Smooth Soil Surfaces Research Articles

Quantifying the changes of soil surface microroughness due to rainfall impact on a smooth surface

Abstract. This study examines the rainfall-induced change in soil microroughness of a bare smooth soil surface in an agricultural field. The majority of soil microroughness studies have focused on surface roughness on the order of ∼ 5–50 mm and have reported a decay of soil surface roughness with rainfall. However, there is quantitative evidence from a few studies suggesting that surfaces with microroughness less than 5 mm may undergo an increase in roughness when subject to rainfall action. The focus herein is on initial microroughness length scales on the order of 2 mm, a low roughness condition observed seasonally in some landscapes under bare conditions and chosen to systematically examine the increasing roughness phenomenon. Three rainfall intensities of 30, 60, and 75 mm h−1 are applied to a smoothened bed surface in a field plot via a rainfall simulator. Soil surface microroughness is recorded via a surface-profile laser scanner. Several indices are utilized to quantify the soil surface microroughness, namely the random roughness (RR) index, the crossover length, the variance scale from the Markov–Gaussian model, and the limiting difference. Findings show a consistent increase in roughness under the action of rainfall, with an overall agreement between all indices in terms of trend and magnitude. Although this study is limited to a narrow range of rainfall and soil conditions, the results suggest that the outcome of the interaction between rainfall and a soil surface can be different for smooth and rough surfaces and thus warrant the need for a better understanding of this interaction.

Effects of soil surface roughness on interrill erosion processes and sediment particle size distribution

Soil surface roughness significantly impacts runoff and erosion under rainfall. Few previous studies on runoff generation focused on the effects of soil surface roughness on the sediment particle size distribution (PSD), which greatly affects interrill erosion and sedimentation processes. To address this issue, a rainfall-simulation experiment was conducted with treatments that included two different initial soil surface roughnesses and two rainfall intensities. Soil surface roughness was determined by using photogrammetric method. For each simulated event, runoff and sediment samples were collected at different experimental times. The effective (undispersed) PSD of each sediment sample and the ultimate (after dispersion) PSD were used to investigate the detachment and transport mechanisms involved in sediment movement. The results show that soil surface roughness significantly delayed runoff initiation, but had no significant effect on the steady runoff rate. However, a significant difference in the soil loss rate was observed between the smooth and rough soil surfaces. Sediments from smooth soil surfaces were more depleted in clay-size particles, but more enriched in sand-size particles than those from rough soil surfaces, suggesting that erosion was less selective on smooth than on rough soil surfaces. The ratio of different sizes of transported sediment to the soil matrix indicates that most of the clay was eroded in the form of aggregates, silt-size particles were transported mainly as primary particles, and sand-size particles were predominantly aggregates of finer particles. Soil surface roughness has a crucial effect on the sediment size distribution and erosion processes. Significant differences of the enrichment ratios for the effective PSD and the ultimate PSD were observed under the two soil surface roughness treatments. These findings demonstrate that we should consider each particle size separately rather than use only the total sediment discharge in assessing and modeling interrill erosion processes.

Soil and environmental factors affecting the efficacy of pyroxasulfone for weed control.

Pyroxasulfone inhibits very-long-chain fatty acid elongase in susceptible weeds and facilitates preemergence weed control. Pyroxasulfone showed 98% control of Echinochloa crus-galli (ECHCG) for up to 63 days at a use rate lower than that of chloroacetamide herbicides. ED90 of pyroxasulfone against ECHCG in soil with high organic matter (OM) content did not differ significantly from that in lower OM soils. The low water solubility and the low vapor pressure of pyroxasulfone resulted in limited horizontal diffusion on the soil surface and low risk of volatilization, respectively. The herbicidal efficacy of pyroxasulfone was affected by clod size and improved with smooth soil surface preparation.

Effects of Soil Surface Irregularities on the Diurnal Variation of Soil Broadband Blue-Sky Albedo

This paper quantitatively explores, in terms of roughness indices, the effect of soil surface irregularities on the diurnal variation of the broadband blue-sky albedo of a large range of soil properties. Field studies were carried out on cultivated and uncultivated soil surfaces in Poland and Israel that vary in roughness and brightness. It was found that these irregularities, formed by different agricultural equipment and modified by rain or sprinkler irrigation, can be quantified by two roughness indices. Soil roughness not only affects the overall level of the diurnal variation of the albedo, but also affects the intensity of the diurnal increase from the solar zenith angle ( ${\thetab_{\mbi s}}$ ) at the local noon to about $75^\circ - 80^\circ$ . The roughness indices are variables that precisely determine only the albedo at the local solar noon of soils with the same color value. If the contents of soil organic carbon (SOC) and calcium carbonate are treated as the dominant variables, combined with one of the indices, these three variables together would significantly describe the albedo at the local solar noon of all soil surfaces. The soils, with their high irregularities, showed almost no rising values of albedo at a ${\thetab_{\mbi s}}$ lower than 75 $^\circ$ , while the smooth soil surfaces exhibited a gradual increase of the albedo at these angles. It is concluded that the roughness indices provide sufficient means to accurately describe the diurnal variation of the albedo of a wide range of surfaces, disregarding other soil properties.

Effect of surface roughness, wavelength, illumination, and viewing zenith angles on soil surface BRDF using an imaging BRDF approach

Compared to non-imaging instruments, imaging spectrometers (ISs) can provide detailed information to investigate the influence of scene components on the bidirectional reflectance distribution function (BRDF) of a mixed target. The research reported in this article investigated soil surface reflectance changes as a function of scene components (i.e. illuminated pixels and shaded pixels), illumination and viewing zenith angles, and wavelength. Image-based BRDF data of both rough and smooth soil surfaces were acquired in a laboratory setting at three different illumination zenith angles and at four different viewing zenith angles over the full 360° azimuth range, at an interval of 20°, using a Specim V10E IS (Specim, Spectral Imaging Ltd., Oulu, Finland) mounted on the University of Lethbridge Goniometer System version 2.5 (ULGS-2.5). The BRDF of the smooth soil surface was dominated by illuminated pixels, whereas the shaded pixels were a larger component of the BRDF of the rough soil surface. As the illumination zenith angle was changed from 60° to 45° and then to 30°, the shadowing effect decreased, regardless of the soil surface. Soil surface reflectance was generally higher at the backscattering view zenith angles and decreased continuously to forward scattering view zenith angles in the light principal plane, regardless of the wavelength, due to the Specim V10E IS seeing more illuminated pixels in the backscattering angles than in the forward scattering angles. Higher soil surface reflectance was observed at higher illumination and viewing zenith angle combinations. For both soil surface roughness categories, the BRDF exhibited a greater range of values in the near-infrared than at the visible wavelengths. This research enhances our understanding of soil BRDF for various soil roughness and illumination conditions.

Runoff, erosion and sediment particle size from smooth and rough soil surfaces under steady rainfall-runoff conditions

The responses of runoff and erosion to soil surface roughness (SSR) have been extensively studied in the past decades; however, most of these studies were conducted at the early stage of rainfall, whereas few studies were specifically conducted during steady runoff conditions. In this study, runoff, soil losses and sediment particle sizes from smooth and rough surfaces were measured after surface runoff stabilisation to improve the understanding of the relationship between SSR and soil erosion. A cascade of two independent soil boxes in which the runoff samples from upslope and downslope boxes can be collected independently or together was used to perform the experiments. The upslope box supplied runoff to the downslope study box. Three rainfall intensities of 50, 75 and 100 mm/h were applied. The results suggest that SSR has a significant effect on soil erosion when runoff reaches a steady state. Although the difference in the runoff rate was small between the rough and smooth surfaces, the sediment rate and concentration of particles were significantly lower for the rough surface than for the smooth surface. Through analysing the particle size distribution (PSD) of sediment, we found that selective sediment delivery is an important reason for the soil erosion reduction by SSR. The rainfall intensity decreased the difference in the sediment rates between the smooth and rough surfaces. The extra inflow increased the runoff rates, sediment rates and concentration rates for both the smooth and rough surfaces; however, the increasing degrees of the runoff rate, sediment rate and concentration rate had significant differences between the rough and smooth surfaces. A stepwise multiple regression showed that significant linear relationships existed between one or more PSDs of 20–50, 50–100, 100–250 and 1000–2000 µm and the sediment rate.

Simulation of Runoff Patterns and Soil Erosion on Mountainous Farmland with and without Plastic-Covered Ridge-Furrow Cultivation in South Korea

<abstract><title><italic>Abstract.</italic></title> Plastic-covered ridge-furrow cultivation (plastic mulch) can substantially influence runoff and soil erosion on agricultural land. However, the impact of this management practice in combination with complex farmland topography has not been thoroughly investigated. The goal of this study was to identify how topography influences runoff patterns and erosion rates of plastic mulch cultivation. We measured runoff and sediment transport on two mountainous fields in South Korea, one with a concave topography and one with a convex topography, during monsoonal rain events. We used the EROSION 3D model to compare flow and sediment transport between plastic mulch, uncovered ridges, and a smooth soil surface. We found the highest runoff and erosion rates from both of the fields with plastic mulch due to the impermeable surface. For the uncovered ridges, we identified 140% higher erosion compared to the smooth surface on the concave field, but 20% lower erosion on the convex field. The simulated sediment transport patterns showed that the ridge-furrow system concentrated overland flow on the concave field, resulting in high erosion rates. On the convex field, the ridge-furrow system prevented flow accumulation and erosion. Our results demonstrate that the effect of ridge-furrow systems on erosion is controlled primarily by the topography. These results have practical consequences for watershed conservation planning and the application of large-scale erosion models. Nevertheless, further research is needed to fully understand the impact of this management system on runoff and erosion on mountainous farmland.

Inter-row tillage for improved soil and water conservation and crop yields on crusted Alfisols

In the semi-arid tropics (SAT),33% areas are occupied by Alfisols and related soils. In SAT these soils have low structural stability and thereby tend to form seal and crusts at the surface. Due to this a large proportion of the rain that falls on Alfisols during the early part of the rainy season,is normally lost as runoff thus causing high soil loss as well as moisture stress to crops. Two tillage studies were conducted first at plot scale (320 m2) during 1991-95 and second at small watershed scale (1.45 ha) during 2007-10,at ICRISAT research station,Hyderabad,India. These studies were conducted to find out whether the problem of excessive runoff and soil loss during the early part of the rainy season can be controlled by various inter-row tillage systems in addition to normal intercultivation by breaking the crust or seal and thereby improving infiltration and soil moisture and reducing runoff and soil loss. The observations on rainfall,runoff,soil moisture,soil loss,soil surface roughness and crop yields were collected from both the studies. Results from these studies have shown that inter-row tillage in addition to normal intercultivation is found effective in controlling early season runoff and soil loss and increasing crop yields. The additional tillage systems are found most effective during low and medium rainfall years and not so much during high rainfall years. The additional tillage with shoe cultivators,which creates rough soil surface (11 mm depression storage),is found most effective in increasing crop yields and reducing runoff and soil loss. The additional tillage with blade harrow which generates smooth soil surface is relatively less effective. In most rainfall conditions,the normal intercultivation with one additional tillage is found adequate for controlling early season runoff and improving soil moisture and crop yields.

Effect of soil surface roughness and scene components on soil surface bidirectional reflectance factor

Wang, Z., Coburn, C. A., Ren, X. and Teillet, P. M. 2012. Effect of soil surface roughness and scene components on soil surface BRF. Can. J. Soil Sci. 92: 297–313. Bidirectional Reflectance factor (BRF) data of both rough [surface roughness index (SRI) of 51%] and smooth soil surfaces (SRI of 5%) were acquired in the laboratory under 30° illumination zenith angle using a Specim V10E imaging spectrometer and an Ocean Optics non-imaging spectrometer mounted on the University of Lethbridge Goniometer System version 2.5 (ULGS-2.5) and version 2.0 (ULGS-2.0), respectively. Under controlled laboratory conditions, the rough soil surface exhibited higher spectral reflectance than the smooth surface for most viewing angles. The BRF of the rough surface varied more than the smooth surface as a function of the viewing zenith angle. The shadowing effect was stronger for the rough surface than for the smooth surface and was stronger in the forward-scattering direction than in the backscattering direction. The pattern of the BRF generated with the non-image based data was similar to that generated with the whole region of interest (ROI) of the image-based data, and that of the whole ROI of the image-based data was similar to that of the illuminated scene component. The BRF of the smooth soil surface was dominated by illuminated scene component, i.e., the sunlit pixels, whereas the shaded scene component, i.e., the shaded pixels, was a larger proportion of the BRF of the rough soil surface. The image-based approach allowed the characterization of the contribution of spatial components in the field of view to soil BRF and improved our understanding of soil reflectance.

A Simplified Close‐Range Photogrammetric Technique for Soil Erosion Assessment

Surface reconstruction using digital photogrammetry offers a great advantage for soil erosion research. The technology can be cumbersome for field application because it relies on the accurate measurement of control points, often using a survey‐grade instrument. Also, even though digital photogrammetry has been used in much soil erosion research, its sensitivity in detecting soil elevation changes has rarely been assessed. This study aimed at simplifying the digital photogrammetric procedure for soil erosion research and assessing the sensitivity of this technology to detect soil erosion. To simplify the technology, we propose to combine a photogrammetric procedure for control point generation in a first step, followed by a conventional photogrammetric digital elevation model (DEM) extraction procedure. The performance of the method was assessed in the laboratory and tested in the field to digitize ephemeral gullies. In the accuracy test of photogrammetric survey step, we found that the maximum length measurement error was 3.4 mm, while the maximum angular deviation from the vertical or horizontal axes was 0.93°. The maximum error between control point coordinates generated by photogrammetry and those generated by a survey‐grade total station was 26 mm on the horizontal axes and 10 mm on the vertical axis. We also found that the sensitivity of digital photogrammetry in detecting soil surface elevation changes was similar to that of a laser scanner when the detection was performed on smooth soil surfaces and when the standard deviation of the elevation changes was approximately three times the precision of the photogrammetric DEM.

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&gt;&gt;0) to the right side (q&gt;0) to the left side (q

Calculating the optimal time when albedo approximates its daily average: an example using soil surfaces with various roughnesses at different latitudes

This paper describes how the blue-sky albedo of soil varies during the whole year from midday to sunset under clear-sky conditions. A hemispherical-directional reflectance model was used to calculate albedo variations associated with smooth, moderate and rough soil surfaces, located between the latitude angles of 75° in the Northern and Southern Hemispheres. We calculate the time when the albedo, acquired by an instantaneous observation, best represents its daily averaged value. This optimal time range is assessed in the context of remote-sensing satellite technology.

Generating 3D soil surfaces from 2D height measurements to determine depression storage

Surface depression storage is an important factor in preventing runoff and erosion in agricultural fields. Furthermore it is a highly dynamic property throughout the growing season. Maximum depression storage (MDS) is generally estimated from roughness indices derived from 2D transects, but these MDS estimations have a high uncertainty. The most reliable way of estimating MDS is by simulating the filling of a digital elevation model (DEM) of the soil surface using an algorithm. Yet, measurements of DEMs are often not available because they result from demanding equipment (laser roughness meters or photogrammetry). The aim of this study was to produce 3D DEMs with correct storage characteristics, using a simulation model that uses common 2D field elevation measurements as input. Two different types of models generating random surfaces, Gaussian and Boolean, were tested for their ability to simulate the soil surface of seedbeds. The models were tested on two experimental soil surfaces representing freshly tilled seedbeds. The DEM of these surfaces was constructed from laser measurements on a regular grid. Transects of these DEMs served as basis to derive the model parameters. Finally the models generated artificial DEMs. MDS was estimated on all DEMs using a filling algorithm included in the PCRaster software. The quality of the simulated surfaces was not only evaluated based on MDS, but also on the roughness index RR, the height distributions, the semivariograms, and their form. Results showed that only one Boolean model generated surfaces with the correct mean MDS values for the smooth soil surface. Almost all models overestimated MDS, although most had correct RR values. None of the models is capable of generating surfaces with realistic storage characteristics for both experimental surfaces. However, the method is promising because it is reproducible; simulated surfaces derived from a same set of parameters are very similar in MDS. When improved, this method is potentially more accurate than the statistical two-dimensional methods based on roughness indices.

Runoff and sediment losses from rough and smooth soil surfaces in a laboratory experiment

Soil surface roughness may significantly impact runoff and erosion under rainfall. A common perception is that runoff and erosion are decreased as a function of roughness because of surface ponding and increased hydraulic roughness that reduces effective flow shear stress. The objective of this study was to measure the effects of initial surface roughness on runoff and erosion under controlled laboratory conditions. Initially, rough and smooth surfaces were exposed to five simulated rainfall applications at 5% and 20% slopes. In all cases, runoff was delayed for the case of the initially rough surface; however, this effect was temporary. Overall, no statistical differences in either total runoff or erosion were measured on the 20% slope. At 5% slope, runoff was less on the rough surface for the first rainfall application but greater on the final three, probably due to the formation of a depositional seal in that case. This resulted in an overall insignificant difference in runoff for the sum of the five rainfall applications. Erosion was greater on the rougher slope at 5% steepness, probably due to concentration of flow as it moved around the roughness elements on the rougher slope. These results indicate that commonly held perceptions of the impact of soil surface roughness on runoff and erosion may not be entirely correct in all cases.

Reanalysis of L-band brightness predicted by the LSP/R model-for prairie grassland: incorporation of rough surface scattering

L-band brightness predicted by the land surface process/radiobrightness (LSP/R) model for prairie grassland appears to be somewhat lower than expected. A crucial reason for the underestimate of the L-band brightness is that the soil surface was treated as smooth. In this paper, surface scattering of the soil determined by the IEM model is incorporated into the LSP/R model to examine its impact on the predicted L-band brightness. Eight sets of surface parameters, two correlation lengths (L) of 3 and 6 cm/spl times/4 root mean squared (RMS) heights (/spl sigma/) of 0.3, 0.6, 0.8, and 1.0 cm, are utilized to characterize the emission of the soil surface. It is found that H-polarized, L-band brightness is expectedly increased by different levels for all of the eight rough surface cases compared to the smooth surface case. The increase in the average of the H-polarized, L-band brightness is by as much as 13.2 K for the case with L=3 cm and /spl sigma/=1.0 cm. In addition, L-band's sensitivity to soil moisture is found to be approximately equal with and without the scattering effects. An increase in H-polarized, L-band brightness by about 12 K at the end of a 14-day simulation by the LSP/R model is in response to a decrease in soil moisture by 7% for all of the nine cases of concern (eight rough plus one smooth soil surfaces).

Predicting Soil Albedo from Soil Color and Spectral Reflectance Data

The albedo of earth surface features, such as soil, is an important component of models that define land‐surface meteorological processes. If land surfaces have no vegetative cover, soil properties determine the amount of solar radiation absorbed or reflected. We evaluated the influence of two soil properties, soil color and soil moisture, on soil albedo. Two soil moisture conditions were studied, air dry and wet, defined as the condition when the water films are absorbed by the soil and no water glistens on the soil surface. The albedos for 26 U.S. soils were measured with an Eppley pyranometer, which integrates radiant energy in wavelengths between 0.3 to 2.8 μm. Soil colors were measured with a Minolta Chroma Meter and spectral reflectance curves from 0.45 to 0.9 μm (measured in 0.1‐μm increments) were determined with a multispectral radiometer. All measurements were made on &lt;2‐mm smooth soil surfaces, and the dry and wet data were combined for statistical analyses. Soil albedos were significantly correlated with Munsell soil color value , blue , green , red , near infrared (NIR), , and sum of the four bands ; however, the slopes and intercepts for these relationships were different. The 52 spectral curves yielded nine cluster groups, which mostly related to the Munsell soil color value and soil albedo soil characteristics. The 0.3‐ to 2.8‐μm albedos of smoothed soils can be accurately estimated using the regression relationship: soil albedo (0.3–2.8 μm) = 0.069 (color value) − 0.114. Using the regression equations presented here, spectral reflectance data in selected visible and NIR bands can also be used to predict albedo.

Surface Roughness Effects on Soil Albedo

Knowledge of how surface roughness influences the reflectance of sunlight from cultivated soils is useful in various applications, such as estimating albedo values used as inputs to soil temperature models and erosion models. The albedos of two soils were studied for dry and wet surfaces with four different roughness conditions, changed from a reference smooth soil surface. The soils were the Gila fine sandy loam [coarse‐loamy, mixed (calcareous), thermic Typic Torrifluvent] (Ap horizon), 10YR 6.0/3.2 dry and 10YR 4.1/3.3 wet, and the Pima clay loam [fine‐silty, mixed (calcareous), thermic Typic Torrifluvent] (Ap horizon), 10YR 5.2/2.3 dry and 10YR 3.3/2.3 wet. Albedo measurements were made during selected mornings with clear skies in 1995 and 1996. The mean albedos of reference smooth surfaces (&lt;2 mm sieved soil) were 0.279 and 0.155 for dry and wet Gila soil and 0.221 and 0.114 for dry and wet Pima soil. Four tillage conditions were studied: rough plow, disk, disk–disk, and seedbed. Tillage direction was north–south in 1995 and east–west in 1996. The goodness of fit of linear relationships determined between mean albedo and surface roughness, measured with a roughness meter and reported as the root mean square deviation, were relatively high; however, the slopes for the regression equations were different for the two soils and the two moisture conditions. The different slopes indicate that the sensitivity of albedo to surface roughness was highest for the most reflective surface (dry Gila soil) and lowest for the least reflective surface (wet Pima soil). The albedos were on average 27, 18, 10, and 8% lower for dry and wet rough‐plow, disk, disk–disk, and seedbed treatments, respectively, as compared with the albedo of the reference smooth soil. These reduction percentages can be used as a general guide to estimate the albedos of tilled soils similar to the Gila and Pima soils studied here.

Surface Roughness Related Processes of Runoff and Soil Loss: A Flume Study

AbstractSoil surface roughness greatly affects surface sealing and runoff generation, yet little information is available about the effect of roughness on the spatial distribution of runoff and on flow concentration. This study tested the hypothesis that runoff distribution and flow concentration differ with roughness and affect the amount of soil loss. Sequences of four rainstorms of constant rainfall amount but decreasing intensity (60, 45, 30, and 15 mm h−1) were applied to the Ap horizon material of a loess soil (Glossic Fragiudalf) packed into a 0.6 by 3.7 m flume. Rough, medium, and smooth soil surfaces were studied at 17, 8, and 2% slope steepness. Surface roughness and flow pathways were visualized with digital elevation maps obtained from laser microrelief measurements. On the smooth surfaces, runoff was uniformly distributed during the first two rainstorms and soil losses were 0.23, 0.07, and 0.12 kg m−2 for the first and 2.26, 0.35, and 0.2 kg m−2 for the second storm at 17, 8, and 2% slope steepness, respectively. On the rough and medium surfaces, flow concentrated in pathways between clods and soil losses were up to eight and three times that on the smooth surfaces during the first and second storms, respectively. During the last two storms, flow concentrated also on the smooth surfaces and soil losses were similar for the three initially different surface configurations. Surface roughness effects on runoff amount were minor, but roughness affected the spatial distribution of runoff, thereby affecting the amount of soil loss.

The use of a microwave backscatter model for retrieving soil moisture over bare soil

Abstract Most attempts at predicting soil moisture from C-band microwave backscattering coefficients for bare soil are made by fitting experimental calibration relations obtained for limited ranges of incidence angle and soil surface roughness. In this paper, a more general approach is discussed using an inversion procedure to extend the use of a single experimental calibration relation to a wider range of incidence angle and surface roughness. A correcting function is proposed to normalize the backscattering coefficients to the conditions (incidence angle and surface roughness) of the calibration relation. This correcting function was derived from simulated data using the physical optics or KirchhofTs scatter model using the scalar approximation. Before discussing the inversion procedure, the backscattering coefficients calculated by the model have been compared with experimental data measured in the C-band, HH polarization and three incidence angles (Θ= 15°, 23°, 50°) under a wide range of surface soil moisture conditions (0.02Hv  0.35cm3 cm-3) and for a single quite smooth soil surface roughness (0–011 s  OOI4/n)m. The model was found to be experimentally validated from 15° to 23° of incidence and for surface soil moistures higher than 0-I0cm3cm-3. For the inversion procedure, it is assumed to have a wider range of validity (15°  Θ 35° ) for ihc incidence angle. A sensitivity analysis of the model to errors on roughness parameter and incidence angle was performed in order to assess the feasability and suitability of the described inversion procedure.

Cropping system effects of maize on infiltration, runoff and erosion on loess soils in South-Limbourg (The Netherlands): A comparison of two rainfall events

Two natural rainfall events are compared to evaluate the effects of three cropping systems of silage maize on soil moisture content, infiltration, runoff and erosion. Both rainfall events took place in early summer. One was a low intensity event with 27.6 mm of rain in 9 hours, and the other a high intensity event with 33.4 mm in 42 minutes. Cropping systems were: 1. (I) a spring tilled system (conventional), 2. (II) an autumn and spring tilled system with summer barley as spring cover crop, and 3. (III) an autumn tilled system with winter rye as winter cover crop and direct drilling of silage maize. During the low intensity event, soil moisture content of the top 5 cm rose to field capacity on all three cropping systems. No runoff was generated. During the high intensity event, soil moisture content rose to field capacity on the two spring tilled cropping systems but was only slightly raised in the direct drill system, in spite of 17.7 mm of infiltrated rain. Runoff coefficients of the high intensity event were 41.7% (conventional system), 14.9% (autumn and spring tilled system) and 47.0% (direct drill system). The direct drill system showed a severely slaked soil surface in early summer, caused by winter rain. The response to rainfall of soil moisture content is ascribed to: 1. (I) a predominance of matrix infiltration on all cropping systems during the low intensity event and on the spring tilled systems during the high intensity event, and 2. (II) a predominance of infiltration via continuous macropores, open to the surface (of biologic origin), by-passing the soil matrix, on the direct drill system during the high intensity event. The presence of continuous, vertical macropores on the direct drill system explains its surprisingly high infiltration capacity, considering its strongly slaked appearance. The smooth soil surface of the direct drill cropping system may have delayed infiltration during the flooded stage of the high intensity event by not providing vent points for the escape of soil air. Soil loss from the direct drill system during the high intensity event was only 15.6% of that from the conventional system. This is ascribed to low detachment rates of soil material by drop impact and/or overland flow, due to the presence of winter rye remains and, especially, the relatively high soil surface shear strength of the direct drill cropping system in early summer.