Surface roughness effects on runoff and soil erosion rates under simulated rainfall

Soil surface roughness is identified as one of the controlling factors governing runoff and soil loss. Yet, most studies pay little attention to soil surface roughness. In this study, we analyzed the influence of surface roughness on runoff and soil erosion rates. Bulk samples of a silt loam soil were collected and sieved to 4 aggregate sizes: 0.003-0.012, 0.012-0.02, 0.02-0.045, 0.045-0.1 m. The aggregates were packed in a 0.60 by 1.2 m soil tray, which was set at a slope of 5%. Rainfall simulations using an oscillating nozzle simulator were executed for 90 min at intensity of 50.2 mm.h-1. The surface microtopography was digitized by an instantaneous profile laser scanner before and after the rainfall application. From the laser scanner data, a digital elevation model was produced and a roughness factor extracted. The data revealed longer times to runoff with increasing soil surface roughness as surface depressions first had to be filled before runoff could take place. Once channels were interconnected, runoff velocity and runoff amount increased as aggregates were broken down and depressions were filled. Rough surfaces were smoothed throughout the rainfall event, diminishing the effect on runoff. Final wash rates were comparable for all different applications. The simulations reveal that the significance of soil surface roughness effect is the delay in runoff for rougher surfaces rather than the decrease of soil erosion amount

Aggregate stability and erosion response to antecedent water content of a loess soil

Soil erosion processes are affected by the erodibility of the soil and by the erosivity of the rain. The effects of rain characteristics and invariant soil properties such as texture and organic matter content on soil erosion processes are well documented. However, the effect of antecedent soil-water content (θa) on aggregate breakdown, seal formation and subsequent soil erosion is much more disputable as opposing effects have been reported. We conducted lab experiments with a rainfall simulator on a Belgian silt loam soil. The objectives were to determine the effect of θa on seal formation, runoff and soil loss and to evaluate its effect on an empirical sediment transport equation. Air-dried soil aggregates were subjected to antecedent soil-water contents of 0.04 (air-dry aggregates), 0.12 and 0.19 m3 m-3. No runoff occurred on the soils with highest antecedent soil-water content, highest total runoff values were observed for the intermediate θa, while intermediate amounts of total runoff were noticed for the air-dry aggregates. Soil loss, however, showed a different trend: highest values were found for the lowest θa, intermediate values for the intermediate θa and no soil loss for the highest θa. We further observed that θa had no influence on the final runoff rates and on the final infiltration rate through the soil surface. In using a water discharge and stream power equation to predict sediment transport, the intercept and exponent of the regression equations were found to be lower for θa of 0.19 m3 m-3 compared to θa of 0.12 m3 m-3, indicating a decreasing erodibility with increasing θa. We therefore suggest including θa as an additional variable to assess soil erodibility in deterministic event-based water erosion models

Amending a loamy sand with three compost types: impact on soil quality

The objective of this study was to investigate the effects of the long-term addition of three compost types (vegetable, fruit and yard waste compost - VFYW, garden waste compost - GW and spent mushroom compost - SM) on the physical properties of a sandy soil and to quantify any such effects using indicators of soil physical quality. Soil samples were taken from a field with annual compost applications of 30 m3/ha for 10 yr and various physico-chemical analyses were undertaken. Results show a significant increase in soil organic carbon (21%) with the VFYW and GW compost types. With SM, soil organic carbon increased by 16%. Increased soil macroporosity and water content at saturation with a corresponding decrease in bulk density were observed for all compost types. However, quantification of these improvements using existing soil physical quality indicators such as the 'S-index', soil air capacity and matrix porosity gave mixed results showing that these indices perform poorly when applied to sandy soils. It is concluded that the long-term application of compost does not significantly improve the physical properties of sandy soils, but the absence of adverse effects suggests that these soils are a viable disposal option for these composts, but new indices of quality are needed for the proper characterization of sandy soils

Quantification of soil surface roughness evolution under simulated rainfall

Soil surface roughness is commonly identified as one of the dominant factors governing runoff and interrill erosion. The objective of this study was to compare several existing soil surface roughness indices and to test the use of the revised triangular prism surface area method (RTPM) to calculate the fractal dimension as a roughness index. A silty clay loam soil was sampled, sieved to four aggregate sizes, and each size was packed in soil trays in order to derive four different soil surface roughness classes. Rainfall simulations using an oscillating nozzle simulator were conducted for 90 min at 50.2 mm h-1 average intensity. The surface microtopography was digitized by an instantaneous profile laser scanner before and after the rainfall application. Calculated roughness indices included random roughness, variogram sill and range, fractal dimension and fractal length using a fractional Brownian motion (fBm) model, variance and correlation length according to a Markov-Gaussian model, and fractal dimension using the RTPM. Random roughness is shown to be the best estimator to significantly distinguish soil surface roughness classes. When taking spatial dependency into account, the variogram sill was the best alternative. The fractal dimension calculated from the fBm model did not yield good results, as only short-range variations were incorporated. The MG variance described the large-scale roughness better than the parameters of the fBm model did. The fractal dimension from the RTPM performed well, although it could not significantly discriminate between all roughness classes. Since it covered a greater range of scales, we believe that it is a good estimator of the overall roughness

Opportunities and challenges in assessing and combating land degradation

Technology development for assessing and combating land degradation faces various challenges, both in high and low income countries. This paper aims to highlight knowledge gaps on spatio-temporal soil functioning and on efficiency of soil conservation measures: (1) “What are current challenges related to assessing land degradation?”, (2) “What do we know about the impact of land degradation on food security?”, and (3) “What is the efficiency of conservation measures?”. The discussion encompasses soil degradation at field plot to continental scale, as well as bottlenecks relevant to both low and high-income countries. Key issues identified within each theme are illustrated using a number of case studies. They illustrate the need for innovative approaches to systematic assessments of the dynamic nature of soil functioning and degradation, of the impact of soil degradation on various ecosystem services, to support the identification and design of suitable soil management, soil conservation or soil improvement measures. Experimental trials and process-based models reflecting ecosystem functioning, though highly time and data demanding, are still needed to pursue better local insights and feed process-based land degradation models applied at watershed scale