Water Erosion Models Research Articles

Modelagem da perda de carbono orgânico do solo por erosão hídrica em uma bacia hidrográfica tropical

ABSTRACT Water erosion under tropical climate conditions is one of the main processes that change the balance between the inputs and outputs of soil organic carbon (SOC). Water erosion modeling using the Erosion Potential Method (EPM) can be used as an alternative to assist in understand soil carbon dynamics and its interaction with the erosive process. In this context, the objective of the study was to estimate carbon losses by water erosion in a watershed with a wide land-use diversity. The modelling was performed based on the soil organic matter content (SOM) of the area, and the estimated soil losses, according EPM. To the SOM determination, soil samples were collected 50 points (0-0.2 m) distributed in the watershed. The data analysis was performed using remote sensing techniques and a Geographic Information System, which was also used to interpolate the SOM content, through the use of the ordinary kriging. The results showed that from 126.53 Mg year-1 of the total eroded organic carbon estimated, 111.60 Mg year-1 were deposited in relief depressions, while 14.93 Mg year-1 reached the water body system. The applied methodology represents a cost-effective and relatively fast method to estimate the soil organic carbon loss by water erosion and allows the determination of the areas that most need intervention, aiming to decrease the impact of agriculture on greenhouse gas emissions. The main advantage of this method is the little input data requirement, which increases the possibility of application in poorly studied regions.

English

This study aimed to demonstrate the effects of spatial resolution in modeling water erosion by the Revised Universal Soil Loss Equation (RUSLE). In this study, three specific objectives were defined: Evaluation of the effect of the geographic information source on water erosion, seasonal effects on the potential production of sediments, as well as public policies concerning the different scenarios. The topographic factor (LS) of this equation was determined using four digital terrain models, with different spatial resolutions (10 and 30 m). The results of this factor prove to be influenced by the resolution of the DEM used. The spatial modeling of water erosion was carried out by combining the various input variables of the RUSLE model. The analysis of the obtained erosion maps revealed that its production is influenced by the spatial resolution and by the seasonality, demonstrating that the DEM obtained via DRONE presented the lowest values of soil loss potential in any scenario. Thus, it was verified a need to implement practices for the management of soil cover and conservation to reduce vulnerability to water erosion in the watershed. Key words: Soil erosion, geographic information system (GIS), watershed, modeling, hydrology.

Mapping Soil Degradation on Arable Land with Aerial Photography and Erosion Models, Case Study from Danube Lowland, Slovakia

The presented study uses the recent colour aerial photographs, historical black and white aerial photographs, and detailed digital elevation model to assess the spatial distribution and long-term temporal dynamics of soil loss in agriculturally intensively exploited loess hilly land with a subcontinental temperate climate. The strongly eroded soils appear in the studied area as bright patterns, surrounded by darker soils, and they are well visible on aerial photos. Three approaches of interpretation of aerial photographs were tested: visual interpretation, pixel-based image classification, and object-based image classification. All three methods provided detailed maps of soil redistribution patterns. The bright areas as the areas of soil degradation characterized by erosion increased from 1949 until 2011 by 76%. A detailed map of areal erosion patterns was used for the validation of water erosion models. LS-factor of USLE and ED’ index of USPED were selected for expressing the relation of real erosion to the terrain. The relationship between surface morphology and real erosion is very complex, and the tested water erosion models do not express it sufficiently. Therefore, the first and second-order directional derivative of the surface elevations with respect to the tillage direction has been tested. The absolute value of the first-order directional derivative showed better results and better corresponded with the real erosion pattern than the other morphometric characteristics. The findings suggest that tillage is the dominant erosion factor in the area.

Forestation does not necessarily reduce soil erosion in a karst watershed in southwestern China

Forestation as part of the Returning Farmland to Forest Project was implemented to mitigate soil erosion in southwestern China. However, whether forestation has effectively reduced soil erosion in southwestern China remains unclear, mostly because of the lack of monitoring forest cover change and soil erosion at watershed scales. We interpreted forest cover change from satellite images and simulated soil erosion changes for the period of 1986–2018 in the Chong’an River Basin with the Water and Tillage Erosion Model and Sediment Delivery Model. Our results show that the change in forest cover has the highest correlation coefficient with the sediment yield in the watershed, with an obvious inverse phase relationship between them for all the simulated years. From 2002 to 2014, large-scale forestation and frequent droughts caused the forest cover to vary, resulting in significant changes in the annual soil erosion amount. Because crevices favoring tree growth are more developed in limestone than in dolomite, the forest cover reduction on dolomite is significantly higher than that on limestone under severe droughts in karst areas. Our study implied that the function of forestation in preventing soil erosion depends on lithology in karst areas.

Water erosion modeling by the Erosion Potential Method and the Revised Universal Soil Loss Equation: a comparative analysis

Water erosion is the principal degradation process of tropical soils, and its effects can be measured by modeling techniques. Erosion models provide a diagnosis of the soil loss intensity and can support the planning of soil conservation practices. Models with low data requirements, such as the Revised Universal Soil Loss Equation (RUSLE) and, more recently, the Erosion Potential Method (EPM), are mainly applied in Brazil. Thus, the objective of this work was to estimate water erosion soil-loss rates using the EPM and RUSLE models on a tropical subbasin, followed by a comparison of their outcomes. The models’ application considered soil physical parameters, edaphoclimatic conditions of the area, land use, and subbasin management practices. The accuracy of the methods was verified using total transported sediment and water discharge data. We compared the models using Pearson's correlation analyses, considering a 5% of significance. We found a predominance of moderate-intensity erosion with average soil loss of 1.17 and 1.46 Mg ha-1 year-1, measured by EPM and RUSLE, respectively. The EPM model underestimated soil losses by 15.27%, and RUSLE overestimated by 19.08%, indicating a higher percentage of areas with high erosion rates (4.60%). The models presented results with a different order of magnitude, but with significant correlations, indicating that both methods pointed out similar zones of intense and light-erosion rates.

What do models tell us about water and sediment connectivity?

Connectivity has been embraced by the geosciences community as a useful concept to understand and describe hydrological functioning and sediment movement through catchments. Mathematical modelling has been used for decades to quantify and predict erosion and transport of sediments, e.g. in scenarios of land use change or conservation measures. Being intrigued by both models and the connectivity concept, as a group of modellers we aimed at investigating what different models could tell us about connectivity. Therefore, we evaluated the response of contrasted spatially-distributed models to landscape connectivity features and explained the differences based on different model structures. A total of 53 scenarios were built with varying field sizes and orientations, as well as the implementation of soil conservation measures. These scenarios were simulated, for two rainfall intensities, with five event- and process-based water and soil erosion models – EROSION3D, FullSWOF_2D, LandSoil, OpenLISEM and Watersed. Results showed that rainfall amount plays the most important role in determining relative export and connected area of runoff and sediment in all models, indicating that functional aspects of connectivity were more important than structural connectivity. As for the role of structural landscape elements, there was no overall agreement between models regarding the effects of field sizes, crop allocation pattern, and conservation practices; agreement was also low on the spatial patterns of connectivity. This overall disagreement between models was unexpected. The results of this exercise suggest that the correct parameterization of runoff and sediment production and of routing patterns may be an important issue. Thus, incorporating connectivity functions based on routing would help modelling forward. Our results also suggest that structural connectivity indices may not suffice to represent connectivity in this type of catchment (relatively simple and monotonous land cover), and functional connectivity indices should be applied.

GIS-based soil erosion modelling under various steep-slope vineyard practices

Soil erosion can cause a progressive degradation of hillslopes, especially in steep-slope agricultural landscapes. In this study, the formation of spatial erosion patterns was evaluated in three typical steep-slope vineyard cultivation practices in northern Italy: dry-stone wall terraces, earth bank terraces and vertical cultivation (Italian: rittochino). UAV surveys in three vineyards provided high-resolution data on topography and land use serving as input for two GIS-based erosion models: the Revised Universal Soil Loss Equation (RUSLE) and SIMulated Water Erosion model (SIMWE). Annual RUSLE simulations showed how the two terracing practices (i.e. dry-stone walls and earth banks) effectively safeguarded large areas from soil loss, whereas the non-terraced vertical cultivation produced widely distributed soil loss with increasing severity according to slope length and steepness. In intense single-event conditions simulated by SIMWE, all three practices showed the formation of critical preferential surface flow patterns, corresponding to several field-observed erosion patterns (piping of stone walls, landslides on earth banks, and rill erosion in the non-terraced vineyard), while also in this case showing the highest erosion rates for the non-terraced vertical cultivation. Simulated flow concentration was strongly determined by the spatial organisation of the hillslope, roads and vines, and several strategies were discussed for erosion mitigation (including drainage systems or enhanced soil cover). Furthermore, the results indicated that SIMWE is an optimal approach for the recognition of soil erosion processes occurring during intense rainfall conditions. This study provides an example of high-resolution erosion risk evaluation, which should play a crucial role in the design and management of steep-slope vineyards.

Water erosion estimate in Belem Stream Watershed in Minas Gerais state

Water erosion causes a diversity of negative environmental impacts, provoking soil degradation and by consequence the agricole production decrease. Due to the damage caused by the soil erosion process, were developed a diversity of water erosion modeling methods in other to support in other to project and implement measures soil conservation. Among the models, the more useful is the Erosion Potential Method (EPM), which recently was adapted to the brazilian tropical conditions. In this context, the objective of this work was estimating the soil loss by Erosion Potential Method in a water basin located in Muzambinho, in the South of Minas Gerais. The EPM model estimated the water erosion in this study area starting with climate, topographic, pedology, land use, and erosive features degree parameters. The modeling stage and the parameters obtaining was done with the Geography Information System and remote sensing help. The total soil loss estimated by the EPM model was 10,418.53 Mg year-1, of which 5.50% reaches the water resources directly contributing to the siltation and water quality depreciation. The higher slope areas and the rural roads with exposed soil are where localize the biggest soil loss degrees. The modeling application was giving up in a simple and fast form, provender satisfactory results that are useful to the planning of soil conservation practices in the water basin.

Application of digital technologies in the study of water erosion of soils in Western Siberia

The analysis of the study of water erosion of soils on the territory of the West Siberian Plain using geo-information technologies (GIS) and Earth remote sensing was carried out. It is shown that GIS and Earth remote sensing are not widely used in erosion studies in Western Siberia and are used by a limited number of modern researchers. However, the use of digital technologies in this area is characterized by the coverage of almost the full range of their capabilities and functions: digital mapping, the formation of spatially-distributed thematic databases, monitoring, space-time analysis, modeling, automated mapping. The bulk of such research is concentrated mainly within the Novosibirsk and Omsk regions, in the Altai Territory, and to a lesser extent in the Tomsk and Kemerovo regions. Digital technologies for studying water erosion in Western Siberia are more often used to study the dependence of water erosion on its determining factors (mainly topography), the effect of water erosion on soils and soil cover, in morphometric analysis of the relief, land classifi cation and mapping. The problem of remote monitoring of the temporal dynamics of water erosion and related changes in topography, soil cover, soil properties, etc. is practically not dealt with. The issues of geoinformational modeling of water erosion in terms of elaboration of detail and scale, and coverage of a larger number of areas require further development. When modeling water erosion, the nature of surface runoff is not always taken into account. The approach to the selection of criteria for the assessment of erosional land at different scales of their mapping is not entirely clear. It remains an open question to develop a methodology for the automated calculation of standards for permissible erosional losses of soil. In general, the use of Earth remote sensing and GIS facilities in the study of water erosion in the soils of Western Siberia is not systematic and comprehensive. This is confi rmed by the presence of a number of problems in the study of water erosion in the given area, which requires a digital approach to their solution.

Modeling of water erosion by the erosion potential method in a pilot subbasin in southern Minas Gerais

Soil losses due to water erosion threaten the sustainability of agriculture and the food security of current and future generations. This study estimated potential soil losses and sediment production under different types of land uses in a subbasin in the Municipality of Alfenas, southern Minas Gerais, southeastern Brazil. The objective of this research was to evaluate the application of the Potential Erosion Method by the Intensity of Erosion and Drainage program and correlate the findings with the results obtained by the Revised Universal Soil Loss Equation as well as geoprocessing techniques and statistical analyses. In the Potential Erosion Method, the coefficient indicating the mean erosion intensity was 0.37, which corresponded to erosion category IV and indicated weak laminar erosion processes, and the total soil loss was 649.31 Mg year-1 and the mean was 1.46 Mg ha-1 year-1. These results were consistent in magnitude with those obtained in the Revised Universal Soil Loss Equation, which estimated a mean soil loss of 1.52 Mg ha-1 year-1 and a total soil loss of 668.26 Mg year-1. The Potential Erosion Method suggests that 1.5% of the area presents potential soil losses above the soil loss tolerance limit, which ranged from 5.19 to 5.90 Mg ha-1 year-1, while the Revised Universal Soil Loss Equation indicated that 7.3% of the area has potential soil losses above the limit. The maximum sediment discharge was 60 Mg year-1, meaning that 9.3% of the total soil loss reached the depositional areas of the river plains or watercourses. The Potential Erosion Method was efficient in the evaluation of water erosion in tropical soils, and the results were consistent with models widely employed in the estimation of soil losses. Thus, the model can support the evaluation of soil losses in Brazil and is a robust tool for evaluating the sustainability of agricultural activities.

Meteoric Beryllium‐10 as a Tracer of Erosion Due to Postsettlement Land Use in West‐Central Minnesota, USA

AbstractMeteoric beryllium‐10 (10Bem, t1/2 = 1.4 Myr) is a cosmogenic radionuclide that remains largely underutilized for deriving hillslope‐scale estimates of erosion on uplands under conditions of land use change. We applied two different models for estimating erosion rates from observed 10Bem concentrations (a one‐dimensional model predicting vertical profiles of 10Bem within hillslope soils [loss only, diffusion only, LODO] and a two‐dimensional model predicting the concurrent evolution of hillslope topography and 10Bem distributions via bioturbation, chemical mobility, and surface erosion [Be2D]). Both models were used to derive pre‐European and post‐European settlement erosion rates (Enat and Epost, respectively) across paired cultivated and uncultivated hillslopes in west‐central Minnesota, USA. Epost estimates from 10Bem were compared to Epost estimates derived from 137Cs inventories and the process‐based Water and Tillage Erosion Model (WaTEM). The results from these models suggest that erosion rates from upper positions on the cultivated hillslope have increased from an average of 0.047 mm/year under natural conditions to Epost values of 3.09 mm/year. The Be2D and LODO models, on average, produced Epost estimates that were similar in magnitude to WaTEM and 137Cs conversion models. This numerical convergence does not imply absolute 10Bem model accuracy, particularly when considering the uncertainties inherent in each approach, but it does suggest that the orders of magnitude increase in estimated erosion rates from Enat to Epost is robust. Additionally, the pattern of Epost estimates produced using 10Bem conversion models is supported by the distribution of soil inorganic carbon at the study site. Our results demonstrate that 10Bem can provide reasonable estimates of both predisturbance and postdisturbance erosion rates in landscapes that have undergone extensive human modification.

Моделирование водной эрозии почв

Моделирование водной эрозии почв

Rusle parameters for modeling the loss of a soil subjected to pig slurry application

Abstract: The objective of this work was to determine adjustment parameters for the revised universal soil loss equation (Rusle) of a soil subjected to pig slurry application. Treatments consisted of 0, 50, 100, and 200 m3 ha-1 pig slurry (PS), after the cultivation of black oat (Avena strigosa), besides the application of 50 m3 ha-1 PS for six times onto the soil surface in a temporal sequence, and a control treatment of soil without cultivation and without pig slurry application. The evaluations were performed for black oat shoot dry mass, root mass and crop residues semi-incorporated into the soil (RMR), soil losses by means of simulated rain, and the parameters for water erosion modeling. The pig slurry application onto soil surface caused a reduction in the values of the soil consolidation parameter (Cf), an increase in the mass of living and dead roots and cultural residues incorporated in the upper layer (0.0-0.1 m) of the soil (Bu), and a reduction in the subfactor prior land use (PLU) of the Rusle.

Process-based soil erodibility estimation for empirical water erosion models

ABSTRACTFunctional relationships between soil erodibility equations of empirically-based revised universal soil loss equation and process-based water erosion prediction project models were investigated using new datasets from rainfall simulation experiments to overcome conceptual differences of models in estimating soil erodibility. Erodibility potentials of two different soils were quantified for three different initial soil moisture conditions, and relations between the process-based erodibility, partitioned as interrill erodibility, rill erodibility and critical shear stress, and empirically-based erodibility were examined. A process-based soil erodibility assessment within the universal soil loss equation was attempted. Statistically significant differences are found when considering the effects of surface hydrologic conditions on soil erodibility. Process-based soil erodibility estimates under dry conditions were found to be comparable with original water erosion prediction project datasets. The results showed that procedure could be useful for tapping into the large number of datasets available and building the next generation of process-based erosion models.

Predicting Forest Road Surface Erosion and Storm Runoff from High-Elevation Sites

Abstract. Forest roads are a concern in management because they represent areas of elevated risks associated with soil erosion and storm runoff connectivity to stream systems. Storm runoff emanating from forest roads and their connectivity to downslope resources can be influenced by a myriad of factors, including storm characteristics, management practices, and the interaction of management practices and successive storm events. Mitigating sediment export and ensuring that storm runoff has negligible impacts on downstream resources requires a more complete understanding of forest road erosion and sediment delivery dynamics. Progress in the area of road and stream connectivity issues hinges on reliable prediction tools to inform broader-scale modeling of watershed-scale effects of forest roads and management practices. In this study, the Water Erosion Prediction Project (WEPP) model was evaluated based on the results from 156 runoff-generating storm events during a continuous five-year study of nine high-elevation road sections in the Appalachian Mountains. The model adequately predicted sediment yield from the road sections with an overall Nash-Sutcliffe model efficiency (E) of 0.76, Willmott refined index of agreement (dr) of 0.56, percent error of 5%, and average storm difference (ASD) of 1.2 kg. In contrast, WEPP predictions of storm runoff were not as good, and the poor agreement was attributed to an inability to determine the source area for runoff from some of the larger runoff events. In general, the WEPP model for these high-elevation sites adequately described the sediment yield for the road sections. Keywords: Forest roads, Long-term simulation, Runoff, Sediment, Water Erosion Modeling, WEPP.

137Cs tracing dynamics of soil erosion, organic carbon, and total nitrogen in terraced fields and forestland in the Middle Mountains of Nepal

The Middle Mountains is one of the regions of Nepal most vulnerable to water erosion, where fragile geology, steep topography, anomalous climatic conditions, and intensive human activity have resulted in serious soil erosion and enhanced land degradation. Based on the Cs-137 tracing method, spatial variations in soil erosion, organic carbon, and total nitrogen (TN) in terraced fields lacking field banks and forestland were determined. Soil samples were collected at approximately 5 m and 20 m intervals along terraced field series and forestland transects respectively. Mean 137Cs inventories of the four soil cores from the reference site was estimated at 574.33 +/- 126.22 Bq m(-2) (1 Bq (i.e., one Becquerel) is equal to 1 disintegration per second (1 dps)). For each terrace, the Cs-137 inventory generally increased from upper to lower slope positions, accompanied by a decrease in the soil erosion rate. Along the entire terraced toposequence, Cs-137 data showed that abrupt changes in soil erosion rates could occur between the lower part of the upper terrace and the upper part of the immediate terrace within a small distance. This result indicated that tillage erosion is also a dominant erosion type in the sloping farmland of this area. At the same time, we observed a fluctuant decrease in soil erosion rates for the whole terraced toposequence as well as a net deposition at the toe terrace. Although steep terraces (lacking banks and hedgerows) to some extent could act to limit soil sediment accumulation in catchments, soil erosion in the terraced field was determined to be serious. For forestland, with the exception of serious soil erosion that had taken place at the top of slopes due to concentrated flows from a country road situated above the forestland site, spatial variation in soil erosion was similar to the "standard" water erosion model. Soil organic carbon (SOC) and TN inventories showed similar spatial patterns to the Cs-137 inventory for both toposequences investigated. However, due to the different dominant erosion processes between the two, we found similar patterns between the < 0.002 mm soil particle size fraction (clay sized) and Cs-137 inventories in terraced fields, while different patterns could be found between Cs-137 inventories and the < 0.002 mm soil particle size fraction in the forestland site. Such results confirm that Cs-137 can successfully trace soil erosion, SOC and soil nitrogen dynamics in steep terraced fields and forestland in the Middle Mountains of Nepal.

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

The combined use of water erosion models and geographic information systems has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimate but require discretization to identify hillslopes and channels. In GeoWEPP, the TOpographic PArameteriZation (TOPAZ) model is used as an automated procedure to extract a watershed boundary, hillslopes and channels from a digital elevation model (DEM). Previous studies in small watersheds have shown that the size of the hillslopes and the channel distribution affect the model estimates, but in large watersheds, the effects on the soil loss estimates have yet to be tested. Therefore, the objective of this study was to evaluate the effect of discretization on the hillslope sediment yield estimates using GeoWEPP in two large watersheds (>10 km2). The watersheds were selected and discretized varying the TOPAZ parameters [critical source area (CSA) and minimum source channel length (MSCL)] in a 30-m resolution digital elevation model. The drainage networks built with TOPAZ were compared with each other using the drainage density index. The results showed that the discretization affected hillslope sediment yield estimates and their spatial distribution more than the total runoff. The drainage density index and the hillslope sediment yield were proportional but inversely related; thus, soil loss estimates were highly affected by the spatial discretization. As a result of this analysis, a method to choose the CSA and MSCL values that generates the greatest fraction of hillslopes having profile lengths less than 200 m was developed. This slope length condition is particularly crucial when using the WEPP and GeoWEPP models, in order for them to produce realistic estimates of sheet and rill erosion. Finally, and as a result of this analysis, a more reliable method was developed for selecting the TOPAZ channel network parameters (CSA and MSCL). Copyright © 2015 John Wiley & Sons, Ltd.

SPATIAL AND TEMPORAL MODELING OF WATER EROSION IN DYSTROPHIC RED LATOSOL (OXISOL) USED FOR FARMING AND CATTLE RAISING ACTIVITIES IN A SUB-BASIN IN THE SOUTH OF MINAS GERAIS

Water erosion is one of the most important soil degradation processes and it can be intensified by land use and vegetal covering changes. Thus, water erosion modeling studies associated to multi temporal analyses of land use are effective in assessing how changes in land cover affects sediment yield. Therefore, considering the modifications in the land use from 1986 to 2011, the aim of this study ranged to estimate water erosion rates and compare them to the soil loss tolerance (SLT) limit in the Latosols (Oxisols) at Ribeirão Caçús sub-basin, in the South of Minas Gerais State, Southeast Brazil, by means of the Revised Universal Soil Loss Equation (RUSLE) in association with the geographic information system (GIS), and geostatistical techniques. So, for each year mapped, soil loss averages were compared by t test at 5% significance to assess the soil degradation stage. The results indicated that, in the period, the soil loss average rate was from 2.4 to 2.6 Mg ha-1 year-1 and the areas with soil loss above the limit of SLT were around 8.0%. The t test demonstrated there was no considerable difference among the soil loss averages (p = 0.18). In consequence, the area of degraded soils did not increase. Thus, the RUSLE model in GIS is a simple and useful tool to estimate the soil loss and help define soil conservation and recovery measures.

Sediment composition for the assessment of water erosion and nonpoint source pollution in natural and fire-affected landscapes

Water erosion is a leading cause of soil degradation and a major nonpoint source pollution problem. Many efforts have been undertaken to estimate the amount and size distribution of the sediment leaving the field. Multi-size class water erosion models subdivide eroded soil into different sizes and estimate the aggregate's composition based on empirical equations derived from agricultural soils. The objective of this study was to evaluate these equations on soil samples collected from natural landscapes (uncultivated) and fire-affected soils. Chemical, physical, and soil fractions and aggregate composition analyses were performed on samples collected in the Chilean Patagonia and later compared with the equations' estimates. The results showed that the empirical equations were not suitable for predicting the sediment fractions. Fine particles, including primary clay, primary silt, and small aggregates (<53μm) were over-estimated, and large aggregates (>53μm) and primary sand were under-estimated. The uncultivated and fire-affected soils showed a reduced fraction of fine particles in the sediment, as clay and silt were mostly in the form of large aggregates. Thus, a new set of equations was developed for these soils, where small aggregates were defined as particles with sizes between 53μm and 250μm and large aggregates as particles>250μm. With r2 values between 0.47 and 0.98, the new equations provided better estimates for primary sand and large aggregates. The aggregate's composition was also well predicted, especially the silt and clay fractions in the large aggregates from uncultivated soils (r2=0.63 and 0.83, respectively) and the fractions of silt in the small aggregates (r2=0.84) and clay in the large aggregates (r2=0.78) from fire-affected soils. Overall, these new equations proved to be better predictors for the sediment and aggregate's composition in uncultivated and fire-affected soils, and they reduce the error when estimating soil loss in natural landscapes.

Evaluating the Impact of the Spatial Distribution of Land Management Practices on Water Erosion: Case Study of a Mediterranean Catchment

Abstract: The spatial distribution of land management practices (LMPs), such as the use of vegetated filters, may have a strong impact on their efficiency in trapping sediments and pollutants. Distributed water erosion models help managers, planners, and policymakers optimize the efficiency of these LMPs regarding their location relative to water and sediment pathways. In this work, the authors analyzed the impact of the spatial distribution of LMPs using an existing distributed model and sensitivity analysis procedures. The distributed model that was used is a distributed single-event physically based water erosion model developed to calculate erosion rates and sediment flow for small (less than 10 km2) agricultural catchments. To measure the impact of the spatial distribution of LMPs, the authors developed a stochastic model that generates LMP locations over the entire catchment. The stochastic model has three input parameters: the density of LMPs, their downslope/ upslope location probability, and the probability density function shape controller. Because of its ability to account for the cross effects between parameters, the variance-based Sobol method was used to calculate the sensitivity of the soil loss ratio of a typical Mediterranean agricultural catchment (Roujan, southern France) to the LMP location model parameters. Three measurement points (two subcatchment outlets and the main outlet) were used to examine the spatially distributed effects of the LMP locations. The simulation results indicated that 70% of the variation of the net erosion is explained by variations in LMP density for the main outlet catchment, making LMP density the most sensitive parameter. However, the total Sobol sensitivity indices indicate a strong interaction among the three parameters when the density values are low (few LMPs are applied). Thus, although the density of the LMPs is the most sensitive parameter, their location may influence their global trapping efficiency in (real) cases where few LMPs are applied.