Average Annual Soil Loss Rate Research Articles

Soil erosion assessment using SWAT, in relation withLand use, agricultural practices, and future climate change in a semi-arid catchment in Tunisia

Abstract Soil erosion is a severe environmental concern arising from intensive agricultural uses, land degradation, and anthropogenic activities. This problem threatens agricultural productivity and sustainable development, particularly in emerging countries. Therefore, evaluating soil erosion is essential in conservation, planning, and management on a watershed or basin scale. This study aims to assess the erosion of soil loss in the El Gouazine Watershed, central Tunisia, using the Soil and water assessment tool (SWAT). We define the impact of soil and water conservation management implementation combined with climate change scenario. We identified the spatial distribution of erosion rates based on soil properties, topography, and land use. The observed specific erosion rate of the watershed is estimated at 1.6 t.ha−1.yr−1, whereas according to the SWAT model, the average soil loss rate is 1.4 t.ha−1.yr−1. Furthermore, the obtained results highlight importance of the slope factor in affecting the severity of the soil loss rates in the El Gouazine watershed. It was also demonstrated that it’s urgent to prioritize other measures such as contour cropping or conservation agriculture, to enhance and strengthen the soils’ resistance against the detachment due to discharge water. In this context, this research found that these techniques decrease considerably the soil loss by 22% for the strip cropping, 33% for the No-tillage, and 72% for the bench terracing. Moreover, these farming techniques, contribute at the same time to the amelioration of the water balance by reducing the evapotranspiration and enhancing the soil water storage. To go further in this study a soil erosion forecast using the worst-case scenario for climate change RCP 8.5 was conducted. an overview of the future soil erosion patterns is obtained. We noticed then a decrease of the average annual soil loss rate until 2050 and then a prominent increase from 2051 to 2100.

Assessment of soil erosion and prioritization of conservation and restoration measures using RUSLE and Geospatial techniques: the case of upper Bilate watershed

Soil erosion is still a vector of environmental and economic concern affecting most parts of the world, especially in Sub-Saharan African countries. Nevertheless, recent human activities in the hills, coupled with poor conservation measures and practices, could have amplified the rate at which soil is lost in the southwestern highlands of Ethiopia. This study focuses on quantifying and prioritizing micro-watersheds that require conservation actions by piloting spatial modeling of soil loss in the upper Bilate watershed. Sentinel image, soil, DEM, rainfall, and support practice data were used. A Revised Universal Soil Loss Equation (RUSLE) using GIS and satellite images was applied. The estimated average annual soil loss rate was demonstrated to be 24.1 t ha−1yr−1 and varied between 0.05 and 498.24 t ha−1yr−1. About 51.2% of the total revealed has a high soil truncation trait, of which 40% of the cropland has exceeded the soil loss tolerances of Ethiopia and tropical regions. The most affected micro-watersheds are MWS 16, 8, 6, and 3, which contributed 39.4% of the average annual loss rate, indicating the hotspots of soil loss problems in the region. This will have far-reaching off-site impacts on food security, soil productivity, human lives, infrastructures, and ecosystem service provisions.

Anticipating Soil Erosivity of Kulfo Watershed in the Southern Main Ethiopian Rift in Response to Changes in Land Use and Land Cover

This study evaluates the land use and land cover (LULC) dynamics that play an indispensable role in the degradation and deterioration of soil and water quality affecting the natural resources throughout the Kulfo watershed in Ethiopia. Directed image classification is initiated for satellite images to study the watershed. The image classification is categorized into ten different LULC classes with validation of ground control points. A Revised Universal Soil Loss Equation (RUSLE) model was used to generate the average soil loss of the watershed. The model involves the Rainfall Erosivity factor (R), Soil Erodibility factor (K), Length and Slope factor (LS), Cover Management factor (C), and Support Practice factor (P). The dynamics of LULC change and rainfall erosivity over the past 30 years have been interpreted using maps from 1990, 2005, and 2020 using the C-factor and R-factor. The remaining factors, like K-factor, LS-factor, and P-factor, were kept constant over the period. The results reveal that the average annual soil loss rate (A) of the watershed is estimated to be 138.8 t ha-1, 161.2 t ha-1, and 173.25 t ha-1 per year, for the selected period intervals. During the past three decades, the soil loss rate in the watershed has increased by 34.4 t ha-1 per year. The watershed and sustainable soil and water conservation practices need special attention to mitigate the severity of soil erosion risks to avoid disaster.

Assessment of soil erosion hazard and its relation to land use land cover changes: Case study from alage watershed, central Rift Valley of Ethiopia

Soil erosion by water and wind is among the most crucial land degradation processes in Ethiopia. This is also the case for Alage watershed located in the cental Rift Valley system. This study aimed at assessment of soil erosion hazard and its relation to land use land cover change in the watershed during the period from 1984 to 2016 for a better land management. The study is based on application of Remote Sensing (RS) and Geographical Information System (GIS) to extract inputs factor values for the Revised Universal Soil Loss Equation (RUSLE). Time-series satellite imageries of Landsat TM 1984, ETM+ 2000 and OLI 2016 were used for land use land cover change detection and determination of cover management (C) factor of the RUSLE. Biophysical data such as rainfall, soil properties, land management practices including soil and water conservation measures within the watershed were collected using field survey and secondary data sources. Slope steepness and slope length factors were derived using Digital Elevaition Model (DEM). Long-term average annual soil loss rates were estimated by the RUSLE integrated with GIS for 1984, 2000 and 2016. Using satellite imageries, the land use land cover and changes within the watershed during the three periods were obtained through a supervised classification with maximum likelihood algorithim. The results of land use land cover change indicated that the proportion of rain-fed cropland, bare land and built up areas increased by 17.4%, 5.9% and 2.9% respectively over the three study period. In contrast the proportion of bush/shrub land, irrigated cropland, grass land, forested areas and waterbodies decresaed by 15.5%, 4.7%, 3.4%, 2.3% and 0.3% respectively during the same period. Estimated average annual soil loss rates showed an increasing trend from 24.3 ton ha−1 yr−1 in 1984 to 38 ton ha−1 yr−1 in 2016. Increasing trends of average annual soil loss rate is attributed to increased proportion of cropland, bare land and built up areas during those periods leading to decreased protective vegetation cover. Hotspot areas within the watershed require implementation of land management practices to prevent further degradation and expansion of gullies. This study is relevant to demonstrate environmental implication of land use land cover change for future land management practices and land use policy in the Rift Valley of central Ethiopia.

GIS based soil loss assessment using RUSLE model: A case of Horo district, western Ethiopia

Land degradation in the form of soil erosion is a worldwide challenge and make environmental problem that affects crop yields, makes livelihoods difficult, and creates crises. The main objective of this study was to measure soil loss using the Revised Universal Soil Loss Equation (RUSLE) Model in Horo district, Western Ethiopia. RUSLE with a Geographical Information System (GIS) was used to quantify soil loss using rainfall, soil, a digital elevation model (DEM), and satellite image datasets as factor value inputs. Those factors are erosivity (R), erodibility (K), topography (LS), cover management (C), and conservation support practice (P) layer values that can be interactively used using weighted overlay in ArcGIS 10.8. The result shows that the maximum and minimum potential annual soil loss of the study area ranged from nil (0.01 t/ha/yr) on plain surfaces to 216.01 t/ha/yr. The average annual soil loss rate in the study area was 13.27 t ha/yr. The highest mean annual soil loss of 216.01 t/ha/yr were observed from farmland and it was the largest portion of the study area, which covered about 64243.02 ha and represented about 73.75% of the total. As a result, forest land (16383.23 ha) was the second-largest, accounting for 18.81% of the total area. Consequently, the study revealed that the farmland was more vulnerable to erosion than other land uses and land cover types. Hence, information on average annual soil loss is important for selecting appropriate conservation measures to reduce on-site soil loss and its off-site effects. Therefore, farmers and other expected bodies should have focused on soil conservation and management practices at the highest soil loss severity classes, which must get priority for conservation by stakeholders, agents, and the government.

Assessing the effectiveness of community-based watershed management practices in reversing land degradation in the Finchwuha watershed, Gojjam, Ethiopia

ABSTRACT Land degradation is an evident and severe environmental problem in Ethiopia. Since 2003 community-based watershed management has been implemented in the study area to reduce land degradation. This study aimed to investigate to what extent the community-based watershed management is effective in rehabilitating the land. Woody vegetative cover, land use/cover (LULC) change and soil erosion rate were selected variables to examine the effectiveness of the management measures. The LULC and woody vegetative cover spatial datasets were created from Landsat satellite images of 2003 and 2019 using ERDAS IMAGINE 2016® and ArcGIS10.8®. The soil loss rate was modelled using geoinformation techniques combined with the Revised Universal Soil Loss Equation. To assess the perception of farmers involved in the watershed rehabilitation activities, qualitative data were collected through Focus Group Discussions and Key Informant interviews. The results showed that the average annual soil loss rate in the study area was 49.5 tonnes (t)/hectare (ha−1)/year(y−1) in 2003 and 23.8 t ha−1y−1 in 2019, which is a 52% decrease over 16 years. Woody vegetative cover and grassland increased by 11% and 103%, respectively. These figures and respondents’ responses, Focus Group Discussants and Key Informants showed that the community-based watershed management measures implemented in the study area were effective for improving vegetation cover and reducing soil loss (reducing land degradation). The sustainability of these achievements is contingent on the availability of a robust local organizational set-up complemented by the provision of natural resources development technologies, capacity building and security of land tenure. In sum, the findings in the study lead to conclude that the active involvement of farmers in land management and security of land tenure are effective approaches to reverse land degradation in the highlands of Ethiopia.

Multi-fractal characteristics of reconstructed landform and its relationship with soil erosion at a large opencast coal-mine in the loess area of China

Post-mining dumps are typical artificial landforms, with original natural features of soil, topography and vegetation radically altered, and soil and water conservation capacity declined accordingly. In this study, the geomorphic characteristics and soil erosion of reconstructed landforms and their relationships in opencast coal mines are studied. The elevation relief features were described using multi-fractal methods, soil erosion rates were evaluated utilizing the revised universal soil loss equation (RUSLE), and the correlations between geomorphic multi-fractal parameters and soil erosion rate were analyzed within a study area of three soil dumps in the Shanxi Pingshuo Antaibao opencast coal-mine of China. The results show that reconstructed landform in opencast coal mines have multi-fractal characteristics. Generalized dimensions (D0, D1, ΔD and D1/D0) and singularity spectra (α0, Δα and Δf) quantify reconstructed geomorphic features. Soil erosion in the sub-areas is slight, indicating that reclamation measures have alleviated soil erosion exacerbated by mining. Geomorphic multi-fractal parameters reflect the differences of soil erosion rate, the increasing trend of D0, D1 and α0 are consistent with that of average annual soil loss rate. It is feasible to apply these parameters to reflect soil erosion of reconstructed landforms. This study provides a new perspective for portraying the reconstructed geomorphic features and soil erosion on opencast coal-mine dumps.

Assessment of soil erosion rate and hotspot areas using RUSLE and multi-criteria evaluation technique at Jedeb watershed, Upper Blue Nile, Amhara Region, Ethiopia

Soil erosion is a difficult forceful practice by which useful surface soil is removed, conveyed, and stored at a detached place causing the exposure of subsurface soil and siltation in reservoirs and natural streams. It also degraded different agricultural areas at different rates and different locations as well as created gulleys, but these degraded areas, degradation rates, and gulley locations were not well identified and quantified. Therefore; the core objective of this study is to evaluate soil erosion rate and to identify soil erosion hotspot areas as well as to identify gulley locations using Revised Universal Soil Loss Equation (RUSLE), Multi-criteria Evaluation Analysis Techniques, and Geographic Information System (GIS). Land Use/Land Cover (LU/LC) map, slope map, rainfall map, and Digital Elevation Model (DEM) were the necessary inputs used for this study. The results of this study indicated that the potential annual soil loss of the watershed ranged from 0.0 to 706.7 tons per hectare per year with an average annual soil loss rate of 27.7 tons per hectare per year. From the total area of the watershed (859.2 km2), the potential area for gully expansion is 63km2. The overall analysis indicated that 4.8% of the total watershed is highly sensitive; 54.24% is moderately sensitive; 17.69% is marginally sensitive while, 23.28% is currently not sensitive and the remaining 0.06% is a /constraint to erosion. Hence, the Areas which were categorized under highly and moderately sensitive classes needed direct mediation for better conservation planning. It is concluded that Gulley, LU/LC, Topographical wetness index, and soil types are factors that enable soil erosion from high to low, respectively. It is recommended that the concerned bodies should have to take care of the area from further soil erosion through creating awareness among the society about the sustainable use of natural resources and conservation methods.

Assessment of Soil Loss Rates in Asreh Watershed (North Jordan Badia) Using RUSLE and GIS

In arid lands, rainwater harvesting can play an important role in making more water available since most of the rainfall runoff evaporates. If rainwater can be collected, it will form a useful resource. Jordan is classified as one of the poorest countries regarding water resources with an arid and semi-arid climate. For these limited and vital sources of water, good estimation of rainfall runoff quantity and quality can enhance the sustainability of water harvesting projects. The hydrologic estimations of runoff quantities and qualities are essential, and several techniques to achieve that exist. Revised Universal Soil Loss Equation (RUSLE) is one of the widely used techniques to assess the soil erosion due to runoff, by assessing other physical factors that affect the soil loss. RUSLE combined five parameters to identify the soil loss rate: rainfall erosivity, topographic, soil erodibility, vegetation cover and management, and land management. Based on RUSLE results, areas are classified as a highly soil loss rate if the annual rates exceeded 20 tons per hectare. The Asreh watershed is a 196 km2 area that is mostly wasted land and receives an annual rainfall between 50 and 300 mm per year. The RUSLE equation inputs parameters for the study area are found and the equation is applied for the watershed. Results of RUSLE application on the Asreh watershed showed that the average annual soil loss rate is about 7.8 tons per hectare, about 73% of the area are classified as low soil loss rate with less than 10 tons per hectare per year, and only 13% of the area is classified as a high soil loss rate of more than 20 tons per hectare per year.

Assessment of Current and Future Climate Change Impact on Soil Loss Rate of Agewmariam Watershed, Northern Ethiopia

Soil erosion is 1 of the most important environmental problems that pose serious challenges to food security and the future development prospects of Ethiopia. Climate change influences soil erosion and is critical for the planning and management of soil and water resources. This study aimed to assess the current and future climate change impact on soil loss rate for the near future (2011-2040), middle future (2041-2070), and far future (2071-2100) periods relative to the reference period (1989-2018) in the Agewmariam watershed, Northern Ethiopia. The 20 models of Coupled Model Intercomparison Project phase 5 global climate models (GCMs) under Representative Concentration Pathway (RCP) 4.5 (intermediate scenario) and 8.5 (high emissions scenario) scenarios were used for climate projection. The statistical bias correction method was used to downscale GCMs. Universal Soil Loss Equation integrated with geographic information system was used to estimate soil loss. The results showed that the current average annual soil loss rate and the annual total soil loss on the study area were found to be 25 t ha−1 year−1 and 51 403.13 tons, respectively. The soil loss has increased by 3.0%, 4.7%, and 5.2% under RCP 4.5 scenarios and 6.0%, 9.52%, and 14.32% under RCP 8.5 scenarios in the 2020s, 2050s, and 2080s, respectively, from the current soil loss rate. Thus, the soil loss rate is expected to increase on all future periods (the 2020s, 2050s, and 2080s) under both scenarios (RCP 4.5 and RCP 8.5) due to the higher erosive power of the future intense rainfall. Thus, climate change will exacerbate the existing soil erosion problem and would need for vigorous new conservation policies and investments to mitigate the negative impacts of climate change on soil loss.

Soil erosion assessment in a semi-arid environment: a case study from the Argana Corridor, Morocco

Soil erosion is a widespread problem that continues to expand in magnitude and scope due to ever-changing anthropogenic and climatic conditions. The High Atlas Mountains in Morocco are a typical case where this problem affects the ecological and socioeconomic activities of the region. The main objective of this study is to provide an erosion risk analysis of the Argana Corridor in the High Atlas of Morocco using GIS, Remote Sensing and the Revised Universal Soil Loss Equation (RUSLE). The erosion assessment is based on various controlling factors including climate, topography, vegetation cover, soil erodibility and soil conservation practices. Findings indicate that the study area is subjected to significant erosion, reaching an average annual soil loss rate of 47.52 t/ha/year, and an annual erosion amount of 5,233,840 tons. Collectively, the methodology and results provide a decision support system for stakeholders in the region, and a framework for studies in data-scarce regions.

Evaluation of potential sites for soil erosion risk in and around Yamuna River flood plain using RUSLE

In general, agricultural intensification and human intervention lead to the soil erosion problem. Remarkably, marginal alluvial plains of vast Indo-Gangetic plain consistently suffer a great peril of land degradation in and around the Yamuna-Chambal valley. This is probably due to the geologic evolution of the landscape. Geomorphology and the land forms developed in and around the studied countryside themselves indicate the erosional processes. However, quantification of erosion rates and mapping of most intense erosion areas in and around Agra, Firozabad and Etawah district of Uttar Pradesh have been carried out using geospatial technology. A Geographic Information System (GIS)-based Revised Universal Soil Loss Equation (RUSLE) model was used to analyse grid cell–based erosion rates by incorporating all the crucial factors, i.e. rainfall, slope, soil, length slope, cover management and practice management factors. An average annual soil loss rate of 445 t ha−1 year−1 was observed in the study area. Moreover, the intensity-based categorization reveals that 64% area is at high erosion risk. The Google Earth imagery along with Triangular Irregular Network (TIN) model presents the erosion-associated features and slope gradient of the Yamuna River watershed further validates the results obtained in the present study.

English

Soil erosion is the most challenging and continuous environmental problems resulting in both on-site and off-site effects in the world particularly in Ethiopia. Karesa watershed is one of the most erosion-prone watersheds which received little soil conservation attention. This study was conducted to estimate average annual soil loss rate using Geographic Information System and Universal Soil Loss Equation Model adapted to Ethiopian condition. The following datasets were obtained from different sources for estimating annual soil loss such as 15 years mean annual rainfall data for estimating erosivity factor, digital soil map for estimating soil erodibility factor, 30 m × 30 m resolution Digital Elevation Model for estimating slope length and slope steepness (LS) factor, Landsat6ETM+ images with 30 m × 30 m resolution for detecting vegetation cover and conservation practice factor. The result reveals that 42,413.72 ton per year soil loss from 9939 ha entire watershed or 4.27 tons per hectare per year average annual soil loss rate was observed. The mean annual soil loss rate was classified into four erosion severity classes as very less, less, moderate and high. The result also implies that 94.4% (9383.07 ha) of the watershed areas contributes 81.13% of the total soil loss which were observed from two slope classes (0-15% and 15-30%) and categorized under very less to less soil loss (0-6.25 tons ha-1yr-1). On the other hand, moderate to high soil loss (6.25-25 tons ha-1yr-1) was obtained on slope classes of >30% which covers 555.93 ha (5.6%) of the watershed areas and contributes 18.82% of the total soil loss indicating the maximum share of slope mainly due to cultivation of marginal land,intensive cultivation, poor vegetation cover during critical rainfall period. Moreover, about 2,184.93 ha of the watershed area requires integrated soil and water conservation measures. Key words: Conservation priority, soil erosion, Universal Soil Loss Equation Model (USLE), geographic information system (GIS), Karesa watershed   &nbsp

D-RUSLE: a dynamic model to estimate potential soil erosion with satellite time series in the Italian Alps

ABSTRACTSoil erosion is addressed as one of the main hydrogeological risks in the European Union. Since the average annual soil loss rate exceeds the annual average formation rate, soil is considered as a non-renewable resource. Besides, human activities, human-induced forces and climate change have further accelerated the erosion processes. Therefore, understanding soil erosion spatial and temporal trends could provide important information for supporting government land-use policies and strategies for its reduction. This paper describes the Dynamic Revised Universal Soil Loss Equation (D-RUSLE) model, a modified version of the well-known RUSLE model. The RUSLE model formulation was modified to include variations in rainfall erosivity and land-cover to provide more accurate estimates of the potential soil erosion in the Italian Alps. Specifically, the modelling of snow occurrence and the inclusion of Earth Observation data allow dynamic estimation of both spatial and temporal land-cover changes. Results obtained in Val Camonica (Italy) show that RUSLE model tends to overestimate erosion rates in Autumn/Winter because not considering snow cover and vegetation dynamics. The assimilation of satellite-derived information in D-RUSLE allows a better representation of soil erosion forcing, thus proving a more accurate erosion estimate for supporting government land-use policies and strategies for reducing this phenomenon.

GIS estimation of annual average soil loss rate from Hangar River watershed using RUSLE

Abstract Currently, soil erosion is the major environmental problem in the Blue Nile, Hangar watershed in particular. This study aimed to estimate the spatially distributed mean annual soil erosion and map the most vulnerable areas in Hangar watershed using the revised universal soil loss equation. In this model, rainfall erosivity (R-factor), soil erodibility (K-factor), slope steepness and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (P-factor) were considered as the influencing factors. Maps of these factors were generated and integrated in ArcGIS and then the annual average soil erosion rate was determined. The result of the analysis showed that the amount of soil loss from the study area ranges from 1 to 500 tha−1 yr−1 with an average annual soil loss rate of 32 tha−1 yr−1. Considering contour ploughing with terracing as a fully developed watershed management, the resulting soil loss rate was reduced from 32 to 19.2 tha−1 yr−1. Hence, applying contour ploughing with terracing effectively reduces the vulnerability of the watershed by 40%. Based on the spatial vulnerability of the watershed, most critical soil erosion areas were situated in the steepest part of the watershed. The result of the study finding is helpful for stakeholders to take appropriate mitigation measures.

Soil erodibility mapping using the RUSLE model to prioritize erosion control in the Wadi Sahouat basin, North-West of Algeria.

Soil losses must be quantified over watersheds in order to set up protection measures against erosion. The main objective of this paper is to quantify and to map soil losses in the Wadi Sahouat basin (2140km2) in the north-west of Algeria, using the Revised Universal Soil Loss Equation (RUSLE) model assisted by a Geographic Information System (GIS) and remote sensing. The Model Builder of the GIS allowed the automation of the different operations for establishing thematic layers of the model parameters: the erosivity factor (R), the erodibility factor (K), the topographic factor (LS), the crop management factor (C), and the conservation support practice factor (P). The average annual soil loss rate in the Wadi Sahouat basin ranges from 0 to 255tha-1year-1, maximum values being observed over steep slopes of more than 25% and between 600 and 1000m elevations. 3.4% of the basin is classified as highly susceptible to erosion, 4.9% with a medium risk, and 91.6% at a low risk. Google Earth reveals a clear conformity with the degree of zones to erosion sensitivity. Based on the soil loss map, 32 sub-basins were classified into three categories by priority of intervention: high, moderate, and low. This priority is available to sustain a management plan against sediment filling of the Ouizert dam at the basin outlet. The method enhancing the RUSLE model and confrontation with Google Earth can be easily adapted to other watersheds.

GIS-RUSLE Interphase Modelling of Soil Erosion Hazard and Estimation of Sediment Yield for River Nzoia Basin in Kenya

River Nzoia basin is predisposed to degradation attributed to poor anthropogenic land use practices, soil erosion and sedimentation. The objective of this study was to model soil erosion hazard and estimate sediment yield for river Nzoia basin. Database of the basin comprised of 90 m DEM, LandSat imagery, rainfall, and soil data. Simulated RUSLE model factors (R, K, LS, and C) were multiplied using the raster calculator in ArcGIS 10.1. This generated the soil erosion hazard map for river Nzoia basin with an average annual soil loss rate of 0.51 and a maximum of 8.84 Mton ha-1 yr-1. This translates into a mean annual soil loss of 6.579 × 105 Mtonyr-1. Sediment Delivery Ratio (SDR) of 0.121 revealed that 87.9% of the soil eroded by water in the basin is deposited before reaching the basin outlet. Average annual sediment yield estimated was 0.06 Mtonyr-1. Soil erosion modeling results showed that river Nzoia basin is experiencing varying erosion rates spatially. The interplay among the RUSLE factors strongly influence average annual soil loss rates. Areas experiencing high soil loss rates are closely linked to annual cropland, deforested and high elevation points. Low rates of soil loss are attributable to soil conservation practices and protected areas such as game parks. Thus, there is a close coupling between soil loss and land use category in river Nzoia basin. Sustainable land use practices should be embraced to support conservation programmes to mitigate soil erosion, prevent sedimentation and reduce sediment yield in the river channel.

SPECIFICS OF SEDIMENT REDISTRIBUTION WITHIN A SMALL ARABLE CATCHMENT DURING DIFFERENT PERIODS OF ITS CULTIVATION (GRACHEVA LOSCHINA CATCHMENT, THE KURSK REGION)

The paper discusses results of quantitative assessment of sediment redistribution within a small arable catchment during a few different time intervals. Application of several independent methods allowed more reliable determination of individual components of the local sediment budget. The results show that during approximately 130 years of traditional cultivation about 90% of sediment from eroded arable slopes reached the small valley bottom. After introduction of soil conservation measures this value decreased to less than 20%. At the same time, average annual soil loss rate for the entire catchment have decreased by more than 2 times – from 13.9–14.4 t/ha × year to 7.0 t/ha × year.

Estimating Conservation Needs for Rangelands Using USDA National Resources Inventory Assessments

This study presents (1) the overall concept of assessing non-federal western rangeland soil loss rates at a national scale for determining areas of vulnerability for accelerated soil loss using USDA Natural Resources Conserva- tion Service (NRCS) National Resources Inventory (NRI) data and the Rangeland Hydrology and Erosion Model (RHEM) and (2) the evaluation of a risk-based vulnerability approach as an alternative to the conventional average annual soil loss tolerance (T) for assessment of rangeland sustainability. RHEM was used to estimate runoff and soil loss at the hillslope scale for over 10,000 NRCS NRI sample points in 17 western states on non-federal rangelands. The national average annual soil loss rate on non-federal rangeland is estimated to be 1.4 ton ha -1 year -1 . Nationally, 20% of non- federal rangelands generate more than 50% of the average annual soil loss. Over 29.2 × 10 6 ha (18%) of the non-federal rangelands might benefit from treatment to reduce 1559-1570soil loss to below 2.2 ton ha -1 year -1 . National average an- nual soil loss rates combine areas with low and accelerated soil loss. Evaluating data in this manner can misrepresent the magnitude of the soil loss problem on rangelands. Between 23% and 29% of U.S. non-federal rangelands are vulnerable to accelerated soil loss (≥2.2 ton ha -1 event -1 ) if assessed as a function of vulnerability to a runoff event with a return peri- od of ≥25 years. The NRCS has not evaluated potential soil loss risk in national reports in the past, and adaptation of this technique will allow the USDA and its partners to be proactive in preventing accelerated soil loss on rangelands.

Application of Erosion 2D Model for Erosion Studies in Makurdi Metropolis of Benue State, Nigeria

The equations of Erosion 2D Model (a physically based model) were transformed into a computer programme called EROSOFT and used to predict the rate of soil loss in Makurdi metropolis. The model has detachment, transport and deposition components. Four sites were chosen within the metropolis for this study. Soil samples were collected from the sites for laboratory analysis. Rainfall and runoff fluids were collected from the sites to determine their densities. Levelling instrument was used to detremine the channels slopes. The model predicted an average annual soil loss rate of 310kg m-2s-1 for the metropolis. The sensitivity analysis of the model indicates that straight slopes are more prone to soil erosion. The result of the model deviates slightly from established facts that, sandy soils are more erodible and hence prone to be easily detached. Nevertheless, the model shows that soil erosion is influenced by slope geometry and rainfall intensity. The study attributes the major causes of soil erosion in the city to urban runoff concentration and removal of vegetation, and therefore suggests the use of land grading, land forming and cover cropping as well as conservation structures like road side drains for the control of erosion in the metropolis.