Effects of Past Copper Contamination and Soil Structure on Copper Leaching from Soil

Paradelo, Marcos; Møldrup, Per; Arthur, Emmanuel; Naveed, Muhammad; Holmstrup, Martin; López-Periago, J. Eugenio; Jonge, Lis Wollesen de

doi:10.2134/jeq2013.05.0209

Cited by 23 publications

(18 citation statements)

References 56 publications

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“…Luo et al (2010b) also found smaller dispersivities (i.e., more uniform flow) in columns with larger imaged macroporosity. Other recent studies performed under near‐saturated conditions also found that preferential flow at a given water flow rate was weaker in columns with larger macroporosity (e.g., Larsbo et al, 2014; Katuwal et al, 2015b; Paradelo et al, 2013, 2016). Larsbo et al (2014) explained this finding qualitatively in terms of a multiscale percolating pore network: the columns of smaller imaged porosity had smaller near‐saturated hydraulic conductivities, which presumably resulted in increased water pressures that were sufficient to generate flow in larger (but still percolating) pores.…”

Section: Experimentation From Pore To Catchment Scalesmentioning

confidence: 66%

Understanding Preferential Flow in the Vadose Zone: Recent Advances and Future Prospects

Jarvis

Koestel

Larsbo

2016

Vadose Zone Journal

195

188

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Core Ideas Understanding of preferential flow is improving, stimulated partly by new technologies. Empirical process understanding has outstripped the capability of models to predict. Better models must await future advances in computational power. In this update, we review some of the more significant advances that have been made in the last decade in the study of preferential flow through the vadose zone as well as suggest some research needs in the coming years. We focus mostly on work that aims to improve understanding of the processes themselves and less on more applied aspects concerning the various consequences of preferential flow (e.g., for surface water and groundwater quality). In recent years, the research emphasis has shifted somewhat toward the two extremes of the scale continuum, the pore scale and the scale of management (field, catchments, and landscapes). This trend has been facilitated by significant advances in both measurement technologies (e.g., noninvasive imaging techniques and high frequency–high spatial resolution monitoring of soil moisture at field and catchment scales) and application of novel methods of analysis to large datasets (e.g., machine learning). This work has led to a better understanding of how pore network properties control preferential flow at the pore to core scales as well as some new insights into the influence of site attributes (climate, land uses, soil types) at field to landscape scales. We conclude that models do not at present fully reflect the current state of process understanding and empirical knowledge of preferential flow. However, we expect that significant advances in computational techniques, computer hardware, and measurement technologies will lead to increasingly reliable model predictions of the impacts of preferential flow, even at the larger scales relevant for management.

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Section: Experimentation From Pore To Catchment Scalesmentioning

confidence: 66%

Understanding Preferential Flow in the Vadose Zone: Recent Advances and Future Prospects

Jarvis

Koestel

Larsbo

2016

Vadose Zone Journal

195

188

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“…This suggests that biopore-dominated and matrix-dominated flow columns should be discerned as an initial step prior to studying the relationships between macropore flow and CT-derived macroporosity. Both Paradelo et al (2013) and Luo et al (2010) found similar relationships between saturated hydraulic conductivity and CTderived macroporosity, with R 2 ranging from 0.50 to 0.60. A stronger power regression was observed when K sat was plotted as a function of the effective percolating macroporosity (R 2 increased from 0.43 to 0.76), for the soil columns associated with biopore-dominated flow (Fig.…”

Section: Variablementioning

confidence: 79%

“…Larsbo et al (2014) reported significant correlations between X-ray CT-derived macropore network characteristics and flow and transport parameters. Paradelo et al (2013) found that CT-derived macroporosity was strongly correlated with saturated hydraulic conductivity, solute dispersivity, and contaminant breakthrough. Luo et al (2010) reported that macroporosity, path number, hydraulic radius, and macropore angle were the most useful X-ray CT-derived parameters for predicting macropore flow and transport under saturated conditions.…”

Section: Introductionmentioning

confidence: 96%

Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

Naveed

Møldrup

Schaap

et al. 2016

Hydrol. Earth Syst. Sci.

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Abstract. Prediction and modeling of localized flow processes in macropores is of crucial importance for sustaining both soil and water quality. However, currently there are no reliable means to predict preferential flow due to its inherently large spatial variability. The aim of this study was to investigate the predictive performance of previously developed empirical models for both water and air flow and to explore the potential applicability of X-ray computed tomography (CT)-derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height) were extracted from the topsoil (5 cm to 8.5 cm depth) in a 15 m × 15 m grid from an agricultural field located in Silstrup, Denmark. All soil columns were scanned with an industrial X-ray CT scanner (129 µm resolution) and later employed for measurement of saturated hydraulic conductivity, air permeability at −30 and −100 cm matric potential, and gas diffusivity at −30 and −100 cm matric potential. Distribution maps for saturated hydraulic conductivity, air permeability, and gas diffusivity reflected no autocorrelation irrespective of soil texture and organic matter content. Existing empirical predictive models for saturated hydraulic conductivity and air permeability showed poor performance, as they were not able to realistically capture macropore flow. The tested empirical model for gas diffusivity predicted measurements at −100 cm matric potential reasonably well, but failed at −30 cm matric potential, particularly for soil columns with biopore-dominated flow. X-ray CT-derived macroporosity matched the measured airfilled porosity at −30 cm matric potential well. Many of the CT-derived macropore network characteristics were strongly interrelated. Most of the macropore network characteristics were also significantly correlated with saturated hydraulic conductivity, air permeability, and gas diffusivity. The predictive Ahuja et al. (1984) model for saturated hydraulic conductivity, air permeability, and gas diffusivity performed reasonably well when parameterized with novel, X-ray CTderived parameters such as effective percolating macroporosity for biopore-dominated flow and total macroporosity for matrix-dominated flow. The obtained results further indicate that it is crucially important to discern between matrixdominated and biopore-dominated flow for accurate prediction of macropore flow from X-ray CT-derived macropore network characteristics.

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“…Macroporosity and limiting macroporosity (minimum macroporosity along the soil column) were found to be good predictors of air permeability at −3 kPa matric potential in undisturbed soils from a clay gradient field (Naveed et al, 2013). The degree of preferential flow and the release of Cu in a polluted soil have been estimated from the macroporosity derived from X‐ray CT images (Paradelo et al, 2013). Larsbo et al (2014) also found significant relationships between the degree of preferential flow and the CT‐derived macropore characteristics like macroporosity, macropore surface area, aggregate thickness, and connectivity.…”

mentioning

confidence: 99%

X‐ray CT‐Derived Soil Characteristics Explain Varying Air, Water, and Solute Transport Properties across a Loamy Field

Paradelo

Katuwal

Møldrup

et al. 2016

Vadose Zone Journal

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Core Ideas We used CT‐derived parameters to explain solute, water, and air transport at field scale. CTmatrix was found to be the best parameter to explain solute transport. Limiting macroporosity gave the highest correlations with water and air transport. Combining macroporosity and CTmatrix improved the relationships of water and air flow. The characterization of soil pore space geometry is important for explaining fluxes of air, water, and solutes through soil and understanding soil hydrogeochemical functions. X‐ray computed tomography (CT) can be applied for this characterization, and in this study CT‐derived parameters were used to explain water, air, and solute transport through soil. Forty‐five soil columns (20 by 20 cm) were collected from an agricultural field in Estrup, Denmark, and subsequently scanned using a medical CT scanner. Nonreactive tracer leaching experiments were performed in the laboratory along with measurements of air permeability (Ka) and saturated hydraulic conductivity (Ksat). The CT number of the matrix (CTmatrix), which represents the moist bulk density of the soil matrix, was obtained from the CT scans as the average CT number of the voxels in the grayscale image excluding macropores and stones. The CTmatrix showed the best relationships with the solute transport characteristics, especially the time by which 5% of the applied mass of tritium was leached, known as the 5% arrival time (t0.05). The CT‐derived macroporosity (pores >1.2 mm) was correlated with Ka and log10(Ksat). The correlation improved when the limiting macroporosity (the minimum macroporosity for every 0.6‐mm layer along the soil column) was used, suggesting that soil layers with the narrowest macropore section restricted the flow through the whole soil column. Water, air, and solute transport were related with the CT‐derived parameters by using a best subsets regression analysis. The regression coefficients improved using CTmatrix, limiting macroporosity, and genus density, while the best model for t0.05 used CTmatrix only. The scanning resolution and the time for soil structure development after mechanical activities could be factors that increased the uncertainty of the relationships. Nevertheless, the results confirmed the potential of X‐ray CT visualization techniques for estimating fluxes through soil at the field scale.

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Effects of Past Copper Contamination and Soil Structure on Copper Leaching from Soil

Cited by 23 publications

References 56 publications

Understanding Preferential Flow in the Vadose Zone: Recent Advances and Future Prospects

Understanding Preferential Flow in the Vadose Zone: Recent Advances and Future Prospects

Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

X‐ray CT‐Derived Soil Characteristics Explain Varying Air, Water, and Solute Transport Properties across a Loamy Field

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