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Soil erosion accelerated by human activities is a critical challenge affecting soil health, agricultural productivity, food security and environmental sustainability in the highlands of Ethiopia. The aim of this study was to examine the dynamics of soil loss and sediment yield potential, and identify soil erosion hotspots using RUSLE with GIS in th...
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... Localized studies were conducted to calibrate the model parameters based on field observations, soil analysis, rainfall data, and erosion monitoring [4], [40]. The application of RUSLE in Ethiopia has played a vital role in generating awareness about soil erosion, guiding land management decisions, and implementing soil erosion control measures [7], [9], [41]. It has contributed to developing soil and water protection strategies, such as terracing, agroforestry, and improved farming practices, to moderate the impact of erosion and preserve soil fertility [26], [38]. ...
... The p values range from 0 to 1, with 0 representing well-managed fields and 1 representing unmanaged fields [9]. It considers practices such as contour plowing, terracing, bunds, and other soil conservation techniques. ...
Soil erosion is one of Ethiopia's most severe ecological problems, affecting agricultural output, water quality, and ecosystem well-being. The RUSLE (Revised Universal Soil Loss Equation) model is an extensively used tool for estimating soil erosion, but its applicability in Ethiopia has yet to be effectively evaluated. This article systematically examines the RUSLE model's application in estimating soil loss, emphasizing Ethiopia. A wide-ranging search technique was used to categorize appropriate research articles, books, and other sources related to the practice of the RUSLE model for estimating soil loss in Ethiopia for this review paper. This review observes the model's strengths and limitations, examines the factors contributing to soil erosion, and identi es region-speci c strategies for effective soil conservation and mitigation. This review helps the management of soil erosion challenges in Ethiopia by advancing our understanding of the model's utility and providing valuable insights. The ndings of this review presented here are critical for estimating soil erosion. They will play a more signi cant role in improving agricultural methods, protecting soil resources, and ensuring the overall ecological well-being of the country.
... Localized studies were conducted to calibrate the model parameters based on field observations, soil analysis, rainfall data, and erosion monitoring [4], [40]. The application of RUSLE in Ethiopia has played a vital role in generating awareness about soil erosion, guiding land management decisions, and implementing soil erosion control measures [7], [9], [41]. It has contributed to developing soil and water protection strategies, such as terracing, agroforestry, and improved farming practices, to moderate the impact of erosion and preserve soil fertility [26], [38]. ...
... The p values range from 0 to 1, with 0 representing well-managed fields and 1 representing unmanaged fields [9]. It considers practices such as contour plowing, terracing, bunds, and other soil conservation techniques. ...
Soil erosion is one of Ethiopia's most severe ecological problems, affecting agricultural output, water quality, and ecosystem well-being. The RUSLE (Revised Universal Soil Loss Equation) model is an extensively used tool for estimating soil erosion, but its applicability in Ethiopia has yet to be effectively evaluated. This article systematically examines the RUSLE model's application in estimating soil loss, emphasizing Ethiopia. A wide-ranging search technique was used to categorize appropriate research articles, books, and other sources related to the practice of the RUSLE model for estimating soil loss in Ethiopia for this review paper. This review observes the model's strengths and limitations, examines the factors contributing to soil erosion, and identifies region-specific strategies for effective soil conservation and mitigation. This review helps the management of soil erosion challenges in Ethiopia by advancing our understanding of the model's utility and providing valuable insights. The findings of this review presented here are critical for estimating soil erosion. They will play a more significant role in improving agricultural methods, protecting soil resources, and ensuring the overall ecological well-being of the country.
... It forecasts annual soil loss as a product of rainfall erosivity (R), soil erodibility (K), topography (LS), cover and management (C), and support practice (P) (Mustefa et al., 2019;Hagos, 2020;Sinshaw et al., 2021;Mengie et al., 2022). Consequently, RUSLE integrated with GIS-based soil erosion models provides a valuable tool for assessing erosion and prioritizing possible land management measures (Bewket & Teferi, 2009;Belayneh et al. 2019;Kebede et al., 2021;Yeneneh et al., 2022). In this study, the RUSLE model was utilized which is a powerful and widely used model for predicting soil erosion rates. ...
... These include very slight (0-5 t ha −1 year −1 ), slight (5-15 t ha −1 year −1 ), moderate (15-30 t ha −1 year −1 ), severe (30-50 t ha −1 year −1 ), and very severe (> 50 t ha −1 year −1 ). These have been adapted from the published articles of multiple authors (Belayneh et al., 2019;Negese et al., 2021;Yeneneh et al., 2022). ...
Erosion of soil refers to the process of detaching and transporting topsoil from the land surface by natural forces such as water, wind, and other factors. As a result of this process, soil fertility is lost, water bodies’ depth is reduced, water turbidity rises, and flood hazard problems, etc. Using a numerical model of erosion rates and erosion risks in the Jejebe watershed of the Baro Akobo basin in western Ethiopia, this study mapped erosion risks to prioritize conservation measures. In this study, the Revised Universal Soil Loss Equation (RUSLE) model was used, which was adapted to Ethiopian conditions. To estimate soil loss with RUSLE, the rainfall erosivity (R) factor was generated by interpolating rainfall data, the soil erodibility (K) factor was derived from the soil map, the topography (LS) factor was determined from the digital elevation model (DEM), cover and management (C) factor derived from the land use/cover data, and conservation practices (P) factor generated from digital elevation model (DEM) and land use/cover data were integrated with remote sensing data and the GIS 10.5 environment. The findings indicated that the watershed annual soil loss varies from nearly 0 on a gentle slope of forest lands to 265.8 t ha⁻¹ year⁻¹ in the very steep slope upper part of the watershed, with a mean annual soil loss of 36.2 t ha⁻¹ year⁻¹. The total annual soil loss in the watershed is estimated to be around 919,886.5 tons per year. To minimize the amount of soil erosion in the watershed that had been most severely affected, we identified eight conservation strategies that could be implemented. These strategies were based on the participatory watershed development (PWD) principles established by the Ethiopian government and the severity of the erosion in the watershed. The study’s findings showed that a GIS-based RUSLE soil erosion assessment model can provide a realistic prediction of the amount of soil loss that will occur in the watershed. This tool can also help identify the priority areas for implementing effective erosion control measures.
... Soil erosion is a serious and continuous environmental problem particularly in the highlands of Ethiopia [31]. Soil erosion increased by human activities is a critical challenge affecting soil health, agricultural productivity, food security, and environmental sustainability in the highlands of Ethiopia [30]. Besides the land degradation in the highlands of Ethiopia [17], soil erosion is causing downstream sedimentation problems in water supply and hydropower-generating reservoirs [2]. ...
Erosion is the most widespread form of soil degradation overall in the world. In the current study, soil erosion is quantified, and areas prone to high risk of soil erosion are identified under current management in the Holeta watershed, Awash Basin, Ethiopia, where lands are primarily cultivated. The Soil and Water Assessment Tool (SWAT) was applied to simulate the baseline hydrologic and soil erosion processes. The model used spatial (i.e., DEM, land use, and soil maps) and temporal (climate) data to simulate different biophysical processes. Moreover, streamflow and sediment data were acquired and analyzed for model calibration and validation. The performance of the model during calibration and validation with both streamflow and sediment loads was evaluated against the measured data by using statistical parameters (R² = 0.64, 0.81, NSE = 0.61, 0.76, PBIAS = 12.6%, 9.8%, respectively) during calibration and validation with streamflow and (R² = 0.78, 0.68, NSE = 0.74, 0.61, PBIAS = 16.1%, 18.2%, respectively) while calibration and validation by sediment. The annual sediment load in the Holeta watershed varies from 2 to 136.4 t/ha/year with an average of 18 t/ha/year. The annual severity of sediment load was prioritized under very low, low, moderate, high, very high, and severe. About 13.3% of the Holeta watershed’s sub-basin contributed a higher sediment yield than average under current management. The significant sediment yield is generated from cultivated areas whereas; the lowest magnitude is generated from forested areas. Overall, since the generated sediment is within the tolerated range, current conservation retains soil loss for sub-basin 2, 4–15, and effective management practices can be identified by further study and established for the erosion-affected areas (sub-basins 1 and 3).
... Soil erosion affected approximately 65% of the soil in Sub-Saharan African nations as a result of poor management [4]. The overall yearly soil loss for the entire Suha watershed grew from 1.22 million tons in 1985 to 2.43 million tons in 2019, according to research by Ref. [12]. Additionally, in the past, problems with soil pressure brought on by human population growth, excessive use of natural resources, a lack of soil management techniques like shifting cultivation and intercropping, and a lack of periods of fallow land were all contributing factors. ...
... The other limitation was the lack of a similar and global standard for soil severity classification ranges. Some scholars divide it into seven categories: low (below 10), moderate (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), high (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), very high (30-35), severe (35-40), very severe (40-45), and extremely severe (above 45) [16], Other classifications were as follows: 0-10 Low, 10-20 Moderate, 20-30 High, 30-50 Very High, and >50 Severe [11]. Another scholar classified it as 0-42 (low), 43-128 (medium), and >128 (high) [2]. ...
... Soil erosion was classified into five severity classes based on the above (Fig. 9) and below ( Table 5). These were; very slight (0-10), slight (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20), moderate (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30), severe , and very severe (>50). Based on this range, 1058 and 1599 ha of land were classified as very severe and severe respectively. ...
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.
Changes in land use and land cover (LULC) are becoming recognized as critical to sustainability research, particularly in the context of changing landscapes. Soil erosion is one of the most important environmental challenges today, particularly in developing countries like Ethiopia. The objective of this study was evaluating the dynamics of soil loss, quantifying sediment yield, and detecting soil erosion hotspot fields in the Boyo watershed. To quantify the soil erosion risks, the Revised Universal Soil Loss Equation (RUSLE) model was used combined with remote sensing (RS) and geographic information system (GIS) technology, with land use/land cover, rainfall, soil, and management approaches as input variables. The sediment yield was estimated using the sediment delivery ratio (SDR) method. In contrast to a loss in forest land (1.7 %), water bodies (3.0 %), wetlands (1.5 %), and grassland (1.7 %), the analysis of LULC change (1991–2020) showed a yearly increase in the area of cultivated land (1.4 %), built-up land (0.8 %), and bare land (3.5 %). In 1991, 2000, and 2020, respectively, the watershed's mean annual soil loss increases by 15.5, 35.9, and 38.3 t/ha/y. Approximately 36 cm of the watershed's economically productive topsoil was lost throughout the study's twenty-nine-year period (1991–2020). According to the degree of erosion, 16 % of the watershed was deemed seriously damaged, while 70 % was deemed slightly degraded. Additionally, it is estimated for the year 2020 that 74,147.25 t/y of sediment (8.52 % of the total annual soil loss of 870,763.12 t) reach the Boyo watershed outlet. SW4 and SW5 were the two sub-watersheds with the highest erosion rates, requiring immediate conservation intervention to restore the ecology of the Boyo watershed.
The Revised Universal Soil Loss Equation (RUSLE) is the most widely used erosion model for decision making on conservation priority. However, interpreting estimates of the mean annual soil loss alone could not accurately depict the spatial variation of soil erosion severity due to its inherent mathematical errors. This study aims to optimize the model’s outputs through detailed analysis of land use/cover dynamics in Upper Awash River Basin, central Ethiopia (7815.1 km²). The analysis include annual rate of change, net gain or loss, and conversion pathways. Results of the estimated mean annual soil loss in the basin varies between 4.1 t/ha/y and 5.1 t/ha/y during three consecutive decades (1990-2000, 2000-2010, and 2010-2020). The cultivated land cover exhibits slight erosion severity (< 5 t/ha/y), while contributing up to 59% the total annual soil loss (3198.8 Mt/ha). Although the net loss of cultivated land cover outweighing the gain during these decades, it progressively encroaches forests (142.2 km²), shrubs (780.8 km²), and grasslands (274.5 km²). Such net loss of protective land covers will inevitably increase the soil erosion risk. Findings from the study would be useful, enabling conservation practitioners to understand the overall severity of soil erosion and make informed decisions.
Water erosion is one of the major land degradation problems all over the globe, and its accurate quantification in different land use contexts is required in order to propose suitable conservation measures and curtail related hazards. In the Andaman and Nicobar (A&N) Islands, the land use changes due to faster urbanization and deforestation practices have led to accelerated erosion at many points around the inhabited Islands. Moreover, agricultural land uses in the A&N Islands are vulnerable to severe soil erosion, mainly due to cultivation practices along the steep slopes and mono-cropping culture. A study was conducted by establishing runoff plots in areas with different land uses to measure soil and nutrient losses and to estimate soil erosion using a semi-process-based soil erosion model, i.e., Revised Morgan Morgan and Finney (RMMF). The RMMF model was calibrated using primary data from runoff plots for the years 2019–21, validated for the year 2022, and applied in a Geographical Information System (GIS) to estimate soil erosion spatially over the Andaman ecosystem. The RMMF model simulated soil erosion during validation with a coefficient determination (R2) greater than 0.87 as compared to measured soil erosion from the runoff plots. The study revealed that annual N, P, and K losses of 41–81%, 42–95%, and 7–23%, respectively, due to runoff from various land uses. The land use land classification analysis of the Andaman Islands revealed that about 88% of the total geographical area is under the forest and mangrove land uses, which exhibited very slight soil erosion of
