Simulated Soil Loss Research Articles

Assessing soil conservation strategies for upland cropping in Northeast Thailand with the WaNuLCAS model

Soil conservation approaches and agroforestry systems can play an important role in controlling erosion from tropical hillside cropping systems. Experimental testing of their potential application domain and design, however, is costly and time consuming. We, therefore, tested the ability of the Water, Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) model. The specific objectives of the study were: (i) to evaluate the WaNuLCAS model for predicting water induced erosion under different soil conservation strategies, (ii) to use the model for a better understanding of various soil conservation measures in controlling erosion, and (iii) to assess the magnitude and dynamics of key processes influencing the efficiency of soil conservation measures. A 3-year-data set (2003–2005) from a field experiment from the Loei province in Northeast Thailand on the impact of soil conservation (Leucaena hedgerow, Jack bean relay cropping) under minimum tillage on runoff and soil loss was tested. Results indicated that WaNuLCAS was able to predict soil loss and runoff well at the test site; i.e. R 2 = 0.80 and 0.82, respectively. In the calibration procedure a sub data set was used, where adjusting crop development parameters was an important step for improving simulated soil loss (R 2 = 0.75) and runoff (R 2 = 0.89). Soil conservation measures such as Leucaena hedges were effective techniques to control runoff and soil loss. Implementing a dynamic soil structure module in combination with minimum tillage reduced runoff and soil loss via an increase in available macropores and hence drainage over time which improved simulation results. Relay cropping with Jack bean played an important role in the control treatment in reducing soil loss during the third year due to its additional soil cover and positive impact on soil fertility as suggested by the model. Hence, the WaNuLCAS model is a valuable tool to study and understand processes and to explore management options for improving tropical hillside cropping threatened by soil degradation.

Evaluation of the SWEEP model during high winds on the Columbia Plateau

AbstractA standalone version of the Wind Erosion Prediction System (WEPS) erosion submodel, the Single‐event Wind Erosion Evaluation Program (SWEEP), was released in 2007. A limited number of studies exist that have evaluated SWEEP in simulating soil loss subject to different tillage systems under high winds. The objective of this study was to test SWEEP under contrasting tillage systems employed during the summer fallow phase of a winter wheat–summer fallow rotation within eastern Washington. Soil and PM10 (particulate matter ≤10 µm in diameter) loss and soil and crop residue characteristics were measured in adjacent fields managed using conventional and undercutter tillage during summer fallow in 2005 and 2006. While differences in soil surface conditions resulted in measured differences in soil and PM10 loss between the tillage treatments, SWEEP failed to simulate any difference in soil or PM10 loss between conventional and undercutter tillage. In fact, the model simulated zero erosion for all high wind events observed over the two years. The reason for the lack of simulated erosion is complex owing to the number of parameters and interaction of these parameters on erosion processes. A possible reason might be overestimation of the threshold friction velocity in SWEEP since friction velocity must exceed the threshold to initiate erosion. Although many input parameters are involved in the estimation of threshold velocity, internal empirical coefficients and equations may affect the simulation. Calibration methods might be useful in adjusting the internal coefficients and empirical equations. Additionally, the lack of uncertainty analysis is an important gap in providing reliable output from this model. Published in 2009 by John Wiley & Sons, Ltd.

Simulating site-specific impacts of climate change on soil erosion and surface hydrology in southern Loess Plateau of China

Abstract Proper spatial and temporal treatments of climate change scenarios projected by General Circulation Models (GCMs) are critical to accurate assessment of climatic impacts on natural resources and ecosystems. The objective of this study was to evaluate the site-specific impacts of climate change on soil erosion and surface hydrology at the Changwu station of Shaanxi, China using a new spatiotemporal downscaling method. The Water Erosion Prediction Project (WEPP) model and climate change scenarios projected by the U.K. Hadley Centre's GCM (HadCM3) under the A2, B2, and GGa emissions scenarios were used in this study. The monthly precipitation and temperature projections were downloaded for the periods of 1900–1999 and 2010–2039 for the grid box containing the Changwu station. Univariate transfer functions were derived by matching probability distributions between station-measured and GCM-projected monthly precipitation and temperature for the 1950–1999 period. The derived functions were used to spatially downscale the GCM monthly projections of 2010–2039 in the grid box to the Changwu station. The downscaled monthly data were further disaggregated to daily weather series using a stochastic weather generator (CLIGEN). The HadCM3 projected that average annual precipitation during 2010–2039 would increase by 4 to 18% at Changwu and that frequency and intensity of large storms would also increase. Under the conventional tillage, simulated percent increases during 2010–2039, compared with the present climate, would be 49–112% for runoff and 31–167% for soil loss. However, simulated soil losses under the conservation tillage during 2010–2039 would be reduced by 39–51% compared with those under the conventional tillage in the present climate. The considerable reduction in soil loss in the conservation tillage indicates the importance of adopting conservation tillage in the region to control soil erosion under climate change.

Soil erosion modelling with EUROSEM at Embori and Mukogodo catchments, Kenya

AbstractThe applicability of the European Soil Erosion Model (EUROSEM) in Kenya was tested on two subcatchments: Embori, which lies within a large‐scale commercial wheat‐ and barley‐growing region on the slopes of Mt Kenya; and Mukogodo, a dry rangeland region used for communal grazing, which lies at lower altitudes. For both catchments, EUROSEM was used to simulate interrill erosion from single storm events on plots of 10 m by 2 m. The model was calibrated and validated for a barley crop at Embori and three treatments of bare, grass and shrub covers at Mukogodo. The results indicated that EUROSEM was applicable to the Embori catchment, as correlation coefficients of 0·91 and 0·84 were obtained between observed and simulated runoff and soil loss, respectively. However, for Mukogodo, the model did not adequately predict soil loss from vegetated plots having grass or shrubs, although it could predict runoff from bare plots and grass quite well (R2 = 0·97, R2 = 0·60, respectively) as well as soil loss from bare plots (R2 = 0·58), but the standard errors of estimate at 4·67 mm were rather high (P = 0·95). Thus, EUROSEM requires improvements in terms of being able to predict runoff and soil loss in semi‐arid regions of Kenya, so that it can accommodate multiple vegetation covers, rangeland conditions and soils with surface sealing properties. In addition, the model requires further testing to sample a wider range of climatic and land use types for it to be applicable to Kenya and rangeland conditions generally. Copyright © 2006 John Wiley & Sons, Ltd.

Spatial downscaling of global climate model output for site-specific assessment of crop production and soil erosion

Spatial and temporal mismatches between coarse resolution projections of global climate models (GCMs) and fine resolution data requirements of ecosystems models are the major obstacles for assessing the site-specific climatic impacts of climate change on natural resources and ecosystems. The objectives of this study were to: (i) develop a simple method for statistically downscaling GCM monthly output at the native GCM grid scale to station-scale using transfer functions, and (ii) further demonstrate the site-specific impact assessment of climate change on water resources, soil erosion, and crop production at Kingfisher, OK, US using the water erosion prediction project (WEPP) model. Monthly precipitation and temperature projected by the UK Hadley Centre's Climate Model (HadCM3) under the GGa emissions scenario were downloaded for the periods of 1900–1999 and 2070–2099 for the grid box containing the target station. Univariate transfer functions were derived by calibrating probability distributions of GCM-projected monthly precipitation and temperature to match those of local climatology for the 1950–1999 period. Derived functions, which were tested for 1900–1949, were used to spatially downscale the HadCM3 monthly projections of 2070–2099 to the target station. Downscaled monthly data were further disaggregated to daily weather series using a stochastic weather generator (CLIGEN) for driving the WEPP model. Disaggregated daily series preserve the monthly means and variances of precipitation and temperature of the downscaled HadCM3 output. Simulated annual runoff under the changed climate, compared with the present climate, increased by 40–48% despite the projected 5% decrease in precipitation. Simulated plant transpiration, soil evaporation, and long-term soil water reserve decreased by 5, 16.5, and 5.5%, respectively. Simulated soil loss rates were increased by some 44% under conventional tillage and doubled under conservation tillage and no-till. Simulated wheat yield increased by approximately 14% in all three tillage systems. The overall results show that the proposed downscaling technique is simple and sound, which provides an effective alternative for assessing the site-specific impacts of climate change on soil erosion and crop production. Nevertheless, the technique suffers from the same shortcomings as all other statistical downscaling methods, as it largely relies upon the accuracy of GCM projections as well as the applicability of transfer functions to future climate.

Guidelines for soil conservation towards integrated basin management for sustainable development: A new approach based on the assessment of soil loss risk using remote sensing and GIS

Soil suspension in the Cidanau River of western Java, Indonesia, has increased recently, perhaps because of rapid environmental change in this watershed region. The objectives of this research are to assess soil loss risk using remote sensing and GIS and to develop effective guidelines for soil conservation in this watershed. To assess soil loss risk, a new soil loss model based on Universal Soil Loss Equation (USLE) was applied, in which C factor (crop management factor) was estimated using the perpendicular vegetation index (PVI); this was computed with satellite remote sensing data and used to simulate soil loss risk. The simulation showed that areas with highest risk of soil loss are on northern- and southern-facing hillsides with poor vegetation. Guidelines for soil conservation in the watershed were proposed: under these guidelines soil-loss risk is managed by evaluating the effectiveness of contour farming, belt farming, and mulch farming. Some recommended measures for soil conservation are as follows: (1) Green vegetation cover should be preserved as much as possible. (2) Vegetation coverage must be increased by forestation in steep sloped areas. (3) Belt farming and contour farming are recommended in areas with slopes under 100%, and mulch farming (more than 50% ground cover mulching is recommended) is desirable in areas with slopes over 100% and without green cover.

EVALUATION OF THE UNIVERSAL SOIL LOSS EQUATION (USLE) IN SEMI-ARID AND SUB-HUMID CLIMATES OF INDIA

The Universal Soil Loss Equation (USLE) was evaluated for various crops in the semi-arid and the sub-humidregions of India. The predictions were made considering yearwise data of the experimental period as well as on an averageannual basis. Model efficiency based on the annual data series was relatively poor (0.46) in the semi-arid region comparedto the model efficiency (0.76) for the sub-humid region. However, on an average annual basis, the model efficiency improvedsignificantly to 0.81 in the semiarid region, and compared well to the annual series in the sub-humid region (0.75). Thecoefficient of determination (R2) between measured and simulated soil loss values was 0.88 and 0.91 on an annual basis, and0.93 and 0.94 on an average annual basis for the semi-arid and sub-humid regions, respectively. The soil loss predicted bythe USLE for the two regions and for both data sets was found to agree well with the observed data. The analysis of soil lossdata also revealed that simulated and observed soil loss values exhibited higher variation in the semi-arid region as comparedto the sub-humid region for both the annual and the average annual data sets, which was attributed to erratic and unevendistribution of rainfall in the semi-arid region. The Students t-test between observed and simulated values revealed thatUSLE estimates were not statistically different from measured values at the 1% level of significance on an annual as well asan average annual basis in the semi-arid and the sub-humid regions of India.

Developing interactive land use scenarios on the Loess Plateau in China, presenting risk analyses and economic impacts

This study aimed to present a risk analysis of the effects of different land use scenarios on reducing soil and water losses, using a physically based hydrological and soil erosion model. We quantified the effect of various land use scenarios on the expected rate of discharge and sediment loss during a single rain event in a small agricultural watershed on the Loess Plateau in China, using the geometric mean and stochastic distributions of measured field saturated conductivity ( K s ) values. Land use scenarios were based upon physical, economic and agricultural interests, and effects on farmers’ incomes were evaluated using empirically derived equations. A physically based hydrological and soil erosion model was used to quantify the effects of land use on discharge and soil loss. Using geometric mean values of K s as the model input resulted in higher values for runoff coefficients and total soil loss compared with the use of stochastic K s values. The use of stochastic K s -distributions resulted in a range of model outcomes reflecting the effect of spatial heterogeneity on simulated discharge and soil loss. The conservation-driven scenario was most effective in reducing water and sediment losses by runoff and erosion, followed by the soil-driven scenario and the agriculture-driven land use scenario. Only the agriculture-driven scenario resulted in a small increase in household income, while a serious loss of income is predicted for the other scenarios. The use of variability of parameters and a Monte Carlo analyses allows statistical analyses and comparison of computed results for alternative land use scenarios, and leads to a more balanced judgement.

Comparison of wind erosion measurements in Germany with simulated soil losses by WEPS

The Wind Erosion Prediction System (WEPS) is a process-based model that simulates daily weather and field conditions along with hourly wind speeds and erosion. Its physical basis should allow model application to regions outside the US for which it was originally developed. The objective of this study was to compare results from measured wind erosion with simulated soil losses as a first example of WEPS use in Germany. Another objective was to introduce methods and techniques for quantifying wind erosion in preparation for model comparison studies to be undertaken within the Global Change and Terrestrial Ecosystems Soil Erosion Network. Comparisons between the measured and simulated erosion were based on single erosion events and outputs from the erosion submodel of WEPS. Multiple runs of the model were performed with varying roughness parameters to set the simulated threshold wind speed equal to that measured during the first erosion event after a tillage operation. This initial data set was used, depending on the rainfall or erosion, as the basis for the gradually changing roughness, crust cover and the fraction of erodible material on crust for all the following erosion events. Thus, the accuracy of the simulation depends much more on the relationship between erosion events, than on a good agreement for one single event. The results showed excellent agreement between measured and simulated erosion ( R 2>0.9). This is mainly attributed to the good agreement with the four largest erosion events in which transport exceeded 100 kg/m width. Excluding these events, R 2 was reduced to about 0.6 for all other erosion events. Spatial and temporal variability of the soil transport were also reasonably simulated.

An assessment of uncalibrated CLIGEN in Australia

Daily weather data are required as climate input to many models that continuously simulate natural resources systems. CLIGEN is a stochastic weather generator to produce 10 daily weather variables to meet this need. CLIGEN has primarily been used to provide climate input for the process-based runoff and soil erosion prediction model WEPP (water erosion prediction project). Runoff and erosion prediction is particularly sensitive to the four precipitation variables generated by CLIGEN. Weather data for 43 sites representing all major climate zones around Australia were used to prepare input parameter files for CLIGEN to generate 100 years climate data for each of these sites. The quality of generated precipitation variables was assessed in terms of (1) simulated runoff and soil loss for each of three soils under bare fallow conditions with WEPP, (2) climate inputs for the revised universal soil loss equation (RUSLE), and (3) a comparison with published rainfall intensity maps for fixed average recurrence interval and duration. This paper shows that uncalibrated CLIGEN can generate the required climate data for WEPP for these sites. Model efficiency between predicted runoff and soil loss using CLIGEN-generated and observed precipitation data is in excess of 0.95. Generated rainfall erosivity for RUSLE is systematically higher than (about 50% for the R-factor and 25% for the 10-year storm erosivity index) and closely related to the measured erosivity for these sites (r2=0.88–0.94), a trend consistent with what is observed for sites in the United States. CLIGEN can also be used to predict the seasonal distribution of rainfall erosivity quite well for all climate zones in Australia. Detailed analysis of the observed 6 min intensity data for these sites shows that over-prediction of rainfall erosivity and rainfall intensity at short time scales in general is an outcome of the particular storm pattern adopted in CLIGEN for WEPP, not an intrinsic deficiency of CLIGEN per se.

Evaluation of the Wind Erosion Prediction System (WEPS) erosion submodel on cropland fields

This study represents part of a project by the Global Change and Terrestrial Ecosystem Soil Erosion Network to validate wind erosion models. Soil loss measurements from 46 storm events from eroding fields in six states were compared to predictions from the Wind Erosion Prediction System (WEPS) erosion submodel. The field data were collected from small (2.5 ha), circular, cropland fields with nonerodible boundaries. Samplers were arranged in vertical clusters to sample horizontal soil discharge passing a point. Weather data, including wind speed, wind direction, solar radiation, relative humidity, air temperature, and rainfall, were collected on-site. Temporal field site characteristics were measured periodically and included surface roughness, plant/residue cover, and dry aggregate size distribution. The WEPS erosion submodel was used to calculate the threshold erosion friction velocity based on surface conditions and then simulate soil loss during daily periods when the speed exceeded that threshold. Measured and simulated erosion values were in reasonable agreement ( R 2=0.71). On average, the erosion model underpredicted soil loss, and the probable reasons are discussed.

Aggregate stability as an indicator of soil susceptibility to runoff and erosion; validation at several levels

The evaluation of soil susceptibility to runoff and water erosion in the field is often expensive or time-consuming. Several authors have reported that susceptibility is linked to aggregate stability, whose determination is far easier. However, this susceptibility has generally been deduced from rainfall simulation experiments on sieved soil samples, whose behaviour is not always representative of field-scale phenomena. Our aim was to extend the validity of relationships between soil aggregation and erosion through comparisons of topsoil aggregate stability and field-assessed susceptibility to runoff and erosion. Susceptibility to runoff and erosion was determined at several levels: first, on a southern French Regosol, through measurements of runoff and soil loss from 1-m 2 microplots under simulated rainfall; second, from 100- to 800-m 2 runoff plots on a Nitosol in Benin, a Ferralsol in Cameroon and a Regosol in Mexico (with additional data on Syria from the literature); and finally, soil susceptibility to erosion was determined through semi-quantitative assessment of the frequency of erosion features on vineyard hillsides in southern France. Aggregate stability was determined by immersion in water and wet-sieving of 2-mm sieved, air-dried 0- to 10-cm soil samples, which actually tests aggregate resistance to slaking. Under simulated rainfall, runoff depth and soil loss after 30 min were negatively correlated with topsoil content in stable macroaggregates (>0.2 mm). On runoff plots, 3-year runoff rate and soil loss were negatively correlated with topsoil aggregate stability, especially stable macroaggregate content; these correlations were improved when slope gradient and climate aggressiveness were considered in addition to aggregate stability. On vineyard hillsides, the frequency index of erosion features was negatively correlated with topsoil content in stable macroaggregates, especially in the absence of conservation practices. These results confirm that aggregate stability is a relevant indicator of soil susceptibility to runoff and erosion, especially in Mediterranean and tropical areas where intense rainfall is frequent. They also confirm that simple laboratory determination can provide data closely correlated with those resulting from field investigations.

Soil loss predictions with three erosion simulation models

Quantification of soil loss is one of the greatest challenges in natural resources and environmental planning. Computer simulation models are becoming increasingly popular in predicting soil loss for various land use and management practices. In this study, three soil erosion prediction models — the Water Erosion Prediction Project (WEPP), the Erosion Productivity Impact Calculator (EPIC), and the Areal Nonpoint Source Watershed Environment Response Simulation (ANSWERS) were used for simulating soil loss and testing the capability of the models in predicting soil losses for three different tillage systems (ridge-till, chisel-plow, and no-till). For each model, the most sensitive model parameters were calibrated using measured soil erosion data. After calibration, models were run and predicted soil loss values were compared with the measured soil loss values. The measured soil erosion data were collected from an erosion experiment field of Kansas State University at Ottawa (Kansas), USA. Field experiments were conducted from 1995 to 1997 on small plots to measure runoff and soil losses under all three tillage systems. All three models were evaluated on the basis of individual event, total yearly, and mean event-based soil loss predictions. Results showed that all the three models performed reasonably well and the predicted soil looses were within the range of measured values. For ridge-till and chisel-plow systems, WEPP and ANSWERS gave better predictions than those by EPIC model. For no-till system, WEPP and EPIC predictions were better than those by ANSWERS. The overall results indicate that WEPP predictions were better than those by the other two models in most of the cases, and it can be used with reasonable degree of confidence for soil loss quantification for all the three tillage systems.

Modelling of event-based soil erosion in Costa Rica, Nicaragua and Mexico: evaluation of the EUROSEM model

This study was undertaken as part of a larger project to evaluate the impact of soil erosion on soil productivity in Costa Rica, Nicaragua and Mexico. An important part of the overall project consists of the use of the event-based EUROSEM model (European Soil Erosion Model) to predict soil erosion rates. This paper evaluates the use of the model both for single event and yearly soil loss estimations using erosion plot data from Nicaragua and data obtained through rainfall simulator experiments in Costa Rica and Mexico. EUROSEM was calibrated based on the hydrographs followed by the sedigraphs in Costa Rica and Mexico and this was followed by a model validation. In Nicaragua, model calibration was done using total soil loss values for 1993 and the model was consecutively validated using plot data for 1994 and 1995. The study stresses the importance of calibrating the model for individual catchments, and that the total area of plant stems and soil cohesion are crucial calibration parameters when modelling grassland with cover percentages above 60%. EUROSEM generally did not perform well on single event simulations in terms of simulating hydrographs and sedigraphs. Whereas the difference between observed and simulated total soil loss was between 0.0% and 100.0%, differences in total discharge, peak run-off rate and peak soil loss ranged between 2.0% and 326.5%. The difference was attributed to the model's inability to model crusting. The application of the model for yearly soil loss predictions looks promising with simulated and observed total soil loss values in Nicaragua differing by between 2.5% and 5.0%.

Farmer participatory research to minimize soil erosion on steepland vegetable systems in the Philippines

Soil erosion coupled with productivity decline is considered a major constraint to sustainable vegetable production in Southeast Asian steeplands, yet soil conservation technologies acceptable to vegetable growers have not been developed. Effectiveness of high-value contour hedgerows species [(Asparagus ( Asparagus officinalis L.), pineapple ( Ananas comosus (L.) Merr.), pigeon peas ( Cajanus cajan (L.) Millsp.), lemon grass ( Cymbopogon flexuosus (Nees ex Steud.) Wats.), and tea ( Camellia sinensis (L.) O. Kuntze)] on control of steepland erosion was evaluated in a replicated researcher-managed field experiment, and 12 farmer-managed erosion-runoff plots from 1995 to 1998 across the landscape of the Manupali watershed in Mindanao, the Philippines. Annual soil loss from 42% slopes with superimposed researcher-managed high-value contour hedgerows treatment (45.4 Mg ha −1) was lower by 30% compared to the conventional practice of up-and-down cultivation (65.3 Mg ha −1). Annual soil loss measured in farmers’ plots ranged from 1.4 Mg ha −1 to 52.5 Mg ha −1 on slopes ranging from 16 to 65%. Soil pH, organic C, total-N, and P downslope were greater by 7, 28, 13, and 10%, respectively, compared to upslope. Total-N, organic C, soil pH, Mg, and K measured at the end of the experiment in the researcher-managed contour hedgerows plots were lower by 45, 20, 30, 53, and 70%, respectively, compared to initial values. The Erosion-Productivity Impact Calculator (EPIC) model was used to assess the effects of annual cropping sequences under a contour hedgerow system on slopes ranging from 15 to 65%. The cabbage ( Brassica oleracea var . capitata L.)-tomato ( Lycopersicon esculentum Mill.)-cabbage sequence (the first crop planted in January) resulted in an average simulated annual soil loss of 28.1 Mg ha −1across slope ranging from 15 to 65%, whereas tomato-cabbage-tomato resulted in an annual simulated soil loss of 98.3 Mg ha −1. The cropping sequence of tomato-cabbage-tomato lost 3.0 Mg ha −1 more soil at 15% slope than did the cabbage-tomato-cabbage sequence, while at 65% slope, the tomato-cabbage-tomato sequence lost 181.2 Mg ha −1 more than the other sequence. On average, two-thirds of the total soil loss occurred during September–December. In order to reduce soil loss and increase productivity in steep sloping lands, high-value contour hedgerows with sequential cropping sequences that include either corn ( Zea mays L.) or cabbage rather than tomato during the most erosive period of the year and variable fertility management strategies along the slope positions are suggested. The coincidence of predicted to actual soil loss from farmer-managed plots, based largely upon model development from researcher-managed plots, and the acute awareness instilled amongst farmer cooperators of the magnitude of soil loss, strengthen the argument for farmer participatory research.

IMPROVEMENT AND EVALUATION OF CLIGEN FOR STORM GENERATION

The program, CLIGEN, generates peak rainfall intensity and storm duration and other daily weather variables for WEPP to predict the rate of runoff and soil loss. Unrealistic peak rainfall intensity simulated by CLIGEN (version 4.2) led to a discovery of a software bug and subsequent modification of the method to estimate the monthly mean of the maximum 30-min rainfall depth for storm generation. To evaluate the modified CLIGEN, break-point rainfall data for 14 sites in the United States were used for periods varying from 4 to 19 years. The modified CLIGEN was then used to generate weather data for a period of 100 years for the 14 sites. WEPP (version 99.5) was run for the 14 sites, using three soil types for each site, so that the simulated mean annual runoff and soil loss can be compared with those using the observed break-point data. For most (> 96%) of the 42 site-soil combinations tested, there is no significant difference in WEPP-simulated mean annual runoff and soil loss at the 0.05 level between the break-point rainfall data and CLIGEN-generated rainfall data. The bias in the mean is less than 2 to 3% for runoff and soil loss when all sites are considered. The minimum bias in the mean annual runoff and soil loss lends support for the modified CLIGEN to generate input for WEPP for the purpose of runoff and soil loss predictions.

Application of the EROSION 3D model to the CATSOP watershed, The Netherlands

This paper describes the application of the EROSION 3D soil erosion model to the CATSOP catchment in the Netherlands using data of 10 storms from the period of 1987 to 1993. Based on observed runoff data the model was calibrated by adjusting initial soil moisture. The computations result in a raster map showing the spatial pattern of predicted erosion and deposition within the catchment. The map corresponds qualitively well with reality. For a quantitative evaluation, the model results were compared with observed sediment data measured at the channel when it leaves the catchment. The comparison shows that simulated soil loss was generally too high. This discrepancy might be caused by weak input data and the presence of processes—such as erosion and deposition within the channel—which are not covered by the model.

Regional assessment of soil erosion using the distributed model SEMMED and remotely sensed data

The soil erosion model for Mediterranean regions (SEMMED) is presented and used to produce regional maps of simulated soil loss for two Mediterranean test sites: one in southern France and one in Sicily. The model demonstrates the integrated use of (1) multi-temporal Landsat Thematic Mapper (TM) images to account for vegetation properties, (2) a digital terrain model in a GIS to account for topographical properties and to assess the transport capacity of overland flow, (3) a digital soil map to assess the spatial distribution of soil properties, and (4) a limited amount of soil physical field data. The principle drawbacks of the model are that it does not account for soil particle detachment by overland flow nor for soil surface crusting. The model is most sensitive to the initial soil moisture storage capacity and the soil detachability index. The main advantages of SEMMED are that it simulates processes at a regional scale and, where possible, it uses available data sources such as remote sensing imagery, digital elevation models (DEM) and (digital) soil databases, which usually are not available for smaller catchment areas. Using SEMMED it is possible to produce regional maps of erosion assessments, which are of more practical use in land use planning and land management than simple extrapolations from small plot experiments.

Estimating storm erosion with a rainfall simulator

Interpreting soil loss from rainfall simulators is complicated by the uncertain relationship between simulated and natural rainstorms. Our objective was to develop and test a method for estimating soil loss from natural rainfall using a portable rainfall simulator (1 m2 plot size). Soil loss from 12 rainstorms was measured on 144-m2 plots with barley residue in conventional tillage (CT), reduced tillage (RT) and zero tillage (ZT) conditions. A corresponding "simulated" soil loss was calculated by matching the simulator erosivity to each storm's erosivity. High (140 mm h−1) and low (60 mm h−1) simulation intensities were examined. The best agreement between simulated and natural soil loss occurred using the low intensity, after making three adjustments. The first was to compensate for the 38% lower kinetic energy of the simulator compared with natural rain. The second was for the smaller slope length of the simulator plot. The third was to begin calculating simulator erosivity only after runoff began. After these adjustments, the simulated soil loss over all storms was 99% of the natural soil loss for CT, 112% for RT and 95% for ZT. Our results show that rainfall simulators can successfully estimate soil loss from natural rainfall events. Key words: Natural rainfall events, simulated rainfall, erosivity, tillage

Effects of crust and cracks on simulated catchment discharge and soil loss

Sealing, crusting and cracking of crusts of the soil surface has been observed in many parts of the world in areas with sandy, silty and loamy soils. Sealing and crust formation occurs under the influence of rain storm and drying weather. With prolonged drying, surface crusts might crack, leading to complex situations with respect to infiltration and runoff generation. Cracking of crusted loamy soils appears to be a general process. This study aims to measure the hydraulic properties of fully crusted and cracked-crusted areas and to evaluate the effects of these measurements on catchment discharge and soil loss in a loess region of the Netherlands, using the LISEM soil erosion model. Samples with minimum infiltration rates (fully crusted) and with maximum infiltration rates (cracked-crusted surfaces) were taken from fields with bare soil or winter wheat and their soil hydraulic functions were measured. The results of these measurements were used as input in the LISEM soil erosion model. Simulations of discharge and soil loss were done for each of these two land-uses and for two rain events. Additionally, simulated discharge and soil loss under actual recorded land-use were calculated. In all cases, soils with no surface cracks produced higher figures for discharge and soil loss than those where 10% of the surface crust was cracked. For a good interpretation of the results for soil loss, the spatial distribution of cracked-crusted areas and fully crusted areas has to be investigated in detail. To deal with cracked-crusted and fully crusted areas in simulation modelling, care has to be taken to accurately measure the soil physical functions representing the maximum and minimum infiltration rates. An assignment of these functions to calculation grids has to be made. As the LISEM model is capable of assigning different soil physical functions to each calculation grid, an improved prediction of the soil physical behaviour of the catchment can be simulated.