Average Soil Loss Research Articles

Evaluation of soil loss estimation using the RUSLE model and SCS-CN method in hillslope mining areas

Mining operations result in the generation of barren land and spoil heaps which are subject to high erosion rate during the rainy season. The present study uses the Revised Universal Soil Loss Equation (RUSLE) and SCS-CN (Soil Conservation Service - Curve Number) process to estimate in Kiruburu and Meghahatuburu mining sites areas. The geospatial model of annual average soil loss rate was determined by integrating environmental variables parameters in a raster pixels-based GIS framework. GIS layers with, rainfall passivity and runoff erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management(C) and conservation practice (P) factors were calculated to determine their effects on annual soil erosion in the study area. The coefficient of determination (r2) was 0.834, which indicates a strong correlation of soil loss with runoff and rainfall. Sub -watersheds 5,9,10 and 2 experienced high level of highly runoff. Average annual soil loss was calculated (30*30m raster grid cell) to determine the critical soil loss areas (Sub-watershed 9 and 5). Total soil erosion area was classified into five class, slight (10,025 ha), moderate (3125 ha), high (973 ha), very high (260 ha) and severe (53 ha). The resulting map shows greatest soil erosion of >40th-1 y-1 (severe) through connection to grassland, degraded and open forestry on the erect mining side-escutcheon. The Landsat pan sharpening image and DGPS survey field data were used in the verification of soil erosion results.

Development Land Erosion Model Using Model Builder GIS (Case Study: Citepus Watershed)

Land erosion is the impact of increasing runoff discharge and land use conversion to impervious areas. Land erosion usually calculated by formula called USLE (Universal Soil Loss Equation) then modified as MUSLE (Modified Universal Soil Loss Equation). These formula calculate average annual soil loss in tons/areas depends on rainfall erosivity (R), soil erodibility factor (K), topographic factor (LS), cropping and conservation factor (CP). GIS (Geographic Information System) is a system designed to capture, manipulate, and analyze spatial/geographic data. There are some tools related water resources analysis in ArcGIS such as: watershed analysis and also have a tools for user to create their own model called model builder. This research was aim to create a model to calculate land erosion using MUSLE formula by model builder in ArcGIS. The output for this research is the model which can be used to calculate annual soil loss in watershed area based on GIS systems. For the model trial and case study, we use Citepus watershed located on Bandung West Java, that has 5 river branches: Cibogo, Cikakak, Cilimus, Cipedes and Ciroyom. As the result of the model, the value of average annual soil loss in Citepus watershed can be calculated automatically by developed model.

Impact of Land Use Land Cover on Soil Erosion in Krishna Lower Subbasin

Soil degradation is a severe environmental problem confronting the world today. A study was undertaken to apply revised universal soil loss equation (RUSLE) to estimate the soil erosion and effect of land use and land cover on soil erosion in Krishna lower sub-basin using Remote Sensing and GIS. Spatial map of each RUSLE parameters was derived in Arc GIS 10.1 and ERDAS IMAGINE 9.3 for the 11317.36 km2 Krishna lower sub-basin catchment in Andhra Pradesh. The values of R, K, LS, C, P factors of the catchment area were used to generate soil erosion spatial maps. The study showed that the average annual soil loss was sensitive to rainfall factor, R, land use and land cover. The computed maximum annual soil erosion for the years 1993 to 2015 was 28.69 t.ha-1. yr-1. Severe erosion was found in settlements, wasteland and during rabi crop. The estimated soil loss from “high” to “very high” occurred in scrubland. Moderate erosion occurred in double/ triple cropping area, and slight erosion occurred in forest and during kharif crop.

СОВРЕМЕННЫЙ ТРЕНД ЭРОЗИОННО-АККУМУЛЯТИВНЫХ ПРОЦЕССОВ В МАЛОМ РАСПАХАННОМ ВОДОСБОРЕ, РЕСПУБЛИКА ТАТАРСТАН, "Геоморфология"

Анализ аккумуляции наносов в днищах долин первого порядка позволяет дать достаточно надежную количественную оценку общей интенсивности и временн й изменчивости эрозионных процессов на сельскохозяйственных землях, подходящих практически вплотную к этим долинам. С использованием радиоактивного цезия-137 в качестве хрономаркера, а также усовершенствованных эрозионных моделей USLE и Государственного гидрологического института, изучение аккумулированных наносов в днище малой долины “Темева речка” (площадь водосбора - 1.13 км2), расположенной в северо-западной части Республики Татарстан (бассейн р. Мёша), показало заметное снижение темпов смыва почв с пахотной части водосбора за последние десятилетия. Так, если за период 1963-1986 гг. темпы аккумуляции в днище малой долины смытого со склонов водосбора почвенного материала составляли 0.92-1.81 см/год, то за период 1987-2015 гг. - 0.17-0.50 см/год, т.е. сократились как минимум в 3-5 раз. Причиной отмеченного уменьшения темпов смыва почв и аккумуляции наносов явилось сокращение объемов поверхностного стока со склонов в период снеготаяния, вызванное повышением температуры воздуха в весеннее время года, уменьшением глубины промерзания почв и снижением частоты выпадения экстремальных ливней со слоем 40-50 мм. Влияние хозяйственной деятельности на уменьшение темпов эрозионно-аккумулятивных процессов было, по всей видимости, несущественным, хотя некоторое изменение севооборотов с увеличением доли многолетних трав, очевидно, повлияло на снижение темпов смыва в теплое время года. Данная эрозионная тенденция и климатические причины, ее обусловившие, имели региональный характер и ранее выявлены в ряде регионов южной половины Европейской территории России.

Quantification of soil and water losses in an extensive olive orchard catchment in Southern Spain

A sound understanding of erosive processes at different scales can contribute substantially to the design of suitable management strategies. The main aim of this work was to evaluate key factors at the pedon scale that cause soil erosion to occur. To achieve this goal, we quantified infiltration, permeability, soil losses and runoff volumes in a small Southern Spanish catchment cultivated with olive orchards. To assess which factor contributed most to speeding up soil erosion, a Spearman rank coefficient and principal components analysis were carried out. The results confirmed low infiltration values (11.8 mm h−1) in the surface soil layers and high permeability values (24.6 mm h−1) in the sub-surface soil layers, and produced an average soil loss of 19.7 g m−2 and average runoff coefficients of 26.1%. Statistical analyses showed that: i) the generation of runoff was closely correlated with soil loss; and, ii) an increase in the vegetation cover helped reduce soil erosion. In comparison to larger areas such as a catchment, the pedon scale produced lower or similar soil losses and runoff coefficients in rainfall simulation conditions, although the influence of vegetation cover as a control factor was also detected.

Modelling surface geomorphic processes using the RUSLE and specific stream power in a GIS framework, NE Peloponnese, Greece

Mediterranean regions, with climate variability and long histories of human disturbance, are particularly vulnerable to soil erosion and sediment redistribution. This study examines surface soil stability and stream energy of the 243 km2 Inachos River watershed in the northeast Peloponnese, Greece. This mountainous, semi-arid Mediterranean region has an extensive history of human activity. Soil loss and stream energy are each quantified by applying the Revised Universal Soil Loss Equation (RUSLE) using the Unit Stream Power Erosion Deposition (USPED) method and the specific stream power approach to the main river channels. These models are used to indicate the spatial variability in geomorphic activity. Results show an average soil loss for the Inachos River catchment of 15.0 t ha−1 a−1, exceeding the rate of soil formation. Values range from nil in low gradient environments to 4287 t ha−1 a−1 in steep, mountainous regions. Gradient and rainfall erosivity are the primary factors. High specific stream power in the upper watershed exceeds 17,100 W m−2, resulting in the mobilization of sediment into channelized debris flows that transport sediment from the steep hillslopes. Episodic high-magnitude precipitation events promote the longitudinal connectivity of the catchment. The long occupation and agricultural history, extending as far back as Neolithic time, has accelerated downslope sediment transport.

Integration of geospatial technologies with RUSLE for analysis of land use/cover change impact on soil erosion: case study in Rib watershed, north-western highland Ethiopia

In recent times, soil erosion interlocked with land use and land cover (LULC) changes has become one of the most important environmental issues in developing countries. Evaluation of this complex interaction between LULC change and soil erosion is indispensable in land use planning and conservation works. This paper analysed the impact of LULC change on soil erosion in the north-western highland Ethiopia over the period 1986–2016. Rib watershed, the area with dynamic LULC change and severe soil erosion problem, was selected as a case study site. Integrated approach that combined geospatial technologies with revised universal soil loss equation model was utilized to evaluate the spatio-temporal dynamics of soil loss over the study period. Pixel-based overlay of soil erosion intensity maps with LULC maps was carried out to understand the change in soil loss due to LULC change. Results showed that the annual soil loss in the study area varied from 0 to 236.5 t ha−1 year−1 (tons per hectare per year) in 1986 and 0–807 t ha−1 year−1 in 2016. The average annual soil loss for the entire watershed was estimated about 40 t ha−1 year−1 in 1986 comparing with 68 t ha−1 year−1 in 2016, a formidable increase. Soil erosion potential that was estimated to exceed the average soil loss tolerance level increased from 34.5% in 1986 to 66.8% in 2016. Expansion of agricultural land at the expense of grassland and shrubland was the most detrimental factor for severe soil erosion in the watershed. The most noticeable change in soil erosion intensity was observed from cropland with mean annual soil loss amount increased to 41.38 t ha−1 year−1 in 2016 from 26.60 in 1986. Moreover, the most successive erosion problems were detected in eastern, south-eastern and northern parts of the watershed. Therefore, the results of this study can help identify the soil erosion hot spots and conservation priority areas at local and regional levels.

Environmental Impact Assessment (EIA) and Assessment of Soil Loss in Sandur Taluk due to Mining Activity in and Around Bellary District, South India

The catchment boundary of Sandur Taluk covers an area about 1254.02 sq km. It is well known for repository of Iron and manganese ore mineralization, more than hundred mining companies were operated within the Sandur Taluk and majority of hillocks have undergone by mining activity. The Sandur Taluk is affected by excavation of Iron ore. An attempt is made to Environmental Impact Assessment (EIA) by attributing various parameters like Land Use Land cover, Soil, Geomorphology, and catchment boundary etc., The erosion is a natural geomorphic process occurring continually over the earth’s surface and it largely depends on topography, vegetation, soil and climatic variables and, therefore, exhibits pronounced spatial variability due to catchments heterogeneity and climatic variation. This problem can be circumvented by discrediting the catchments into approximately homogeneous sub-areas using Geographic Information System (GIS). Soil erosion assessment modeling was carried out based on the Revised Universal Soil Loss Equation (RUSLE). A set of factors are involved in RUSLE equation are A = Average annual soil loss (mt/ha/year), R = Rainfall erosivity factor (mt/ha/year), k = Soil erodibility factor, LS = Slope length factor, C = Crop cover management factor, P = Supporting conservation practice factor. These factors extracted from different surface features by analysis and brought in to raster format. The output depicts the amount of sediment rate from a particular grid in spatial domain and the pixel value of the outlet grid indicates the sediment yield at the outlet of the watershed.

ESTIMATIVA DA VULNERABILIDADE DOS SOLOS À EROSÃO HÍDRICA NA BACIA HIDROGRÁFICA DO RIO CERVO – MG

Objetivou-se no presente trabalho estimar a distribuição espacial do potencial anual médio de perda de solos na bacia hidrográfica do Rio Cervo, MG, a fim de identificar as áreas mais susceptíveis à erosão hídrica e subsidiar possíveis alterações na gestão dos recursos naturais. Para isso foi aplicado o modelo RUSLE (Revised Universal Soil Loss Equation) implementado em um ambiente SIG. Os fatores utilizados pelo modelo foram gerados em formato raster e combinados por meio de álgebra de mapas. O fator de erosividade da chuva (R) foi obtido com base em um modelo geográfico multivariado desenvolvido para o Sudeste do Brasil; o fator de cobertura e manejo do solo (C), foi derivado do mapa de uso do solo confeccionado a partir de imagens Rapideye referentes ao ano de 2015; o fator erodibilidade do solo (K), foi obtido pelo mapa de solos, e o fator topográfico (LS), pelo MDE (Modelo digital de elevação). Os resultados mostraram que 40,59% dos solos da bacia hidrográfica apresentam perdas superiores a 10 t ha-1 ano-1, com predomínio da classe de vulnerabilidade “muito alta”; e 41% da área total apresenta perda de solo superior à taxa tolerável. A partir distribuição espacial das nascentes, verificou-se que 35,6% dessas estão localizadas em áreas que apresentam perdas de solo superiores a 15 t ha-1 ano-1, este resultado é decorrente do predomínio de solo exposto, pastagem e agricultura combinado a regiões de Neossolo Litólico. Desta forma, verificou-se a necessidade de implementar práticas de manejo da cobertura e conservação do solo a fim de reduzir a vulnerabilidade à erosão hídrica na bacia hidrográfica do Rio Cervo.

Tillage management impacts on soil compaction, erosion and crop yield in Stagnosols (Croatia)

The sustainability of agroecosystems is closely related to successful soil conservation. Sustainable land use practices are crucial to reduce the impacts of agriculture on land degradation and maintain long-term soil productivity. In this context, is important to avoid practices that deteriorate the soil (e.g. soil erosion), and find the most suitable to maintain soil and crops productivity. The objective of this work is to compare the impact of different tillage systems on soil compaction, erosion and crop production on clay loam Stagnosols in Croatia. Three tillage treatments were studied: conventional tillage (CT), no-tillage (NT) and deep tillage (DT). Soil water content, bulk density and penetration resistance were determined in the 0–10, 10–20, 20–30 and 30–40cm soil depths. Soil erosion was measured during rainfall events. The results showed that tillage treatments influenced the soil physical parameters, soil loss and crop yields. During first four years of study NT increased (p<0.05) bulk density in the 0–10cm depth by an average of 8% and 7% in relation to CT and DT. Conventional tillage treatment increased (p<0.05) bulk density in the 30–40cm depth by an average of 6% and 5% in relation to NT and DT. No-tillage treatment had a significantly higher penetration resistance (PR) comparing to CT and DT in 2012 and 2014. During the flowering time of 2013, PR was significantly higher in NT at 20–30cm depth than in the other treatments. This was observed also in 2014 at 20–30 and 30–40cm depth. Average annual soil loss under NT (0.53tha−1year−1) and DT (3.11tha−1year−1) were significantly lower than that under CT (13.11tha−1year−1). No-tillage had lower crop grain yields compared to CT and DT, but higher yields in dry years, as consequence of the high capacity for water retention. We recommended DT treatment for investigation at the field scale to assess its suitability for wider application on clay loam soils on sloped areas.

An integrated approach for management of agricultural non-point pollution sources in the Czech Republic

We report a new, integrated approach to the identification and localization of potential critical areas of non-point agricultural water pollution in the Czech Republic. The methodology is presented in model catchments of IV. order, namely the Hrejkovický and Bilinský brooks in the water reservoir Orlik watershed. The risk rate of non-point source pollution is evaluated with the help of GIS tools, integrating the assessment of geomorphology, land use and soil conditions within a territory in conjunction with the agricultural tile drainage systems. Besides the areas prone to erosion and ‘direct protection localities’ along water courses, spots with increased potential of nutrient leaching into groundwater and drainage water are delineated, based on a synthetic map of shallow groundwater vulnerability. These spots are classified using analysis of the Valuated Soil Ecological Units (VSEU) code, while agricultural drainage systems are identified according to the documents of the former Agricultural Water Management Authority of the Czech Republic. Results from geographical analysis show differences between intrinsic parameters of model catchments, which influence the vulnerability potential towards diverse types of non point pollution. The potential pollution thread of surface and groundwater by leaching is relatively high in both catchments, in the Bilinský brook catchment due to prevailing arable land on first and second vulnerability classes within the tile drainage subcatchments and in the Hrejkovický brook catchment due to dense occurence of first and second vulnerable clasess in the catchment area, though comprised from a third by grassland. Water erosion potential jeopardy is bigger within the Bilinský brook catchment with 10% of arable land having the average soil loss 4–10 t ha−1 y−1, contrary to 2% within the Hrejkovický brook catchment. Presented approach can help in prioritizing protective measures and management strategies in a catchment to curtail the negative impacts of non point agricultural pollution in water bodies and in the whole environment.

Effects of shrub on runoff and soil loss at loess slopes under simulated rainfall

Improved understanding of the effect of shrub cover on soil erosion process will provide valuable information for soil and water conservation programs. Laboratory rainfall simulations were conducted to determine the effects of shrubs on runoff and soil erosion and to ascertain the relationship between the rate of soil loss and the runoff hydrodynamic characteristics. In these simulations a 20° slope was subjected to rainfall intensities of 45, 87, and 127 mm/h. The average runoff rates ranged from 0.51 to 1.26 mm/min for bare soil plots and 0.15 to 0.96 mm/min for shrub plots. Average soil loss rates varied from 44.19 to 114.61 g/(min·m2) for bare soil plots and from 5.61 to 84.58 g/(min·m2) for shrub plots. There was a positive correlation between runoff and soil loss for the bare soil plots, and soil loss increased with increased runoff for shrub plots only when rainfall intensity is 127 mm/h. Runoff and soil erosion processes were strongly influenced by soil surface conditions because of the formation of erosion pits and rills. The unit stream power was the optimal hydrodynamic parameter to characterize the soil erosion mechanisms. The soil loss rate increased linearly with the unit stream power on both shrub and bare soil plots. Critical unit stream power values were 0.004 m/s for bare soil plots and 0.017 m/s for shrub plots.

Runoff and soil erosion of field plots in a subtropical mountainous region of China

Anthropogenic pressure coupled with strong precipitation events and a mountainous landscape have led to serious soil erosion and associated problems in the subtropical climate zone of China. This study analyzes 1576 rainfall-runoff-soil loss events at 36 experimental plots (a total of 148 plot-years of data) under a wide range of conditions in subtropical mountainous areas of China where slope farming is commonly practiced. The plots, which have standardized dimensions, represent five common types of land use and have four different slopes. Event-based analyses show that almost half of the total rainfall caused soil erosion in the study area. The dominant factor controlling the runoff coefficient is the slope gradient rather than the land use type. The maximum soil lossfor crop plots under steep tillage (35°) is 5004tkm−2 for a single event. Among the common local crops, the average soil loss values increase in the following order: buckwheat<mung bean<sesame. Among the most widespread grasses, orchards and crops, the soil loss increase in the following order: red clover<nectarine<orange<maize. A large proportion of the soil loss is caused by a small number of extreme events. The annual average soil loss of the 44 plots ranges from 19 to 4090tkm−2year−1. The annual soil loss of plots of different land use types decrease in the following order: bare land (1533tkm−2year−1)>cropland (1179tkm−2year−1)>terraced cropland (1083tkm−2year−1)>orchard land (1020tkm−2year−1)>grassland (762tkm−2year−1)>terraced orchard land (297tkm−2year−1)>forest and grassland (281tkm−2year−1).

Assessing soil erosion using USLE model and MODIS data in the Guangdong, China

In this study, soil erosion in the Guangdong, China during 2012 was quantitatively assessed using Universal Soil Loss Equation (USLE). The parameters of the model were calculated using GIS and MODIS data. The spatial distribution of the average annual soil loss on grid basis was mapped. The estimated average annual soil erosion in Guangdong in 2012 is about 2294.47t/ (km2.a). Four high sensitive area of soil erosion in Guangdong in 2012 was found. The key factors of these four high sensitive areas of soil erosion were significantly contributed to the land cover types, rainfall and Economic development and human activities.

Soil Erosion Evaluation and Mapping Based on Geomatic Techniques in Wadi El Malleh Watershed

Soil erosion by water considered is serious problem in the Mediterranean region due to the climate aggressiviness of the mountainous terrain, the traditional farming practices and other anthropogenic pressure on its land and soil. The present study was scheduled to use Geographical Information System (GIS), Remote Sensing data and the Revised Universal Soil Loss Equation (RUSLE) model to evaluate the annual average soil loss and sedimentation rate from Wadi El Malleh watershed, which is located in the Northern-Fez (Morocco), and covers an area of 34 km2 . In fact, RUSLE and SEDIMENTATION models were combined with GIS techniques to predict the spatiotemporal distribution of soil erosion and deposition under different land uses. The land use was assessed using the Google Earth image, which was taken in 2013. The image was first geo-referenced and projected into Moroccan coordinates system and classified by ArcGIS software. The use of RUSLE model allowed the estimation of static soil loss. Then the results of RUSLE were applied in the deposition modelling calculations to assess the spread of soil loss downstream by SEDIMENTATION model. The values of the annual net soil erosion obtained by this study were (81.86 t/ha/y) in bad land, (-19.19 t/ha/y) in irrigated agriculture areas and (-13.66 t/ha/y) in reforestation land where the negative values indicated deposition.

Assessment of soil erosion in a tropical mountain river basin of the southern Western Ghats, India using RUSLE and GIS

Revised Universal Soil Loss Equation (RUSLE) model coupled with transport limited sediment delivery (TLSD) function was used to predict the longtime average annual soil loss, and to identify the critical erosion-/deposition-prone areas in a tropical mountain river basin, viz., Muthirapuzha River Basin (MRB; area = 271.75 km2), in the southern Western Ghats, India. Mean gross soil erosion in MRB is 14.36 t ha−1 yr−1, whereas mean net soil erosion (i.e., gross erosion–deposition) is only 3.60 t ha−1 yr−1 (i.e., roughly 25% of the gross erosion). Majority of the basin area (∼86%) experiences only slight erosion (<5 t ha−1 yr−1), and nearly 3% of the area functions as depositional environment for the eroded sediments (e.g., the terraces of stream reaches, the gentle plains as well as the foot slopes of the plateau scarps and the terrain with concordant summits). Although mean gross soil erosion rates in the natural vegetation belts are relatively higher, compared to agriculture, settlement/built-up areas and tea plantation, the sediment transport efficiency in agricultural areas and tea plantation is significantly high, reflecting the role of human activities on accelerated soil erosion. In MRB, on a mean basis, 0.42 t of soil organic carbon (SOC) content is being eroded per hectare annually, and SOC loss from the 4th order sub-basins shows considerable differences, mainly due to the spatial variability in the gross soil erosion rates among the sub-basins. The quantitative results, on soil erosion and deposition, modelled using RUSLE and TLSD, are expected to be beneficial while formulating comprehensive land management strategies for reducing the extent of soil degradation in tropical mountain river basins.

Modelling spatially distributed soil losses and sediment yield in the upper Grande River Basin - Brazil

Water erosion negatively affects soil fertility, soil structure, and water availability to plants. Moreover, off-site erosion effects contribute to the sedimentation and eutrophication of water courses. The Grande River is one of the main tributaries of the Paraná River, and an important source of hydroelectric power in Brazil. The Upper Grande River Basin covers an area of 15,705km2, mostly occupied by rangelands. Shallow and little permeable Cambisols are the predominant soil class in the basin, which, combined with the intensive and highly concentrated summer rainfall, characterize an erosion-prone scenario. The aim of this study was to model the soil losses and the sediment yield in the Upper Grande River Basin. It also sought to quantify the sediment delivery to the two main hydroelectric power plant reservoirs in the basin: Camargos/Itutinga and Funil. Geographical Information Systems (GIS) were used to apply the Revised Universal Soil Loss Equation (RUSLE) and the Sediment Delivery Distributed model (SEDD) in the study area. The models were calibrated using sediment transport data obtained from a river gauging station located in a subwatershed. RUSLE predictions estimated that the average soil losses in the Upper Grande River Basin were of 22.35tha−1yr−1, and that bare soils, eucalypt and agriculture suffered the highest erosion rates among the identified land use classes. The average specific sediment yield in the basin was of 1.93tha−1yr−1. According to the model calibration, the specific sediment yield predictions showed an error of 0.01tha−1yr−1, or 0.6%. Agriculture and eucalypt forests, which compose approximately 10% of the study area, contribute to more than 40% of the sediment yield in the basin. The model predictions estimated that 1.45milliontyr−1 of sediments are delivered to the Camargos/Itutinga power plant reservoir, whereas the Funil power plant reservoir receives a sediment input of 1.68milliontyr−1. Although model calibration yielded small errors in relation to the observed sediment measurements, the relative lack of available data has impaired a more thorough validation of the employed models. Nevertheless, the results indicate that the RUSLE/SEDD approach may be useful for analyzing sediment transport in Brazilian watersheds, where limited input data is available.

Application of RUSLE model for soil loss estimation of Jaipanda watershed, West Bengal

Soil erosion is a major environmental problem due to both natural and anthropogenic factors and continuous erosion leads to land degradation. In the present study, soil loss in Jaipanda watershed of West Bengal, India is estimated employing revised universal soil loss equation (RUSLE) model and adopting integrated analysis in GIS. The factors used in RUSLE are namely the rainfall and runoff erosivity factor (R), soil erodibility factor (K), slope length and steepness factor (LS), cover and management factor (C) and support practice factor related to slope direction (P). These factors were computed from different data which have been obtained from meteorological station, soil maps, topographic maps, digital elevation model and satellite image. The five RUSLE factors were represented by raster layers in a GIS framework and then multiplied together to estimate the soil erosion rate in the study area. The study provided a reliable prediction of soil erosion rates and erosion potential zones within the watershed. The average soil loss amount for this watershed is about 0.59 tons/ha/year.

Mapping soil erosion hotspots and assessing the potential impacts of land management practices in the highlands of Ethiopia

An enormous effort is underway in Ethiopia to address soil erosion and restore overall land productivity. Modelling and participatory approaches can be used to delineate erosion hotspots, plan site- and context-specific interventions and assess their impacts. In this study, we employed a modelling interface developed based on the Revised Universal Soil Loss Equation adjusted by the sediment delivery ratio to map the spatial distribution of net soil loss and identify priority areas of intervention. Using the modelling interface, we also simulated the potential impacts of different soil and water conservation measures in reducing net soil loss. Model predictions showed that net soil loss in the study area ranges between 0.4 and 88tha−1yr−1 with an average of 12tha−1yr−1. The dominant soil erosion hotspots were associated with steep slopes, gullies, communal grazing and cultivated areas. The average soil loss observed in this study is higher than the tolerable soil loss rate estimated for the highland of Ethiopia. The scenario analysis results showed that targeting hotspot areas where soil loss exceeds 10tha−1yr−1 could reduce net soil loss to the tolerable limit (<2tha−1yr−1). The spatial distribution of soil loss and the sediment yield reduction potential of different options provided essential information to guide prioritization and targeting. In addition, the results can help promoting awareness within the local community of the severity of the soil erosion problem and the potential of management interventions. Future work should include cost-benefit and tradeoff analyses of the various management options for achieving a given level of erosion reduction.

A comparison of the abilities of the USLE-M, RUSLE2 and WEPP to model event erosion from bare fallow areas

Traditionally, the Universal Soil Loss Equation (USLE) and the revised version of it (RUSLE) have been applied to predicting the long term average soil loss produced by rainfall erosion in many parts of the world. Overtime, it has been recognized that there is a need to predict soil losses over shorter time scales and this has led to the development of WEPP and RUSLE2 which can be used to predict soil losses generated by individual rainfall events. Data currently exists that enables the RUSLE2, WEPP and the USLE-M to estimate historic soil losses from bare fallow runoff and soil loss plots recorded in the USLE database. Comparisons of the abilities of the USLE-M and RUSLE2 to estimate event soil losses from bare fallow were undertaken under circumstances where both models produced the same total soil loss as observed for sets of erosion events on 4 different plots at 4 different locations. Likewise, comparisons of the abilities of the USLE-M and WEPP to model event soil loss from bare fallow were undertaken for sets of erosion events on 4 plots at 4 different locations. Despite being calibrated specifically for each plot, WEPP produced the worst estimates of event soil loss for all the 4 plots. Generally, the USLE-M using measured runoff to calculate the product of the runoff ratio, storm kinetic energy and the maximum 30-minute rainfall intensity produced the best estimates. As to be expected, ability of the USLE-M to estimate event soil loss was reduced when runoff predicted by either RUSLE2 or WEPP was used. Despite this, the USLE-M using runoff predicted by WEPP estimated event soil loss better than WEPP. RUSLE2 also outperformed WEPP.