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Estimation of soil waterfront velocity and saturated hydraulic conductivity in a Hele-Shaw apparatus with an optical flow method
Abstract
The estimation of saturated hydraulic conductivity is a key parameter for studying the water flow in the unsaturated zone of the soil. In this work, a combined modelling approach of the waterfront movement is elaborated, integrating a physical analogue type device with image analysis. A customized Hele-Shaw apparatus is designed for the wetting process visual inspection, while an optical flow algorithm is used for the numerical calculation of flow velocity and saturated hydraulic conductivity values at a pixel level of the image processing. Saturated hydraulic conductivity values estimated by the proposed method are in close agreement with values found in the literature under similar soil conditions. Also, the proposed method seems to be a useful tool for a comprehensive analysis of the waterfront movement in the vadose zone.
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The saturated soil hydraulic conductivity (Ksat) is a key parameter in many hydrological and climate models. Ksat values are primarily determined from basic soil properties and may vary over several orders of magnitude. Despite the availability of Ksat datasets in the literature, significant efforts are required to combine the data before they can be used for specific applications. In this work, a total of 13 258 Ksat measurements from 1908 sites were assembled from the published literature and other sources, standardized (i.e., units made identical), and quality checked in order to obtain a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most regions across the globe, with the highest number of Ksat measurements from North America, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11 584 measurements), bulk density (11 262 measurements), soil organic carbon (9787 measurements), moisture content at field capacity (7382), and wilting point (7411) are also included in the dataset. To show an application of SoilKsatDB, we derived Ksat pedotransfer functions (PTFs) for temperate regions and laboratory-based soil properties (sand and clay content, bulk density). Accurate models can be fitted using a random forest machine learning algorithm (best concordance correlation coefficient (CCC) equal to 0.74 and 0.72 for temperate area and laboratory measurements, respectively). However, when these Ksat PTFs are applied to soil samples obtained from tropical climates and field measurements, respectively, the model performance is significantly lower (CCC = 0.49 for tropical and CCC = 0.10 for field measurements). These results indicate that there are significant differences between Ksat data collected in temperate and tropical regions and Ksat measured in the laboratory or field. The SoilKsatDB dataset is available at https://doi.org/10.5281/zenodo.3752721 (Gupta et al., 2020) and the code used to extract the data from the literature and the applied random forest machine learning approach are publicly available under an open data license.
The performance of optical flow estimation is affected by many factors. The impact of illumination changes and video quality degradation in unmanned aerial vehicles videos on optical flow estimation cannot be ignored. Inspired by the human retina’s visual adaptation mechanism, we propose a mechanism for illumination adjustment that imitates retinal processing in order to reduce illumination variation. We further introduce an edge refinement mechanism into optical flow estimation that is based on a weighted neighborhood filtering. The experimental results on public benchmarks inlcuding KITTI 2012, KITTI 2015, MPI Sintel and Middlebury show that the proposed approach is robust on illumination and preserves accurate motion details. Further, experiments on outdoor livestock UAV videos show that the proposed approach implements illumination robustness and preserves the accurate detection of motion edges in other types of video. The performance of the proposed method on public benchmarks and livestock UAV videos demonstrates that the proposed approach improves motion edge accuracy of optical flow fields in varying illumination.
Saturated hydraulic conductivity (K sat) is fundamental to shallow groundwater processes. There is an ongoing need for observed and model validated K sat values. A study was initiated in a representative catchment of the Chesapeake Bay Watershed in the Northeast USA, to collect observed K sat and validate five K sat pedotransfer functions. Soil physical characteristics were quantified for dry bulk density (bdry), porosity, and soil texture, while K sat was quantified using piezometric slug tests. Average bdry and porosity ranged from 1.03 to 1.30 g/cm 3 and 0.51 to 0.61, respectively. Surface soil (0-5 cm) bdry and porosity were significantly (p < 0.05) lower and higher, respectively, than deeper soils (i.e., 25-30 cm; 45-50 cm). bdry and porosity were significantly different with location (p < 0.05). Average soil composition was 92% sand. Average K sat ranged from 0.29 to 4.76 m/day and significantly differed (p < 0.05) by location. Four models showed that spatial variability in farm-scale K sat estimates was small (CV < 0.5) and one model performed better when K sat was 1.5 to 2.5 m/day. The two-parameter model that relied on silt/clay fractions performed best (ME = 0.78 m/day; SSE = 20.68 m 2 /day 2 ; RMSE = 1.36 m/day). Results validate the use of simple, soil-property-based models to predict K sat , thereby increasing model applicability and transferability.
Saturated soil hydraulic conductivity (Ksat) is a key parameter in many hydrological and climatic modeling applications, as it controls the partitioning between precipitation, infiltration and runoff. Ksat values are primarily determined from soil textural properties and soil forming processes, and may vary over several orders of magnitude. Despite availability of Ksat datasets at catchment or regional scale, significant efforts are required to import and bind the data before it could be used for modeling. In this work, a total of 1,910 sites with 13,267 Ksat measurements were assembled from published literature and other sources, standardized, and quality-checked in order to provide a global database of soil saturated hydraulic conductivity (SoilKsatDB). The SoilKsatDB covers most global regions, with the highest data density from the USA, followed by Europe, Asia, South America, Africa, and Australia. In addition to Ksat, other soil variables such as soil texture (11,667 measurements), bulk density (11,151 measurements), soil organic carbon (9,787 measurements), field capacity (7,389) and wilting point (7,418) are also included in the dataset. The results of using the SoilKsatDB to fit Ksat pedotransfer functions (PTFs) for temperate climatic regions and laboratory based soil samples based on soil properties (sand and clay content, bulk density) show that reasonably accurate models can be fitted using Random Forest (best CCC = 0.70 and CCC = 0.73 for temperate and lab based measurements, respectively). However when temperate and laboratory based Ksat PTFs are applied to soil samples from tropical climates and field measurements, respectively, the model performance is significantly lower (CCC = 0.51 for tropical and CCC = 0.13 for field samples). PTFs derived for temperate soils and laboratory measurements might not be suitable for estimating Ksat for tropical regions or field measurements, respectively. The SoilKsatDB dataset is available at https://doi.org/10.5281/zenodo.3752721 and the code used to produce the compilation is publicly available under an open data license.
Classical experimental techniques to determine point values of saturated hydraulic conductivity () are complex and time consuming; therefore, the development of pedotransfer functions, PTFs, to derive from easily available soil properties is of great importance. However, PTFs have been generally developed at the local scale, while hydrological modeling requires estimates at larger scales. A small Austrian catchment, where detailed soil characteristics were available, was selected to address this issue. Values of field-scale saturated hydraulic conductivity (), observed in a number of catchment areas by double-ring infiltrometers, were used to develop two PTFs, one by multiple linear regression (PTF) and one by ridge regression (PTF). Training and validation of the PTFs in the monitored areas indicate that the PTF provides better outcomes with smaller average errors. This suggests that the ridge regression is a valid alternative to the classical multiple linear regression technique. Predictions of by the PTFs in the remaining areas, where infiltration measurements were not performed, were also made to obtain a map of for the whole catchment. Two alternative approaches were used: Method A—soil properties were first interpolated and then the PTFs applied; Method B—the PTFs were first applied to sites with available soil properties and then interpolated. The maps of obtained by the PTF are not representative of the spatial variability. On the other hand, the map generated by the PTF with Method A is consistent with catchment morphology and soil characteristics.
Agricultural expansion in the Kharga Oasis, in the western desert of Egypt, depends strongly on irrigation. Soil hydraulic conductivity is therefore a key property for reclaiming desert land and planning irrigation schemes. Soil samples collected at 10-m intervals in a 120 m by 120 m plot were analysed for hydraulic conductivity together with 12 other basic physical and chemical soil properties. The resulting data were analysed statistically using Pearson correlation, principal component analysis and linear regression. The hydraulic conductivity values varied over four orders of magnitude and, because of the saline–sodic nature of the soil, were about two orders of magnitude smaller than what is generally reported in the literature for similar soil textures. Results showed that the hydraulic conductivity was correlated significantly with soil variables that relate to soil structure, such as wilting point, field capacity and SAR, and less to variables that relate to soil texture, such as silt and clay fractions. Pedotransfer functions for hydraulic conductivity were derived by stepwise multiple linear regression and fitted by residual maximum likelihood. The first model was based directly on soil properties, whereas the second model was based on principal components. Both models showed that part of the variation in hydraulic conductivity encountered in the field could be explained, but with large uncertainty probably resulting from sampling and measurement errors, randomness and soil heterogeneity, or other soil properties that were not observed. The most significant predictors for the first model were wilting point, SAR and silt fraction. The second model used the first two principal components of the soil variables as predictors, the first one related to soil structure and the second to soil texture.
A novel proximal sensing framework for high-resolution soil water content profile retrieval under laboratory conditions is introduced. Constant head upward flow experiments were conducted for a number of soils that cover a wide textural range. The soils were packed into quartz Hele-Shaw cells and the profile was imaged at high temporal frequency with a shortwave infrared (SWIR) camera in the 900-1700 nm electromagnetic domain during upward infiltration of water. The SWIR reflectance recorded for each spatial pixel was converted to soil water content with a recently developed linear physical model. Because of the linearity of the model, its parameters were assumed to be identical at both the pixel and column scales, allowing for simple self-calibration during the experiment. The obtained water content profiles were in good agreement with soil water content data independently measured with a recently developed time domain reflectometry (TDR) array with 1-cm depth resolution. In addition, the accuracy of the soil water content profiles was verified based on the water mass balance. The high spatiotemporal-resolution SWIR reflectance-derived water content profiles allow calculation of water flux densities, which provides a potential new avenue for rapid estimation of soil hydraulic properties and processes via inverse numerical or analytical modeling.
Moving vehicle detection plays an important role in intelligent transportation systems. One of the common methods used in moving vehicle detection is optical flow. However, conventional Horn–Schunck optical flow consumes too much time when calculating dense optical flows so that it cannot meet the real-time requirements. This paper proposes a novel improved Horn–Schunck optical flow algorithm based on inter-frame differential method. In our algorithm, optical flow field distribution is only calculated for pixels with larger gray values in the difference image, while for other pixels we applied the iterative smooth. The number of vehicles in the videos of traffic conditions is counted by setting the virtual loop and detecting optical flow information. To extract the moving vehicle as accurately as possible, we also propose a method to obtain moving vehicle minimum bounding rectangle based on the connected region analysis. Finally, we compare the improved optical flow with other four optical flow algorithms in moving vehicle extraction and vehicle flow detection, from which our method gives a much more accurate result.
Current deformation measurement techniques suffer from limited spatial resolution. In this work, a highly accurate and high-resolution Horn–Schunck optical flow method is developed and then applied to measuring the static deformation of a birdlike flexible airfoil at a series of angles of attack at Reynolds number 100,000 in a low speed, low noise wind tunnel. To allow relatively large displacements, a nonlinear Horn–Schunck model and a coarse-to-fine warping process are adopted. To preserve optical flow discontinuities, a nonquadratic penalization function, a multi-cue driven bilateral filtering and a principle component analysis of local image patterns are used. First, the accuracy and convergence of this Horn–Schunck technique are verified on a benchmark. Then, the maximum displacement that can be reliably calculated by this technique is studied on synthetic images. Both studies are compared with the performance of a Lucas–Kanade optical flow method. Finally, the Horn–Schunck technique is used to estimate the 3-D deformation of the birdlike airfoil through a stereoscopic camera setup. The results are compared with those computed by Lucas–Kanade optical flow, image correlation and numerical simulation.
The hydraulic conductivity function, which is required to solve the Richards equation, is difficult to measure. Therefore prediction methods are frequently used where the shape of the conductivity function is estimated from the more easily measured water retention characteristic. Errors in conductivity estimations can arise either from an invalidity of the prediction model for a given soil, or from an incorrect description of the retention data. This second error source is particularly important for soils with heterogeneous pore systems that cannot be adequately described by the usually used retention functions. To describe the retention characteristics of such soils, a flexible θ(ψ) function was formed by superimposing unimodal retention curves of the van Genuchten (1980) type. By combining this retention model with the conductivity prediction model of Mualem (1976), conductivity estimations for soils with heterogeneous pore systems are obtained. Estimated conductivities by this model and the classical van Genuchten-Mualem method can differ by orders of magnitude. Thus reported disagreements between measured and estimated conductivities may in some cases be due to an inadequate description of the retention data rather than due to a failure of the prediction model.
A new and relatively simple equation for the soil-water content-pressure head curve is described. The particular form of the equation enables one to derive closed-form analytical expressions for the relative hydraulic conductivity, when substituted in the predictive conductivity models of N. T. Burdine or Y. Mualem. The resulting expressions contain three independent parameters which may be obtained by fitting the proposed soil-water retention model to experimental data. Results obtained with the closed-form analytical expressions based on the Mualem theory are compared with observed hydraulic conductivity data for five soils with a wide range of hydraulic properties.
We reviewed the use of the van Genuchten–Mualem (VGM) model to parameterize soil hydraulic proper es and for developing pedotransfer func ons (PTFs). Analysis of litera-ture data showed that the moisture reten on characteris c (MRC) parameteriza on by se ng shape parameters m = 1 − 1/n produced the largest devia ons between fi ed and measured water contents for pressure head values between 330 (log 10 pressure head [pF] 2.5) and 2500 cm (pF 3.4). The Schaap–van Genuchten model performed best in describing the unsaturated hydraulic conduc vity, K. The classical VGM model using fi xed parame-ters produced increasingly higher root mean squared residual, RMSR, values when the soil became drier. The most accurate PTFs for es ma ng the MRC were obtained when using textural proper es, bulk density, soil organic ma er, and soil moisture content. The RMSR values for these PTFs approached those of the direct fi t, thus sugges ng a need to improve both PTFs and the MRC parameteriza on. Inclusion of the soil water content in the PTFs for K only marginally improved their predic on compared with the PTFs that used only textural proper es and bulk density. Including soil organic ma er to predict K had more eff ect on the predic on than including soil moisture. To advance the development of PTFs, we advocate the establishment of databases of soil hydraulic proper es that (i) are derived from standardized and harmonized measurement procedures, (ii) contain new predictors such as soil structural proper es, and (iii) allow the development of me-dependent PTFs. Successful use of structural proper es in PTFs will require parameteriza ons that account for the eff ect of structural proper es on the soil hydraulic func ons.
Knowledge of hydraulic properties is essential for understanding water movement in soil. However, very few data on these properties are available from the Loess Plateau of China. We determined the hydraulic properties of two silty loam soils on agricultural land at sites in Mizhi and Heyang in the region. Undisturbed soil cores were collected from seven layers to one meter depth to determine saturated hydraulic conductivity, soil water retention curves and unsaturated hydraulic conductivity (by the hot-air method). Additional field methods (internal drainage and Guelph permeameter) were applied at the Heyang site to compare differences between methods. Soil water retention curves were flatter at Mizhi than at Heyang. Water contents at saturation and wilting point (1500 kPa) were higher at Heyang than at Mizhi. However, unsaturated hydraulic conductivity was lower at Heyang than at Mizhi, with maximum differences of more than six orders of magnitude. Nevertheless, the two soils had similar saturated hydraulic conductivities of about 60 cm day− 1. Comparison between the methods showed that soil water retention curves obtained in the laboratory generally agreed well with the field data. Field-saturated conductivities had similar values to those obtained using the soil core method. Unsaturated hydraulic conductivities predicted by the Brooks–Corey model were closer to field data than corresponding values predicted by the van Genuchten model.
While different optical flow techniques continue to appear, there has been a lack of quantitative evaluation of existing methods. For a common set of real and synthetic image sequences, we report the results of a number of regularly cited optical flow techniques, including instances of differential, matching, energy-based, and phase-based methods. Our comparisons are primarily empirical, and concentrate on the accuracy, reliability, and density of the velocity measurements; they show that performance can differ significantly among the techniques we implemented.
Soil hydraulic properties are necessary for many studies of water and solute transport but often cannot be measured because of practical and/or financial constraints. We describe a computer program, rosetta, which implements five hierarchical pedotransfer functions (PTFs) for the estimation of water retention, and the saturated and unsaturated hydraulic conductivity. The hierarchy in PTFs allows the estimation of van Genuchten water retention parameters and the saturated hydraulic conductivity using limited (textural classes only) to more extended (texture, bulk density, and one or two water retention points) input data. rosetta is based on neural network analyses combined with the bootstrap method, thus allowing the program to provide uncertainty estimates of the predicted hydraulic parameters. The general performance of rosetta was characterized with coefficients of determination, and root mean square errors (RMSEs). The RMSE values decreased from 0.078 to 0.044 cm3 cm−3 for water retention when more predictors were used. The RMSE for the saturated conductivity similarly decreased from 0.739 to 0.647 (dimensionless log10 units). The RMSE values for unsaturated conductivity ranged between 0.79 and 1.06, depending on whether measured or estimated retention parameters were used as predictors. Calculated mean errors showed that the PTFs underestimated water retention and the unsaturated hydraulic conductivity at relatively high suctions. rosetta's uncertainty estimates can be used as an indication of model reliability when no hydraulic data are available. The rosetta program comes with a graphical user interface that allows user-friendly access to the PTFs, and can be downloaded from the US Salinity Laboratory website: http://www.ussl.ars.usda.gov/.
Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image. An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences. The algorithm is robust in that it can handle image sequences that are quantized rather coarsely in space and time. It is also insensitive to quantization of brightness levels and additive noise. Examples are included where the assumption of smoothness is violated at singular points or along lines in the image.
The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical formulation, however, has changed little since the work of Horn and Schunck. We attempt to uncover what has made recent advances possible through a thorough analysis of how the objective function, the optimization method, and modern implementation practices influence accuracy. We discover that “classical” flow formulations perform surprisingly well when combined with modern optimization and implementation techniques. Moreover, we find that while median filtering of intermediate flow fields during optimization is a key to recent performance gains, it leads to higher energy solutions. To understand the principles behind this phenomenon, we derive a new objective that formalizes the median filtering heuristic. This objective includes a nonlocal term that robustly integrates flow estimates over large spatial neighborhoods. By modifying this new term to include information about flow and image boundaries we develop a method that ranks at the top of the Middlebury benchmark.
We examine the development of instability studies in the oil industry and in soil physics, the former being far more advanced has tended to mold the latter. This had some unfortunate consequences as oil studies tended to rely heavily on Hele-Shaw cells, which provide a poor model for soils. In soil physics creation of column flow in soils has serious implications for infiltration and the transport of pollutants. It is to John Philip's credit that he recognized fairly early the practical importance of instability in soils.
Water infiltration into coarse textured dry porous media becomes instable depending on flow conditions characterized through dimensionless quantities, i.e. the Bond number and the Capillary number. Instable infiltration fronts break into flow fingers which we investigate experimentally using Hele-Shaw cells. We further developed a light transmission method to measure the dynamics of water within flow fingers in great detail with high spatial and temporal resolution. The method was calibrated using x-ray absorption and the measured light transmission was corrected for scattering effects through deconvolution with a point spread function. Additionally we applied a dye tracer to visualize the velocity field within flow fingers. We analyzed the dynamics of water within the finger tips, along the finger core behind the tip, and within the fringe of the fingers during radial growth. Our results confirm previous findings of saturation overshoot in the finger tips and revealed a saturation minimum behind the tip as a new feature. The finger development was characterized by a gradual increase in water content within the core of the finger behind this minimum and a gradual widening of the fingers to a quasi-stable state which evolves on time scales that are orders of magnitudes longer than those of fingers' evolution. In this state, a sharp separation into a core with fast convective flow and a fringe with exceedingly slow flow was detected. All observed phenomena could by consistently explained based on the hysteretic behavior of the soil- water characteristic and on the positive pressure induced at the finger tip by the high flow velocity.
In this study optical flow method was used for soil small deformation measurement in laboratory tests. The main objective was to observe how the deformation distributes along the whole height of cylindrical soil specimen subjected to torsional shearing (TS test). The experiments were conducted on dry non-cohesive soil specimens under two values of isotropic pressure. Specimens were loaded with low-amplitude cyclic torque to analyze the deformation within the small strain range (0.001–0.01%). Optical flow method variant by Ce Liu (2009) was used for motion estimation from series of images. This algorithm uses scale-invariant feature transform (SIFT) for image feature extraction and coarse-to-fine matching scheme for faster calculations. The results were validated with the Particle Image Velocimetry (PIV). The results show that the displacement distribution deviates from commonly assumed linearity. Moreover, the observed deformation mechanisms analysis suggest that the shear modulus G commonly determined through TS tests can be considerably overestimated.
This study aims to develop a method to automatically recognize nursing behaviors of sow in videos by exploiting the spatio-temporal relations. The method firstly detected spatio-temporal key cuboids which may have nursing interactions in them, and then Oriented Nursing Flows (ONuF) of the spatio-temporal key cuboids was proposed to further recognize nursing behaviors. In the first step, the temporal key episodes were first detected in video using optical flow-based features containing the distribution of nursing pixel and distance among moving pixels to estimate the distribution of motion all over the frame. Then, spatial key regions in the temporal key episodes were located by identifying the spatial position and geometric properties of the sow and her piglets using a fully convolutional network-based semantic segmentation approach. In the second step, to further recognize nursing behavior, a new feature descriptor ONuF, estimating the motion orientation change and motion magnitude of spatio-temporal key cuboids, was proposed and used to learn a SVM classifier. Testing on a set of 451 video episodes, the accuracy of classifying nursing was 94.5% with a sensitivity of 89.4% and with a specificity of 99.1%. Testing on a set of two days of continuous videos, the accuracy of recognizing nursing was 97.6% with a sensitivity of 92.1% and with a specificity of 98.6%. In addition, the nursing duration and nursing interval were counted from the recognition results of nursing behaviors in continuous videos. The results indicate that the method exploiting the spatio-temporal relations using fully convolutional network and oriented optical flow can be used for automatically recognizing nursing behaviors from daily behavioral videos of lactating sows.
The hydraulic conductivity of soil is an important parameter that is required for seepage calculations. Currently, many methods are available to predict this parameter, but the accuracy of the theoretical method is not adequate. In this paper, the existing theoretical model of the Hagen–Poiseuille law was modified based on the flow resistance of a sphere to estimate hydraulic conductivity. In the model, the capillary diameter calculated from the soil porosity and gradation is recommended for use as the average pore diameter. In a comparison with the experimental results, the modified formula showed a higher level of accuracy than the traditional model and other empirical methods. The model considers the grain size distribution, which is determined to be more reasonable than other models. We also show that the model may be invalid for nonuniform soil and that the results are very sensitive to changes in particle size and porosity. The model can be used to predict the hydraulic conductivity at any temperature and may give results that are different from experimental data because of the experimental boundary and the effect of the experimental process. The container’s boundary, unsaturated soil, and the internal instability of the soil during the test may all lead to differences between experimental results and the predicted values. © Soil Science Society of America, 5585 Guilford Rd., Madison WI 53711 USA. All Rights reserved.
This study compares saturated hydraulic conductivities (Ks) of three sandy soils such as coarse, medium and fine sand. The Ks was obtained using three different methods: empirical methods based on the grain size analysis, the relative effective porosity model (REPM), and breakthrough curve analyses based on tracer tests. Column drainage tests were performed to characterize the water retention properties of the samples, which are required in the REPM. Bench scale tracer tests with various conditions were conducted to obtain reasonable linear velocities of the samples using breakthrough curve analyses and then Ks was estimated using Darcy's law. For the REPM, the differences of Ks for the coarse and fine sand soils were less than one order of magnitude; however, the difference of Ks values between the empirical methods and the breakthrough curve analyses was larger than one order of magnitude. The comparison results suggest that the REPM can be a reliable method for estimating Ks for soil grains, and is cost effective due to its experimental simplicity.
The saturated hydraulic conductivity, Ks, 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 Ks have frequently provided conflicting results. Comparison of Ks 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 Ks 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 Ks. We find that the DRI grossly overestimates Ks, the GUELPH-CHP gives conflicting estimates of Ks with substantial overestimation in laboratory experiments and underestimation at the plot scale, whereas the CSIRO-TP yields average Ks 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 Ks 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 Ks using these methods and the characterization of field scale variability from multiple local measurements.
Arresting the recent observed warming of the earth’s climate is a challenge requiring the reduction of anthropogenic emissions of carbon dioxide. One option for reducing emissions into the atmosphere is to capture and sequester the released carbon dioxide in geological formations. However, potential geological storage first requires a risk assessment of carbon dioxide escaping to overlying layers and back to the atmosphere through leakage pathways in the formation. This, in turn, requires an understanding of fluid flow through the leakage pathways. In this study, the effect of leakage pathways on the flow of a gravity current was investigated, using an analogue system, a Hele-Shaw cell. Fluid was introduced through the top edge of the cell and flowed out through one or more holes in its impermeable base. The height of the accumulated fluid above the base of the cell at various points along its length and the outflow rate of fluid through the holes was measured. This measurement was conducted with varying conditions of the location, number and strength of source as well as the location and number of holes. At steady state, the fluid motion was in accordance with Darcy’s Law for horizontal flow in a long thin current. In another set of experiments, in which inflow was stopped and the fluid was allowed to drain out of a single open hole, the outflow rate was in accordance with Darcy’s law for one-dimensional flow in the vertical direction until the fluid height above the hole fell below a certain limit. This threshold height was found to be 1.3 cm, which was similar in magnitude to the length of the hole. A time series of photographs tracked the flow of coloured dye. The photographs demonstrated that at steady state the fluid travelled for some distance beyond the hole before draining through it. This implies that contaminants may be transported in a formation even beyond an outlet before finally draining out through it. The photographs also documented the shape of the interface between the newly introduced dye and the ambient fluid in the cell. These shapes were found to be different in a cell placed horizontally versus one placed on an incline, suggesting that the geometry and flow conditions in a formation affect the transport of an injected fluid. These findings may be used as a basis for predicting behaviour of a fluid injected into a fractured formation in the subsurface.
MORE than one hundred years ago, the French philosopher Coulomb caused a disc suspended by a torsion wire to oscillate in a vessel of liquid, arid lie thus ascertained that the resistance to various bodies under such circumstances, when the movement is a slow one, varies directly as the velocity of the motion. This law of resistance, it should be noted, is quite contrary to that of the friction between solid bodies as investigated by General Morin. Colonel Beaufoy, Froude, and others, however, found that, at higher velocities, the resistance varied more nearly as the square of the velocity. The difference of the two conditions in which the variation was directly, or, as the higher power, undoubtedly represented on the one hand the condition of water in which the mere viscosity came into play, resisting the shearing stress of the layers in passing, over each other, and on the other hand the condition when the breaking up of the water into eddying motion caused the resistance to become much greater.
With the demands of quality management and process control in an industrial environment machine vision is becoming an important issue. This handbook of machine vision is written by experts from leading companies in this field. It goes through all aspects of image acquisition and image processing. From the viewpoint of the industrial application the authors also elucidate in topics like illumination or camera calibration. Attention is paid to all hardware aspects, starting from lenses and camera systems to camera-computer interfaces. Besides the detailed hardware descriptions the necessary software is discussed with equal profoundness. This includes sections on digital image basics as well as image analysis and image processing. Finally the user is introduced to general aspects of industrial applications of machine vision, such as case studies and strategies for the conception of complete machine vision systems. With this handbook the reader will be enabled not only to understand up to date systems for machine vision but will also be qualified for the planning and evaluation of such technology.
Water-repellent soils occur all over the world and affect both groundwater pollution and crop yield. The finger-like wetting patterns in these soils have many similarities with unstable wetting fronts in coarse-grained sandy soils. Our objectives were to study the water movement in water-repellent sand and to examine how the theory for unstable wetting fronts applies to water-repellent sands. Infiltration experiments, in which moisture content and matric potentials were measured, were carded out in slab chambers with identical sands but with different levels of water repellence. Soil water characteristics were determined in separate experiments. Infiltration in the hydrophilic soil resulted in a uniform and horizontal front. All water-repellent sands showed a fingered flow pattern. For negative water-entry values, water infiltrated without delay. For positive values, water entered the soil only after the depth of the ponded water equaled or exceeded the water-entry pressure, which increased with increasing repellency. The finger widths predicted with the unstable flow theory agreed rather well with the observed values. In general, the research showed that the wetting patterns of water-repellent sands depended directly on the soil water characteristic curve. This implies that the type of wetting front and risk to groundwater pollution can be predicted based on laboratory-measured soil hydraulic properties.
Evaporation rates from porous media may vary considerably due to changes in internal transport mechanisms and potential interruption of hydraulic continuity; both are influenced by media pore space properties. Evaporation behavior in layered porous media is affected by thickness and sequence of layering and capillary characteristics of each layer. We propose a composite characteristic length for predicting drying front depth at the end of a period with a high and constant drying rate (stage 1 evaporation) from layered porous media. The model was tested in laboratory experiments using Hele-Shaw cells filled with alternating layers of coarse and fine sands considering different combinations of thicknesses and positions. The presence of textural interfaces affects drying rate, modifies liquid phase configuration, and affects the dynamics of the receding drying front. Neutron radiography measurements were used to delineate dynamics of liquid phase distribution with high temporal and spatial resolution. Results show that air invading an interface between fine and coarse sand layers results in a capillary pressure jump and subsequent relaxation that significantly modify liquid phase distribution compared with evaporation from homogeneous porous media. Insights are potentially useful for designing mulching strategies and capillary barriers aimed at reducing evaporative losses.
The accurate knowledge of hydraulic properties for unsaturated soils is critical in addressing problems in a variety of disciplines such as hydrology, ecology, environmental sciences, soil science, and agriculture. The purpose of this paper is to review the characterization of unsaturated soil hydraulic properties for their applicability in models simulating unsaturated water transport. In a theoretical section, we present the fundamentals for the definitions of the hydraulic properties in the framework of the continuum theory as well as provide the common parameterizations of the hydraulic functions. The characterization and parameterization of hysteresis and the phenomenon of dynamic effects in hydraulic properties are addressed in subsequent sections. Finally we discuss issues related to the handling of spatial and temporal variability, including geostatistical characterization, upscaling, and scale dependency of effective properties. The review closes with a summary on limits and opportunities for modeling water transport with Richards' equation.
Many environmental studies on the protection of European soil and water resources make use of soil water simulation models. A major obstacle to the wider application of these models is the lack of easily accessible and representative soil hydraulic properties. In order to overcome this apparent lack of data, a project was initiated to bring together the available hydraulic data which resided within different institutions in Europe into one central database. This information was then used to derive a set of pedotransfer functions applicable to studies at a European scale. These pedotransfer functions predict the hydraulic properties from parameters collected during soil surveys and can be a good alternative for costly and time-consuming direct measurement of these properties. A total of 20 institutions from 12 European countries collaborated in establishing the database of draulic operties of uropean oils (HYPRES). This database has a flexible relational structure capable of holding a wide diversity of both soil pedological and hydraulic data. As these data were contributed by 20 different institutions it was necessary to standardise both the particle-size and the hydraulic data. A novel similarity interpolation procedure was successfully used to achieve standardization of particle-sizes according to the FAO clay, silt and sand particle-size ranges. Standardization of hydraulic data was achieved by fitting the Mualem-van Genuchten model parameters to the individual θ(h) and K(h) hydraulic properties stored in HYPRES. The HYPRES database contains information on a total of 5521 soil horizons (including replicates). Of these, 4030 horizons had sufficient data to be used in the derivation of pedotransfer functions. Information on both water retention and hydraulic conductivity was available for 1136 horizons whereas 2894 horizons had only information on water retention. Each soil horizon was allocated to one of 11 possible soil textural/pedological classes derived from the six FAO texture classes (five mineral and one organic) and the two pedological classes (topsoil and subsoil) recognised within the 1:1 000 000 scale Soil Geographical Data Base of Europe. Next, both class and continuous pedotransfer functions were developed. By using the class pedotransfer functions in combination with the 1:1 000 000 scale Soil Map of Europe, the spatial distribution of soil water availability within Europe was derived.
Wetting front instability in the vadose zone causes the formation of fingers which can rapidly transport both water and solute to the phreatic surface. The development of the unstable flow field in laboratory experiments is described for an initially dry, two-layer sand system, in which the top layer has a finer texture than the bottom layer. The effect of repeated infiltration cycles and of initial moisture content at field capacity are presented. Fingers once formed in the dry porous media are found to not change location even after several infiltration events. Only saturation and subsequent drainage alters the finger structure within the chamber. In Eastern Long Island, New York, USA, field infiltration experiments using the combination of two dyes showed that water moved through finger-like structures.
Functional evaluations of pedotransfer functions (PTFs) were performed. In a first sample problem, the influence of uncertainty in the PTF was examined on the basis of two functional criteria: the moisture supply capacity (MSC) and the downward flux below the root zone (DFR). In a second sample problem the effect of the uncertainty in the PTFs and the variability in soil properties within a map unit were analyzed. It was found that an improved estimate to the hydraulic properties, obtained by calibrating PTFs using detailed textural information, did not substantially reduce the dispersion of the MSC and DFR distributions. Results from the second sample problem indicated that >90% of the variation in the simulated MSC was caused by estimation errors in the hydraulic properties, overwhelming the map unit variability. -from Authors
Handbook of Machine and Computer Vision -. In: The Guide for Developers and Users
- A Hornberg
Hornberg, A., 2017. Handbook of Machine and Computer Vision -. In: The Guide for
Developers and Users. Wiley-VCH, Göppingen, Germany. https://doi.org/10.1142/
9789814273398.
Preferential solute transport through layered soils
- G Oosting
- R Glass
- T Steenhuis
Oosting, G., Glass, R., Steenhuis, T., 1987. Preferential solute transport through layered
soils. In: Winter Meeting of. American Society of Agricultural Engineers. American
Society of Agricultural Engineers, Chicago, US, pp. 87-2624.
SoilKsatDB: global soil saturated hydraulic conductivity measurements for geoscience applications
- Gupta
Preferential solute transport through layered soils
- Oosting
Modeling leakage pathways in subsurface formations: Fluid drainage through multiple fractures in porous media: insights from Hele Shaw cell experiments
- Ray