Erosion Risk Map Research Articles

Assessment of soil erosion risk using an integrated approach of GIS and Analytic Hierarchy Process (AHP) in Erzurum, Turkiye

Assessing soil erosion hazards and mapping the spatial distribution of soil erosion have an essential role in sustainable forest management. In this study, the potential soil erosion risk was evaluated through the Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS) in the Oltu forest planning unit, Erzurum. Seven erosion-related criteria, including slope, bedrock type, relative relief, drainage density and frequency, rainfall, and land use/land cover (LULC) were used for the present assessment. According to the AHP analysis, the slope was the most influential factor (21%) followed by bedrock type (19%), land cover (17%), and relative relief (14%) in the soil erosion process. The soil erosion risk in the study area was strongly influenced by the LULC where 59.46% is bare land with high erosion risk and 12.07%, with the lowest risk, is in an area with any forest cover. The estimated soil erosion risk was classified into five different classes namely very low, low, moderate, high, and very high. The results showed that this study area is highly prone to soil erosion. The larger proportion of the area (39.16%) is exposed to high to very high erosion, mainly determined by forest cover and geomorphology. To analyze the accuracy of the soil erosion risk map, 40 points were selected randomly in this study area. In these points, predicted values were compared to the real values obtained by Google Earth-colored images. The area under the ROC curve (AUC) method was applied to validate the efficiency of the AHP which showed a satisfactory accuracy of 81.00%. Findings presented that including the more influencing factors with a slope instead of including only the slope contributes to a more accurate erosion risk map. This study highlighted that GIS-based multi-criteria decision-making is a valuable and practical tool for decision-makers and land managers in creating soil erosion susceptibility maps and determining high-priority areas that require conservation measures for sustainable land use management by reducing the economic and ecological impacts of soil loss. Also, this approach can be practically applied in other planning units.

Erosion hotspot mapping using integrated morphometric parameters and Land use/land cover of Jigjiga Watershed, Ethiopia

Integration of morphometric parameters (MPs) and Land use/land cover (LU/LC) is crucial to prioritise the sub-watershed for conservation management to control soil erosion. The main objective of this study is to develop erosion hotspot mapping using integrated MPs and the LU/LC of Jigjiga Watershed further precisely to map soil erosion hotspots using MPs, LU/LC types and mapping of erosion hotspots by average weightage of MPs and LU/LC types. The study used the digital elevation model data for MPs analysis to extract the areal, linear and relief aspects to determine erosion risk mapping further using ArcGIS 10.5 software. The Jigjiga watershed was sub-divided into fifteen sub-watersheds and coded as JSW-1 to JSW-15. The MPs and LU/LC types computed values were used to rank and prioritise the sub-watersheds. Jigjiga Sub-watershed, LU/LC types were analysed for erosion risk area mapping using the Compound Priority method. The degree of prioritisation used for this study for the MPs and LU/LC types was very high, high, moderate, low, and very low. Accordingly, the erosion hotspots mapping results showed that the sub-watersheds JSW-15 and JSW-14 were categorised under a high priority based on MPs, whereas the JSW-14 was put under a very high priority by LU/LC. The JSW-1, JSW-5, JSW-9 and JSW-13 need high priority for natural resources conservation, both methods of MPs and mean weightage of LU/LC and MPs. The integration of erosion hotspot mapping from MPs and LU/LC parameters correlated for JSW-2, JSW-3, JSW-10, JSW-11, JSW-13 and JSW-14 common values of final erosion prioritisation. This research has provided information on land degraded areas for watershed managers, urban planners and decision-makers to manage the natural resources for sustainable watershed development.

Study of soil erosion risk in the basin of Northern Al-Kabeer river at Lattakia-Syria using remote sensing and GIS techniques

Soil erosion is the most importantchallenge foragriculturepresently onthe Syrian coast, especially in areas close to rivers and lakes.This study is to produce a soil erosion risk map based on the COoRdination of Information on the Environment (CORINE) model for the Northern Al-Kabeer River, Lattakia Province.To achieve this objective, the first phase of the study evaluated the soil erosion potential, by estimating soil texture, soil depth and granulometry. Soil was classified according to its erosion potential. A soil erosion potential map was obtained from data on soil erodibility, erosivity and slope.A land cover map of the study area was produced and classified into two classes according to soil protection. A risk map of soil erosion was prepared from information on land cover and potential risk erosion classes obtained previously.The results showed that 2.47% of the study area is in high risk soil erosion areas, 22.18% in moderate risk areas, and 75.35% in low risk areas. The high risk erosion areas were mainly located in the center and northern location within the study area. This study also confirms that land cover is the highest determinant of soil erosion.Land cover accounted for 60.93% of the erosion risk.

Prediction, validation, and uncertainties of a nation-wide post-fire soil erosion risk assessment in Portugal

Wildfires are a recurrent and increasing threat in mainland Portugal, where over 4.5 million hectares of forests and scrublands have burned over the last 38 years. These fire-affected landscapes have suffered an intensification of soil erosion processes, which can negatively affect soil carbon storage, reduce fertility and forest productivity, and can become a source of pollutants. The main objective of the present study is to produce a post-fire soil erosion risk map for the forest and shrubland areas in mainland Portugal and assess its reliability. To this end, the semi-empirical Morgan–Morgan–Finney erosion model was used to assess the potential post-fire soil erosion according to distinct burn severity and climate scenarios, and the accuracy of the predictions was verified by an uncertainty analysis and validated against independent field datasets. The proposed approach successfully allowed mapping post-fire soil erosion in Portugal and identified the areas with higher post-fire erosion risk for past and future climate extremes. The outcomes of this study comprise a set of tools to help forest managers in their decision-making for post-fire emergency stabilization, ensuring the adequate selection of areas for mitigation to minimize the economic and environmental losses caused by fire-enhanced soil erosion.

Erosion risk mapping of Anambra State in southeastern Nigeria: soil loss estimation by RUSLE model and geoinformatics

Erosion risk mapping of Anambra State in southeastern Nigeria: soil loss estimation by RUSLE model and geoinformatics

Soil erosion risk analysis and mapping for conservation planning at Mihtsab-Azmati micro-dam watershed, Northern Ethiopia

This study was conducted to quantify, analyze and map soil erosion risk areas using remotely sensed data and GIS-based Revised Universal Soil Loss Equation (RUSLE) model at Mihtsab-Azmati Irrigation Dam Watershed, Northern Ethiopia. Based on the result, the watershed has potential soil erosion risk which ranges from 0 ton hectare−1 year−1 to 2980.12 ton hectare−1 year−1 with an average annual soil erosion rate of 110.06 ton hectare−1 year−1. From the entire watershed area, only 27% of it has a soil loss a value less than 15 ton hectare−1 year−1 which is relatively categorized under low soil erosion risk, while the remaining area (73%) experiences moderate to very high soil loss rates. A large area (50.7%) is under high to very high soil loss (>50 ton hectare−1 year−1). The majority of the study watershed area experiences a very high soil erosion rate and this could be a major threat to the new irrigation dam constructed at the outlet of the watershed due to the sedimentation problem, which could decrease the economic lifespan of the dam. Hence, from the conservation perspective, a large proportion of the upper watershed area requires immediate and appropriate soil conservation measures.

TASOW – A tool for the automated selection of potential windbreaks

Wind erosion is a process in which soil particles are detached from soils and transported downwind. One effective measure to reduce wind erosion are vegetated windbreaks such as hedgerows as they reduce wind speeds and likewise the forces which detach and transport soil particles.However, the planting of new windbreaks is driven by policy decisions as well as planning considerations. To get an initial idea of potential locations for new windbreaks, we present an automated routine as a model in ESRI ArcGIS Pro to propose plantation locations. The main input to the model is a wind erosion risk map. The results are potential locations for windbreaks that are ranked according to their suitability. The model parameters are adjustable, transferable to other regions and can be altered by to the user's needs.•Limit the wind erosion risk map to the most prone fields•Selection of unprotected sites perpendicular to the main wind direction•Suggestions for suitable sites for the potential planting of new windbreaks

Comparison of the Spatial Wind Erosion Patterns of Erosion Risk Mapping and Quantitative Modeling in Eastern Austria

Various large-scale risk maps show that the eastern part of Austria, in particular the Pannonian Basin, is one of the regions in Europe most vulnerable to wind erosion. However, comprehensive assessments of the severity and the extent of wind erosion risk are still lacking for this region. This study aimed to prove the results of large-scale maps by developing high-resolution maps of wind erosion risk for the target area. For this, we applied a qualitative soil erosion assessment (DIN 19706) with lower data requirements and a more data-demanding revised wind erosion equation (RWEQ) within a GIS application to evaluate the process of assessing wind erosion risk. Both models defined similar risk areas, although the assignment of severity classes differed. Most agricultural fields in the study area were classified as not at risk to wind erosion (DIN 19706), whereas the mean annual soil loss rate modeled by RWEQ was 3.7 t ha−1 yr−1. August was the month with the highest modeled soil loss (average of 0.49 t ha−1 month−1), due to a low percentage of vegetation cover and a relatively high weather factor combining wind speed and soil moisture effects. Based on the results, DIN 19706 is suitable for a general classification of wind erosion-prone areas, while RWEQ can derive additional information such as seasonal distribution and soil loss rates besides the spatial extents of wind erosion.

On the use of the Land Degradation Neutrality concept in mediterranean watersheds for land restoration and erosion counteraction

This study aims to implement the Land Degradation Neutrality (LDN) concept on a test site: the 309 km2 Nahr Ibrahim watershed Lebanon, by integrating soil erosion as an LDN indicator given its status as a land degradation driver and common concern of the Mediterranean region. Land degradation was mapped, and erosion risk maps were also established. Through LDN's response strategy, an alternative LDN based land use/land cover (LU/LC) scenario was obtained. The LDN scenario was then tested for adoption as a counter-erosion measure. Under current land occupation conditions, a 63.54% (194 km2), 4.20% (12.82 km2) and 32.32% (98.7 km2) distribution of lands being underutilized, managed within their capability, and being used in a manner that exceeds their capability, respectively, was found. Soil erosion risks under current conditions were distributed as 3.88%, 38.19% and 54.48% low, moderate and high erosion risks, respectively. Following the proposed LDN scenario, 86.7 km2 (28% of the basin) were restored, while erosion risks shifted to 5.19%, 45.66% and 45.71% for low, moderate, and high erosion risks, respectively. The presented approach revealed the efficiency of LDN not only as a land restoration tool, but also as a powerful counter-erosion measure.

Soil Erosion Estimation in Arid Area by USLE Model Applying GIS and RS: Case of Oued El Hamma Catchment, South-Eastern Tunisia

Soil erosion risk is one of the most severe environmental problems that can affect water availability, agricultural productivity and consequently countries’ sustainable development worldwide. The current study was performed in the Oued El Hamma Catchment, South-Eastern Tunisia to estimate the soil loss, applying the Universal Soil Loss Equation (USLE) integrated with Geographic Information System (GIS) and Remote Sensing (RS) approaches. The main objective of this research was to identify the vulnerable zones to elaborate a soil erosion risk map in the study catchment. The adopted approach was built essentially on five factors including rainfall erosivity, topography, soil erodibility, field management practice and vegetation cover factors. In addition, the soil erodibility factor was simulated based on soil properties obtained via in-situ measurements of the soil sampling and analysis campaigns. The spatial erosion risk map of Oued El Hamma Catchment was established with four distinct erosion classes based on the intensity of soil loss. The mean soil loss rate is approximately 0.2 t/ha/yr. The maximum soil loss in the study area was 17 t/ha/yr in Matmata mountainous regions. The results obtained showed that erosion risk was minimal in most of the catchment (99%). The erosion risk was moderate to high in a limited coverage observed especially in South sector (< 1%) that is subjected to a greater soil loss risk than 5 t/ha/yr. Finally, it is important to note that the developed soil erosion risk map represents an efficient tool to help decision makers evolving strategies for water and soil conservation works in such arid areas where farmlands are vulnerable and extremely scarce.

Impacts of Land Cover Changes on Soil Erosion for Agricultural Sustainability in Maragua Sub-Watershed: Case Study in Murang’a County, Kenya

Soil erosion affects the yield production becoming a major constraint to agriculture and environmental sustainability. In the last decade, Maragua watershed has undergone major environmental changes. This study explicates the detection of land cover change and how this has affected the amount of soil loss. Three epochs each spanning ten years from 1987 all though to 2017 was selected for this study. To prioritize conservation of predisposed areas, climatic conditions and topography factors that accelerate soil erosion were used in the RUSLE model to generate erosion risk maps and change analysis was carried out to show the trend in soil erosion. Land cover classification, was performed and a trend in the change was examined. To achieve the main objective; randomly created point sampled within the study area were used to demonstrate consistent trends in land cover changes that resulted in high erosion areas. The results of this study shows that bare land and cropland land covers were the major causes of increased soil erosion over the period of the study. The spatial and quantitative information on soil erosion this research provides can be used in managing resources and help implement practical approaches for agricultural sustainability.

Tools for USLE-CP-factor calculation and actual erosion risk on field block level for Switzerland

The calculation of the cover management factor (C-factor) and support practices factor (P-factor) is an important element in the Universal Soil Loss Equation (USLE). In Switzerland, a potential soil erosion risk map of arable land and a field block map that represents the basis of the agriculturally used areas in the country are available. A CP-factor tool was developed adapted to Swiss agronomic and environmental conditions, which allows to calculate CP-factors easily for various crop rotations and management practices. The calculated CP-factor values can be linked to any field block in the potential soil erosion risk map to determine the actual soil erosion risk for the field block. A plausibility check with other C-factor tools showed a sound match. This user-friendly calculation makes the CP-Tool and the actual erosion risk more accessible for authorities and GIS users. With Python and QGIS as open source resources, it is also possible to easily improve the tools. Linking the two tools provides substantial added value for education and training, advising farmers and policy, as well as scientific research, and can serve as a reference for other countries.•USLE-CP-factor and actual erosion risk calculation on small scale field block level.•Developed and programmed based on open source resources for further improvements.•Both tools increase the knowledge of management practices for GIS- and non GIS users.

Enset-based land use land cover change detection and its impact on soil erosion in Meki river watershed, Western Lake Ziway Sub-Basin, Central Rift Valley of Ethiopia

BackgroundWater erosion, upland degradation and deforestation are key environmental problems in the Meki river watershed. The study assessed the land use land cover change (LULCC) for 30 years and it examined the contribution of indigenous Enset-based land use system (EBLUS) to reduce soil erosion and prevent water bodies including Lake Ziway from sedimentation which was not considered in the former studies. GPS based data collected and satellite based LULC analysis using ERDAS Imagine 2014 performed to investigate existing farm management practices and land cover respectively. HEC-GEOHMS, Geo-statistical interpolation and RUSLE were applied to model watershed characteristics, spatial climate parameters and soil loss respectively.ResultMeki river watershed (2110.4 km2 of area) is dominantly covered by cultivated LUS (41.5%), EBLUS (10.65%), Bush and Chat LUS (25.6%), Forest and plantations LUS (14.14%), built-up (7.4%) and water bodies (0.75%). Soil loss is increasing from 1987 to 2017 and a larger part of the watershed suffers a moderately severe to very severe risk (18 t ha−1 year−1 to > 80 t ha−1 year−1) in all sub-watersheds irrespective of the land use systems which shows the watershed is facing sever degradation problem. The mean soil loss of 30.5 t ha−1 year−13 and 31.905 t ha−1 year−1 are verified from Enset growing zones and non-Enset growing zones of the watershed respectively.ConclusionEBLUS saves significant amount of soil despite the steepness of the slopes of the Enset growing zones of the watershed. Hence, expansion of EBLUS can contribute in sustaining water bodies, including Lake Ziway by reducing soil loss rate and sedimentation problem for the ecological sustainability of the watershed. Therefore, separate land use policy and awareness creation are mandatory for such EBLUS expansion, sustainable watershed management interventions and conservation of the natural environment in the watershed based on its suitability and severity of erosion risk mapping.

Mapping of soil sensitivity to water erosion by RUSLE model: case of the Inaouene watershed (Northeast Morocco)

The sources of land degradation in many watersheds are runoff and erosion. In order to delay this degradation resulting in the loss of soil fertility, a system for its quantification needs to be established. Erosion severely impacts our natural capital and requires several studies and prevention and management steps. This research focuses on validating the revised universal soil loss equation (RUSLE) method through evidence from remote sensing (RS) and the Geographic Information System (GIS) in the watershed of the Inaouene river upstream of the Idriss 1st dam in the Taza region (northeast of Morocco). In this context, the approach adopted was performed, consists in combining the revised universal soil loss equation (RUSLE) to quantify erosion and GIS to spatialize the factors responsible for water erosion and soil loss (climate, soil, vegetation, and topography) GIS to produce a map of erosion risk. The results achieved show that the Inaouene watershed is characterized by an average climatic aggressiveness, a sparse vegetation cover without any safeguards, moderate to high erodible soils with a maximum ranging from 50 to 150 t/h/year. Topography characterized by high (50%) to moderately broken reliefs. The human intervention remains the most mattering factor in the embrittlement and the accentuation of the soils vulnerability for erosion for every dominant natural factor. The results of this study could be of use in prioritizing areas for soil conservation measures and watershed development and management. It is a tool for decision-makers, planners, and decision-makers in soil and water conservation decision-making to implement anti-erosion strategies to reduce the impact of erosion.

Mapping of water erosion by GIS/RUSLE approach: watershed Ayda river—Tunisia study

In Tunisia, land degradation is mainly caused by heavy rainwater. The complexity of this natural phenomenon in the catchment area of the Ayda river located in the highlands of Siliana, Tunisia, is linked to a rather reduced vegetal cover because of the hardness of the climate and the anthropic actions. It covers an area of 7.30 Km2 drained mainly by Ayda river. It is characterized by moderately rugged terrain with a minimum altitude of 844 m and maximum of 1182 m. For slopes, they can be very strong by 70% but also in some locations does not exceed 6%. Several methods and models are commonly used for water erosion study. The revised universal soil loss equation (RUSLE) was chosen in our study. It is an empirical and spatialized model, based on the characteristics of the watershed, such as the slope, the vegetation, and the state of erosion of its soils and their protection. Integration of this model data with geographic information system (GIS) allowed us to establish an erosion risk map to quantify soil loss, target areas of high erosion, and direct erosion control measures. Each of these factors has been expressed as a thematic map. The resulting soil loss map shows a variation in the erosion rate value, between 9 t/ha/year downstream of Ayda river and a maximum value 330 t/ha/year towards land without vegetation and areas with high slope values mainly in the southwestern part of the basin at Djebel Barbrou and Kef Guedouara respectively, which are the most vulnerable to water erosion.

Comparing potential risk of soil erosion using RUSLE and MCDA techniques in Central Ethiopia

Water erosion remains a threat to subsistence agriculture. Insofar, spatial-based soil erosion risk mapping is investigated to assist interventions across varying scales. The Revised Universal Soil Loss Equation (RUSLE) model and Multi-Criteria Decision Analysis (MCDA) techniques are most recently used to map soil erosion hotspots in Ethiopia. Aligned to that, this study aims to identify and compare the risk of soil erosion using the RUSLE and MCDA approach in Sodo watershed covering 80.54 km2, central Ethiopia. The adjusted parameters of RUSLE and MCDA demanding soil, land use, and terrain feature data were used for the study. Finally, cross-comparison was effected to check their consistency. The RUSLE model shows 68.91% of the study area accounted for a soil loss of 75 ton/ha/year. Generally, the mean annual gross soil loss amounts to 783,170 tons, with the mean soil loss rate of 35.28 tons/ha/year. This is 1.96 times higher than the tolerable limit for Ethiopian highlands. The MCDA result shows that 5.6%, 50.57%, and 43.83% of the watershed are highly, moderately, and slightly sensitive to soil erosion, respectively. The overlay result reveals that 49.4% of the risk and location of land susceptibility was similarly estimated by RUSLE and MCDA. This is a “good agreement” with a Kappa value of 0.62. The consistency increases with a decreasing level of sensitivity. Therefore, this could be an input for local decision-makers and experts at large.

Assessment of LULC Change and Its Impact on Soil Erosion Using GIS and Revised Universal Soil Loss Equation Model

Land use is one of the vital factors in estimating soil erosion over an area. Significant changes in spatio-temporal land use distribution might lead to water runoff which causes soil erosion events. It is important to assess the soil erosion risk for hydropower reservoir as part of sediment management activities. This study aims to assess the impact of land use and land cover (LULC) changes on soil erosion risk at Chenderoh catchment in Perak. LULC distribution within the study area was mapped for 2008, 2010 and 2015 by using land use maps obtained from Department of Agriculture, Malaysia. The soil loss rate was measured using the Revised Universal Soil Loss Equation (RUSLE) utilizing spatial data of rainfall factor, soil erodibility, topographical factor, conservation factor, and support practice factor. Average soil loss was calculated according to sub-catchment of Chenderoh, and it is found that the soil loss trend marginally increases from year 2008 to 2015. Based on soil erosion risk map results, it is found that conversion of forest land to agriculture is the main contributor to soil loss, which might be due to land clearance and agriculture practice activities.

Mapping erosion risk for saline rangelands of the Mancos Shale using the rangeland hydrology erosion model

AbstractThis research used the rangeland hydrology and erosion model (RHEM) to map erosion risks affecting water quality of the Colorado River that originate on the Mancos Shale formation in Utah, Colorado, New Mexico, and Arizona. The Mancos Shale is a significant source of salinity to the river, and a portion of that salt load derives from erosion of rangeland soils. Here we demonstrate that the hillslope‐scale RHEM model can effectively characterize erosion risk across this large, discontinuous region. Inputs to RHEM included digital elevation data, maps of soil properties, the LANDFIRE vegetation map, Landsat and MODIS satellite imagery, field data from the Rangeland National Resource Inventory program of the US Natural Resources Conservation Service, and rainfall data from Atlas 14 of the U.S. National Atmospheric and Oceanographic Administration. RHEM predicted sediment yield at a 30‐m spatial resolution for storms with 30‐ and 60‐min durations whose intensities corresponded to 10‐ and 25‐year return frequencies. Results corresponded reasonably with prior field experiments that used the Walnut Gulch Rainfall Simulator (WGRS), with a Spearman's rank‐order correlation of .76 for cumulative sediment yield after 20 min of rainfall. Issues of input map accuracy were identified for rainfall intensity and estimates for sodium adsorption ratio (SAR) of soils. Correction of erroneous SAR at WGRS sites in one location improved rank‐order correlation to .93, indicating very good model performance where map inputs are accurate. The high‐resolution map of erosion risk developed from RHEM can help to prioritize specific areas for more intensive study and action.

Modelling of gully erosion risk using new ensemble of conditional probability and index of entropy in Jainti River basin of Chotanagpur Plateau Fringe Area, India

Gully erosion, in the fringe areas of the Chotanagpur, is one of the important environmental issues from the perspective of agricultural sustainability, economic framework and land-resource management. The spatial gully erosion risk map (SGERM) can afford to identify the locales sensitive to gully erosion hazard. The present work intends toward modelling spatial gully erosion risk using the new ensemble model in a plateau fringe semi-agricultural watershed of Jainti River (542.69 km2) in Jharkhand, India. Coupling field operation (gully boundary and area measurement) and geostatistical models, the study was accomplished. Field gullies were split into training and validation sets using random partitioning method. Selected predisposing variables for gully erosion based on physical appearances of this basin and literature survey are slope steepness, length-slope factor, soil type, geomorphology, rainfall erosivity, distance from river, stream power index, topographical position index, topographical wetness index, altitude, slope aspect, land use/land cover, normalised difference vegetation index and geology. To prepare the statistical database, information regarding the number of pixel of individual parameter was extracted using GIS software and for tracing the response of each variable for gully erosion, entropy values were calculated against each of them using IoE. While the probability of gullying within each sub-class of each variable was computed using the CP model. In case of ensemble of CP-IoE, variable weights were assigned through IoE and weights to the sub-classes were assigned through CP. The results of CP, IoE and ensemble models that quantified 10.58%, 7.73% and 8.25% areas of the basin were under the very high-risk category respectively. Based upon the results of ROC curves, the predicting accuracy of ensemble model with the highest area under curve (AUC) is better in comparison to individual CP and IoE models.

Remote Sensing and GIS Application to Erosion Risk Mapping in Lagos

Increased population, unhealthy agricultural practices, indiscriminate land clearing and illegal structures have led to an increase of erosion in Nigeria and Lagos State in particular. This research focused on identifying land use/land cover changes in Eti-Osa LGA of Lagos State and estimating the actual erosion risk using Remote Sensing and Geography Information System. In addition, this research evaluated the perception of communities within the study area with the view to understanding the risk involved in erosion. Maximum Likelihood Algorithm was the classification method applied on the Landsat imageries (1986-2016) to identify the changes on the land use/land cover types. Analysis of Variance (ANOVA) was used to evaluate the perception of communities within the study area and Revised Universal Soil Loss equation (RUSLE) model was used to estimate the actual erosion risk. The result showed that the sediment yield of the study area was estimated to be between 0 to 48ton/ha/yr. The estimated soil losses were higher in Eti-Osa West compared to other parts of Iru/Victoria Island, and Ikoyi/Obalende areas which recorded low losses. Land uses mostly affected by very high and severe erosion are the bare soils and the crop lands having about 3% to 4% respectively. It can be concluded that rainfall, lack of cover for the surface soil were the major causes of soil loss in the study area.