Soil Erosion Assessment Research Articles

Assessment of soil erosion using two spatial approaches: RUSLE and SWAT Model

In this paper, we attempted to review the erosion in the Ouergha watershed by applying two spatial approaches. The Ouergha watershed has an area of around 7300 km² representing approximately 18.2% of the Sebou basin of which it is the main tributary. In order to develop the erosion map using the SWAT model, it was important to prepare a large spatial database describing basin proprieties, furthermore, the daily hydro-climatic data. This model integrates MUSLE equation for the estimation of specific degradation. In addition, the estimation of erosion through SWAT was consolidated by constructing an erosion mapping through RUSLE method. This method was applied following an approach based on the use of remote sensing data and GIS tools to produce the major factors involved in the erosive process and their integration into RUSLE. The results obtained, in cartographic form, make it possible to target areas that require priority action for a larger-scale analysis, with a view to finding appropriate solutions to fight against erosion and protect the natural environment. Soil degradation in the Ouergha watershed is around 27 ton/ha/year (SWAT_MUSLE) and 25 ton/ha/year (RUSLE). Average sediment yield was estimated for Al Wahda dam of 10.4 Million tons.

Potential application of Thorium isotopes in upland maize soils for assessment of soil erosion

Soil core samples from upland maize field at Mae Ramah district, Tak province were analysed for thorium isotopes using the modified method. The measures Th-232, Th-230 and Th-228 revealed that the rock parent material is the dominant source at these sites while fertilizer is an important supplement. Migration behaviour of Thorium isotopes varying with seasonal and human activities during cultivation period such as ploughing, harrowing, and applying fertilizer resulted in different distribution of Thorium isotopes in soils. It was observed the descending and ascending of Th-232, Th-230 and Th-228 concentrations in maize soils along the 250 meters line transect sampling. The highest Th-232 found in the upland maize soils was 11.76 Bq/kg or 5344.56 Bq/m2 while the lowest was 1.88 Bq/kg or 289.40 Bq/m2. Erosion and deposition of topsoil in the site should be the most possible reason for the significantly lower thorium isotopes values and vice versa along downhill soils. These results demonstrated that Thorium isotopes could be applied as an ideal substitute of Cs-137 for soil erosion study in the future. Further study is to collect additional line transect sampling including increase with the distance.

Recent advances in the assessment of soil erosion vulnerability in watersheds

Water induced soil erosion has always been a matter of concern in watersheds as they increase the soil vulnerability towards erosion. If unchecked, the eroded material reduces the capability of the river to carry the adequate amount of water and increase the amount of sediments in the watershed area. Determining vulnerability of soil to erosion plays a key role in identifying the extent of fragility and helps in making appropriate plans for conservation. Among various methods present to assess soil erosion vulnerability, there is a need to understand the frequently used methods so far and its advancement with time. Various models have been used in past two decades (1991-2019) and the Revised Universal Soil Loss Equation (RUSLE) is the most used model because of its quantitative ability to estimate the average annual soil loss due to erosion in a watershed and its compatibility with the GIS interface. Different approaches like MCDM, SWAT etc. are being utilised to study soil erosion vulnerability of watersheds. This review showed that the frequently used MCDM method is a Compound Factor (CF) method and that RUSLE is a most used quantitative approach. The review identifies 14 different methods which includes 4 methods which provide quantitative estimation while the other 10 methods are used for qualitative assessment of soil erosion vulnerability. Being the most adopted approach, various modifications of different factors of RUSLE introduced by researchers have made it more efficient with time. This review identifies the trend in advancement of various approaches and methods to study soil erosion vulnerability of watersheds around the world and also how various studies are distributed in the Himalayan and non-Himalayan region. The review also provides an understanding of the status of various current approaches to study soil erosion in a watershed and lists the improvements adopted in the frequently used approaches during 1991 and 2019.

Land use/land cover analysis based prioritization of micro watersheds of Jhelum basin, North Western Himalayas using Geospatial Techniques

Soil erosion is the most devastating hazard which affects land qualities and water resources. An attempt to assess the erosion hazard and prioritization of watersheds for treatment would aid in better planning in combating this menace. Watershed prioritization is the ranking of different micro-watersheds of the catchment according to the order in which they have to be taken for treatment and soil conservation measures. Present study is an attempt to prioritize the micro-watersheds of Chandanwari watershed representing western Himalayas based on land use/land cover to assess soil erosion susceptibility using geographical information system (GIS). Images were classified into categories using supervised classification by maximum likelihood algorithm. Seven such LULC classes were identified, viz., agriculture, wasteland, impervious surface, forest, pasture, shrub and snow. Areas under perennial water (alpine lakes and stream) were also classified. Results of prioritization of micro-watersheds based on Land use/Land cover analysis show that micro-watersheds CMW6, CMW7 and CMW8 belong to very severe erosion class; while CMW1, CMW3 and CMW5 cover under severe erosion class and are more susceptible to soil erosion and need adequate management and planning to mitigate the problem of environmental degradation.

Vineyards Assessed Under a Biophysical Approach: Findings From the Biohydrology and TERRAenVISION Meetings

During the Biohydrology 2019 (24-27 July 2019, Valencia, Spain) and TERRAenVISION 2019 (2-7 September 2019, Barcelona, Spain) meetings, the scientific sessions joined reputed scientists around the world. Innovative debates during these scientific sessions about vineyards focused on the use of new technologies to assess soil erosion and nutrient losses, benefits or damages generated by tillage, the use of cover crops, and the introduction of organic farming. Among all the high-quality posters and oral presentations in these 2 abovementioned conferences, 3 groups from different countries with an extended list of publications decided to publish their new findings on the special issue: Vineyards Assessed Under a Biophysical Approach.

Spatiotemporal dynamics of soil erosion in the ecotone between the Loess Plateau and Western Qinling Mountains based on RUSLE modeling, GIS, and remote sensing

The Maiji District of Tianshui City (Gansu Province, China) is a typical transition region in the ecotone between the Loess Plateau and the Western Qinling Mountains. Exploring the spatiotemporal dynamics of soil erosion in this ecotone is critical for the scientific and impactive mitigation of soil erosion hazards in this ecologically fragile region. With geographic information system (GIS) and remote sensing (RS), we used the revised universal soil loss equation (RUSLE) model to assess soil erosion in the Maiji District and analyzed its dynamic changes between the years 2000, 2005, 2010, and 2015. We also derived a minimum erosion cell for the study region to assess the impacts of different factors upon soil erosion. Our results showed that total soil losses in the study region changed from 2000 to 2015, being steady initially, then increasing, and finally decreasing. Among different erosion classes, slight to light erosion was the most prevalent form, while areas under moderate to higher classes of soil erosion shifted towards a lower class over time. In each year, soil loss consistently increased before it decreased with an increasing class of elevation and slope (respectively, 1500 m a.s.l. and 30° as critical thresholds). However, notable differences were evident between years in soil loss trends with varying classes of vegetation coverage and rainfall erosivity; vegetation coverage could mitigate the adverse impact of rainfall erosivity and thus constrain soil erosion hazards. In conclusion, the situation of soil erosion exhibited an overall trend of improvement in the transition region of the Maiji District. While topography determines the basic pattern of soil erosion occurrence, interactions between vegetation coverage and rainfall erosivity drive the dynamic development of soil erosion in our study region. Since vegetation coverage is a manageable factor, its reasonable and responsible regulation presents an effective way to mitigate soil erosion hazards in this region of China.

Analysis of soil erosion in central and eastern China: A spatial model approach

Soil erosion is a widespread environmental problem that threatens environmental sustainability. The purpose of this study is to explore the spatial characteristics of soil erosion in 24 provinces in central and eastern China, which are mainly affected by hydraulic erosion. Initially, the Revised Universal Soil Loss Equation model is used to evaluate the intensity of soil erosion. Then, the global spatial correlation and spatial spillover effects of soil erosion in the study area are analyzed by using Moran’s I index test and the spatial Markov chain method, respectively. Finally, the spatial Durbin model is introduced to analyze the spatial correlation of soil erosion and the spatial spillover effects of soil erosion–influencing factors. Results show that soil erosion in 24 provinces exhibits a significant spatial correlation and spatial spillover effect, and the intensity of soil erosion in each province is affected by the intensity of soil erosion in neighboring provinces. Simultaneously, soil erosion in each province demonstrates spatial aggregation characteristics, showing high–high and low–low aggregations in spatial distribution. In addition, the regression results of the spatial Durbin model indicate that the soil erosion–influencing factors exhibit spatial spillover effects. Each influencing factor will not only affect the intensity of soil erosion in this province, but it will also affect those in neighboring provinces. In conclusion, the spatial characteristics of soil erosion should be considered in the prevention and control of soil erosion in 24 provinces in central and eastern China, and overall and regional cooperative soil and water conservation policies should be formulated. This study promotes research on soil erosion from the spatial dimension and provides a new practical approach for regional soil erosion assessment.

GIS and RS Based Soil Erosion Modelling in Sri Lanka: A Review

Purpose : Over the seventy years, various soil erosion modeling methods were developed in the world with different input requirements and complexity. Some of these soil erosion models have been applied in Sri Lanka covering several regions of the country at different scenarios over the past twenty years. Thus, the prime objective of this study is to compare commonly practiced GIS/ RS based soil erosion assessment models and derivation techniques of model parameters used in Sri Lanka. Research Method : Scholarly research articles, conference proceeding papers, and previously published literature on GIS/ RS based soil erosion models over the past twenty years were critically reviewed, examined, and compared to find various methodologies in the derivation of soil erosion model parameters, analysis methods, and applications with special reference to Sri Lanka. Findings : The results revealed that, in each case, the empirical soil erosion models have been applied to predict soil erosion rates in terms of rill and sheet erosion excluding gully erosion. Furthermore, soil loss at the catchment or entire country scale has been assessed in each case by using different derivation methods. The assessed soil erosion model parameters are R factor (rainfall erosivity), K factor (soil erodibility), LS factor (slope gradient), C factor (crop management factor), and P factor (support practice factor). Originality/ Value : Different derivation methods of soil erosion model parameters (R, K, LS, C, and P) were critically evaluated in order to find the most appropriate methods that can be applied in Sri Lanka in future research studies.

A review of soil erosion modeling by R/USLE in Morocco: Achievements and limits

Soil erosion is a major cause of land degradation. It can be estimated with several models, such as empirical, conceptual and physical based. One of the empirical models used worldwide nowadays for soil erosion assessment is the Universal Soil Loss Equation (USLE) and its updated form, the Revised Universal Soil Loss Equation (RUSLE). In Morocco, this model is being used to assess and quantify soil loss by water erosion. In spite of this, it was noted that limited studies employed correctly this important tool. The goal of this review paper was to identify potential usage of R/USLE models in Morocco. This was done by evaluating the conducted studies concerning these models and main gaps and challenges were determined accordingly. Improvement options and future requirements for using R/USLE models were recommended. In order to assess the statues of the R/USLE models applications, the 56 published documents related to R/USLE models conducted in Morocco during the first use till 2020 were collected and reviewed. These publications covered five main areas. The main benefits as well as gaps of the conducted studies were discussed for each area. Current concerns, need of future studies as well as related recommendations and suggestions were also presented.

Assessment of Soil Erosion by RUSLE Model using Remote Sensing and GIS - A case study of Ziz Upper Basin Southeast Morocco

Assessment of Soil Erosion by RUSLE Model using Remote Sensing and GIS - A case study of Ziz Upper Basin Southeast Morocco

Vulnerability of Potential Soil Erosion and Risk Assessment at Hilly Farms using InSAR Technology

Vulnerability of Potential Soil Erosion and Risk Assessment at Hilly Farms using InSAR Technology

Impacts of rainstorms on soil erosion and organic matter for different cover crop systems in the western coast agricultural region of Syria

AbstractMore and more cultivated coastal territories of Syria are being affected by increasing land degradation processes, specifically, by soil erosion due to non‐sustainable soil management. The use of cover crops can be considered an ideal solution to reduce the negative impacts of extreme rainfall events on soil erosion. However, there is no enough information about the main cultivated areas of Syria due to the current conflicts and the very few types of research conducted there. Therefore, the main aim of this research was to assess soil erosion (soil loss and sediment concentration) and hydrological response (run‐off and infiltration) considering the impact of different types of cropping systems on soil organic matter. To achieve this goal, using erosion plots, five grouped natural rainfall events and soil samples were collected, and infiltration measurements were performed between November 2012 and April 2013 (rainy season) on three different cropping systems (wheat, vetch, bean and control) with different sloping gradients (8% and 20%) in Tartous governorate (W Syria). Our results showed a cumulative rainfall amount from 68.8 to 201 mm during the study period. The highest sediment yield was generated in the control and wheat plots, registering 0.468 and 0.368 kg m−2, respectively, with an inclination of 8%. For an inclination of 20%, the control and wheat plots registered 1.145 and 0.967 kg m−2, respectively. In comparison with the control plots, there was a decrease in the total eroded organic matter, which ranged from 0.0579 (control) to 0.0289 (bean) kg m−2 year−1 in the plots with 20% inclination, and from 0.0233 (control) to 0.0069 (bean) kg m−2 year−1 with 8% inclination. To sum up, bean and vetch play an effective role to mitigate soil erosion, delay run‐off and reduce sediment yield. The output of this research provides first insights into the impact of different land uses on soil loss. Also, it could help rural inhabitants and farmers to correctly manage their soils against soil erosion processes.

Suitability of TRMM Products with Different Temporal Resolution (3-Hourly, Daily, and Monthly) for Rainfall Erosivity Estimation

Rainfall erosivity (RE) is a significant indicator of erosion capacity. The application of Tropical Rainfall Measuring Mission (TRMM) rainfall products to deal with RE estimation has not received much attention. It is not clear which temporal resolution of TRMM data is most suitable. This study quantified the RE in the Poyang Lake basin, China, based on TRMM 3B42 3-hourly, daily, and 3B43 monthly rainfall data, and investigated their suitability for estimating RE. The results showed that TRMM 3-hourly product had a significant systematic underestimation of monthly RE, especially during the period of April–June for the large values. The TRMM 3B42 daily product seems to have better performance with the relative bias of 3.0% in summer. At the annual scale, TRMM 3B42 daily and 3B43 monthly data had acceptable accuracy, with mean error of 1858 and −85 MJ∙mm/ha∙h and relative bias of 18.3% and −0.85%, respectively. A spatial performance analysis showed that all three TRMM products generally captured the overall spatial patterns of RE, while the TRMM 3B43 product was more suitable in depicting the spatial characteristics of annual RE. This study provides valuable information for the application of TRMM products in mapping RE and risk assessment of soil erosion.

Modeling and optimization of experimental designs for soil loss assessment at plot scale

Appropriate investigation of soil erosion triggering/controlling factors is of great importance for natural resources management. Usually, soil erosion assessment is time consuming and impose high costs to researchers and managers. Therefore, design of experiments methods can be good approaches to achieve the purpose to which adequate attention has not been paid yet. This study was aimed to assess two response surface methods of Box-Behnken (BBM) and Face-centered central composite (FCCM) as well as a fractional factorial design of experiment Taguchi method (TM) for modeling and optimization of soil loss process at plot scale. So far, no studyhas been conducted to evaluate and compare the ability of BBM, FCCM, and TM in soil erosion modeling, optimization and assessment. Rainfall simulations were performed in the conditions determined by BBM, FCCM experimental designs and TM orthogonal arrays, and in-situ soil loss measurements were performed at small plot scale. Although, results showed that BBM outperformed FCCM and TM, the ANOVA test indicated verified non-significant difference (p = 0.921 at 0.01 significance level) in performances of the modeling procedures. It was further shown that TM had an acceptable performance with regard to the very limited number of required measurement tests. Results further showed that there was a good agreement (r = 0.97) between the results of TM with just 16 runs and BBM with 56 runs with respective RMSEs of 8.16 and 5.08. Therefore, TM can be suggested for soil erosion studies when there are limitations in time and expenses for simulations. However, if the limitations can be overcome, BBM can be suggested as a better design of experiment in soil erosion studies.

Identification of areas vulnerable to soil erosion and risk assessment of phosphorus transport in a typical watershed in the Loess Plateau

Soil erosion is an increasingly serious eco-environmental problem and an important driver of phosphorus loss, which not only reduces soil productivity but also decreases water availability. The integration of the universal soil loss equation (USLE) and the geographic information system (GIS) technique is globally popular for erosion prediction and assessment. The Fen River basin is located in the east of the Loess Plateau and has eco-environmental problems of soil erosion and eutrophication because of excess phosphorus content. This study attempted to use the USLE model to evaluate soil erosion and the transport of the resulting particulate phosphorus in the Fen River basin under a GIS framework. The results showed that soil erosion in 15.8% of the study area exceeded 8000 t/(km2·a) and was mainly distributed in the upper Fen River basin. Soil erosion was greatest in the bareland area, with an average of approximately 1.22 × 104 t/(km2·a), followed by that in grassland. Soil erosion in the study area is most sensitive to the rainfall erodibility (R), followed by the soil erodibility (K), topographic factors including slope steepness (S) and slope length (L), the soil and water conservation factor (P), and the vegetation cover and management factor (C). Similar to soil erosion, the high-risk areas of particulate phosphorus transport were mainly concentrated in the upper reaches of the basin. The study also pointed out that the combined use of available data sources with the USLE model and GIS technique is a viable option to calculate soil erosion and assess the risk of particulate phosphorus transport, which could provide a scientific basis for reducing soil erosion and controlling phosphorus migration.

Susceptibility to Soil Erosion and Risk Assessment at Hilly Farms Using Geospatial Techniques

Soil erosion is a serious environmental challenge which persistently diminishes available land resources globally.The impact of soil erosion is more severeat hilly regions where various techniques are deployed to evaluateits risk levels. However, the traditional approach of estimating the magnitude of erosion is tedious, costly, and considerably time consuming. This study was intended to assess the risk associated with soil erosion at hilly areas of Cameron Highlands through geospatial means. The Digital Elevation Model (DEM) with 5m resolution from Interferometric Synthetic Aperture Radar (IfSAR) was utilized to generate the slope inthe highlands. Soil erosion rates was estimated using Universal Soil Loss Equation (USLE), while information about land use and cover were sourced from relevant government agencies. Inversed Distance Weighted (IDW) method of spatial interpolation was applied to predict the values of unknown pixels. The analysis shows that, there is 217.5 km2of the highlands which is greater than 45-degreeaccounted for about 30.5% of the total land area. Moreover, erosion risk assessment indicated that 66.3%, 11.4%, 11.7% and 10.8% are respectively classified as very low, law, moderate and high susceptible to soil erosion. In general, the risk of soil erosion is relatively low and could be attributed to den sevegetation coverage within the study watershed despite the steep slopes where it was found to be at very high risk to soil erosion susceptibility. However, there is need to deploy best management practices to reduce the effect of soil disturbances at hilly areas and prevent excessive soil loss in future.

Influence of DEM Elaboration Methods on the USLE Model Topographical Factor Parameter on Steep Slopes

Runoff erosion is an important theme in hydrological investigations. Models assessing soil erosion are based on various algorithms that determine the relief coefficient using rasterized digital elevation models (DEMs). For evaluation of soil loss, the most-used model worldwide is the USLE (Universal Soil Loss Equation), where the most essential part is the LS parameter, which is, in turn, generated from two parameters: L (slope length coefficient) and S (slope inclination). The most significant limitation of LS is the difficulty in obtaining the data needed to generate detailed DEMs. We investigated three popular data generation methods: aerial photographs (AP), aerial laser scanning (ALS), and terrestrial laser scanning (TLS) by assessing the quality and effect of DEMs generated from each method over an area of 40 m × 200 m in Silesia, Poland. Additionally, the relationship between particular LSUSLE parameter components was carried out based on its final distribution. Our results show that resolution strongly influences DEMs and the LSUSLE parameters. We found a strong relationship between the degree of height data resolution and the accuracy level of the calculated parameters. Based on our investigations we confirmed the highest influence on the LSUSLE came from the S parameter. Additionally, we concluded that in examinations over large areas, terrestrial laser scanners are not ideal; the benefits of their additional accuracy are outweighed by the additional time and labor consumption; in addition, terrestrial-based scans are sometimes not possible due to ground obstacles the limited scope of most lasers. Aerial photographs or point clouds generated by aerial laser scanners are sufficient for most purposes connected with surface flow, and further developments can be based on the use of these techniques for obtaining ground information for modeling erosion processes.

Assessment of Soil Erosion Using the RUSLE Model for the Epworth District of the Harare Metropolitan Province, Zimbabwe

Urban development without adequate soil erosion control measures is becoming a major environmental concern in developing urban areas across Africa. These environmental disturbances encompass rampart Land Use and Land Cover changes (LULC) due to a high population growth rate and increased economic activities. To understand the influence of accelerated LULC changes and urban expansion as major drivers in landscape degradation in the Epworth district of the Harare Metropolitan Province, the RUSLE model was employed. This considers land use, soil, climate and topography as input parameters in the assessment of the extent and impact of these drivers on soil erosion. The Revised Universal Soil Loss Equation (RUSLE) was used to predict the potential erosion between 1984 and 2018 and soil erosion risk for the years 2000 and 2018. The mean rate of the predicted potential soil erosion was 13.2 t ha−1 yr−1 (1984–2018); areas especially vulnerable to erosion were predicted for foot slope areas with direct tributaries to the major streams and steep sloping zones. The average soil erosion risk was estimated at 1.31 t ha−1 yr−1 for the year 2000 and 1.12 t ha−1 yr−1 for 2018. While the overall potential soil loss decreased between 2000 and 2018, the potential soil loss was observed to increase tremendously in residential areas, which doubled in extent between 2000 and 2018. The findings reveal that about 40% of the Epworth district was threatened by unsustainable soil loss resulting from increased soil erosion risk within the built-up areas.

Deposition of 137Cs and precipitation distribution in Vojvodina, Northern Serbia after the Chernobyl accident

There is a dilemma whether the Chernobyl accident is the main source of this anthropogenic radionuclide in the region of Vojvodina, Northern Province of Serbia. The difference compared to the other dominant source of radiocaesium in the environment, the nuclear weapon tests, is lying in the local character of contamination due to accidents, which implies it’s highly dependent on meteorological parameters, such as precipitation and wind in the area at that time. According to published data, the average value of surface contamination by radiocaesium on the territory of the former Yugoslavia after the Chernobyl accident was several times higher than the estimated contamination by nuclear testing (1945–1963). The main aim of this research is to explore possible correlations of the spatial distribution of precipitation from April 1986 to December 1987 with the deposition of radiocaesium in the surface soil to justify this claim in the absence of data on caesium deposition before the Chernobyl accident for the Vojvodina region. The database of 137Cs content in Vojvodina soil and precipitation for this region during the timeframe of interest were used. From a total of 245 precipitation stations in Vojvodina, 164 to 244 precipitation stations were selected for analysis in conditionals from different time scale aspects and data validation. The best correlation between amounts of total precipitation and 137Cs content in surface soil obtained for two rainy periods 2nd-5th and 7th-21st May 1986. Further cluster analysis separated four different regions according to 137Cs deposition and precipitation for the mentioned rainy period which could be applied in the field of soil erosion assessment on the local and regional level.

Soil Erosion Susceptibility Mapping in Kozetopraghi Catchment, Iran: A Mixed Approach Using Rainfall Simulator and Data Mining Techniques

Soil erosion determines landforms, soil formation and distribution, soil fertility, and land degradation processes. In arid and semiarid ecosystems, soil erosion is a key process to understand, foresee, and prevent desertification. Addressing soil erosion throughout watersheds scales requires basic information to develop soil erosion control strategies and to reduce land degradation. To assess and remediate the non-sustainable soil erosion rates, restoration programs benefit from the knowledge of the spatial distribution of the soil losses to develop maps of soil erosion. This study presents Support Vector Machine (SVM), Random Forest (RF), and adaptive boosting (AdaBoost) data mining models to map soil erosion susceptibility in Kozetopraghi watershed, Iran. A soil erosion inventory map was prepared from field rainfall simulation experiments on 174 randomly selected points along the Kozetopraghi watershed. In previous studies, this map has been prepared using indirect methods such as the Universal Soil Loss Equation to assess soil erosion. Direct field measurements for mapping soil erosion susceptibility have so far not been carried out in our study site in the past. The soil erosion rate data generated by simulated rainfall in 1 m2 plots at rainfall rate of 40 mmh−1 was used to develop the soil erosion map. Of the available data, 70% and 30% were randomly classified to calibrate and validate the models, respectively. As a result, the RF model with the highest area under the curve (AUC) value in a receiver operating characteristics (ROC) curve (0.91), and the lowest mean square error (MSE) value (0.09), has the most concordance and spatial differentiation. Sensitivity analysis by Jackknife and IncNodePurity methods indicates that the slope angle is the most important factor within the soil erosion susceptibility map. The RF susceptibility map showed that the areas located in the center and near the watershed outlet have the most susceptibility to soil erosion. This information can be used to support the development of sustainable restoration plans with more accuracy. Our methodology has been evaluated and can be also applied in other regions.