Pan-European Soil Erosion Risk Assessment Research Articles

Quantifying aboveground biomass, soil organic carbon and erosion with a detailed crop map and PESERA model in the Yangtze River Basin

AbstractSoil erosion represents a primary threat to soil systems with adverse implications for ecosystem services, crop production, potable water and carbon storage. While numerous studies have quantified the spatial distribution of aboveground Biomass (AGB), soil erosion and soil organic carbon (SOC) in the Yangtze River Basin (YRB), limited attention has been given to assessing the contributions of different land use types and especially crop types to AGB, soil erosion and SOC. In most studies, cropland is taken as a land use class, while detailed crop types and rotation patterns, and their effect on soil erosion and SOC, vary significantly. In this study, we used the Metronamica model to generate a detailed crop rotation and distribution map across the YRB and subsequently employed the Pan‐European Soil Erosion Risk Assessment (PESERA) model to simulate the spatial distribution of AGB, soil erosion and SOC on a monthly basis. PESERA model simulations indicate an average soil erosion rate across the entire YRB of 7.7 ton/ha/yr, with erosion hotspots concentrated in the Sichuan Basin and the central‐southern regions. The southwestern region and western Sichuan show elevated levels of AGB and SOC, while the eastern plains display lower levels. Erosion rates are lowest in areas designated as artificial land, pasture and grassland, whereas croplands and fruit tree plantations experience the highest erosion rates. In terms of crop types, the highest erosion rates and lowest AGB are observed under fallow and potato cultivation, while the lowest erosion rates and highest AGB are found in rice‐wheat rotation fields. To the best of our knowledge, this is the first study taking detailed crop types and patterns into account while evaluating their effect at a relatively large scale (i.e., YRB). These findings can help to develop sustainable soil management and (cropping) conservation strategies.

An integrated modelling approach to derive the grey water footprint of veterinary antibiotics

Water pollution by veterinary antibiotics (VAs) resulting from livestock production is associated with severe environmental and human health risks. While upward trends in global animal product consumption signal that these risks might exacerbate toward the future, VA related water pollution is currently insufficiently understood. To increase this understanding, the present research assesses processes influencing VA pollution from VA administration to their discharge into freshwater bodies, using an integrated modelling approach (IMA). For the VAs amoxicillin, doxycycline, oxytetracycline, sulfamethazine, and tetracycline we estimate loads administered to livestock, excretion, degradation during manure storage, fate in soil and transport to surface water. Fate and transport are modelled using the VA transport model (VANTOM), which is fed with estimates from the Pan-European Soil Erosion Risk Assessment (PESERA). The grey water footprint (GWF) is used to indicate the severity of water pollution in volumetric terms by combining VA loads and predicted no effect concentrations. We apply our approach to the German-Dutch Vecht river catchment, which is characterized by high livestock densities. Results show a VA mass load decrease larger than 99% for all substances under investigation, from their administration to surface water emission. Due to metabolization in the body, degradation during manure storage and degradation in soil, VA loads are reduced by 45%, 80% and 90% on average, respectively. While amoxicillin and sulfamethazine dissipate quickly after field application, significant fractions of doxycycline, oxytetracycline and tetracycline accumulate in the soil. The overall Vecht catchment's GWF is estimated at 250,000 m3 yr−1, resulting from doxycycline (81% and 19% contribution from the German and Dutch catchment part respectively). Uncertainty ranges of several orders of magnitude, as well as several remaining limitations to the presented IMA, underscore the importance to further develop and refine the approach.

Spatial Assessment of the Effects of Land Cover Change on Soil Erosion in Hungary from 1990 to 2018

As soil erosion is still a global threat to soil resources, the estimation of soil loss, particularly at a spatiotemporal setting, is still an existing challenge. The primary aim of our study is the assessment of changes in soil erosion potential in Hungary from 1990 to 2018, induced by the changes in land use and land cover based on CORINE Land Cover data. The modeling scheme included the application and cross-valuation of two internationally applied methods, the Universal Soil Loss Equation (USLE) and the Pan-European Soil Erosion Risk Assessment (PESERA) models. Results indicate that the changes in land cover resulted in a general reduction in predicted erosion rates, by up to 0.28 t/ha/year on average. Analysis has also revealed that the combined application of the two models has reduced the occurrence of extreme predictions, thus, increasing the robustness of the method. Random Forest regression analysis has revealed that the differences between the two models are mainly driven by their sensitivity to slope and land cover, followed by soil parameters. The resulting spatial predictions can be readily applied for qualitative spatial analysis. However, the question of extreme predictions still indicates that quantitative use of the output results should only be carried out with sufficient care.

Spatial and temporal evaluation of soil erosion in Turkey under climate change scenarios using the Pan-European Soil Erosion Risk Assessment (PESERA) model.

The impacts of climate change on soil erosion are mainly caused by the changes in the amount and intensity of rainfall and rising temperature. The combination of rainfall and temperature change is likely to be accompanied by negative or positive variations in agricultural and forest management. Turkey contains vast fertile plains, high mountain chains and semi-arid lands, with a climate that ranges from marine to continental and therefore is susceptible to soil erosion under climate change, particularly on high gradients and in semi-arid areas. This study aims to model the soil erosion risk under climate change scenarios in Turkey using the Pan-European Soil Erosion Assessment (PESERA) model, predicting the likely effects of land use/cover and climate change on sediment transport and soil erosion in the country. For this purpose, PESERA was applied to estimate the monthly and annual soil loss for 12 land use/cover types in Turkey. The model inputs included 128 variables derived from soil, climate, land use/cover and topography data. The total soil loss from the land surface is speculated to be approximately 285.5 million tonnes per year. According to the IPCC 5th Assessment Report of four climate change scenarios, the total soil losses were predicted as 308.9, 323.5, 320.3 and 355.3 million tonnes for RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios respectively from 2060 to 2080. The predicted amounts of fertile soil loss from agricultural land in a year were predicted to be 55.5 million tonnes at present, and 62.7, 59.9, 61.7 and 58.1 under RCP2.6, RCP4.5, RCP6.0 and RCP8.5 respectively. This confirms that approximately 30% of the total erosion occurs over the agricultural lands. In this respect, degraded forests, scrub and arable lands were subjected to the highest erosion rate (68%) of the total, whereas, fruit trees and berry plantations reflected the lowest erosion rates. Low soil organic carbon, sparse vegetation cover and variable climatic conditions significantly enhanced the erosion of the cultivated lands by primarily removing the potential food for organisms. Finally, process-based models offer a valuable resource for decision-makers when improving environmental management schemes and also decrease uncertainty when considering risks.

Soil organic carbon losses by water erosion in a Mediterranean watershed

Soil organic carbon (SOC) is one of the primary elements required in the functioning of ecosystems. Soil erosion, a major mechanism of land degradation, removes SOC and transfers it to the hydrosphere or the atmosphere, thereby affecting key ecosystem functions and services. The Mediterranean region is highly susceptible to land degradation because of erosion due to heavy rains following long, dry, hot summers. Although the Mediterranean landscape typically has a high altitude and incline, the soil is brittle and soft and is easily washed away by rain. Thus, vast regions in Turkey have been afflicted by this type of soil degradation. This study aimed to (1) estimate the temporal distribution of water erosion in the Seyhan River Basin, (2) assess the spatial distribution of SOC and (3) estimate the depletion of SOC through soil erosion using the Pan-European Soil Erosion Risk Assessment model, a physically based, regionally scaled soil erosion model. The annual amount of soil eroded from the Seyhan River Basin is estimated to be 7.8million tonnes per hectare (tha–1year–1). The amount of fertile soil loss from agricultural areas is ~1.2million tonnes per year. The maximum amount of soil erosion occurs in maintenance scrubland and degraded forest areas, contributing to 68% of erosion, followed by that in agricultural land, contributing to 27% of erosion, with the remaining in forests and urban areas.

Soil erosion of Hungary assessed by spatially explicit modelling

ABSTRACTThe conservation of soil resources is increasingly becoming a critical issue worldwide, with growing interest in carbon stocks and water storage within the soil. Hungary is no exception, and there has been a demand for a country level soil erosion map that incorporates digital information available from the latest surveys and digital mapping campaigns. The map presented in this paper in based on the extremely wet year of 2010, and thus provides users a 1:100,000 scale ‘worst case scenario’ of soil erosion risk in Hungary (see Main Map). Results from both the Universal Soil Loss Equation and the Pan-European Soil Erosion Risk Assessment models were combined in order to achieve a map that can be used by a wide range of professionals. Both models estimate soil erosion by water in tonnes per hectare per year.

Combining Qualitative and Quantitative Methods for Soil Erosion Assessments: An Application in a Sloping Mediterranean Watershed, Cyprus

AbstractIn arid and semi‐arid regions, water erosion is difficult to model because of highly irregular precipitation regimes and changes in vegetation cover. The application of quantitative, process‐based models at the catchment scale is often problematic because of large data requirements. Qualitative methods require less data and can be more easily performed in a relatively short time, but they are more subjective. The objective of this research is to develop an erosion assessment methodology that combines qualitative field surveys with quantitative model estimates. The qualitative World Overview of Conservation Approaches and Technologies (WOCAT) methodology is based on expert observations per mapping unit, while the Pan‐European Soil Erosion Risk Assessment (PESERA) model simulates hill slope soil loss based on land cover, soil texture, meteorological data and slope profile. This study was conducted in the 106·4‐km2 Peristerona watershed in Cyprus with a mean local slope higher than 40% in the mountainous upstream area and less than 8% in the plain. Out of 68 units, PESERA and WOCAT results were in agreement in 40 units, while PESERA results were lower in 25 and higher in 3 units. Both methods identified burnt areas and complex cultivation patterns as the most degraded. The total PESERA‐based sediment yield for the watershed was 1·2 Mg ha−1 y−1, which fell within the range of the sediment yield measured at the check‐dam downstream (0·2–2 Mg ha−1 y−1). This study provides a linkage between qualitative and quantitative soil erosion methods and helps to translate the outcomes of the former into the latter, thus providing a good tool for local erosion assessment. Copyright © 2016 John Wiley & Sons, Ltd.

EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

Abstract. The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA), a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km2. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

EVALUATION OF RAINFALL-RUNOFF MODELS FOR MEDITERRANEAN SUBCATCHMENTS

The development and the application of rainfall-runoff models have been a corner-stone of hydrological research for many decades. The amount of rainfall and its intensity and variability control the generation of runoff and the erosional processes operating at different scales. These interactions can be greatly variable in Mediterranean catchments with marked hydrological fluctuations. <br><br> The aim of the study was to evaluate the performance of rainfall-runoff model, for rainfall-runoff simulation in a Mediterranean subcatchment. The Pan-European Soil Erosion Risk Assessment (PESERA), a simplified hydrological process-based approach, was used in this study to combine hydrological surface runoff factors. In total 128 input layers derived from data set includes; climate, topography, land use, crop type, planting date, and soil characteristics, are required to run the model. Initial ground cover was estimated from the Landsat ETM data provided by ESA. <br><br> This hydrological model was evaluated in terms of their performance in Goksu River Watershed, Turkey. It is located at the Central Eastern Mediterranean Basin of Turkey. The area is approximately 2000 km<sup>2</sup>. The landscape is dominated by bare ground, agricultural and forests. The average annual rainfall is 636.4mm. This study has a significant importance to evaluate different model performances in a complex Mediterranean basin. The results provided comprehensive insight including advantages and limitations of modelling approaches in the Mediterranean environment.

Evaluation of RUSLE and PESERA models for predicting soil erosion losses in the first year after wildfire in NW Spain

The accelerated erosion that occurs after wildfire in forest ecosystems is a major factor affecting the sustainability of these environments. Soil erosion prediction models are crucial for estimating fire impacts and for planning post-fire soil stabilization measures. We evaluated the performance of the Revised Universal Soil Loss Equation (RUSLE) and the Pan-European Soil Erosion Risk Assessment (PESERA) models by comparing the soil losses predicted by the models and the soil losses measured in the first year after wildfires in NW Spain. Two alternative RUSLE approaches were also considered: i) the use of reduction coefficients for R and C factors and ii) the application of a soil erodibility reduction factor to take into account soil surface stone cover. The RUSLE model overestimated the observed erosion rates in all cases. The PESERA model performed reasonably well in predicting soil losses, but needs a better characterization of soil burn severity in the soil inputs (crusting and erodibility) because of the high sensitivity of the model to these parameters.In both cases, there is an urgent need for an appropriate assessment of the impact on soil burn severity in the erosional process. This seems critical if these models are to be used for post-fire soil stabilization activities planning.

Erosion rate predictions from PESERA and RUSLE at a Mediterranean site before and after a wildfire: Comparison & implications

Mediterranean ecosystems are commonly vulnerable to wildfires. Accelerated erosion processes due to wildfires in those environments constitute a major restrictive factor in their sustainability. This study aims at evaluating the use of the Revised Universal Soil Loss Equation (RUSLE) and the Pan-European Soil Erosion Risk Assessment (PESERA) models in predicting the changes in spatial variability of soil erosion following a wildfire event. A site in Greece on which a wildfire occurred in the summer of 2007 is used as a case study. Soil erosion rates for the site before and after the fire outbreak were estimated by the two models. Inputs for both models included climatic, land-use, soil type, topography, Earth Observation (EO) as well as management and other ancillary data.Both models showed a substantial increase of soil erosion rates in the affected area as a result of the fire, particularly towards the steeper slopes and on areas of high burning severity. Yet, there were noticeable differences in the predictions between the 2 models in terms of absolute estimates of soil erosion rates before and after the fire event. Mean pre-fire erosion rates from RUSLE were ~2.5 times higher than those from PESERA. RUSLE predicted considerably higher mean erosion in comparison to PESERA for the post-fire conditions, yet of much less spatial variability. Average post-fire soil loss value, compared to pre-fire, was about nine and six times greater when using the RUSLE and the PESERA model respectively. RUSLE predictions were most sensitive to topographic and rainfall erosivity factors. PESERA showed high sensitivity to the vegetation coverage as well as to the soil characteristics inserted as crusting and erodibility variables.To our knowledge, this is the first study performing an intercomparison of soil erosion rate predictions between these two models, particularly so in the context of the influence of wildfire events. This study provides a key contribution towards our ability to better understand the effect of fire on soil erosion in the Mediterranean and elsewhere, as well as the ability of those widely used models as efficient tools to be used for this purpose. The latter is of key significance and practical value for research and policy decision making purposes alike, where information on spatiotemporal estimates of soil erosion rates may be required.

Erosion Modelling In A Mediterranean Subcatchment Under Climate Change Scenarios Using Pan-European Soil Erosion Risk Assessment (PESERA)

Abstract. The Mediterranean region is particularly prone to erosion. This is because it is subject to long dry periods followed by heavy bursts of erosive rainfall, falling on steep slopes with fragile soils, resulting in considerable amounts of erosion. In parts of the Mediterranean region, erosion has reached a stage of irreversibility and in some places erosion has practically ceased because there is no more soil left. With a very slow rate of soil formation, any soil loss of more than 1 t ha−1 yr−1 can be considered as irreversible within a time span of 50-100 years. The objectives of this study were i) to estimate the temporal and spatial distribution of soil erosion under climate change scenarios in study area ii) to assess the hydrological runoff processes. In this study, climate data, land use, topographic and physiographic properties were assembled for Egribuk Subcatchment at Seyhan River Basin in Turkey and used in a process-based Geographical Information System (GIS) to determine the hydrological sediment potential and quantify reservoir sedimentation. The estimated amount of sediment transported downstream is potentially large based on hydrological runoff processes using the Pan-European Soil Erosion Risk Assessment (PESERA) model. The detailed model inputs included 128 variables derived mainly from, soil, climate, land use/cover, topography data sets. The outcomes of this research were spatial and temporal distribution of erosion amount in t ha−1 yr−1 or month−1.

Soil loss estimation and empirical relationships for sediment delivery ratios of European river catchments

ABSTRACTSediment delivery ratios (SDRs) link soil loss to sediment yields (SYs) of river catchments. At large scales, SDR models rely on simple catchment properties. To assess their sensitivity and uncertainty in European regions, I compiled a sediment database and derived 16 soil loss maps varying the approximation of the factors of the universal soil loss equation (USLE). Additionally to parameterizing the USLE, the sensitivity analysis comprised the choice of the soil loss and SDR models. The USLE maps were compared to a Pan-European Soil Erosion Risk Assessment (PESERA) map and two empirical SDR models were applied for explaining the variability of SDR and SY. Most relevant for the model efficiency was the choice of the soil loss model. Unlike the PESERA map, the USLE with the four-parameter SDR model allowed satisfactory results in all regions. Fewer parameters for estimating SDR were less appropriate. Among the USLE factors, the choice of the K factor was most important. The overall model sensitivity to choosing the USLE map and the SDR model was similar. Based on the sensitivity analysis, a most suitable USLE map for predicting SY of European river catchments is proposed. The uncertainty in USLE estimates resulted in an uncertainty of modelled SY varying from 30% to 60% in different regions. No model realization grasped the variability of SDR and SY, so only regional SDR models were feasible. The model application and evaluation were hampered by unrepresentative sediment data and the inherent limitations of the modelling framework.

Assessing soil erosion in Europe based on data collected through a European network

The European Commission Directorate-General for the Environment (DG Environment) and the European Environmental Agency (EEA) have identified soil organic matter conservation and mitigation of soil loss by erosion as priorities for the collection of policy-relevant soil data at the European scale. In order to support European Union (EU) soil management policies, soil quality indicators are required that can be applied using harmonized data for the EU Member States. In 2010, the European Soil Data Centre (ESDAC) of the European Commission conducted a project to collect data on soil erosion from national institutions in Europe, using the European Environment Information and Observation Network for soil (EIONET-SOIL). The aim of this paper is to present a selection of the results obtained for soil erosion from the participating countries. The data collected were compared with estimates of soil loss using the Pan-European Soil Erosion Risk Assessment (PESERA) model, and aggregated soil erosion data from pan-European experimental plot studies. The comparison focuses on eight countries for which complete soil erosion data have been received. Overall, the mean values of soil loss reported by the national institutes (EIONET-SOIL) are larger than the PESERA estimates, with the main differences being for sloping land (> 2°) and for the land cover type forest and heterogeneous agricultural [land cover types according to CORINE (“coordination of information on the environment”) Land Cover 2006].

Mitigating land degradation caused by wildfire: Application of the PESERA model to fire-affected sites in central Portugal

Wildfires represent an important agent of land degradation in temperate sub-humid ecosystems, including southern European Mediterranean countries. Identification of integrated conservation approaches that can reduce or prevent degradational impacts is the aim of the EU-funded DESIRE research program, part of which is concerned with quantifying the likely benefit of acceptable alternative conservation strategies to wildfire. The overall aim of this paper is to apply a modification of the Pan-European Soil Erosion Risk Assessment (PESERA) model in order to compare predicted soil erosion rates of one possible conservation strategy, the regular application of prescribed fire, with that of wildfire. The model is applied to two fire-prone study areas in central Portugal (Góis and Mação) and predicts runoff and erosion at much larger spatial (regional) and temporal (decadal) scales than is usually possible with field monitoring. Simulation using the model was carried out for 50years based on a historical climate time-series. Even assuming very frequent management burns (every 2years) and infrequent wildfires (100years), the model suggests that this conservation measure can generally reduce soil erosion relative to infrequent wildfires, although the predicted soil losses for both types of fire are large compared even with those obtained from small-scale field monitoring. The benefits, limitations, scope for improvement and application to future climatic scenarios of the model in a fire context are discussed.

Reservoir Sedimentation and Flood Control: Using a Geographical Information System to Estimate Sediment Yield of the Songwe River Watershed in Malawi

Severe watershed degradation continues to occur in the tropical regions of southern Africa. This has raised interest to harness and manipulate the potential of the watershed resources for human benefit as the populations grow. Songwe River is one such degrading watershed causing biennial flooding among other problems. In this study, climatic, land use, topographic and physiographic properties were assembled for this watershed and used in a process-based Geographical Information System (GIS) with the aim of determining the hydrological sediment potential of Songwe River watershed and quantifying possibilities of reservoir sedimentation. The study further aimed at determining the critical sediment generating areas for prioritized conservation management and the relationship between the increasing flood events in the floodplains and the rainfall trends. Based on hydrological runoff processes using the Pan-European Soil Erosion Risk Assessment (PESERA) model, the estimated amount of sediment transported downstream is potentially huge. Most of the sediment generation was established to be occurring in the upper sub-basin and specifically from built up village and degraded natural land. These trends have not only caused the increased flooding events in the lower sub-basin, but also pose a great sustainability risk of sedimentation to the proposed reservoir.

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

AbstractThe 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.

Soil erosion modelled with USLE and PESERA using QuickBird derived vegetation parameters in an alpine catchment

The focus of soil erosion research in the Alps has been in two categories: (i) on-site measurements, which are rather small scale point measurements on selected plots often constrained to irrigation experiments or (ii) off-site quantification of sediment delivery at the outlet of the catchment. Results of both categories pointed towards the importance of an intact vegetation cover to prevent soil loss. With the recent availability of high-resolution satellites such as IKONOS and QuickBird options for detecting and monitoring vegetation parameters in heterogeneous terrain have increased. The aim of this study is to evaluate the usefulness of QuickBird derived vegetation parameters in soil erosion models for alpine sites by comparison to Cesium-137 (Cs-137) derived soil erosion estimates. The study site (67km2) is located in the Central Swiss Alps (Urseren Valley) and is characterised by scarce forest cover and strong anthropogenic influences due to grassland farming for centuries. A fractional vegetation cover (FVC) map for grassland and detailed land-cover maps are available from linear spectral unmixing and supervised classification of QuickBird imagery. The maps were introduced to the Pan-European Soil Erosion Risk Assessment (PESERA) model as well as to the Universal Soil Loss Equation (USLE). Regarding the latter model, the FVC was indirectly incorporated by adapting the C factor. Both models show an increase in absolute soil erosion values when FVC is considered. In contrast to USLE and the Cs-137 soil erosion rates, PESERA estimates are low. For the USLE model also the spatial patterns improved and showed “hotspots” of high erosion of up to 16tha−1a−1. In conclusion field measurements of Cs-137 confirmed the improvement of soil erosion estimates using the satellite-derived vegetation data.

Evaluation of the PESERA model in two contrasting environments

AbstractThe performance of the Pan‐European Soil Erosion Risk Assessment (PESERA) model was evaluated by comparison with existing soil erosion data collected in plots under different land uses and climate conditions in Europe. In order to identify the most important sources of error, the PESERA model was evaluated by comparing model output with measured values as well as by assessing the effect of the various model components on prediction accuracy through a multistep approach. First, the performance of the hydrological and erosion components of PESERA was evaluated separately by comparing both runoff and soil loss predictions with measured values. In order to assess the performance of the vegetation growth component of PESERA, the predictions of the model based on observed values of vegetation ground cover were also compared with predictions based on the simulated vegetation cover values. Finally, in order to evaluate the sediment transport model, predicted monthly erosion rates were also calculated using observed values of runoff and vegetation cover instead of simulated values. Moreover, in order to investigate the capability of PESERA to reproduce seasonal trends, the observed and simulated monthly runoff and erosion values were aggregated at different temporal scale and we investigated at what extend the model prediction error could be reduced by output aggregation.PESERA showed promise to predict annual average spatial variability quite well. In its present form, short‐term temporal variations are not well captured probably due to various reasons. The multistep approach showed that this is not only due to unrealistic simulation of cover and runoff, being erosion prediction also an important source of error. Although variability between the investigated land uses and climate conditions is well captured, absolute rates are strongly underestimated. A calibration procedure, focused on a soil erodibility factor, is proposed to reduce the significant underestimation of soil erosion rates. Copyright © 2009 John Wiley & Sons, Ltd.

An evaluation of the pesera soil erosion model and its application to a case study in Zakynthos, Greece

The Pan-European Soil Erosion Risk Assessment (PESERA) model was evaluated using existing soil erosion data collected under various types of climate, vegetation, landscape and soil conditions. The data used represent a variety of typical Mediterranean land uses such as winter wheat, vines, olives and bare, stony land prevailing in hilly areas. Using this data, the model was calibrated for sediment transport by overland flow and results compared to measured soil erosion values from runoff plots and a watershed on a monthly basis. The performance of the model was assessed statistically, showing that it can be satisfactorily used for predicting soil erosion rates under the conditions included in the study. The overall model estimate including all the available experimental data was 0.69 t ha -1 yr -1 with a maximum error of 1.49 t ha -1 yr -1 . After validation, the model was applied to a small watershed (60 ha) of great ecological importance for the sea turtle Caretta caretta. For this purpose, soil and vegetation maps were compiled from all the necessary data for applying the model. The model was run for three years using daily data from an existing nearby meteorological station. The predicted and measured soil erosion rates for a 7-month period were 0.31 t and 0.18t, respectively. Application of the model to each mapping unit showed the over-riding importance of land use for sediment generation under the given climatic conditions. Bare land, occupying 5.5% of the watershed area, generated up to 69% of the total sediments estimated for the watershed. It is concluded that the PESERA model can be used as a regional diagnostic tool under a range of soil, topographic and climatic conditions for identifying the best land use type and vegetation cover to protect hilly areas from soil erosion. The calculated overall root mean square error for the model is 0.06 t ha -1 yr -1 , compared to a soil erosion rate of 0.04 t ha -1 yr -1 , which can be tolerated for protecting the area for the sea turtle.