A new version of the USLE‐MM for predicting bare plot soil loss at the Sparacia (South Italy) experimental site

Improving empirical prediction of plot soil erosion at the event temporal scale has both scientific and practical importance. In this investigation, 492 runoff and soil loss data from plots of different lengths, λ (11 ≤ λ ≤ 44 m), and steepness, s (14.9 ≤ s ≤ 26.0%), established at the Sparacia experimental station, in Sicily, South Italy, were used to derive a new version of Universal Soil Loss Equation (USLE)‐MM model, by only assuming a value of one for the topographic length, L, and steepness, S, factors for λ = 22 m and s = 9%, respectively. An erosivity index equal to (Q_REI₃₀)^b1, Q_R and EI₃₀ being the runoff coefficient and the event rainfall erosivity index, respectively, with b₁ > 1 was found to be an appropriate choice for the Sparacia area. The specifically developed functions for L and S did not differ appreciably from other, more widely accepted relationships (maximum differences by a factor of 1.22 for L and 1.09 for S). The new version of the USLE‐MM performed particularly well for highly erosive events, because predicted soil loss differed by not more than a factor of 1.19 from the measured soil loss for measured values of more than 100 Mg ha^?1. The choice of the relationships to predict topographic effects on plot soil loss should not represent a point of particular concern in the application of the USLE‐MM in other environments. However, tests of the empirical approach should be carried out in other experimental areas in an attempt to develop analytical tools, usable at the event temporal scale, reasonably simple and of wide validity. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparing theoretically supported rainfall‐runoff erosivity factors at the Sparacia (South Italy) experimental site

Interpreting rainfall‐runoff erosivity by a process‐oriented scheme allows to conjugate the physical approach to soil loss estimate with the empirical one. Including the effect of runoff in the model permits to distinguish between detachment and transport in the soil erosion process. In this paper, at first, a general definition of the rainfall‐runoff erosivity factor REF_e including the power of both event runoff coefficient Q_R and event rainfall erosivity index EI₃₀ of the Universal Soil Loss Equation (USLE) is proposed. The REF_e factor is applicable to all USLE‐based models (USLE, Modified USLE [USLE‐M] and Modified USLE‐M [USLE‐MM]) and it allows to distinguish between purely empirical models (e.g., Modified USLE‐M [USLE‐MM]) and those supported by applying theoretical dimensional analysis and self‐similarity to Wischmeier and Smith scheme. This last model category includes USLE, USLE‐M, and a new model, named USLE‐M based (USLE‐MB), that uses a rainfall‐runoff erosivity factor in which a power of runoff coefficient multiplies EI₃₀. Using the database of Sparacia experimental site, the USLE‐MB is parameterized and a comparison with soil loss data is carried out. The developed analysis shows that USLE‐MB (characterized by a Nash–Sutcliffe Efficiency Index NSEI equal to 0.73 and a root mean square error RMSE = 11.7 Mg ha^?1) has very similar soil loss estimate performances as compared with the USLE‐M (NSEI = 0.72 and RMSE = 12.0 Mg ha^?1). However, the USLE‐MB yields a maximum discrepancy factor between predicted and measured soil loss values (176) that is much lower than that of USLE‐M (291). In conclusion, the USLE‐MB should be preferred in the context of theoretically supported USLE type models.     

Testing the Universal Soil Loss Equation‐MB equation in plots in Central and South Italy

Planning soil conservation strategies requires predictive techniques at event scale because a large percentage of soil loss over a long‐time period is due to relatively few large storms. Considering runoff is expected to improve soil loss predictions and allows relation of the process‐oriented approach with the empirical one, furthermore, the effects of detachment and transport on soil erosion processes can be distinguished by a runoff component. In this paper, the empirical model USLE‐MB (USLE‐M based), including a rainfall‐runoff erosivity factor in which the event rainfall erosivity index EI₃₀ of the Universal Soil Loss Equation (USLE) multiplies the runoff coefficient Q_R raised to an exponent b₁ > 1 is tested by the measurements carried out for the Masse (10 plots) and Sparacia (22 plots) experimental stations in Italy. For the Masse experimental station, an exponent b₁ > 1 was also estimated by tests carried out by a nozzle‐type rainfall simulator. For each experimental site in fallow conditions, the effect of the sample size of the plot soil loss measurements on the estimate of the b₁ coefficient was also studied by the extraction of a fixed number N of randomly obtained pairs of the normalized soil loss and runoff coefficient. The analysis showed that the variability of b₁ with N is low and that 350 pairs are sufficient to obtain a stable estimate of b₁. A total of 1,262 soil loss data were used to parameterize the model both locally and considering the two sites simultaneously. The b₁ exponent varied between the two sites (1.298–1.520), but using a common exponent (1.386) was possible. Using a common b₁ exponent for the two experimental areas increases the practical interest for the model and allows the estimation of a baseline component of the soil erodibility factor, which is representative of the at‐site soil intrinsic and quasi‐static properties. Development of a single USLE‐MB model appears possible, and sampling other sites is advisable to develop a single USLE‐MB model for general use.     

Testing assumptions and procedures to empirically predict bare plot soil loss in a Mediterranean environment

Empirical prediction of soil erosion has both scientific and practical importance. This investigation tested USLE and USLE‐based procedures to predict bare plot soil loss at the Sparacia area, in Sicily. Event soil loss per unit area, A_e, did not vary appreciably with plot length, λ, because the decrease in runoff with λ was offset by an increase in sediment concentration. Slope steepness, s, had a positive effective on A_e, and this result was associated with a runoff coefficient that did not vary appreciably with s and a sediment concentration generally increasing with s. Plot steepness did not have a statistically detectable effect on the calculations of the soil erodibility factor of both the USLE, K, and the USLE‐M, K_UM, models, but a soil‐independent relationship between K_UM and K was not found. The erosivity index of the USLE‐MM model performed better than the erosivity index of the Central and Southern Italy model. In conclusion, the importance of an approach allowing soil loss predictions that do not necessarily increase with λ was confirmed together with the usability of already established and largely applied relationships to predict steepness effects. Soil erodibility has to be determined with reference to the specific mathematical scheme and conversion between different schemes seems to need taking into account the soil characteristics. The USLE‐MM shows promise for further developments. The evolutionary concept applied in the development of the USLE should probably be rediscovered to improve development of soil erosion prediction tools. Copyright © 2014 John Wiley & Sons, Ltd.     

An evaluation of the universal soil loss equation and field techniques for assessing soil erosion on a tropical alfisol in western Nigeria

Four techniques for soil erosion assessment were compared over two consecutive seasons for bare-fallow plots and a maize-cowpea sequence in 1985 at IITA, Ibadan, Nigeria. The techniques used were: tracer (aluminium paint), nails (16 and 25), the rill method, and the Universal Soil Loss Equation (USLE). Soil loss estimated by these techniques was compared with that determined using the runoff plot technique. There was significantly more soil loss (P < 0·01) in bare-fallow than in plots under maize (Zea mays) or cowpea (Vigna unguiculata). In the first season, soil loss from plots sown to maize was 40·2 Mg ha^?1 compared with 153·3 Mg ha^?1 from bare-fallow plots. In the second season, bare-fallow plots lost 87·5 Mg ha^?1 against 39·4 Mg ha^?1 lost from plots growing cowpea. The techniques used for assessing erosion had no influence on the magnitude of soil erosion and did not interfere with the processes of erosion. There was no significant difference (P < 0·05) between soil erosion determined by the nails and the runoff plot technique. Soil loss determined on six plots (three under maize, three bare-fallow) by the rill technique, at the end of the season, was significantly lower (P < 0·05) than that determined by the runoff plot technique. The soil loss estimated by the rill method was 143·2, 108·8 and 121·9 Mg ha^?1 for 11, 11, and 8 per cent slopes respectively, in comparison with 201·5, 162·0, and 166·4 Mg ha^?1 measured by the runoff plot method. Soil loss measured on three bare-fallow plots on 10 different dates by the rill technique was also significantly lower (P < 0·01) than that measured by the runoff plot. In the first season the USLE significantly underestimated soil loss. On 11, 11, and 8 per cent slopes, respectively, soil loss determined by the USLE was 77, 92, and 63 per cent of that measured by the runoff plot. However, in the second season there was no significant difference between soil loss determined by the USLE and that determined by the conventional runoff plot technique.     

Plot‐scale measurement of soil erosion at the experimental area of Sparacia (southern Italy)

Obtaining good quality soil loss data from plots requires knowledge of the factors that affect natural and measurement data variability and of the erosion processes that occur on plots of different sizes. Data variability was investigated in southern Italy by collecting runoff and soil loss from four universal soil‐loss equation (USLE) plots of 176 m², 20 ‘large’ microplots (0·16 m²) and 40 ‘small’ microplots (0·04 m²). For the four most erosive events (event erosivity index, R_e ≥ 139 MJ mm ha^?1 h^?1), mean soil loss from the USLE plots was significantly correlated with R_e. Variability of soil loss measurements from microplots was five to ten times greater than that of runoff measurements. Doubling the linear size of the microplots reduced mean runoff and soil loss measurements by a factor of 2·6–2·8 and increased data variability. Using sieved soil instead of natural soil increased runoff and soil loss by a factor of 1·3–1·5. Interrill erosion was a minor part (0·1–7·1%) of rill plus interrill erosion. The developed analysis showed that the USLE scheme was usable to predict mean soil loss at plot scale in Mediterranean areas. A microplot of 0·04 m² could be used in practice to obtain field measurements of interrill soil erodibility in areas having steep slopes. Copyright © 2003 John Wiley & Sons, Ltd.     

Testing a new sampler for measuring plot soil loss

In order to measure soil loss in equipped plots the estimate of the weight of solid material intercepted at their lower end is required. At the experimental area of Sparacia, Sicily, the runoff produced by an erosive event is collected within storage tanks with a capacity of about 1 m³. In this paper, the use of a new sampler is proposed to measure easily the weight of solid material eroded from an experimental plot and collected into a storage tank. The sampler is a cylinder having a closing valve at the bottom. Two different series of runs were carried out both to test the reliability of the sampler and to establish a sampling procedure, respectively. An analysis of various sampling configurations usable in the field differentiated by the number and location of sampling verticals in the tank cross‐section was finally carried out. The results of the present investigation are that the concentration measurement by the sampler was more accurate than that obtained by other methods involving a collection tank, agitation and sampling of the suspension. This sampler is cheap and usable in combination with a quick field sampling procedure which is particularly advisable when the number of plots equipped at an experimental area is large. The sampler was tested using a clay soil contained within cylinders and a cubic tank, but it appeared also to be usable with coarser sediment than clay and in combination with tanks having a different shape. Copyright © 2015 John Wiley & Sons, Ltd.     

Evaluating the effect of land use changes on soil erosion and sediment yield using a grid‐based distributed modelling approach

Processes of soil erosion and sediment transport are strongly influenced by land use changes so the modelling of land use changes is important with respect to the simulation of soil degradation and its on‐site and off‐site consequences. The reliability of simulation results from erosion models is circumscribed by considerable spatial variation in many parameters. However, most of the currently widely used erosion models at the mesoscale are semidistributed, which leads to difficulties in incorporating a high degree of spatial information, especially land use information, so that the effects of land use changes on soil erosion have hitherto not been investigated in detail using these models. In this article, a grid‐based distributed erosion and sediment transport model is introduced, which simulates the spatial pattern of erosion and deposition rates and sediment transport processes in river channels. In this model, land use affects soil erosion through altering soil loss and influencing sediment delivery. Simulated soil erosion for events recorded in 1989 and 1996 in the Lushi basin in China was analyzed by comparing it with historical land use maps. The results indicated that even relatively minor land use changes had a significant effect on regional soil erosion rates and sediment transport to rivers. The average erosion rate increased from 1989 to 1996, after the transformation of forest to farmland. The results of the study suggest that the proposed soil erosion model can be applied in similar river basins. Copyright © 2011 John Wiley & Sons, Ltd.     

Thresholds of land cover to control runoff and soil loss

This research focused on the determination of land cover thresholds that have a significant impact on runoff generation and soil loss at the pedon scale. For this purpose, six erosion micro-plots were set up on grassland and shrubland types of rangeland in the northeast of Iran, and the amounts of vegetation cover, litter, runoff and soil loss on them were measured. A factorial statistical analysis was carried out on the completely randomized design using land cover and rainfall factors. The results show that the effect of rainfall on soil loss and runoff was greater than that of land cover. Also, the effect of land cover on soil loss was greater than that on runoff generation. Furthermore, two specific thresholds were identified: the first was from 10 to 30% of landcover and the second from 50 to 70%.     

Identification of soil erosion and fluvial sediment problems

A computer model has been used to estimate soil loss and sediment yield from irregular field-size units of small watersheds. Input to the model includes spring data (i.e. relating to February through May) for the independent variables of the Universal Soil Loss Equation, and for factors such as surface roughness, an index of overland runoff, and proximity to the stream. Output from the model includes maps of seasonal estimates of potential soil losses, field sediment delivery ratios, and expected sediment yields. On the basis of selected erosion and sediment yield tolerances, the output information has been analysed to identify watershed areas which (1) exhibit both erosion and sediment yield problems; (2) exhibit only erosion problems; (3) exhibit only sediment yield problems; and (4) exhibit neither erosion nor sediment yield problems. The percentage of the watershed area in each category and the percentage of the watershed soil loss and sediment loads contributed by each category are also identified. Application of the procedure for planning remedial control programs for five watersheds is discussed.     

Twenty years of soil erosion on-farm measurement: Annual variation,spatial distribution and the impact of conservation programmes for soil loss rates in Switzerland

Long-term field assessments of soil erosion on the landscape scale are very scarce. Such monitoring programmes create sound data regarding severity, extent, frequency and types of soil erosion and the vulnerability of particular crops. In a 20-year monitoring programme between 1997 and 2017, accurate erosion damage mapping was carried out on 203 fields on arable land in the Canton of Berne (Switzerland). During 115 field inspections, 4060 field years and 2165 mapped erosion systems were recorded. Because several soil conservation programmes were implemented during this period, two 10-year time periods (1st October 1997 to 30th September 2007 [P1] and 1st October 2007 to 30th September 2017 [P2]) were established and compared. The soil erosion rate was already low in P1 (mean: 0.74 t ha⁻¹ year⁻¹), but decreased significantly in P2 (mean: 0.20 t ha⁻¹ year⁻¹). During P1 and P2, respectively, 12 and 42% of the fields were without any visible erosion. Within 10 years, erosion occurred on each field on average 3.2 times in P1 and only 1.3 times in P2. Soil losses are spatially concentrated and linked to topographically defined pathways (thalwegs, slope depressions) or human-made flow pathways (wheel tracks, tramlines, headlands). Financial incentives, rising awareness among farmers, innovative contractor farmers and good extension service of cantonal agencies helped conserve 85% of the arable land in the study area with conservation tillage methods by 2015. As a result, soil erosion was significantly reduced. The field-based measurements show that a significant decrease in soil erosion is possible by changes in soil tillage practices and that erosion control is feasible almost everywhere under real-life conditions on farmers’ fields. In this respect, the Frienisberg region is a case example of successful erosion control. © 2020 John Wiley & Sons, Ltd.     

GIS‐based modelling of soil erosion processes using the modified‐MMF (MMMF) model in a large watershed having vast agro‐climatological differences

The present study demonstrates a spatially distributed application of a field‐scale annual soil loss model, the modified‐MMF (MMMF), to a large watershed using hydrological routing techniques, remote sensing data and geospatial technologies. In this study, the MMMF model is implemented after incorporating the corrections suggested in recent literature along with appropriate modifications of the model to suit the agro‐climatological conditions prevailing in most parts of India. Sensitivity analysis carried out through an Average Linear Sensitivity approach indicates that the model outputs are highly sensitive to soil moisture (MS), bulk density (BD), effective hydraulic depth (EHD), ground cover (GC) and settling velocity for clay (VS_c). During calibration and validation, the performance evaluation statistics are mostly in the range of very good to satisfactory for both runoff and soil loss at the watershed outlet. Even spatial validation of the results of intermediate processes in the water phase and the sediment phase, although qualitative, seems to be reasonable and rational. Furthermore, the soil erosion severity analysis for different land‐uses existing in the watershed indicates that about 90% of the watershed area, especially that occupied by agricultural lands, is vulnerable to the long‐term effects of soil erosion. Copyright © 2018 John Wiley & Sons, Ltd.     

Determining soil erosion rates on semi‐arid watersheds using radioisotope‐derived sedimentation chronology

This study investigates erosion dynamics of the past 90 years in three small semi‐arid watersheds with histories of grazing and vegetation change. Activity of ¹³⁷Cs and excess ²¹⁰Pb from 18 cores collected from sedimentation ponds were measured using a gamma spectrometer. The sediment was dated using a constant rate of supply (CRS) model. This study represents the first time that reservoir sediment accumulation rates determined from fallout isotopes have been verified by direct volumetric measurements of aggradation based on topographic surveys. Measured sedimentation in the ponds ranged between 1.9 and 2.3 cm y^?1, representing average sediment delivery rates from the watersheds of between 0.6 and 2.0 t ha^?1 y^?1. These sediment delivery rates were in agreement with those established by other methods for similar catchments in the region. Past variations in sedimentation rates were identified and correlated with recorded history of anthropogenic disturbance. ¹³⁷Cs and ²¹⁰Pb methods are suitable for use in arid environments and can complement each other to increase reliability of erosion rate estimates. The abundance of stock ponds in southwestern USA presents an opportunity to quantify historic erosion and sediment transfer dynamics in areas that have not been well studied or instrumented. Published 2016. This article is a U.S. Government work and is in the public domain in the USA     

SCALES: a large‐scale assessment model of soil erosion hazard in Basse‐Normandie (northern‐western France)

The cartography of erosion risk is mainly based on the development of models, which evaluate in a qualitative and quantitative manner the physical reproduction of the erosion processes (CORINE, EHU, INRA). These models are mainly semi‐quantitative but can be physically based and spatially distributed (the Pan‐European Soil Erosion Risk Assessment, PESERA). They are characterized by their simplicity and their applicability potential at large temporal and spatial scales. In developing our model SCALES (Spatialisation d'éChelle fine de l'ALéa Erosion des Sols/large‐scale assessment and mapping model of soil erosion hazard), we had in mind several objectives: (1) to map soil erosion at a regional scale with the guarantee of a large accuracy on the local level, (2) to envisage an applicability of the model in European oceanic areas, (3) to focus the erosion hazard estimation on the level of source areas (on‐site erosion), which are the agricultural parcels, (4) to take into account the weight of the temporality of agricultural practices (land‐use concept). Because of these objectives, the nature of variables, which characterize the erosion factors and because of its structure, SCALES differs from other models. Tested in Basse‐Normandie (Calvados 5500 km²) SCALES reveals a strong predisposition of the study area to the soil erosion which should require to be expressed in a wet year. Apart from an internal validation, we tried an intermediate one by comparing our results with those from INRA and PESERA. It appeared that these models under estimate medium erosion levels and differ in the spatial localization of areas with the highest erosion risks. SCALES underlines here the limitations in the use of pedo‐transfer functions and the interpolation of input data with a low resolution. One must not forget however that these models are mainly focused on an interregional comparative approach. Therefore the comparison of SCALES data with those of the INRA and PESERA models cannot result on a convincing validation of our model. For the moment the validation is based on the opinion of local experts, who agree with the qualitative indications delivered by our cartography. An external validation of SCALES is foreseen, which will be based on a thorough inventory of erosion signals in areas with different hazard levels. Copyright © 2010 John Wiley & Sons, Ltd.     

Carbon loss by water erosion in drylands: implications from a study of vegetation change in the south‐west USA

Soil organic carbon (SOC) is an important component of the global carbon cycle yet is rarely quantified adequately in terms of its spatial variability resulting from losses of SOC due to erosion by water. Furthermore, in drylands, little is known about the effect of widespread vegetation change on changes in SOC stores and the potential for water erosion to redistribute SOC around the landscape especially during high‐magnitude run‐off events (flash floods). This study assesses the change in SOC stores across a shrub‐encroachment gradient in the Chihuahuan Desert of the south‐west USA. A robust estimate of SOC storage in surface soils is presented, indicating that more SOC is stored beneath vegetation than in bare soil areas. In addition, the change in SOC storage over a shrub‐encroachment gradient is shown to be nonlinear and highly variable within each vegetation type. Over the gradient of vegetation change, the heterogeneity of SOC increases, and newer carbon from C₃ plants becomes dominant. This increase in the heterogeneity of SOC is related to an increase in water erosion and SOC loss from inter‐shrub areas, which is self‐reinforcing. Shrub‐dominated drylands lose more than three times as much SOC as their grass counterparts. The implications of this study are twofold: (1) quantifying the effects of vegetation change on carbon loss via water erosion and the highly variable effects of land degradation on soil carbon stocks is critical. (2) If landscape‐scale understanding of carbon loss by water erosion in drylands is required, studies must characterize the heterogeneity of ecosystem structure and its effects on ecosystem function across ecotones subject to vegetation change. Copyright © 2013 John Wiley & Sons, Ltd.     

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

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

Complexity‐reduction modelling for assessing the macro‐scale patterns of historical soil moisture in the Euro‐Mediterranean region

Complexity‐reduction modelling can be useful for increasing the understanding of how the climate affects basin soil moisture response upon historical times not covered by detailed hydrological data. For this purpose, here is presented and assessed an empirical regression‐based model, the European Soil Moisture Empirical Downscaling (ESMED), in which different climatic variables, easily available on the web, are addressed for simplifying the inherent complexity in the long‐time studies. To accommodate this simplification, the Palmer Drought Severity Index, the precipitation, the elevation and the geographical location were used as input data in the ESMED model for predicting annual soil moisture budget. The test area was a large region including central Europe and Mediterranean countries, and the spatial resolution was initially set at 50 km. ESMED model calibration was made according to the soil moisture values retrieved from the Terrestrial Water Budget Data archive by selecting randomly 285 grid points (out of 2606). Once parameterized, ESMED model was performed at validation stage both spatially and temporally. The spatial validation was made for the grid points not selected in the calibration stage while the comparison with the soil moisture outputs of the Global Land Data Assimilation System–NOAH10 simulations upon the period 1950–2010 was carried out for the temporal validation. Moreover, ESMED results were found to be in good agreement with a root‐zone soil moisture product obtained from active and passive microwave sensors from various satellite missions. ESMED model was thus found to be reliable for both the temporal and spatial validations and, hence, it might represent a useful tool to characterize the long‐term dynamics of soil moisture–weather interaction. Copyright © 2013 John Wiley & Sons, Ltd.     

Simulation of long‐term soil redistribution by tillage using a cellular automata model

The process of tillage translocation is well studied and can be described adequately by different existing models. Nevertheless, in complex environments with numerous obstacles, such as olive orchards, the application of conventional tillage erosion models is not straightforward. However, such obstacles have important effects on the spatial pattern of soil redistribution and on resulting soil properties. Cellular automata could provide a valuable alternative here. This study aims at developing a cellular automata model for tillage translocation (CATT) that can take into account such obstacles, exploring its possibilities and limitations. Firstly, model outcome was tested on a traditional field with rolling topography, for which caesium‐137 (¹³⁷Cs) inventories are available. The observed spatial soil redistribution patterns could be adequately represented by the CATT model. Secondly, a global sensitivity analysis was performed to explore the effect of input parameter uncertainty on several selected model outputs. The variance‐based extended Fourier Amplitude Sensitivity Test (FAST) method was used to determine first‐ and total‐order sensitivity indices. Tillage depth was identified as the input parameter that determined most of the output variance, followed respectively by tillage direction and speed. The high difference between the total‐ and first‐order sensitivity indices indicated that, in spite of the simple model structure, the model behaves non‐linearly with respect to some of the model output variables. Higher order interactions were especially important for determining the proportion of eroding and deposition cells. Finally, simulations were performed to analyse the model behaviour in complex landscapes, applying it to a field with protruding obstacles (representing olive trees). The model adequately represented some morphological features observed in actual olive orchards, such as mounds around the olive trees. The results show that cellular automata are an appropriate tool to describe long‐term tillage soil redistribution. Copyright © 2010 John Wiley & Sons, Ltd.