Multiscale Soil Investigations: Physical Concepts And Mathematical Techniques

Soil variability has often been considered to be composed of “functional” (explained) variations plus random fl uctuations or noise. However, the distinction between these two components is scale dependent because increasing the scale of observation almost always reveals structure in the noise (Burrough, 1983). Soils can be seen as the result of spatial variation operating over several scales, indicating that factors infl uencing spatial variability differ with scale. Th is observation points to variability as a key soil attribute that should be studied

Multifractal analysis of discretized X-ray CT images for the characterization of soil macropore structures

A correct statistical model of soil pore structure can be critical for understanding flow and transport processes in soils, and creating synthetic soil pore spaces for hypothetical and model testing, and evaluating similarity of pore spaces of different soils. Advanced visualization techniques such as X-ray computed tomography (CT) offer new opportunities of exploring heterogeneity of soil properties at horizon or aggregate scales. Simple fractal models such as fractional Brownian motion that have been proposed to capture the complex behavior of soil spatial variation at field scale rarely simulate irregularity patterns displayed by spatial series of soil properties. The objective of this work was to use CT data to test the hypothesis that soil pore structure at the horizon scale may be represented by multifractal models. X-ray CT scans of twelve, water-saturated, 20-cm long soil columns with diameters of 7.5 cm were analyzed. A reconstruction algorithm was applied to convert the X-ray CT data into a stack of 1480 grayscale digital images with a voxel resolution of 110 microns and a cross-sectional size of 690 × 690 pixels. The images were binarized and the spatial series of the percentage of void space vs. depth was analyzed to evaluate the applicability of the multifractal model. The series of depth-dependent macroporosity values exhibited a well-defined multifractal structure that was revealed by singularity and Rényi spectra. The long-range dependencies in these series were parameterized by the Hurst exponent. Values of the Hurst exponent close to one were observed indicating the strong persistence in variations of porosity with depth. The multifractal modeling of soil macropore structure can be an efficient method for parameterizing and simulating the vertical spatial heterogeneity of soil pore space

Modelling solute transport in soil columns using advective-dispersive equations with fractional spatial derivatives

Solute transport in soils is commonly simulated with the advective–dispersive equation, or ADE. It has been reported that this model cannot take into account several important features of solute movement through soil. Recently, a new model has been suggested that results in a solute transport equation with fractional spatial derivatives, or FADE. We have assembled a database on published solute transport experiments in soil columns to test the new model. The FADE appears to be a useful generalization of the ADE. The order of the fractional differentiation reflects differences in physical conditions of the solute transport in soi

Soil Variability and Biogeochemical Fluxes: Toward a Better Understanding of Soil Processes at the Land Surface

Core Ideas Pattern recognition techniques can help explain biogeochemical flux variability. Dynamic factors and their impact on biogeochemical flux variability need better identification. Controls on biogeochemical fluxes are time and space scale dependent. Soil biogeochemical fluxes in the vadose zone are characterized by a large degree of variability in space and time. This fact leads to the need for the development and application of appropriate methodologies to better understand the high nonlinearity and complex feedback mechanisms responsible for such fluxes. In this sense, there still exists a lack of knowledge in topics such as the scale dependence of the spatial and temporal variability of the controls on soil moisture and biodegradation rates and the dynamic behavior of flow and transport model parameter, and its association with the presence of roots. Knowledge of the variability of biogeochemical fluxes is needed for assorted applications ranging from natural hazards and environmental pollution risk assessment to agricultural production and water resources management. The contributions to this special section epitomize the ongoing effort toward the characterization, quantification, modeling, and understanding of biogeochemical fluxes in the vadose zone at several spatial and temporal scales. The main progress has been the identification of different controls on soil moisture and biodegradation rates depending on the scale of the study as well as the important dependence of the spatial and temporal variability of biogeochemical fluxes on dynamic properties such as vegetation and weather variables

Impact of marble powder amendment on hydraulic properties of a sandy soil

Marble powder is one of carbonate rock amendments that is used to improve soil reaction. We hypothesized that the powdered marble addition can cause favorable changes in hydraulic properties of sandy soils. Six levels of marble powder addition to an aridisol soil (0%; M0; 5%; M5; 10%; M10; 15%; M15; 20%; M20 and 25%, M25; by bulk volume) were analyzed in triplicate. The saturated hydraulic conductivity and soil water retention curves were obtained. Pore space properties were investigated using soil water retention curves, mercury intrusion porosimetry and scanning electron microscopy. The saturated hydraulic conductivity significantly decreased (between 83 and 97% for M5 and M25 respectively) and parameters α and n of the van Genuchten model significantly decreased in marble-amended soils. Both field capacity and permanent wilting point increased with the addition of marble powder. Plant-available water, increased significantly until 10% of marble powder application; higher percentages of application did not provide additional significant changes in the plant-available water. Pore space distributions from soil water retention curves parameters showed an increase in the pore size range and a decrease in the average pore size; pore space distribution from the scanning electron microscopy also showed the presence of a new family of dominant pore sizes which was not detected by the soil water retention curves parameters approach. It was concluded that the addition of marble powder can improve the ability of soil to store water providing an advantage for irrigation water management in water scarce environments. Further research will have to address the impact of marble powder amendment under field semi-arid conditions.This work was partially funded by the project GRE17-12 from the University of Alicante (2018-2019)

Drone-based imaging to assess the microbial water quality in an irrigation pond: A pilot study

Microbial water quality datasets are essential in irrigated agricultural practices to detect and inform measures to prevent the contamination of produce. Escherichia coli (E. coli) concentrations are commonly used to evaluate microbial water quality. Remote sensing imagery has been successfully used to retrieve several water quality parameters that can be determinants of E. coli habitats in waterbodies. This pilot study was conducted to test the possibility of using imagery from a small unmanned aerial vehicle (sUAV or drone) to improve the estimation of microbial water quality in small irrigation ponds. In situ measurements of pH, turbidity, specific conductance, and concentrations of dissolved oxygen, chlorophyll-a, phycocyanin, and fluorescent dissolved organic matter were taken at depths of 0–15 cm in 23 locations across a pond in Central Maryland, USA. The pond surface was concurrently imaged using a drone with three modified GoPro cameras, and a multispectral MicaSense RedEdge camera with five spectral bands. The GoPro imagery was decomposed into red, blue, and green components. Mean digital numbers for 1-m radius areas in the images were combined with the water quality data to provide input for a regression tree-based analysis. The accuracy of the regression-tree data description with “only imagery” inputs was the same or better than that of trees constructed with “only water-quality parameters” as inputs. From multiple cross-validation runs with “only imagery” inputs for the regression trees, the average (±SD) determination coefficient and root-mean-squared error of the decimal logarithm of E. coli concentrations were 0.793 ± 0.035 and 0.131 ± 0.011, respectively. The results of this study demonstrate the opportunities for using sUAV imagery for obtaining a more accurate delineation of the spatial variation of E. coli concentrations in irrigation ponds

Accounting for the three-dimensional distribution of Escherichia coli concentrations in pond water in simulations of the microbial quality of water withdrawn for irrigation

Evaluating the microbial quality of irrigation water is essential for the prevention of foodborne illnesses. Generic Escherichia coli (E. coli) is used as an indicator organism to estimate the microbial quality of irrigation water. Monitoring E. coli concentrations in irrigation water sources is commonly performed using water samples taken from a single depth. Vertical gradients of E. coli concentrations are typically not measured or are ignored; however, E. coli concentrations in water bodies can be expected to have horizontal and vertical gradients. The objective of this work was to research 3D distributions of E. coli concentrations in an irrigation pond in Maryland and to estimate the dynamics of E. coli concentrations at the water intake during the irrigation event using hydrodynamic modeling in silico. The study pond is about 22 m wide and 200 m long, with an average depth of 1.5 m. Three transects sampled at 50-cm depth intervals, along with intensive nearshore sampling, were used to develop the initial concentration distribution for the application of the environmental fluid dynamic code (EFDC) model. An eight-hour irrigation event was simulated using on-site data on the wind speed and direction. Substantial vertical and horizontal variations in E. coli concentrations translated into temporally varying concentrations at the intake. Additional simulations showed that the E. coli concentrations at the intake reflect the 3D distribution of E. coli in the limited pond section close to the intake. The 3D sampling revealed E. coli concentration hot spots at different depths across the pond. Measured and simulated 3D E. coli concentrations provide improved insights into the expected microbial water quality of irrigation water compared with 1D or 2D representations of the spatial variability of the indicator concentration