Sheela Katuwal

Bio: Sheela Katuwal is an academic researcher from Aarhus University. The author has contributed to research in topics: Soil water & Macropore. The author has an hindex of 12, co-authored 19 publications receiving 414 citations.

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

Abstract: 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 ( K a ) and saturated hydraulic conductivity ( K sat ). The CT number of the matrix (CT matrix ), 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 CT matrix 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 ( t 0.05 ). The CT-derived macroporosity (pores >1.2 mm) was correlated with K a and log 10 ( K sat ). 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 CT matrix , limiting macroporosity, and genus density, while the best model for t 0.05 used CT matrix 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.

Effects of CT Number Derived Matrix Density on Preferential Flow and Transport in a Macroporous Agricultural Soil

Abstract: Preferential flow and transport in structured soils can be intimately linked to numerous environmental problems. Surface-applied chemicals are susceptible to rapid transport to deeper depths in structural soil pores, thereby potentially contaminating valuable environmental resources and posing risks to public health. This study focused on establishing links between the structural pore space and preferential transport using a combination of standard physical measurement methods for air and water permeabilities, breakthrough experiments, and X-ray computed tomography (CT) on large soil columns. Substantial structural heterogeneity that resulted in significant variations in flow and tracer transport was observed, despite the textural similarity of the investigated samples. Quantification of macropore characteristics with X-ray CT was useful but not sufficient to explain the variability in air permeability, saturated hydraulic conductivity, and solute transport. This was due to the limited CT scan resolution and large structural variability below this resolution. However, CT matrix , a new parameter derived from the CT number of the matrix excluding stones and large mostly air-filled macropores, was found to be useful for determining the magnitude of preferential flow under boundary conditions of constant, near-saturated flow.

Effect of Root Density on Erosion and Erodibility of a Loamy Soil Under Simulated Rain

Abstract: Although both aboveground and belowground components of vegetation act together in reducing soil erosion, mainly the aboveground component has received attention in past research. The aim of this study was to evaluate the contribution of roots in soil erosion control and the effect of root density in soil erodibility and soil physical properties. Perennial ryegrass (Lolium perenne L. Hugo) was grown in soil pans, and laboratory rainfall simulation experiments were conducted after 4, 8, 12 weeks of their growth with seeding density of 50 kg ha-1, after 4 weeks for seeding density of 100 kg ha-1, and on a control. The experiments with ryegrass were done in the presence of complete plants and after clipping off the shoots. Roots of ryegrass grew rapidly, attaining densities of 0.614 kg m-2 and 2.280 kg m-2 in 4 and 12 weeks, respectively. With increasing root density, splash and wash decreased exponentially. There was positive correlation between soil shear strength and root density, but no influence of roots on bulk density and saturated hydraulic conductivity was observed.

Pedotransfer functions in Earth system science: challenges and perspectives

Abstract: Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration and organic carbon content, root density and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale.

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

Abstract: 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.