Effects of Soil Compaction and Organic Carbon Content on Preferential Flow in Loamy Field Soils

Soares, Antônio Alves; Møldrup, Per; Vendelboe, Anders Lindblad; Katuwal, Sheela; Nørgaard, Trine; Delerue–Matos, Cristina; Tuller, Markus; Jonge, Lis Wollesen de

doi:10.1097/ss.0000000000000105

Cited by 15 publications

(12 citation statements)

References 35 publications

(67 reference statements)

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“…However, the difference in the shape of the EC curves (i.e., the later peak in EC) might be seen as an indication that the CMA and CHA treatments exhibit a larger degree of lateral mass transfer compared with the U, CS, and SA treatments. Previous studies analyzing relations between either SOM or clay/OC (Dexter) ratio and 5% mass recovery of 3 H 2 O at free drainage conditions did not find significant correlations between the soil C parameters and early tracer breakthrough Soares et al, 2015;Vendelboe et al, 2013). This is in accordance with the present study in which a wide range in the clay/OC ratio did not affect either early tracer breakthrough or mass recovery in general.…”

Section: Treatment Colloid Concentrationsupporting

confidence: 91%

Long‐term Effects of Organic Waste Fertilizers on Soil Structure, Tracer Transport, and Leaching of Colloids

2017

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Organic waste fertilizers have previously been observed to significantly affect soil organic carbon (SOC) content and soil structure. However, the effect of organic waste fertilizers on colloid dispersibility and leaching of colloids from topsoil has not yet been studied extensively. We investigated how the repeated application of different types of agricultural (liquid cattle slurry and solid cattle manure) and urban waste fertilizers (sewage sludge and composted organic household waste) affected soil physical properties, colloid dispersion from aggregates, tracer transport, and colloid leaching from intact soil cores. Total porosity was positively correlated with SOC content. Yearly applications of sewage sludge increased absolute microporosity (pores <30 μm) and decreased relative macroporosity (pores >30 μm) compared with the unfertilized control, whereas organic household waste compost fertilization increased both total porosity and the absolute porosity in all pore size classes (though not significant for 100-600 μm). Treatments receiving large amounts of organic fertilizers exhibited significantly lower levels of dispersible colloids compared with an unfertilized control and a treatment that had received moderate applications of cattle slurry. The content of water-dispersible colloids could not be explained by a single factor, but differences in SOC content, electrical conductivity, and sodium adsorption ratio were important factors. Moreover, we found that the fertilizer treatments did not significantly affect the solute transport properties of the topsoil. Finally, we found that the leaching of soil colloids was significantly decreased in treatments that had received large amounts of organic waste fertilizers, and we ascribe this primarily to treatment-induced differences in effluent electrical conductivity during leaching.

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Section: Treatment Colloid Concentrationsupporting

confidence: 91%

Long‐term Effects of Organic Waste Fertilizers on Soil Structure, Tracer Transport, and Leaching of Colloids

2017

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“…For example, Larsbo et al (2016) found that initial tracer breakthrough was faster in columns with smaller volumes of pores between 0.2 and 0.6 mm in diameter but was not correlated with the properties of macropores larger than 1.2 mm in diameter. Other studies found that the strength of preferential flow was significantly and positively correlated with the average gray‐scale value of the region segmented as matrix, which should reflect the volume of pores smaller than the X‐ray resolution, but not with the imaged macroporosity (Soares et al, 2015; Katuwal et al, 2015a; Paradelo et al, 2016).…”

Section: Experimentation From Pore To Catchment Scalesmentioning

confidence: 90%

“…In the past, BTC data were usually fitted with transport models such as the mobile–immobile version of the convection–dispersion equation (CDE), but simpler model‐independent measures that describe the shape of the BTC (i.e., the distribution of solute travel times) are now more often preferred because they make no a priori assumptions about flow mechanisms. In recent years, various BTC shape measures, including temporal moments, the so‐called “holdback factor,” and the normalized 5% arrival time (Koestel et al, 2011) have been used to assess how preferential flow is affected by land use and soil management practices (e.g., Mossadeghi‐Björklund et al, 2016) or soil properties such as texture (Ghafoor et al, 2013), bulk density (Koestel et al, 2013; Soares et al, 2015; Katuwal et al, 2015a), and organic C content (Larsbo et al, 2016).…”

Section: Experimentation From Pore To Catchment Scalesmentioning

confidence: 99%

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

Jarvis

Koestel

Larsbo

2016

Vadose Zone Journal

192

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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“…It is developed on a meltwater sand aquifer, which is overlaid with Weichselian clay till deposits (Lindhardt et al, 2001). For more information on the site characteristics, see Soares et al (2015). The Jyndevad field (54°53′37″ N, 9°7′12″ E, 2.39 ha) is a homogeneous field characterized by sandy soil.…”

Section: Methodsmentioning

confidence: 99%

Combining X‐ray Computed Tomography and Visible Near‐Infrared Spectroscopy for Prediction of Soil Structural Properties

Katuwal¹,

Hermansen²,

Knadel³

et al. 2017

Vadose Zone Journal

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Soil structure is a key soil property affecting a soil's flow and transport behavior. X-ray computed tomography (CT) is increasingly used to quantify soil structure. However, the availability, cost, time, and skills required for processing are still limiting the number of soils studied. Visible near-infrared (vis-NIR) spectroscopy is a rapid analytical technique used successfully to predict various soil properties. In this study, the potential of using vis-NIR spectroscopy to predict X-ray CT derived soil structural properties was investigated. In this study, 127 soil samples from six agricultural fields within Denmark with a wide range of textural properties and organic C (OC) contents were studied. Macroporosity (>1.2 mm in diameter) and CT matrix (the density of the field-moist soil matrix devoid of large macropores and stones) were determined from X-ray CT scans of undisturbed soil cores (19 by 20 cm). Both macroporosity and CT matix are soil structural properties that affect the degree of preferential transport. Bulk soils from the 127 sampling locations were scanned with a vis-NIR spectrometer (400-2500 nm). Macroporosity and CT matrix were statistically predicted with partial least squares regression (PLSR) using the vis-NIR data (vis-NIR-PLSR) and multiple linear regression (MLR) based on soil texture and OC. The statistical prediction of macroporosity was poor, with both vis-NIR-PLSR and MLR (R 2 < 0.45, ratio of performance to deviation [RPD] < 1.4, and ratio of performance to interquartile distance [RPIQ] < 1.8). The CT matrix was predicted better (R 2 > 0.65, RPD > 1.5, and RPIQ > 2.0) combining the methods. The results illustrate the potential applicability of vis-NIR spectroscopy for rapid assessment/prediction of CT matrix .Abbreviations: CT, computed tomography; CT matrix , density of field-moist soil matrix devoid of large macropores and stones; HU, Hounsfield units; MLR, multiple linear regression; OC, organic carbon; PCA, principal component analysis; PLSR, partial least squares regression; RPD, ratio of performance to deviation; RPIQ, ratio of performance to interquartile distance; vis-NIR, visible near-infrared.

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Effects of Soil Compaction and Organic Carbon Content on Preferential Flow in Loamy Field Soils

Cited by 15 publications

References 35 publications

Long‐term Effects of Organic Waste Fertilizers on Soil Structure, Tracer Transport, and Leaching of Colloids

Long‐term Effects of Organic Waste Fertilizers on Soil Structure, Tracer Transport, and Leaching of Colloids

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

Combining X‐ray Computed Tomography and Visible Near‐Infrared Spectroscopy for Prediction of Soil Structural Properties

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