Soil Surface Microtopography Research Articles

Effects of microtopography change driven by seepage and slope gradients on hillslope erosion of purple soil

Seepage is the prominent hydrological process on tilled hillslopes covered by purple soil, which can easily exacerbate slope instability and soil loss. Laboratory simulated experiments with a seepage intensity of 4 L min−1 under different slope gradients (5°, 10°, and 15°) were conducted to analyze how seepage induced the erosion impacts the microtopographic change during water erosion process. Three tillage practices, i.e., smooth slope (CK), artificial diffing (AD) and ridge tillage (RT) with different initial microrelief were designed in this study. Results showed that the variation of soil surface roughness (SSR) to seepage erosion showed CK > AD > RT, and the most severe on the midslope and downslope, fluctuating from −4.23% to 12.40%. The sharpness of soil surface microtopography (SSM) on RT and AD decreased as the slope gradient increased. Compared to CK, AD and RT effectively controlled runoff loss. Both AD and RT were unable to reduce soil loss when the seepage duration exceeded 45 min, that was, the sediment yield increased by 815.50% and 730.25%, respectively. The response of surface runoff and sediment yields to microtopography changes was characterized applying multivariate linear equation. The applicability of multifractal parameters was weakened in the terms of the response to soil erosion caused by seepage. In contrast, the contribution rate of RUp to soil erosion was 69.40% and that of RDown was 58.76% in SSR indexes under seepage condition, which were the optimal parameters assessing the changes of surface runoff and sediment yields. This study contributes to elucidating seepage erosion effects in purple soil slope and understanding hydrological processes based on SSM changes.

Upslope inflow-driven variations in microtopography and size fractions effect on rill erosion in purple soil hillslopes

Upslope drainage area contributing inflow to downslope rill erosion can be affected by the dynamics of eroded sediment and soil surface microtopography. However, limited information has previously not recognized the variation of the sediment particles and microtopography on hillslopes where upslope inflow perpetually exists. A series of scouring flume experiments were performed on a 15° slope under upslope inflow rates (4, 6 and 8 L min−1) to investigate the inflow-driven microtopography and sediment particle-size distribution (PSD) during the rill erosion process. The results indicated that the surface elevation decay mostly occurred in the later stage of rill erosion. The spatial variability of microtopography increased gradually with increasing inflow rates, and obvious microtopography sharpness intensified with the development of rill erosion. The surface runoff under the 8 L min−1 inflow rate increased by 15.03 % and 90.14 % for 6 and 4 L min−1, respectively, and the sediment yield reached a maximum at the rill stabilization stage (RS). The overall particle-size distribution was mainly composed of silt-sized particles, accounting for approximately 40.97 %−50.15 % of the total eroded sediment. Considerable depletion of clay fractions occurred in the rill erosion process. High inflow rate significantly enhanced variation amplitude of critical hydrodynamic parameters (e.g., flow velocity, flow shear stress and Reynolds number). The spatial heterogeneity of microtopography was correlated with the coarser fraction of sediment PSD in rill erosion, suggesting that erosion processes were affected by the interaction between eroded sediment distribution and roughness. These findings highlight the importance of the PSD of eroded sediment and the development of soil surface structure for an in-depth understanding of the purple soil erosion mechanism at the hillslope scale.

Soil Surface Micro-Topography by Structure-from-Motion Photogrammetry for Monitoring Density and Erosion Dynamics

Soil erosion is a major threat to soil fertility, food security and water resources. Besides a quantitative assessment of soil loss, the dynamics of erosion-affected arable soil surfaces still poses challenges regarding field methods and predictions because of scale-dependent and soil management-related complex soil-crop-atmosphere processes. The objective was to test a photogrammetric Structure-from-Motion (SfM) technique for the mm-scale mapping of the soil surface micro-topography that allows the monitoring without special equipment and with widely available cameras. The test was carried out in May 2018 on three plots of 1.5 m2 (upper-, middle-, and footslope) covering surface structural features (tractor wheel lane, seed rows) along a Maize-cultivated hillslope with a coarse-textured topsoil and a runoff monitoring station. The changes in mm-scaled surface micro-topography were derived from repeatedly photographed images of the same surface area during a 2-weeks period with two rain events. A freely available SfM-program (VisualSfM) and the QGIS software were used to generate 3D-models of the surface topography. Soil cores (100 cm3) were sampled to gravimetrically determine the topsoil bulk density. The micro-topographical changes resulting from rainfall–induced soil mass redistribution within the plots were determined from the differences in SfM maps before and after rain. The largest decrease in mean soil surface elevation and roughness was observed after rain for the middle slope plot and primarily in initially less compacted regions. The spatially-distributed intra-plot changes in soil mass at the mm-scale derived from the digital micro-topography models indicated that local depressions were filled with sediments from surrounding knolls during rainfall. The estimated mass loss determined with the SfM technique decreased, if core sample-based soil settlement was considered. The effect of changes in the soil bulk density could be described after calibration also with an empirical model suggested in the Root-Zone-Water-Quality-Model. Uncertainties in the presented plot-scale SfM-technique were due to geo-referencing and the numerical limitations in the freely available SfM-software. The photogrammetric technique provided valuable information on soil surface structure parameters such as surface roughness. The successful application of SfM with widely available cameras and freely available software might stimulate the monitoring of erosion in regions with limited accessibility.

Inferring Sediment Transport Capacity from Soil Microtopography Changes on a Laboratory Hillslope

In hillslope erosion modeling, the Transport Capacity (Tc) concept describes an upper limit to the flux of sediment transportable by a flow of given hydraulic characteristics. This widely used concept in process-based erosion modeling faces challenges due to scarcity of experimental data to strengthen its validity. In this paper, we test a methodology that infers the exceedance of transport capacity by concentrated flow from changes to soil surface microtopography sustained during rainfall-runoff events. Digital Elevation Models (DEMs) corresponding to pre- and post-rainfall events were used to compute elevation change maps and estimate spatially-varying flow hydraulics ω taken as the product of flow accumulation and local slope. These spatial data were used to calculate a probability of erosion PE at regular flow hydraulics intervals. The exceedance of Tc was inferred from the crossing of the PE = 0.5 line. The proposed methodology was applied to experimental data collected to study the impact of soil subsurface hydrology on soil erosion and sediment transport processes. Sustained net deposition occurred under drainage condition while PE for seepage conditions mostly stayed in the net erosion regime. Results from this study suggest pulsating erosion patterns along concentrated flow networks with intermittent increases in PE to local maxima followed by declines to local minima. These short-range erosion patterns could not be explained by current Tc-based erosion models. Nevertheless, Tc-based erosion models adequately capture observed decline in local PE maxima as ω increased. Applying the proposed approach suggests a dependence of Tc on subsurface hydrology with net deposition more likely under drainage conditions compared to seepage conditions.

Quantifying the contributions of soil surface microtopography and sediment concentration to rill erosion

Soil surface microtopography plays a significant role in rill erosion. In addition, upslope inflow has a large effect on downslope soil erosion processes. Experiments including four different upslope filling areas (0 m2, 0.15 m2, 0.30 m2, and 0.45 m2) with a upslope inflow rate (6 L min−1) were conducted in two 1 m × 2 m boxes on a 15° slope to examine the effects of microtopography and sediment concentration on rill erosion processes. The upslope filling areas were used to simulate different areas of earthen dike terraces. The results showed that the minimum values of soil surface elevation increased from −120 mm to −110 mm as the upslope filling area increased. The values of the simple fractal dimension (f(α)max), the singular index span (Δα) and the difference of multifractal spectrum (Δf(α)) reached minimum values in the 0.45 m2 upslope filling area. With the development of rill erosion, the soil surface microtopography tended to sharpen, and the relative elevation changed greatly. The runoff and soil loss associated with rill erosion gradually decreased as the upslope filling area increased. We identified the temporal evolution of rill erosion using Morlet wavelet analysis. The main period of temporal fluctuation of rill erosion was 28 min under different upslope filling areas. Multi-scale periods of temporal fluctuation of rill erosion emerged with the increase in upslope filling area. The Δα significantly affected the runoff and soil loss. The proportional contributions of Δα to the runoff and sediment yield were 80.95% and 77.34%, respectively. While the contributions of sediment concentration to runoff and sediment yield were 17.05% and 20.66%, respectively. The findings are important significance for better understanding rill erosion mechanisms of purple soil.

Effect of tillage, slope, and rainfall on soil surface microtopography quantified by geostatistical and fractal indices during sheet erosion

Abstract Tillage and slope will influence soil surface roughness that changes during rainfall events. This study tests this effect under controlled conditions quantified by geostatistical and fractal indices. When four commonly adopted tillage practices, namely, artificial backhoe (AB), artificial digging (AD), contour tillage (CT), and linear slope (CK), were prepared on soil surfaces at 2 × 1 × 0.5 m soil pans at 5°, 10°, or 20° slope gradients, artificial rainfall with an intensity of 60 or 90 mm h−1 was applied to it. Measurements of the difference in elevation points of the surface profiles were taken before rainfall and after rainfall events for sheet erosion. Tillage practices had a relationship with fractal indices that the surface treated with CT exhibited the biggest fractal dimension D value, followed by the surfaces AD, AB, and CK. Surfaces under a stronger rainfall tended to have a greater D value. Tillage treatments affected anisotropy differently and the surface CT had the strongest effect on anisotropy, followed by the surfaces AD, AB, and CK. A steeper surface would have less effect on anisotropy. Since the surface CT had the strongest effect on spatial variability or the weakest spatial autocorrelation, it had the smallest effect on runoff and sediment yield. Therefore, tillage CT could make a better tillage practice of conserving water and soil. Simultaneously, changes in semivariogram and fractal parameters for surface roughness were examined and evaluated. Fractal parameter – crossover length l – is more sensitive than fractal dimension D to rainfall action to describe vertical differences in soil surface roughness evolution.

Experimental Setup for Splash Erosion Monitoring—Study of Silty Loam Splash Characteristics

An experimental laboratory setup was developed and evaluated in order to investigate detachment of soil particles by raindrop splash impact. The soil under investigation was a silty loam Cambisol, which is typical for agricultural fields in Central Europe. The setup consisted of a rainfall simulator and soil samples packed into splash cups (a plastic cylinder with a surface area of 78.5 cm2) positioned in the center of sediment collectors with an outer diameter of 45 cm. A laboratory rainfall simulator was used to simulate rainfall with a prescribed intensity and kinetic energy. Photographs of the soil’s surface before and after the experiments were taken to create digital models of relief and to calculate changes in surface roughness and the rate of soil compaction. The corresponding amount of splashed soil ranged between 10 and 1500 g m−2 h−1. We observed a linear relationship between the rainfall kinetic energy and the amount of the detached soil particles. The threshold kinetic energy necessary to initiate the detachment process was 354 J m−2 h−1. No significant relationship between rainfall kinetic energy and splashed sediment particle-size distribution was observed. The splash erosion process exhibited high variability within each repetition, suggesting a sensitivity of the process to the actual soil surface microtopography.

Establishment of Salsola tragus on aeolian sands: A Southern Colorado Plateau case study

AbstractRussian-thistle (Salsola tragus L.), is a nonnative, C4 photosynthesizing, annual plant that infests disturbed and natural areas in the arid U.S. Southwest. Land managers of natural areas may need to decide whether a S. tragus infestation is potentially harmful and whether it should be actively managed. One factor informing that decision is an understanding of the conditions under which this weed emerges and establishes and how those processes affect where and when infestations occur. We studied S. tragus establishment on aeolian (windblown) sandy soils at Petrified Forest National Park, AZ. Our sites were a previously disturbed sand sheet and a semistabilized sand dune. Measurements in plots on these sites over two growing seasons revealed a similar number of S. tragus seedlings emerging on both sites early in the 2015 growing season. As the season progressed, S. tragus cover (seedling survival and growth) was lower on the sand dune, except for a plot placed entirely on a coppice mound. In 2016, S. tragus seedling emergence and development of cover, measured on plots at both sites, was exceptionally low, as was summer rainfall. A growth chamber assay of seedling emergence from soil and litter samples collected at each site showed emergence was greatest from samples collected where S. tragus litter remained on the soil surface, and otherwise was infrequent. Our study suggests that S. tragus emergence and early establishment are sensitive to low precipitation and that soil-surface microtopography and grass and shrub cover may be determinants of the spatial pattern of infestation on sandy soils. As aeolian sands occur throughout drylands of the U.S. Southwest, deeper understanding of the conditions under which S. tragus seedlings emerge and establish can inform management of this invasive annual in those habitats.

Modeling the Effects of Spatial Variability of Irrigation Parameters on Border Irrigation Performance at a Field Scale

The interaction between surface and subsurface water flows plays an important role in surface irrigation systems. This interaction can effectively be simulated by the physical-based models, which have been developed on the basis of the numerical solutions to the Saint-Venant and Richards’ equations. Meanwhile, the spatial variability of field physical properties (such as soil properties, surface micro-topography, and unit discharge) affects the interaction between surface and subsurface water flows and decreases the accuracy of simulating surface irrigation events at large scales. In this study, a new numerical methodology is developed based on the physical-based model of surface irrigation and the Monte Carlo simulation method to improve the modeling accuracy of surface irrigation performance at a field scale. In the proposed numerical methodology, soil properties, unit discharge, surface micro-topography, roughness, border length, and the cutoff time for the unit discharge are used as the stochastic parameters of the physical-based model, while field slope is assumed as the constant value because of the same field tillage and management conditions at a field scale. Monte Carlo simulation is used to obtain the stochastic parameter sample combinations of the physical-based model to represent the spatial variability of field physical properties. The updated stochastic simulation model of surface micro-topography, which is developed to model the spatial distribution of surface elevation differences (SED), is used to obtain the surface micro-topography samples at a field scale. Compared with the distributed-parameter modelling methodology and the field experimental data, the proposed numerical methodology presents the better simulation performance.

Effect of tillage on soil erosion before and after rill development

AbstractTillage has a large effect on soil surface microtopography and consequently on soil erosion. Here, we measured soil and water loss from soil prepared by contour tillage (CT) and reservoir tillage (RT), and to analyse why tilled slopes produce more sediment run‐off. Rainfall experiments (90 mm/hr) were carried out to simulate the overland and rill flow erosion processes. Soil type is silt clay loam. Results showed that CT and RT reduced surface run‐off by 60% compared with a smooth slope during overland flow, whereas only a small reduction in run‐off occurred during rill flow. Sediment erosion from CT was reduced by about 30–60% compared with a smooth slope for both overland and rill flow erosion processes. Although RT also resulted in reduced sediment erosion during overland flow, sediment erosion increased by 25% during rill flow, leading to an overall increase in sediment flow on the RT‐treated slope. For slopes with CT, sediment production depends on the ridges, but furrows limit sediment transport. For slopes with RT, sediment production depends on the depressions, but once the depressions fill with sediment, rainwater outflowing from the depressions cause rill flow erosion and greater sediment loss compared with CT. Our results suggest that sediment and run‐off differences for different surface microtopographies induced by tillage are significant, especially during the rill flow erosion process. Future studies should address rill erosion on tilled sloped land with different microtopographies to better determine how rills are triggered and change during rainfall.

Application of Digital Elevation Model (DEM) for description of soil microtopography changes in laboratory experiments

Abstract In the study we evaluated spatial and quantitative changes in soil surface microtopography to describe water erosion process under simulated rain with use of a non-contact optical 3D scanner. The experiment was conducted in two variants: with and without drainage layer. Two clay soils collected from farmlands from the catchment of lake Zgorzała (Warsaw) were investigated. Six tests of simulated rain were applied, with 55 mm·h−1. The surface roughness and microrelief were determined immediately after every 10 min of rainfall simulation by 3D scanner. The volume of surface and underground runoff as well as soil moisture were measured. The surface points coordinates obtained while scanning were interpolated using natural neighbour method and GIS software to generate Digital Elevation Models (DEM) with a 0.5 mm resolution. Two DEM-derived surface roughness indices: Random Roughness (RR) and Terrain Ruggedness Index (TRI) were used for microrelief description. Calculated values of both roughness factors have decreased with time under the influence of rainfall in all analyzed variants. During the sprinkling the moisture of all samples had been growing rapidly from air-dry state reaching values close to the maximum water capacity (37–48% vol.) in 20–30 min. Simultaneously the intensity of surface runoff was increasing and cumulative runoff value was: 17–35% for variants with drainage and 72–83% for the variants without drainage, relative to cumulative rainfall. The observed soil surface elevation changes were associated with aggregates decomposition, erosion and sedimentation, and above all, with a compaction of the soil, which was considered to be a dominant factor hindering the assessment of the erosion intensity of the of the scanned surface.

Effects of structural and depositional crusts on soil erosion on the Loess Plateau of China

ABSTRACTConventional tillage practices used on the Loess Plateau lead to different soil surface micro-topography which results in forming two types of soil crusts. The objective of this study was to explore the formation position, properties and erosion characteristics of structural crusts and depositional crusts under the influences of the microtopography in the rainfall experiments. Two simulated rainstorms were applied in the experiments. The first rainfall event was used for soil crust formation, then the following simulated rainfall storms at 40 mm h−1, 60 mm h−1, and 80 mm h−1 rates were applied to the soil boxes set to a 17.6% (10°) slope under three tillage types (contour tillage, artificial digging, and straight slope conditions) to investigate the resulting runoff discharge rate and sediment yield on crusted soil surface. Results show that: (1) structural crusts formed on the mounds, and depositional crusts formed in the depressions after the first rainfall events; structural crusts exhibit a lower thickness, bulk density, higher porosity and shear strength than depositional crusts; (2) structural crusts increased the runoff yield less and decreased the sediment yield more than depositional crusts; and (3) the runoff yield was significantly greater, and the sediment yield was lower on the crusted soil surface than that on the uncrusted soil surface, regardless of the effect of the tillage treatments.

Moiré as a low-cost, robust, optical-technique to quantify soil surface condition

The microtopography of the soil surface is important for water entry, run-off and aeration. Despite the need there remain limited options for accurate, robust, low-cost, field based methods to measure soil surface microtopography such as created by the passage of agricultural machines including tyres and tracks. The Moiré technique (MT) has been used for shape analysis of biological samples. The technique uses an interference phenomenon created by light gratings projected onto the surface of interest. First, using commonly available equipment, we calibrated the technique against objects of known shapes and dimensions and achieved a sensitivity of about 1mm. We then used the technique in the field, with the same equipment, to assess the imprint created by the tread pattern of a tyre during a single passage of a tractor and to determine the depth of imprint created after multiple passes of the same tractor. The area of the soil surface studied was 450×600mm. All image processing and analysis of the data were done using a standard lap-top computer with free platform software. To within the sensitivity of the deployed MT we were able to determine features such as surface roughness and depth of rutting and by subtraction to determine the consequences of multiple passes. We conclude that the MT has wide utility for studying soil surface conditions. Further as all the equipment is commonly available and the software is free platform the use of the MT in this form can be very widely adopted.

Assessing the performance of structure‐from‐motion photogrammetry and terrestrial LiDAR for reconstructing soil surface microtopography of naturally vegetated plots

AbstractSoil microtopography is a property of critical importance in many earth surface processes but is often difficult to quantify. Advances in computer vision technologies have made image‐based three‐dimensional (3D) reconstruction or Structure‐from‐Motion (SfM) available to many scientists as a low cost alternative to laser‐based systems such as terrestrial laser scanning (TLS). While the performance of SfM at acquiring soil surface microtopography has been extensively compared to that of TLS on bare surfaces, little is known about the impact of vegetation on reconstruction performance. This article evaluates the performance of SfM and TLS technologies at reconstructing soil microtopography on 6 m × 2 m erosion plots with vegetation cover ranging from 0% to 77%. Results show that soil surface occlusion by vegetation was more pronounced with TLS compared to SfM, a consequence of the single viewpoint laser scanning strategy adopted in this study. On the bare soil surface, elevation values estimated with SfM were within 5 mm of those from TLS although long distance deformations were observed with the former technology. As vegetation cover increased, agreement between SfM and TLS slightly degraded but was significantly affected beyond 53% of ground cover. Detailed semivariogram analysis on meter‐square‐scale surface patches showed that TLS and SfM surfaces were very similar even on highly vegetated plots but with fine scale details and the dynamic elevation range smoothed out with SfM. Errors in the TLS data were mainly caused by the distance measurement function of the instrument especially at the fringe of occlusion regions where the laser beam intersected foreground and background features simultaneously. From this study, we conclude that a realistic approach to digitizing soil surface microtopography in field conditions can be implemented by combining strengths of the image‐based method (simplicity and effectiveness at reconstructing soil surface under sparse vegetation) with the high accuracy of TLS‐like technologies. Copyright © 2015 John Wiley & Sons, Ltd.

Termografia para determinação da microtopografia da superfície do solo em diferentes condições de cobertura morta

In this study we present an infrared thermography technique that can be useful to detect soil surface microtopography in the presence of mulch. Laboratory test were carried out where the performance of the technique was evaluated in a surface with artificial rills and in a surface with microtopography created by water erosion, for different mulch cover conditions (bare soil, 2 and 4 t ha-1). Microtopography was detected applying heated water on the soil surface and recording the temperature with an infrared video camera. The technique allowed us to obtain 3D models of soil surface elevation both in the scenario with artificial rills and in the scenario with microtopography created by water erosion. With this technique it was possible to identify preferential flow paths and the different elements of microtopography, even in the presence of 2 t ha-1 of mulch covering the soil surface. In the scenario with cover density of 4 t ha-1, the detection of the thermal radiation emitted by the soil surface was severely affected, resulting in a decrease of the performance of the technique.

Quantification of Soil Random Roughness and Surface Depression Storage: Methods, Applicability, and Limitations

Soil surface microtopography controls surface runoff, infiltration, and other hydrologic processes by storing water in depressions, changing flow directions and accumulations, and even altering the entire drainage system. Studies have been conducted to characterize surface microrelief and quantify surface depression storage. Various indices have been proposed to quantify soil surface roughness, and some indices have been further used to estimate maximum depression storage (MDS). Random roughness (RR) has been one of the widely used indices for estimating MDS over the past four decades. However, there have been some confusions and controversies on the data processing procedures and computation methods associated with the RR index-based approach. The focus of this study is on evaluating the performance and applicability of the RR index-based approach that incorporates four different data processing procedures for a series of microtopographic surfaces. It is demonstrated that selecting proper data processing procedures is critical and helpful to improve the estimation of RR and MDS. Particularly, removal of oriented roughness (slope and tillage marks) is a necessary data processing procedure. For a real soil surface, the relationship of MDS and slope is nonlinear and the changing pattern of MDS with RR varies, depending on the surface microtopographic conditions. In addition, the mean upslope depression (MUD) method is applied to estimate MDS for tillage surfaces. It has been found that the RR index-based approach is better suited for gentle sloping surfaces, while the MUD index method is able to provide improved estimation of MDS for steeper slopes.

Modeling the dynamics of soil erosion and size‐selective sediment transport over nonuniform topography in flume‐scale experiments

Soil erosion and the associated nutrient fluxes can lead to severe degradation of surface waters. Given that both sediment transport and nutrient sorption are size selective, it is important to predict the particle size distribution (PSD) as well as the total amount of sediment being eroded. In this paper, a finite volume implementation of the Hairsine‐Rose soil erosion model is used to simulate flume‐scale experiments with detailed observations of soil erosion and sediment transport dynamics. The numerical implementation allows us to account for the effects of soil surface microtopography (measured using close range photogrammetry) on soil erosion. An in‐depth discussion of the model parameters and the constraints is presented. The model reproduces the dynamics of sediment concentration and PSD well, although some discrepancies can be observed. The calibrated parameters are also consistent with independent data in the literature and physical reason. Spatial variations in the suspended and deposited sediment and an analysis of model sensitivity highlight the value of collecting distributed data for a more robust validation of the model and to enhance parametric determinacy. The related issues of spatial resolution and scale in erosion prediction are briefly discussed.

Estimating changes in effective values of surface detention, depression storage and friction factor at the interrill scale, using a cheap and fast method to mold the soil surface micro-topography

Abstract Surface detention and depression storage constitute the two conceptual storages of water at the soil surface and depend on the spatial configuration of the micro-topography. To be able to measure directly those storages and investigate how they evolve with time and precipitation, it is necessary to isolate the impact of the micro-topography from the infiltration. Therefore we developed a fast and cheap in-situ molding method (+/−85 €/m 2 ) that combines alginate, plaster and lacquer. It allows creating stable and impermeable artificial micro-topographies that reproduce real field situations and that can be submitted to various laboratory runoff simulations. Both the surface of a specific soil and its artificial reproduction were measured with a laser scanner in order to assess the quality of the molding method. This method is shown to be precise with a standard deviation of 0.55 mm, which is also the spatial resolution of the laser scanner method. This novel molding method was applied to get ten footprints of the micro-topography of a loamy bare soil, at different levels of cumulative rainfall erosivity value (R), starting with a tilled soil, and letting it evolve with natural rain events. We studied the evolution of the bulk values of depression storage and surface detention at the interrill scale, considering that these bulk values may provide useful input to hillslope models for which the size of the single grid cell corresponds to the size of our entire molds. We related the hydraulic properties to R, assuming that R would help explain the change in hydraulic parameters of micro-topographies over time. We found a general decrease of maximum depression storage and steady state surface detention with R. We finally parametrized surface detention by an effective friction factor, using a classical equation for an equivalent laminar sheet flow. A simple model to compute the surface detention as a function of the discharge per unit width and the cumulative rainfall erosivity was proposed.

A multifractal approach to characterize cumulative rainfall and tillage effects on soil surface micro-topography and to predict depression storage

Abstract. Most of the indices currently employed for assessing soil surface micro-topography, such as random roughness (RR), are merely descriptors of its vertical component. Recently, multifractal analysis provided a new insight for describing the spatial configuration of soil surface roughness. The main objective of this study was to test the ability of multifractal parameters to assess in field conditions the decay of initial surface roughness induced by natural rainfall under different soil tillage systems. In addition, we evaluated the potential of the joint use of multifractal indices plus RR to improve predictions of water storage in depressions of the soil surface (MDS). Field experiments were performed on an Oxisol at Campinas, São Paulo State (Brazil). Six tillage treatments, namely, disc harrow, disc plough, chisel plough, disc harrow + disc level, disc plough + disc level and chisel plough + disc level were tested. In each treatment soil surface micro-topography was measured four times, with increasing amounts of natural rainfall, using a pin meter. The sampling scheme was a square grid with 25 × 25 mm point spacing and the plot size was 1350 × 1350 mm (≈1.8 m2), so that each data set consisted of 3025 individual elevation points. Duplicated measurements were taken per treatment and date, yielding a total of 48 experimental data sets. MDS was estimated from grid elevation data with a depression-filling algorithm. Multifractal analysis was performed for experimental data sets as well as for oriented and random surface conditions obtained from the former by removing slope and slope plus tillage marks, respectively. All the investigated microplots exhibited multifractal behaviour, irrespective of surface condition, but the degree of multifractality showed wide differences between them. Multifractal parameters provided valuable information for characterizing the spatial features of soil micro-topography as they were able to discriminate data sets with similar values for the vertical component of roughness. Conversely, both, rough and smooth soil surfaces, with high and low roughness values, respectively, can display similar levels of spectral complexity. Although in most of the studied cases trend removal produces increasing homogeneity in the spatial configuration of height readings, spectral complexity of individual data sets may increase or decrease, when slope or slope plus tillage tool marks are filtered. Increased cumulative rainfall had significant effects on various parameters from the generalized dimension, Dq, and singularity spectrum, f(α). Overall, micro-topography decay by rainfall was reflected on a shift of the singularity spectra, f(α) from the left side (q>>0) to the right side (q>0) to the left side (q

Controls of land use and soil structure on water movement: Lessons for pollutant transfer through the unsaturated zone

Summary To address the effects of land use and land cover (LULC) on soil structure formation and the significance on preferential flow during infiltration, dye tracer experiments were conducted on five sites differing in LULC, yet displaying similar soil textural characteristics and parent material. Two grassland sites, two farmland sites (tilled and untilled) and one site located in a deciduous forest were investigated. At each site, the same sprinkling experiment was carried out with a Brilliant Blue FCF solution of 4 g L −1 to visualize flow paths. To explore the effects of different rainfall amounts (20, 40 and 60 mm), each 1.2 × 1.5 m experimental plot was subdivided into three smaller subplots, which were irrigated with an intensity of 15 mm h −1 for 80, 160 and 240 min, respectively. During the tracer application, water content changes were continuously measured with 16 time domain reflectometry probes horizontally installed into the profile at different depths. After the experiments vertical and horizontal soil sections were excavated and photographed. The pictures were processed using digital image analysis and the resulting dye patterns analyzed for volume and surface density, maximum infiltration depth and macropore structure. Additionally, flow processes were classified into distinct flow type categories. The tracer experiments revealed that preferential flow processes significantly differed among sites of differing LULC yet similar soil texture. As primary controlling factors soil structure, surface micro-topography, surface cover and topsoil matrix characteristics were identified. The effects of different rainfall application amounts were complex and strongly varied among sites, stressing the strong control LULC exerts on water flow in soils. Overall this suggests that land use effects on soil properties need to be considered in hydrological models to obtain realistic predictions concerning water quality and quantity.