Distribution Of Saturated Hydraulic Conductivity Research Articles

Incorporating machine learning models and remote sensing to assess the spatial distribution of saturated hydraulic conductivity in a light-textured soil

Saturated soil hydraulic conductivity (Ksat) is a key component in hydrogeology and water management. This study aimed at evaluating popular tree-based machine learning algorithms (Random forest (RF), Quantile random forest (QRF), Cubist (Cu), and Decision tree regression (DTr)) to assess the spatial distribution of Ksat in a sandy agricultural field. Soil surface reflectance derived from Landsat-8 (OLI/TIRS) (several remotely sensed data including original surface reflectances of spectral bands and 22 remote sensing indices) as well as limited ground measured soil data were used as predictor covariates. Using collected disturbed and undisturbed soil samples, physicochemical properties (Ksat, porosity, organic matter, and texture contents) were determined. Based on novel supervised feature selection, covariates including Landsat-8 spectral Band2, Band4, Band6, and Band7, normalized difference pond index (NDPI), normalized difference vegetation index (NDVI), and silt content were identified as the most important factors in Ksat prediction. Variable importance analysis showed Band7 and Band6 were explaining 54% of the total Ksat variation. The model evaluation, using five statistics cretria, Taylor diagram and the Kruskal–Wallis (KW) test, demonstrates the outperformance of RF being followed by QRF, Cu, and DTr models. Accordingly, the RF method combined with an optimized sampling approach provides the most accurate digital soil Ksat map. The uncertainty analysis showed no significant different trend in Ksat predictions by applying more dense datasets confirming original-limited data (n = 28) was efficient and sufficient to derive a reliable Ksat-map. The developed approach, which can be scaled up at a large scale, seems to be useful in modelling water flow and solute transport for water and nutrient management purposes toward precision agriculture.

Numerical assessments of recharge-dominated groundwater flow and transport in the nearshore reclamation area in western Taiwan.

This study employed experimental and numerical methods to assess the behavior of conservative solute transport for a selected temporary solid waste site in a reclamation area in western Taiwan. Calibrating a site-specific numerical model, finite element model of water flow through saturated-unsaturated media (FEMWATER), relies on observations from field- and laboratory-scale hydraulic tests and spatial-temporal monitoring. The field-scale experiment used a modified hydraulic tomography survey (MHTS) to identify near surface aquifer stratifications and estimate the distribution of saturated hydraulic conductivity. The pressure plate experiments provided parameters for the van Genuchten soil characteristic model. Sensitivity analyses were then conducted based on varied recharge rates and dispersivities applied to the calibrated model. Observations of groundwater levels and salinity in the wells indicated that the regional groundwater flow was from southeast to northwest. In addition, a shallow freshwater layer was noted in the study area. The tidal-induced amplitudes for water level fluctuation in the wells ranged from 2 to 20cm, depending on their distance from the seawater body. MHTS showed clear stratification, similar to that of well loggings at the storage site. The hydraulic conductivity at the test site ranged from 8 to 10m/day, which is close to that obtained from the laboratory falling head test. The results of particle-tracking modeling showed that the critical recharge rate for the site needed to enhance plume traveling is 1000mm/year. The increase in dispersivity values induced a decrease in plume travel time of up to 1000days from the site to the coastal line. A special case for pulse releasing solute at the site shows that the key factor in controlling plume migration is the recharge rate. This is due to the low natural head gradient in the reclamation area. The results therefore suggest that a land drainage system near the site can play an important role in contaminant transport in the reclamation area.

Hydraulic conductivity of active layer soils in the McMurdo Dry Valleys, Antarctica: Geological legacy controls modern hillslope connectivity

Spatial variability in the hydraulic and physical properties of active layer soils influences shallow groundwater flow through cold-desert hydrological systems. This study measures the saturated hydraulic conductivity and grain-size distribution of 90 soil samples from the McMurdo Dry Valleys (MDV), Antarctica—primarily from Taylor Valley—to determine what processes affect the spatial distribution of saturated hydraulic conductivity in a simple, mineral-soil-dominated natural hillslope laboratory. We find that the saturated hydraulic conductivity and the grain-size distribution of soils are organized longitudinally within Taylor Valley. Soils sampled down-valley near the coast have a higher percentage of fine-sized sediments (fine sand, silt, clay) and lower saturated hydraulic conductivities than soils collected up-valley near Taylor Glacier (1.3×10−2 vs. 1.2×10−1cm/s). Soils collected mid-valley have intermediate amounts of fines and saturated hydraulic conductivity values consistent with a hydrogeologic gradient spanning the valley from high inland to low near the coast. These results suggest the organization of modern soil properties within Taylor Valley is a relict signature from past glaciations that have deposited soils of decreasing age toward the mouth of the valley, modified by fluvial activity acting along temporal and microclimate gradients.

Effects of heterogeneity distribution on hillslope stability during rainfalls

The objective of this study was to investigate the spatial relationship between the most likely distribution of saturated hydraulic conductivity (Ks) and the observed pressure head (P) distribution within a hillslope. The cross-correlation analysis method was used to investigate the effects of the variance of lnKs, spatial structure anisotropy of lnKs, and vertical infiltration flux (q) on P at some selected locations within the hillslope. The cross-correlation analysis shows that, in the unsaturated region with a uniform flux boundary, the dominant correlation between P and Ks is negative and mainly occurs around the observation location of P. A relatively high P value is located in a relatively low Ks zone, while a relatively low P value is located in a relatively high Ks zone. Generally speaking, P is positively correlated with q/Ks at the same location in the unsaturated region. In the saturated region, the spatial distribution of Ks can significantly affect the position and shape of the phreatic surface. We therefore conclude that heterogeneity can cause some parts of the hillslope to be sensitive to external hydraulic stimuli (e.g., rainfall and reservoir level change), and other parts of the hillslope to be insensitive. This is crucial to explaining why slopes with similar geometries would show different responses to the same hydraulic stimuli, which is significant to hillslope stability analysis.

Runoff–infiltration partitioning using an upscaled Green–Ampt solution

AbstractA new set of formulae for calculating regionally averaged infiltration rates into heterogeneous soils is presented. The solutions are based upon an upscaled approximation of the explicit Green‐Ampt (GA) infiltration solution, and require specification of the spatial distribution of saturated hydraulic conductivity and/or initial soil water deficit in the sub‐basin. The resultant areal averaged infiltration formulae, which ignore the impacts of run on or spatial correlation, are easily integrated into existing distributed surface water schemes, and can also be used to calculate saturated soil surface area. The impacts of preferential flow may be investigated through the use of a bimodal conductivity distribution. The solutions are tested against Monte Carlo simulations and assessed for accuracy. Interesting results are obtained regarding the impacts of upscaling on GA infiltration, most notably that the cumulative infiltration is most impacted by low‐conductivity soils and that calibration of the standard (point‐scale) GA equation to basin‐scale hydrographs will lead to an underestimation of average system hydraulic conductivity. Copyright © 2010 John Wiley & Sons, Ltd.

Testing a Grid‐Based Soil Erosion Model across Topographically Complex Landscapes

This study was conducted to evaluate the overall performance of the Precision Agricultural‐Landscape Modeling System (PALMS) for calculating runoff and soil loss under cropped conditions. The PALMS model uses a lognormal distribution of saturated hydraulic conductivity across the fields to simulate typical soil heterogeneity within soil texture classes. Runoff and soil loss data were collected in three farm fields for a total of 75 runoff events during 2 yr under six cropping scenarios (alfalfa [Medicago sativa L.] and corn [Zea mays L.] no‐tilled, corn and soybean [Glycine max (L.) Merr.] moldboard plowed, and alfalfa and corn chisel plowed). For individual storms, calculated runoff and sediment loss from PALMS were compared with corresponding measurements for each farm during the entire cropping season. The coefficient of determination (r2) between runoff calculations and measurements was 0.84. The r2 between soil loss calculations and measurements with the storm‐by‐storm simulations during both seasons was 0.78. Based on these continuous simulation results, the PALMS calculations appear to have lower relative errors with large events than small events, a desirable result because large events are most important in assessing the environmental consequences of management practices.

A Geostatistical Inverse Method for Variably Saturated Flow in the Vadose Zone

A geostatistical inverse technique utilizing both primary and secondary information is developed to estimate conditional means of unsaturated hydraulic conductivity parameters (saturated hydraulic conductivity and pore size distribution parameters) in the vadose zone. Measurements of saturated hydraulic conductivity and pore size distribution parameters are considered as the primary information, while measurements of steady state flow processes (soil‐water pressure head and degree of saturation) are regarded as the secondary information. This inverse approach relies on the classical linear predictor (cokriging) theory and takes the advantage of the spatial cross correlation between the soil‐water pressure head and each of the following: degree of saturation, saturated hydraulic conductivity, and a pore size distribution parameter. Using an approximate perturbation solution for steady, variably saturated flow under general boundary conditions, the cross covariances between the primary and secondary information are derived. The approximate solution is formulated on the basis of a first‐order Taylor series expansion of a discretized finite element equation. The sensitivity matrix in the solution is evaluated by an adjoint state sensitivity approach for flow in heterogeneous media under variably saturated conditions. Through several numerical examples the inverse model demonstrates its ability to improve the estimates of the spatial distribution of saturated hydraulic conductivity and pore size distribution parameters using the secondary information.

Quantification and modeling of macropore drainage

A series of experiments on undisturbed soil columns, followed by interpretation using simulation modeling, were conducted to estimate the influence of soil structure upon macroporosity and water flow. Four large soil columns taken from Niagara silt loam and Rhinebeck silty clay loam profiles were placed on a grid sampler to obtain 25 subsample outflow measurements per column. Columns were saturated from the bottom and saturated hydraulic conductivity was measured under shallow ponding. Columns were then gravity drained while outflow was collected. Saturated hydraulic conductivity and drainage volume were lognormally distributed over the column bottom area. Drainage volumes were not significantly different among columns or soils, at the 5% level. Analysis of the drainage rates of the columns indicated that soil texture influenced macropore geometry by controlling soil structure and plant rooting. Geometric scaling factors from the distribution of saturated hydraulic conductivity, applied to conductivity and potential in simulations of column drainage, did not reproduce the observed distribution of drainage volume. When additional normally-distributed coefficients were applied to porosity, the simulated drainage distributions were not significantly different from observed drainage distributions, at the 5% level.

EVALUATION OF SPATIAL DISTRIBUTION OF HYDRAULIC CONDUCTIVITY USING EFFECTIVE POROSITY DATA

The use of spatial distribution of effective porosity (Φe) to estimate the distribution of saturated hydraulic conductivity (K2) is evaluated on five new soils and on a combination of soils. The K2 is related to Φe by a generalized Kozeny-Carman equation. This equation is then combined with scaling

Macroporosity to Characterize Spatial Variability of Hydraulic Conductivity and Effects of Land Management

AbstractTo develop simplified methods of hydraulic characterization of field soils and effects of management, frequency distribution of macroporosity (or effective porosity) in a soil is investigated as a measure of its saturated hydraulic conductivity distribution. The effective porosity (φe) of a soil is related to its saturated hydraulic conductivity (Ks) by a generalized Kozeny‐Carman equation. The exponent of this relationship is assumed to vary within a narrow range (value of 4 or 5). The equation is then combined with scaling theory to derive the frequency distribution of Ks scaling factors from the φe distribution. These concepts are tested on experimental data for two widely different soils, a mollisol and an oxisol. The φe is defined as total porosity minus soil water content at −33 kPa pressure head. The exponent of the Ks‐φe relationship is found to be nearly 4 for the soil‐core data of both soils, while for a smaller set of in‐situ field data for oxisol, which was within a narrow range of φe, the value of the exponent was smaller. There was a considerable scatter in the relationships. However, with the exponent set equal to 4 or 5 the distribution of Ks scaling factors derived from φe distribution closely matched the experimental Ks‐derived distribution. The approach has a promise for large‐scale applications.

Statistical and Stochastic Analyses of Hydraulic Conductivity and Particle‐Size in a Fluvial Sand

AbstractAn untilled medium‐grained fluvial sand near Socorro, N. Mex., was sampled in horizontal and vertical transects to study the statistical and stochastic properties of particle‐size parameters and saturated hydraulic conductivity. Hydraulic conductivity is log‐normally distributed, whereas the 10% finer, median, and geometric mean particle sizes are normally distributed. The strongest correlation between hydraulic conductivity and particle‐size distribution parameters is that of the log of hydraulic conductivity with the 10% finer particle size. Stochastic analyses using the autocorrelation function and spectrum indicate that the log of hydraulic conductivity and particle size are characterized by dissimilar spatial correlation structures in the vertical directions. In general, particle size is more structured, regular, and predictable and shows a close similarity with the stratigraphy as observed in the field. On the other hand, hydraulic conductivity in the vertical direction may best be modeled as a simple random variable. Variogram and kriging analyses indicate that both hydraulic conductivity and particle size are relatively isotropic in the horizontal plane and that marked similarities in spatial structure exist in this plane. The spatial distribution of saturated hydraulic conductivity in the horizontal plane is estimated reasonably well using the empirical relationship between particle size and conductivity along with the kriged estimates of the 10% finer particle size.