model is applied to cadmium accumulation in a sandy soil and uptake of cadmium by barley. Sensitivity analysis showed that the sensitivity of the leaching rate to changes in soil chemical and soil physical parameters decreases as a function of time, and becomes zero when steady state is reached. In contrast, accumulation of cadmium in soil and the plant uptake rate of barley are increasingly sensitive to soil chemical and soil physical parameters as time preceeds. To analyse cadmium behaviour in a field that is heterogeneous with respect to soil physical properties, the interstitial flow velocity was assumed to be a random, lognormally distributed variate. Using Monte Carlo simulation, the average plant uptake rate appeared to be much higher in the stochastic analysis than in the deterministic approach. Steady state is reached after a very long period of time. For a lognormally distributed proton activity, causing heterogeneity with respect to the sorption capacity of the soil, the model predicted similar deviations from the deterministic approach. It is concluded that reference values for groundwater and crop quality are exceeded earlier in a heterogeneous field than in a homogenous soil profile. Moreover, when average values suggest an acceptable situation, variability of the leaching rate and the plant uptake rate can still cause exceedance of reference values in part of the field. Therefore, it is reasoned that environmental quality standards should take soil heterogeneity into account.     

Simulation evaluation of the effects of non-uniform flow and degradation parameter uncertainty on subsurface-flow constructed wetland performance.

Although constructed wetland treatment systems have been used in a variety of applications, uncertainty in adequately determining flow conditions or hydraulic residence times ("hydraulic efficiencies") and degradation model parameters remains a problem with their design. Breakthrough or impulse-type tracer studies in constructed wetlands often result in residence-time distributions exhibiting long skewed "tails" suggesting multiple flow channels or perhaps unrealistically large dispersion factors. A fractional-flow analysis is developed here to quantify possible flow non-uniformity in a subsurface-flow constructed wetland and is then used to assess the effects of non-uniformity and degradation model parameter variability on constituent (for example, chemical oxygen demand) removal. A model application to tracer data developed previously demonstrates how flow non-uniformity alone can account for significant "tailing" and can be related to even moderate estimated dispersion numbers. From the analysis, it is evident that flow non-uniformity is of greater concern than decay parameter uncertainty, and that, from a constructed wetland design and operation perspective, every effort should be made to ensure relative flow uniformity across the constructed wetland.     

Multi-process herbicide transport in structured soil columns: experiments and model analysis

Model predictions of pesticide transport in structured soils are complicated by multiple processes acting concurrently. In this study, the hydraulic, physical, and chemical nonequilibrium (HNE, PNE, and CNE, respectively) processes governing herbicide transport under variably saturated flow conditions were studied. Bromide (Br-), isoproturon (IPU, 3-(4-isoprpylphenyl)-1,1-dimethylurea) and terbuthylazine (TER, N2-tert-butyl-6-chloro-N4-ethyl-1,3,5-triazine-2,4-diamine) were applied to two soil columns. An aggregated Ap soil column and a macroporous, aggregated Ah soil column were irrigated at a rate of 1 cm h(-1) for 3 h. Two more irrigations at the same rate and duration followed in weekly intervals. Nonlinear (Freundlich) equilibrium and two-site kinetic sorption parameters were determined for IPU and TER using batch experiments. The observed water flow and Br- transport were inversely simulated using mobile-immobile (MIM), dual-permeability (DPM), and combined triple-porosity (DP-MIM) numerical models implemented in HYDRUS-1D, with improving correspondence between empirical data and model results. Using the estimated HNE and PNE parameters together with batch-test derived equilibrium sorption parameters, the preferential breakthrough of the weakly adsorbed IPU in the Ah soil could be reasonably well predicted with the DPM approach, whereas leaching of the strongly adsorbed TER was predicted less well. The transport of IPU and TER through the aggregated Ap soil could be described consistently only when HNE, PNE, and CNE were simultaneously accounted for using the DPM. Inverse parameter estimation suggested that two-site kinetic sorption in inter-aggregate flow paths was reduced as compared to within aggregates, and that large values for the first-order degradation rate were an artifact caused by irreversible sorption. Overall, our results should be helpful to enhance the understanding and modeling of multi-process pesticide transport through structured soils during variably saturated water flow.     

Soil phosphorus quantity-intensity relationships to predict increased soil phosphorus loss to overland and subsurface flow

Soil phosphorus (P) quantity-intensity (q-i) relationships, based on common extraction methods, may potentially be used to estimate the risk of P loss in overland flow and subsurface drainage water. Some workers have used nonlinear q-i relationships to derive thresholds in soil test P (STP; a quantity factor) above which the risk of P loss increases, while others find linear relationships and no threshold. We present here a simple modelling exercise (based on Langmuir adsorption theory) along with data from literature to explain the behaviour of q-i relationships, and to give an explanation for this apparent discrepancy. The data indicate that q-i relationships are dependent upon the soil to solution ratio of the P intensity parameter, adsorption capacity (Qmax) and strength (K) of the soil, and the total range in STP. In turn, this affects the calculation of a threshold in STP. The q-i relationship tends towards linearity under conditions of a narrow total range of STP and/or when using a wide soil to solution ratio for estimating the P intensity parameter. Under such conditions, a threshold is difficult to detect, and uncertain. We conclude that the sensitivity of thresholds to experimental conditions and soils needs to be considered if thresholds are to be successful in environmental management to decrease P loss to surface waters.     

DNAPL distribution in the source zone: effect of soil structure and uncertainty reduction with increased sampling density

This paper focuses on parameters describing the distribution of dense nonaqueous phase liquid (DNAPL) contaminants and investigates the variability of these parameters that results from soil heterogeneity. In addition, it quantifies the uncertainty reduction that can be achieved with increased density of soil sampling. Numerical simulations of DNAPL releases were performed using stochastic realizations of hydraulic conductivity fields generated with the same geostatistical parameters and conditioning data at two sampling densities, thus generating two simulation ensembles of low and high density (three-fold increase) of soil sampling. The results showed that DNAPL plumes in aquifers identical in a statistical sense exhibit qualitatively different patterns, ranging from compact to finger-like. The corresponding quantitative differences were expressed by defining several alternative measures that describe the DNAPL plume and computing these measures for each simulation of the two ensembles. The uncertainty in the plume features under study was affected to different degrees by the variability of the soil, with coefficients of variation ranging from about 20% to 90%, for the low-density sampling. Meanwhile, the increased soil sampling frequency resulted in reductions of uncertainty varying from 7% to 69%, for low- and high-uncertainty variables, respectively. In view of the varying uncertainty in the characteristics of a DNAPL plume, remedial designs that require estimates of the less uncertain features of the plume may be preferred over others that need a more detailed characterization of the source zone architecture.     

Deterministic and stochastic modelling of water, heat and nitrogen dynamics on different scales with WHNSIM

With respect to groundwater quality objectives, it is difficult to understand the nitrogen balance and nitrogen dynamics of agricultural ecosystems without the support of deterministic and stochastic simulation tools. This paper focuses on the deterministic and stochastic modelling of water, heat and nitrogen dynamics in the soil compartments of agricultural ecosystems. The deterministic nitrogen simulation model for agricultural soils presented in this paper, WHNSIM, was originally designed for site conditions typical of southern Germany but can easily be applied to other regions due to its physically based design. Model results are compared with data originating from different experimental sites in Germany. Special consideration is given to the effects of spatial variability. Two different techniques of Monte Carlo simulation are used to study the impact of parameter variability on target variables of nitrogen dynamics on the field scale. Moreover, a procedure is presented that allows modelling nitrogen dynamics on the scale of small catchment areas, combining the geographical information system Arc Info with agricultural management data and model calculations.     

Predicting stream-water quality using catchment and soil chemical characteristics

The distribution and chemistry of soils in 10 upland catchments in NE Scotland have been used to develop a means of predicting minimum, maximum and mean concentrations of calcium and hydrogen ions in streams. The approach is based on the control of stream-water chemistry by soil chemical properties. Stream-water chemistry was monitored over a two-year period. Each catchment was surveyed and soils sampled to characterize the chemistry of the main soil units. Stream-water chemical parameters are related to the chemical characteristics of the upper and lower soil horizons in the catchments. The contribution of each soil unit is assessed using randomly generated flow paths. Soil chemistry is weighted according to the distribution of soils in the immediate vicinity of the stream. In this paper the approach is largely confined to the prediction of minimum, maximum and mean concentrations of calcium ions in stream waters. In the longer term, the approach may have the potential to predict what effects changes in soil chemistry and management practice (drainage, ploughing) will have on water quality in upland catchments.     

Simplified contaminant source depletion models as analogs of multiphase simulators

Four simplified dense non-aqueous phase liquid (DNAPL) source depletion models recently introduced in the literature are evaluated for the prediction of long-term effects of source depletion under natural gradient flow. These models are simple in form (a power function equation is an example) but are shown here to serve as mathematical analogs to complex multiphase flow and transport simulators. The spill and subsequent dissolution of DNAPLs was simulated in domains having different hydrologic characteristics (variance of the log conductivity field=0.2, 1 and 3) using the multiphase flow and transport simulator UTCHEM. The dissolution profiles were fitted using four analytical models: the equilibrium streamtube model (ESM), the advection dispersion model (ADM), the power law model (PLM) and the Damkohler number model (DaM). All four models, though very different in their conceptualization, include two basic parameters that describe the mean DNAPL mass and the joint variability in the velocity and DNAPL distributions. The variability parameter was observed to be strongly correlated with the variance of the log conductivity field in the ESM and ADM but weakly correlated in the PLM and DaM. The DaM also includes a third parameter that describes the effect of rate-limited dissolution, but here this parameter was held constant as the numerical simulations were found to be insensitive to local-scale mass transfer. All four models were able to emulate the characteristics of the dissolution profiles generated from the complex numerical simulator, but the one-parameter PLM fits were the poorest, especially for the low heterogeneity case.     

Online update of model state and parameters of a Monte Carlo atmospheric dispersion model by using ensemble Kalman filter

For an atmospheric dispersion model designed for the assessment of nuclear accident consequences, some uncertain model parameters, such as source term and weather conditions, may influence the reliability of model predictions. In this respect, good estimations of both model state and uncertain parameters are required. In this paper, an ensemble Kalman filter (EnKF) based method for simultaneous state and parameter estimation, using off-site radiation monitoring data, is presented. This method is based on a stochastic state space model, which resembles the parameter errors with stochastic quantities. Three imperfect parameters, including the source release rate, wind direction and turbulence intensity were perturbed simultaneously, and multiple parameter estimation were performed. Having been tested against both simulated and real radiation monitoring data, the method was found to be able to realistically reconstruct the real scene of dispersion, as well as the uncertain parameters. The estimated parameters given by EnKF nicely converge to the true values, and the method also tracks the temporal variation of those parameters.