Variability Of Soil Hydraulic Conductivity Research Articles

Probabilistic analysis of land subsidence due to pumping by Biot poroelasticity and random field theory

Land subsidence is a global problem in urban areas. The main cause of land subsidence is the pumping of subsurface water. It is of great significance to study the subsurface settlement and water flow of the lands due to pumping. In this study, the probabilistic analysis of land subsidence due to pumping is performed by Biot’s poroelasticity and random field theory based on a case study. The results show that the change of deformation of the aquifer is far less significant than the hydraulic head over the years. When considering the spatial variability of soil strength, the land subsidence suffers from great uncertainty when the correlation length is large. Nevertheless, the spatial variability of soil strength on the uncertainty of hydraulic head can be ignored. When considering the spatial variability of soil hydraulic conductivity, the uncertainty of the hydraulic head is mainly located near the bedrock and increases markedly along with the rise of the correlation length. Time is another important factor to increase the uncertainty of the hydraulic head. However, its contribution to the uncertainty of displacement is insignificant.

Assessment of hydraulic conductivity improvement due to vibration application at riverbank

Groundwater abstraction is a process of obtaining subsurface water sources for variety purpose of consumption. However, due to long and continuous pumping, the efficiency might decrease because of soil clogging. This decreased can be quantified and reflected as the change of hydraulic conductivity (K) values at the pumping site. This study aims to assess the variability of soil hydraulic conductivity at groundwater pumping site and also to study the effectiveness of vibration method to improve the hydraulic conductivity by comparing the result of before and after vibration is applied. The study was carried out by measuring the K values using slug test at wells MW01 and MW02 with two durations of vibration which were 45 minutes and 60 minutes. The result shows that values of hydraulic conductivity of the soil were found to have increased for both MW0l and MW02 wells. On first trial, the hydraulic conductivity increases for MW0l and MW02 are 16.7% and 39.3% while on second trial, the percentage increases for MW01 and MW02 are 54.3% and 11.1% respectively. Although the change for MW02 decreased for 60 minutes vibration, it can still be noted as there is a positive impact of vibration to the K value and further extensive data collection will be able to provide better assessment. Thus, it has been proven that the vibration method can be effective in reducing the soil clogging effect and also able to improve the hydraulic conductivity of the soil.

Spatial variability of soil hydraulic conductivity and runoff generation types in a small mountainous catchment

As an important soil property, saturated hydraulic conductivity (Ks) controls many hydrological processes, such as runoff generation types, soil moisture storage and water movement. Because of the extremely harsh natural environmental conditions and soil containing a significant fraction of gravel fragments in high-elevation mountainous catchments, the measurement data of Ks and other soil properties are seriously lacking, which leads to poor understanding on its hydrological processes and water cycle. In this study, the vertical variation (0–150 cm) of Ks and other soil properties from 38 soil profiles were measured under five different land cover types (alpine barren, forest, marshy meadow, alpine shrub and alpine meadow) in a small catchment in Qilian Mountains, northwestern China. A typical characteristic of soil in mountainous areas is widespread presence of rock and gravel, and the results showed that the more rock and gravel in the soil, the higher Ks and bulk density and the lower the soil capillary porosity, field water capacity and total porosity. The Ks of the lower layer with rock and gravel (18.49 ± 10.22 mm·min−1) was significantly higher than that of the upper layer with relatively fine textured soil (0.18 ± 0.18 mm-min−1). The order of values of the Ks in different land cover types was alpine barren, forest, alpine shrub, marshy meadow and alpine meadow, and the values of the Ks in the alpine barren were significantly higher than those of other land covers. Most rainfall events in the research catchment had low rain intensity (<0.04 mm·min−1), and deep percolation (DP) was the dominant runoff generation type. When the rainfall intensity increased (0.11 mm·min−1), subsurface stormflow (SSF) appeared in the alpine meadow. Infiltration excess overland flow (IOF), SSF and DP existed simultaneously only when the rainfall intensity was extremely high (1.91 mm·min−1). IOF and SSF were almost never appeared in the alpine barren because of high Ks. The alpine barren was the main runoff-contributed area in the mountainous catchment because of high Ks and low water-holding capacity, and the alpine shrub and meadow showed more ecological functions such as natural water storage and replenishment pool than contribution of runoff.

Assessing field-scale variability of soil hydraulic conductivity at and near saturation

Saturated hydraulic conductivity (Ks) is a crucial hydraulic property for assessing soil water dynamics. Understanding the spatial variability of Ks in a field is important for site-specific resource management. However, direct measurement of hydraulic conductivity K as a function of soil water pressure head h [K(h)] is time consuming and laborious. Alternatively, pedotransfer functions (PTFs) have been developed to predict Ks indirectly based on more easily measurable soil properties. Although PTFs have been used for decades, their validity for estimating the field-scale spatial variability of Ks remains unclear. The objectives of this study were to characterize the spatial pattern of K(h) at and near saturation in an agricultural field by a coregionalization technique, and in comparison, to evaluate the performance of ROSETTA PTF in characterizing the spatial variability of K(h) at the field scale. Surface soil (7–13 cm) K(h) in the vertical direction was measured at 48 locations in a 71-m by 71-m grid within a no-till farmland. Apparent electrical conductivity was densely measured using a contact sensor Veris 3150 and used as ancillary variable in a coregionalization approach. Experimental semivariograms and cross semivariograms were derived and applied in cokriging to generate K(h) maps. Geostatistical analysis presented similarities in maps of measured K(h) with ROSETTA-predicted K(h) data for a matric potential of −10 cm. However, the strong spatial heterogeneity of measured Ks, which was caused by macropores, observed in the field was not captured by ROSETTA estimates. The results indicated that texture dominated PTFs like ROSETTA, in which soil structure is not considered, might be useful in characterizing the spatial pattern of unsaturated hydraulic conductivity rather than Ks. Field scale Ks maps based on PTF estimates should be evaluated carefully and handled with caution.

Determination of Spatial and Temporal Variability of Soil Hydraulic Conductivity for Urban Runoff Modelling

Soil hydraulic conductivity has a direct influence on infiltration rate, which is of great importance for modelling and design of surface runoff and stormwater control measures. In this study, three measuring techniques for determination of soil hydraulic conductivity were compared in an urban catchment in Ljubljana, Slovenia. Double ring (DRI) and dual head infiltrometer (DHI) were applied to measure saturated hydraulic conductivity (Ks) and mini disk infiltrometer (MDI) was applied to measure unsaturated hydraulic conductivity (K), which was recalculated in Ks in order to compare the results. Results showed significant differences between investigated techniques, namely DHI showed 6.8 times higher values of Ks in comparison to DRI. On the other hand, Ks values obtained by MDI and DRI exhibited the lowest difference. MDI measurements in 12 locations of the small plot pointed to the spatial variability of K ranging between 73%–89% as well as to temporal variability within a single location of 27%–99%. Additionally, a reduction of K caused by the effect of drought-induced water repellency was observed. Moreover, results indicate that hydrological models could be enhanced using different scenarios by employing a range of K values based on soil conditions.

An Appraisal on the Interpolation Methods Used for Predicting Spatial Variability of Field Hydraulic Conductivity

Knowledge of spatial variability of soil hydraulic conductivity is a key parameter for hydrological modeling. Spatial variability of soil hydraulic conductivity, Ks is attributed to soil heterogeneities associated with texture/structure, different initial conditions, meteorological changes, and clogging. The spatial variability is quantified by employing interpolation methods to point measurements performed in the field. There are not many studies reported in the literature that deals with the critical evaluation of the relative performance of different interpolation methods for predicting spatial variability of hydraulic conductivity. The primary objective of this study is to perform a critical evaluation of five interpolation methods, namely Kriging, Inverse Distance Weighted, Natural Neighbor, Spline and Trend for the spatial prediction of hydraulic conductivity. The accuracy of different methods was assessed by comparing the predicted values with the measured hydraulic conductivity of selected locations. It was noted that the Kriging method with exponential model gave a better spatial prediction as compared to other methods. The spatial variability of Ks was found to be in the same pattern as that of the percentage variation of the sand fraction for both the sites investigated in this study. It was further noted that the prediction of Ks was found to be more precise for those stations with a higher percentage of sand. A sudden transition of soil type from sand to silt was found to influence the accuracy of spatial prediction.

Field scale hydraulic conductivity and compressibility of organic clays

This paper uses the results of an extensive subsurface investigation performed along the Inner Harbor Navigational Canal in New Orleans, Louisiana to identify the scale effect of soil hydraulic conductivity (K) and compressibility (mv) for geotechnical and geoenvironmental analyses. The magnitude and variability of soil hydraulic conductivity and compressibility parameters were obtained from laboratory 1-D consolidation and permeameter tests, CPTu dissipation tests, field piezometer slug tests, and multiple well pump tests. The geometric means of horizontal hydraulic conductivity (Kh) measured by the laboratory permeameter, slug, and field pump tests are 2.5×10−7, 1.6×10−6, and 1.3×10−5cm/s, respectively. This represents a scale effect of about 50 times when increasing the sample volume tested from the laboratory to field scale. The uncertainty in vertical hydraulic conductivity (Kv), Kh, and mv values was determined using a coefficient of variation, which ranges from 0.34 to 0.73. While Kh is scale dependent, a comparison of mv evaluated from field pump and 1-D consolidation tests indicates that sample volume does not significantly impact measured values of mv, which signifies that laboratory consolidation tests can be used to predict field scale compressibility.

Spatial information of soil hydraulic conductivity and performance of cokriging over kriging in a semi-arid basin scale

Unlike the studies in small parcels by systematic measurements, the spatial variability of soil properties is expected to increase in those over relatively large areas or scales. Spatial variability of soil hydraulic conductivity (Kh) is of significance for the environmental processes, such as soil erosion, plant growth, transport of the plant nutrients in a soil profile and ground water levels. However, its variability is not much and sufficiently known at basin scale. A study of testing the performance of cokriging of Kh compared with that of kriging was conducted in the catchment area of Saraykoy II Irrigation Dam in Cankiri, Turkey. A total of 300 soil surface samples (0–10 cm) were collected from the catchment with irregular intervals. Of the selected soil properties, because the water-stable aggregates (WSA) indicated the highest relationship with the hydraulic conductivity by the Pearson correlation analysis, it is used as an auxiliary variable to predict Kh by the cokriging procedure. In addition, the sampling density was reduced randomly to n = 175, n = 150, n = 75 and n = 50 for Kh to determine if the superiority of cokriging over kriging would exist. Statistically, the results showed that all reduced Kh was as good as the complete Kh when its auxiliary relations with WSA were used in cokriging. Particularly, the results of the “Relative Reduction in MSE” (RMSE) revealed that the reduced data set of n = 75 produced the most accurate map than the others. In this basin-scaled study, there was a clear superiority of the cokriging procedure by the reduction in data although a very undulating topography and topographically different aspects, two different land uses with non-uniform vegetation density, different parent materials and soil textures were present in the area. Hence, using the statistically significant auxiliary relationship between Kh and WSA might bring about a very useful data set for watershed hydrological researches.

Reply to the discussion by Chen et al. on “Wetting front advancing column test for measuring unsaturated hydraulic conductivity”Appears in Canadian Geotechnical Journal, 47(10): 1159–1161.

The authors appreciate R. Chen, Z.H. Li, and J.H. Li for their interest in and valuable thoughts about the paper. Our paper presents an efficient method for measuring unsaturated hydraulic conductivity of soil. The proposed method utilizes water contents recorded at one monitoring section to calculate the hydraulic conductivity with the help of instantaneous wetting front advancing velocity. In the new method, a wetting zone (i.e., the zone between the monitoring section and the wetting front) is assumed to advance a distance of Dh in a small time step of Dt. In the wetting zone, the water content contours are assumed to be stationary. In this small time step, the water content change in the wetting zone is assumed to be very small compared with the water content change due to the advancement of the wetting zone, namely QB calculated using eq. [8] in Li et al. (2009). As mentioned in the Discussion, the water content profile advances along the soil column in a way similar to wave propagation. Such propagation is under constant boundary conditions both at the front and back of the wetting zone. In our experiments and the simulations in the Discussion, the water content at the front of the wetting zone is lower than the residual water content and the hydraulic conductivity at the front of the wetting zone is extremely low (e.g., lower than 10–13 m/s). Hence, the boundary conditions (i.e., the water content, suction, and hydraulic conductivity along the advancing path) at the front of the wetting zone are considered to be unchanged in the small time step. However, the boundary conditions at the back of the wetting zone vary during the wetting process. Consider a wetting zone with a suction equivalent to the air-entry value (AEV) at the back. If the wetting front advances a distance of Dh in Dt, the change in suction at the back of the wetting zone will be Du = gwDh where gw is the unit weight of water. The relative change of suction will then be Du/AEV. If the testing material is a coarse sand or gravel, the AEV is usually small and Du/AEV could be large. Such a large change induced by gravity in the boundary condition at the back of the wetting front will change the wetting front advancing process. For example, in the capillary experiment conducted on GW-GM with sand, the observed wetting front could only reach 113 mm above the water table. This is because the dominant pores in the GW-GM with sand are large, i.e., above 1 mm (Zhang and Li 2010). Similar problems should be considered in the numerical simulation of flow in uniform sand. Referring to Fig. D1 in the Discussion, the AEV of the uniform sand is about 3 kPa (i.e., 300 mm water head). During the capillary rise process, the final water content in a wetted section of the sand column will decrease gradually when the height is above 300 mm, approaching the water content at the hydrostatic state. Hence, the boundary condition at the back of the wetting zone changes during the capillary process. For such a soil, the wetting front advancing experiment should be carried out in a horizontal soil column, in which the effect of gravity on the boundary condition is less significant. For clays, the AEV values are likely high (say, above 100 kPa or 10 000 mm head); the change of suction, Du, at the back of the wetting zone is negligible. In this case, the boundary condition at the back of the wetting zone can be considered to be constant. Referring to Fig. D2 in the Discussion, the wetting front advancing velocities are indeed different if different water contents are used to define the wetting front. Let us consider the wetting front advancing velocities in silty clay in Fig. D2 at any instant. The slopes of the three curves may differ by 2 times at >3 104 s. That is to say, the calculated hydraulic conductivity may differ within 2 times when different definitions of the wetting front are used. The error is in reality much smaller when a consistent set of definitions is followed. Considering the high variability of soil hydraulic conductivity, such an error may be considered acceptable in engineering practice. Received 31 May 2010. Accepted 16 August 2010. Published on the NRC Research Press Web site at cgj.nrc.ca on 1 October 2010.

The indirect estimation of saturated hydraulic conductivity of soils, using measurements of gas permeability. I. Laboratory testing with dry granular soils

A comprehensive knowledge of soil hydraulic conductivity is essential when modelling the distribution of soil moisture within soil profiles and across catchments. The high spatial variability of soil hydraulic conductivity, however, necessitates the taking of many in situ measurements, which are costly, time-consuming, and labour-intensive. This paper presents an improved method for indirectly determining the saturated hydraulic conductivity of granular materials via an in situ gas flow technique. The apparatus employed consists of a cylindrical tube which is embedded in the soil to a prescribed depth. Nitrogen at a range of pressures was supplied to the tube and allowed to escape by permeating through the soil. A 3-dimensional, axisymmetric, steady-state, finite element flow model was then used to determine the value of the soil intrinsic gas permeability which produces the best fit to the pressure–air flow data. Saturated hydraulic conductivities estimated from the application of the gas flow technique to 5 granular soils covering a wide range of permeabilities were in close agreement with values determined using a conventional permeameter. The results of this preliminary study demonstrate the potential of this approach to the indirect determination of saturated hydraulic conductivity based on measurement of gas flow rates in granular and structured soils.

An experimental analysis of hydrodynamic behaviour on soils and hillslopes in a subtropical mountainous environment (Western Sierra Madre, Mexico)

Many soils parameters and features play a role in explaining the hydrodynamic behaviour of a watershed. Textural data are relatively easy to obtain and to spatialise, due to their low spatial variability. Inversely, structural features usually exhibit great spatial variability and thus, are difficult to interpolate and to integrate in the framework of a hydrologic model. However, structural characteristics of the soils seem to have a greater influence on catchment hydrological balance than the textural ones. The objectives of this study were to identify which parameters control the soil surface hydrological behaviour and quantify the magnitude of their spatial variability. Measurements of soils characteristics, including bulk density and hydraulic conductivity, were carried out in five watersheds in the Western Sierra Madre (Northern Mexico). It is shown in this study that on a natural grassland under subtropical mountainous climate, spatial variability of soil hydraulic conductivity is almost as high at a 1-m 2 scale as at a 1-km 2 one. The main discriminating variables which account for the spatial variability appeared to be the lithology and overall the soil surface features, both being related. The latter seems to be a synthetic indicator of basin hydrodynamic behaviour, and to be easier than others to spatialise.

Spatial variability of soil hydraulic conductivity along a tropical rainforest catena

We investigate the spatial variability of saturated hydraulic conductivity ( K sat) along a tropical rainforest catena, which consists of a Typic Kandiudult (Latossolo Vermelho Distrofico argissolico) and Plinthic Hapludox (Latossolo Amarelo Distrofico tipico). The former soil type extends from midslope to interfluve and has a high clay content throughout the profile, whereas the latter soil type extends from the midslope to valley bottom and only has a high clay content at depths >90 cm. We measured K sat along a transect at depths of 20, 30, 50 and 90 cm with a compact, constant-head permeameter. K sat is not significantly different ( α=0.10) between these soil types at any depth except for 90 cm. Ordinary and robust linear regression models with distance from the interfluve as in the independent variable showed no significant change in K sat as a function of topography. Loess regression showed some dependency of K sat on topography only at the 90-cm depth. Semivariograms showed no apparent spatial structure in K sat at distances ≥25 m for all depths. We conclude that the strong topography dependence of soil types along this catena and, hence, primary soil attributes, is not reflected in a similar dependence of K sat, and tentatively attribute this lack of dependence to the overriding influence of bioturbation-controlled macroporosity. We outline a framework for detecting possible K sat–topography relationships based on the distinction between bioturbation-controlled nonstructural macroporosity and mineralogy-controlled structural macroporosity.

Spatial and temporal variability of soil hydraulic conductivity in relation to soil water distribution, using an exponential model.

An internal drainage experiment was conducted to examine soil water content variability in space and in time. It is shown that the flux-gradient model used to describe water flow in field soil profiles, based on the Darcy–Buckingham equation, yielded results of extreme variability and questionable validity. The problem lies in the representativeness of a site due to soil variability, horizontally and vertically in time, which added to the character of the hydraulic conductivity versus soil water content relation, which in many cases can be approximated by exponential functions, leads to coefficients of variation up to 170% in the estimation of soil hydraulic conductivity values.

Measuring the Spatial Variability of Soil Hydraulic Conductivity Using an Automatic Neutron Moisture Gauge

AbstractSoil internal drainage was measured along a 100‐m transect with 20 neutron probe access tubes at 5‐m intervals using an automatic neutron moisture gauge and a tensiometer data logger. Geostatistical analysis of the measurement results (in terms of hydraulic conductivity, K, vs. water content, θ) at depths of 60 and 90 cm, showed no autocorrelation among the sites. Measurement results related to depths of 120 and 150 cm were deleted because of the lack of a unit hydraulic gradient. Variance analysis indicated that the 60‐ and 90‐cm layers values could be considered together as a unique soil layer. The exponential regression equation computed from 240 K(θ) pairs, gave correlation coefficient of 0.90 for this soil layer. The K variation coefficient between 32 and 40% θ was 75% for the 60‐ and 90‐cm soil depths. This value is consistent with other published findings.

Statistical Analysis of Salinity and Texture Effects on Spatial Variability of Soil Hydraulic Conductivity

AbstractA statistical analysis that identifies the dominant factors responsible for the spatial variability of the saturated conductivity (Ks) in a selected field is presented. The variables are considered random functions of the space coordinates. Two types of stationarity are investigated: constant mean and stationary variogram (stationarity of order 2) and trend of the means (nonstationarity of the mathematical expectation) with stationary covariances. Linear models of statistical dependence were used. Elimination of factors of minor importance was based on correlation analysis. Electrical conductivity (EC) and percent sand were the most important independent variables, whereas Ks was the dependent variable. The analysis showed that soil salinity (EC) accounted for only 10 to 15% of the variability of Ks texture (percent sand) explained 25 to 45% of the Ks variability, and 10 to 15% of the variability was explained by the interaction between salinity and texture. Various soil factors other than salinity and texture accounted for 30 to 50% of the variability in Ks. Semivariograms and covariograms of Ks, EC, and percent sand did not have a sill because of a significant horizontal linear trend. Calculations showed that the trend accounted for about a half of the variability of the original data. Semivariograms and covariograms of a new population of residuals after extracting the trend gave values of the sills equal to the variances. The integral scale of the residuals of Ks and percent sand was estimated to be about 15 to 20 m, whereas salinity (EC) did not display a spatial structure. The results can be generalized for other studies with different values of variances and covariances of soil salinity and soil texture.