Trine Norgaard

Comparative Mapping of Soil Physical–Chemical and Structural Parameters at Field Scale to Identify Zones of Enhanced Leaching Risk

Preferential flow and particle-facilitated transport through macropores contributes significantly to the transport of strongly sorbing substances such as pesticides and phosphorus. The aim of this study was to perform a field-scale characterization of basic soil physical properties like clay and organic carbon content and investigate whether it was possible to relate these to derived structural parameters such as bulk density and conservative tracer parameters and to actual particle and phosphorus leaching patterns obtained from laboratory leaching experiments. Sixty-five cylindrical soil columns of 20-cm height and 20-cm diameter and bulk soil were sampled from the topsoil in a 15-m × 15-m grid in an agricultural loamy field. Highest clay contents and highest bulk densities were found in the northern part of the field. Leaching experiments with a conservative tracer showed fast 5% tracer arrival times and high tracer recovery percentages from columns sampled from the northern part of the field, and the leached mass of particles and particulate phosphorus was also largest from this area. Strong correlations were obtained between 5% tracer arrival time, tracer recovery, and bulk density, indicating that a few well-aligned and better connected macropores might change the hydraulic conductivity between the macropores and the soil matrix, triggering an onset of preferential flow at lower rain intensities compared with less compacted soil. Overall, a comparison mapping of basic and structural characteristics including soil texture, bulk density, dissolved tracer, particle and phosphorus transport parameters identified the northern one-third of the field as a zone with higher leaching risk. This risk assessment based on parameter mapping from measurements on intact samples was in good agreement with 9 yr of pesticide detections in two horizontal wells and with particle and phosphorus leaching patterns from a distributed, shallow drainage pipe system across the field.

Predicting soil organic carbon at field scale using a national soil spectral library

Visible and near infrared diffuse reflectance (vis-NIR) spectroscopy is a low-cost, efficient and accurate soil analysis technique and is thus becoming increasingly popular. Soil spectral libraries are commonly constructed as the basis for estimating soil texture and properties. In this study, partial least squares regression was used to develop models to predict the soil organic carbon (SOC) content of 35 soil samples from one field using (i) the Danish soil spectral library (2688 samples), (ii) a spiked spectral library (a combination of 30 samples selected from the local area and the spectral library, 2718 samples) and (iii) three sub-sets selected from the spectral library. In an attempt to improve prediction accuracy, sub-sets of the soil spectral library were made using three different sample selection methods: those geographically closest (84 samples), those with the same landscape and parent material (96 samples) and those with the most alike spectra to spectra from the field investigation (100 samples). These sub-sets were used to develop three calibration models and in predictions of SOC content. The results showed that the geographically closest model, which used the fewest number of samples, gave the lowest root mean square error of prediction (RMSEP) of 0.19% and the highest ratio of performance to deviation (RPD) of 3.7, followed by the spiked library, same parent material, the spectral library and the most alike spectra. The spiked library model also gave a low RMSEP value of 0.19% and high RPD value of 3.7% and performed markedly better than the model without spiking, despite using 30 samples for library spiking. The accuracy of the model developed using a sub-set from a spectral library was highly dependent on geographical location, soil parent material and landscape.

Water and solute transport in agricultural soils predicted by volumetric clay and silt contents.

Solute transport through the soil matrix is non-uniform and greatly affected by soil texture, soil structure, and macropore networks. Attempts have been made in previous studies to use infiltration experiments to identify the degree of preferential flow, but these attempts have often been based on small datasets or data collected from literature with differing initial and boundary conditions. This study examined the relationship between tracer breakthrough characteristics, soil hydraulic properties, and basic soil properties. From six agricultural fields in Denmark, 193 intact surface soil columns 20cm in height and 20cm in diameter were collected. The soils exhibited a wide range in texture, with clay and organic carbon (OC) contents ranging from 0.03 to 0.41 and 0.01 to 0.08kgkg(-1), respectively. All experiments were carried out under the same initial and boundary conditions using tritium as a conservative tracer. The breakthrough characteristics ranged from being near normally distributed to gradually skewed to the right along with an increase in the content of the mineral fines (particles ≤50μm). The results showed that the mineral fines content was strongly correlated to functional soil structure and the derived tracer breakthrough curves (BTCs), whereas the OC content appeared less important for the shape of the BTC. Organic carbon was believed to support the stability of the soil structure rather than the actual formation of macropores causing preferential flow. The arrival times of 5% and up to 50% of the tracer mass were found to be strongly correlated with volumetric fines content. Predicted tracer concentration breakthrough points as a function of time up to 50% of applied tracer mass could be well fitted to an analytical solution to the classical advection-dispersion equation. Both cumulative tracer mass and concentration as a function of time were well predicted from the simple inputs of bulk density, clay and silt contents, and applied tracer mass. The new concept seems promising as a platform towards more accurate proxy functions for dissolved contaminant transport in intact soil.

Effects of soil compaction and organic carbon content on preferential flow in loamy field soils

Abstract Preferential flow and transport through macropores affect plant water use efficiency and enhance leaching of agrochemicals and the transport of colloids, thereby increasing the risk for contamination of groundwater resources. The effects of soil compaction, expressed in terms of bulk density (BD), and organic carbon (OC) content on preferential flow and transport were investigated using 150 undisturbed soil cores sampled from 15 × 15–m grids on two field sites. Both fields had loamy textures, but one site had significantly higher OC content. Leaching experiments were conducted in each core by applying a constant irrigation rate of 10 mm h−1 with a pulse application of tritium tracer. Five percent tritium mass arrival times and apparent dispersivities were derived from each of the tracer breakthrough curves and correlated with texture, OC content, and BD to assess the spatial distribution of preferential flow and transport across the investigated fields. Soils from both fields showed strong positive correlations between BD and preferential flow. Interestingly, the relationships between BD and tracer transport characteristics were markedly different for the two fields, although the relationship between BD and macroporosity was nearly identical. The difference was likely caused by the higher contents of fines and OC at one of the fields leading to stronger aggregation, smaller matrix permeability, and a more pronounced pipe-like pore system with well-aligned macropores.

Field-scale Variation in Colloid Dispersibility and Transport: Multiple Linear Regressions to Soil Physico-Chemical and Structural Properties.

Water-dispersible soil colloids (WDC) act as carriers for sorbing chemicals in macroporous soils and hence constitute a significant risk for the aquatic environment. The prediction of WDC readily available for facilitated chemical transport is an unsolved challenge. This study identifies key parameters and predictive indicators for assessing field-scale variation of WDC. Samples representing three measurement scales (1- to 2-mm aggregates, intact 100-cm rings, and intact 6283 cm columns) were retrieved from the topsoil of a 1.69-ha agricultural field in a 15-m by 15-m grid to determine colloid dispersibility, mobilization, and transport. The amount of WDC was determined using (i) a laser diffraction method on 1- to 2-mm aggregates and (ii) an end-over-end shaking method on 100-cm intact rings. The accumulated amount of colloids leached from 20-cm by 20-cm intact columns was determined as a measure of the integrated colloid mobilization and transport. The WDC and the accumulated colloid transport were higher in samples from the northern part of the field. Using multiple linear regression (MLR) analyses, WDC or amount of colloids transported were predicted at the three measurement scales from 24 measured, geo-referenced parameters to identify parameters that could serve as indicator parameters for screening for colloid dispersibility, mobilization, and transport. The MLR analyses were performed at each sample scale using all, only northern, and only southern field locations. Generally, the predictive power of the regression models was best on the smallest 1- to 2-mm aggregate scale. Overall, our results suggest that different drivers controlled colloid dispersibility and transport at the three measurement scales and in the two subareas of the field.

Clay-to-Carbon Ratio Controls the Effect of Herbicide Application on Soil Bacterial Richness and Diversity in a Loamy Field

Soil texture and soil organic carbon (OC) influence the bacterial microenvironment and also control herbicide sorption. A field-scale exploratory study was conducted to investigate the potential interaction between soil texture parameters, herbicides, and soil bacterial richness and diversity. Glyphosate and bentazon were used to evaluate the herbicidal effect on bacterial community under different conditions created by clay and OC gradients in a loamy field. Metabarcoding by high-throughput sequencing of bacterial rDNA was used to estimate bacterial richness and diversity using OTUs, abundance-based coverage (ACE), Shannon diversity index, and phylogenetic diversity. In general, bacterial richness and diversity increased after bentazon application and decreased after glyphosate application. There was no significant effect for field locations with Dexter n (the ratio between clay and OC) values below 4.04 (the median of the values in the field study). The correlation coefficient (r) between bacterial richness and clay decreased after bentazon application, but increased after glyphosate application. Correlations between Dexter n and bacterial indices followed the same pattern, decreasing after bentazon application and increasing after glyphosate application. This indicated that the specific chemical nature of individual herbicides affected bacterial communities. This study reinforced the importance of including soil physical and chemical characteristics to explain the influence of pesticides on the variation in soil bacterial communities in agroecosystems.

Visible–Near-Infrared Spectroscopy can predict Mass Transport of Dissolved Chemicals through Intact Soil

The intensification of agricultural production to meet the growing demand for agricultural commodities is increasing the use of chemicals. The ability of soils to transport dissolved chemicals depends on both the soil’s texture and structure. Assessment of the transport of dissolved chemicals (solutes) through soils is performed using breakthrough curves (BTCs) where the application of a solute at one site and its appearance over time at another are recorded. Obtaining BTCs from laboratory studies is extremely expensive and time- and labour-consuming. Visible–near-infrared (vis–NIR) spectroscopy is well recognized for its measurement speed and for its low data acquisition cost and can be used for quantitative estimation of basic soil properties such as clay and organic matter. In this study, for the first time ever, vis–NIR spectroscopy was used to predict dissolved chemical breakthrough curves obtained from tritium transport experiments on a large variety of intact soil columns. Averaged across the field, BTCs were estimated with a high degree of accuracy. So, with vis-NIR spectroscopy, the mass transport of dissolved chemicals can be measured, paving the way for next-generation measurements and monitoring of dissolved chemical transport by spectroscopy.

Particle Leaching Rates from a Loamy Soil Are Controlled by the Mineral Fines Content and the Degree of Preferential Flow

The mobilization and transport of colloid particles in soils can have negative agronomic and environmental effects. This work investigates the controls of particle release and transport from undisturbed soil columns sampled from an agricultural, loamy field with clay and silt contents of 0.05 to 0.14 and 0.07 to 0.16 kg kg, respectively. Forty-five soil columns (20 × 20 cm) were collected from the field and exposed to a constant irrigation of 10 mm h for 8 h. The accumulated mass of particles in the outflow from each column was highly correlated ( = 0.88) with the volumetric mass of fines (MF). The MF is defined as the sum of clay and fine silt (<20 μm) multiplied by the soil bulk density and divided by the particle density of the mineral fines. Thereby, MF represents both the particle source available for mobilization and leaching and an indicator of soil structure. The particle release process showed two linear particle release rates. Although the two particle release rates were distinctly different, both were strongly correlated with MF. The difference between the two rates was related to the degree of preferential flow characterized by the 5% arrival time of an applied tracer pulse. Soil columns with a longer 5% arrival time (less preferential flow) showed a distinct difference between the two rates, whereas soil columns with a short 5% arrival time and fast water transport showed resemblance between the two particle release rates. Thus, the combined effects of particle source, type, and pathways (via soil structure and compaction) need consideration to understand and predict particle transport dynamics through intact topsoil.