Average Soil Loss Research Articles

Quantification of Soil–Water Erosion Using the RUSLE Method in the Mékrou Watershed (Middle Niger River)

Despite nearly a century of research on water-related issues, water erosion remains one of the greatest threats to soil health and soil ecosystem services around the world. Yet, to date, data on water erosion needed to develop mitigation strategies are scarce, especially in the Sahelian regions. The current study therefore sets out to estimate annual soil losses caused by water erosion and to analyze trends over the period of 1981–2020 in the Mékrou watershed, located in the Middle Niger river sub-basin in West Africa. The Revised Universal Soil Loss Equation, remote sensing, and the Geographic Information System (GIS) were deployed in this study. Several types of data were used, including rainfall data, sourced from meteorological stations and reanalysis datasets, which capture the temporal variability of erosive forces. Soil properties, including texture and organic matter content, were derived from FAO global soil databases to assess soil erodibility. High-resolution digital elevation models (30 m) provided detailed topographic information, crucial for calculating slope length and steepness factors. Land use and land cover data were extracted from satellite imagery, enabling the analysis of vegetation cover and anthropogenic impacts over four decades. By integrating and treating these data, this study reveals that the estimated average annual amount of water erosion in the Mékrou watershed is 6.49 t/ha/yr over 1981–2020. The dynamics of the ten-year average are highly variable, with a minimum of 3.45 t/ha/yr between 1981 and 1990, and a maximum of 8.50 t/ha/yr between 1991 and 2000. Even though these average soil losses in the Mékrou basin are below the tolerable threshold of 10 t/ha/yr, mitigation actions are needed for prevention. In addition, the spatial dynamics of water erosion are noticeably heterogeneous. The study reveals that 72.7% of the surface area of the Mékrou watershed is subject to slight water erosion below the threshold, compared with 27.3%, particularly in the mountainous south-western part, which is subject to intense erosion above the threshold. This research is the first study of soil erosion quantification with the RUSLE method and GIS in the Mékrou watershed, and fills a critical knowledge gap of the water erosion in this watershed, providing insights into erosion dynamics and supporting future sustainable land management strategies in vulnerable Sahelian landscapes.

Soil erosion susceptibility maps and raster dataset for the hydrological basins of North Africa

Soil erosion in North Africa modulates agricultural and urban developments as well as the impacts of flash floods. Existing investigations and associated datasets are mainly performed in localized urban areas, often representing a limited part of a watershed. The above compromises the implementation of mitigation measures for this vast area under accentuating extremes and continuous hydroclimatic fluctuations. To address this deficiency, we use the Revised Universal Soil Loss Equation to map surface erosion, providing the first insight into the decadal impacts of land degradation, which are largely unconstrained on North Africa’s continental scale. We generate soil erosion maps for the major hydrological basins of North Africa using Google Earth Engine and multiple hydroclimatic and land use datasets, covering 5.8 million square kilometers. The generated geospatial dataset integrates land use, soil erodibility, slope, vegetation cover, and land practices. The resulting product is an expansive and publicly available Soil erosion susceptibility maps and rasters dataset (SESMAR). This dataset is a crucial step toward understanding the drivers of soil erosion in this vast, poorly characterized area as well as its potential to be used for future soil conservation campaigns for both agricultural and urban planning. We validate SESMAR using the Global Rainfall Erosivity Database (GloREDa) and the European Soil Data Centre (ESDAC) datasets as well as published peer-reviewed reports across 20 watersheds, demonstrating a robust agreement in assessing the average annual soil loss values and soil erosion classes in local areas covered by independent study teams. Our continental maps show commendable accuracy, supporting scientists, practitioners, and policymakers in their efforts for more resilient land management practices across North Africa to mitigate rising hydroclimatic extremes.

Assessment of soil erosion and sediment delivery ratio in the Arghandab Catchment, Kandahar Province, Afghanistan by using GIS-based RUSLE method

A significant proportion of Arghandab Catchment in Kandahar Province, Afghanistan has been under potential degradation threat due to soil erosion. This study assessed the extent of soil erosion and estimated the sediment delivery ratio (SDR) in the catchment by employing the Revised Universal Soil Loss Equation (RUSLE), utilizing the Geographic Information System (GIS) and the Remote Sensing (RS) techniques. Data, related to rainfall erosivity (R factor), soil erodibility (K factor), slope length and steepness (LS factor), cover management (C factor), and support practices (P factor), employed for the RUSLE model were processed using the GIS tools and R-Studio software. Average RUSLE factor values estimated in the studied area ranged from 51.8 to 124 MJ mm ha−1 h−1 year−1, 0.03725 t ha h ha−1 MJ−1 mm−1, 9.2, 0.445, and 0.75 for R, K, LS, C, and P factors, respectively. The results revealed that the average annual soil loss from the catchment was 6.81 t ha−1 yr−1, ranging from 0.002 t ha−1 yr−1 in the flat areas up to 94.7 t ha−1 yr−1 in the hilly and mountainous regions. Soil classes of slight, moderate, high, very high, severe, and very severe covered areas of 20.1% (263,542.3 ha), 12.2% (160,286.5 ha), 22.8% (298,740.6 ha), 20.3% (265,546.8 ha), 17.6% (231,224.4 ha) and 6.9% (90,879.9 ha), respectively. The computed SDR for Dahla Reservoir located in the catchment was found to be in between 24.2% and 36%. LS factor was identified as the most crucial variable associated with soil erosion. The findings from this study can be applied when designing effective conservation strategies in the management of erosion and water management.

The effect of surface flow conditions on WEPP interrill erodibilities

The Water Erosion Prediction Project erosion model (WEPP) was developed as an event-based more process-based replacement for Universal Soil Loss Equation (USLE) based models in predicting soil erosion as a guide to conserving soil in the USA. However, WEPP has not been shown to predict event soil losses for bare fallow USLE plots better than USLE-based models when stipulated input values have been used. To some extent, this problem can be attributed to the availability of more refined and site-specific input parameters for the USLE-based models. This is true with respect to WEPP’s capacity to model raindrop-driven erosion on USLE plots under natural rainfall. Stipulated values for WEPP interrill erodibilities in the USA were determined only for ridge side slopes but USLE-based models focus on the prediction of long-term average annual soil loss caused by both sheet and rill erosion on planar surfaces. The interrill erodibilities determined for ridge side slopes did not correlate well with those on adjacent flat surfaces sloping along the land slope under the same rainfall conditions. Surface flow conditions, particularly flow depth, differ between the short high gradient side slopes associated with ridges, and the lower gradient slopes in interrill and sheet erosion areas on USLE plots. Failure of WEPP to account for the influence of different flow conditions between ridged and flat areas on raindrop-driven erosion affects the veracity of WEPP to predict average annual soil loss on USLE plots under natural rainfall and the use of WEPP to act as a replacement for USLE based models as an aid to make land management decisions to conserver soil in the USA.

Influences of vegetation types and near-surface characteristics on hydrodynamics and soil erosion of steep spoil heaps under rainfall and overland flow conditions

Spoil heaps, are characterized by loose structure, high infiltration, steep slopes, etc, and have become a source of soil erosion and geological disasters. Vegetation was regarded as an effective way to curb soil erosion of spoil heaps. However, few studies have been conducted to explore the effects of vegetation types and their near-surface characteristics on hydrodynamics and soil erosion of steep spoil heaps. This study aimed to address this research gap by conducting field simulated rainfall and rainfall with run-on experiments using simulated spoil heap plots with 3.4m × 2m × 0.6m (length × width × depth) and a slope of 30 degree. The material used in the spoil heaps comprised a uniform mixture of silt soil particles, constituting 90% by mass, and gravel, constituting 10% by mass. For this study, bare slope (BS), Artemisia gmelinii (A. gmelinii), and Cynodon dactylon (C. dactylon) treatments were designed. Additionally, the grass-covered underwent two treatments: intact grass (IG) and only root (OR). The simulation experiments consisted of two types: rainfall conditions with intensities of 0.8, 1.2, and 1.8mmmin-1, and rainfall with run-on conditions with three intensities and a discharge flow rate of 15Lmin-1. The results showed that: under rainfall conditions, A. gmelinii had a higher soil loss reduction benefit (93.3%) than C. dactylon (88.5%), while the percentages reversed with A. gmelinii at 82.1% and C. dactylon at 91.9% under rainfall with run-on. Moreover, A. gmelinii exhibited higher runoff volume reduction benefits than C. dactylon under both experimental conditions, except for rainfall intensity of 0.8mmmin-1 in IG treatments. The canopy of A. gmelinii accounted for 53% to 69% of the reduction in average soil loss rate, whereas the root and canopy of C. dactylon contributed 58% and 162% under rainfall and rainfall with run-on conditions, respectively. During heavy rainfall events, vegetation could experience more severe soil and runoff loss compared to BS once its aboveground canopy was lost. Furthermore, A. gmelinii had a greater effect in reducing average velocity and increasing resistance coefficient compared to C. dactylon. Additionally, C. dactylon had twice the effect in improving shear stress and stream power than A. gmelinii. Vegetation influences slope sediment and runoff yield by modulating erosion dynamic parameters. This study can serve as a valuable reference and practical guidance for the ecological restoration of similar engineering spoil heaps in the future.

Estimating soil erosion in response to land use/cover change around Ghibe III hydroelectric dam, Southern Ethiopia

Soil erosion is a hazard in every part of the world. The small-scale farmers often grapple with low agricultural production and food insecurity. This study was conducted to estimate soil loss in response to land use/cover change in 1990, 2000, 2010, and 2020 around Ghibe hydroelectric III dam in Southern Ethiopia. The Revised Universal Soil Loss Equation (RUSLE) model was applied using a geographic information system (GIS). Digital elevation model with 30 m to determine topographic factor and supportive practice (P) factor, rainfall from the National Meteorological Institute to calculate the erosivity (R) factor, a digital soil map of the world for erodibility (K) factor, and Landsat 5TM images of 1990, 2000, 2010, and the Landsat 8 OLI of 2020 to determine trends of land use/cover change and the cover management (C) factor were employed. The raster layers of topography, cover management, rainfall erosivity, soil erodibility, and conservation techniques were processed and multiplied using the GIS platform. The overall accuracy of supervised classification was 89.89. The results showed that the percentage of cropland and built-up areas increased by 11.93 and 32.44%, respectively throughout the three study periods. Conversely, the proportion of forest land, grassland, bare land, and bushland declined by 8.2, 9.3, 10.13, 8.6%, respectively. The average annual soil loss rates increased from 30.95 t ha−1 yr−1 in 1990 to 43.85 t ha−1 yr−1in 2020. This is significantly higher than the maximum threshold rate of erosion for Ethiopian highlands (11 t ha−1 yr−1). The local government officers, non-governmental organizations, and farmers who are trained should strengthen watershed management techniques.

Reviewing the Impact of Engineering Measures on Soil Erosion in Jammu and Kashmir Anantnag Watershed

Planners now find that stopping soil loss in India's watersheds must be their top priority. Currently, a wide range of mathematical models are used worldwide to predict soil erosion. The Revised Universal Soil Loss Equation (RUSLE), which is frequently used to predict average soil loss, is one such model. Recently, there has been an increased emphasis on applying USLE/RUSLE in conjunction with Geographic Information System (GIS) technology, enabling grid-based analysis for predicting soil erosion and aiding management methods. This study assesses the efficacy of flood control and erosion management programs launched in 1914. Four different maps representing the possible erosion threats were created for four different time periods, and a comparison study was carried out to assess the changes that occurred. The implementation of various strategies such as terracing, afforestation, and rehabilitation in the watershed led to a noteworthy prediction of decreased soil loss in the watershed. In the temperate region of Jammu and Kashmir and sparsely vegetated areas, the rate of anticipated soil loss decreased from 632 to 378 metric tons per hectare per year between 1990 and 2020, indicating the efficacy of soil conservation measures in mitigating potential soil loss.

The Cross-Verification of Different Methods for Soil Erosion Assessment of Natural and Agricultural Low Slopes in the Southern Cis-Ural Region of Russia

The conventional measuring methods (runoff plots and soil morphological comparison) and models (WaTEM/SEDEM and regional model of Russian State Hydrological Institute (SHI)) were tested with regard to the Southern Cis-Ural region of Russia, along with data from rainfall simulation for assessing soil erosion. Compared with conventional methods, which require long-running field observations, using erosion models and rainfall simulation is less time-consuming and is found to be fairly accurate for assessing long-term average rates of soil erosion and deposition. In this context, 137Cs can also be used as a marker of soil redistribution on the slope. The data of soil loss and sedimentation rates obtained by using conventional measuring methods were in agreement with the data based on the used contemporary modeling approaches. According to the erosion model calculations and data on the fallout of radionuclides in the Southern Cis-Ural (54°50–25′ N and 55°44–50′ E), the average long-term annual soil losses were ~1.3 t·ha−1 yr−1 in moderate (5°) arable slopes and ~0.2 t·ha−1 yr−1 in meadows. In forests, surface erosion is negligible, or its rates are similar to the rate of soil formation of clay–illuvial chernozems. The rates of soil erosion and sediment deposition on the arable land obtained using different methods were found to be very close. All the methods, including the WaTEM/SEDEM, allowed us to measure both soil erosion and intra-slope sedimentation. The regional SHI model fairly accurately assesses soil erosion in the years when erosion events occurred; however, soil erosion as a result of snowmelt did not occur every year, which should be taken into account when modeling. The concentrations of 137Cs in the topsoil layer (0–20 cm) varied from 0.9 to 9.8 Bq·kg−1, and the 137Cs inventories were 1.6–5.1 kBq·m−2, with the highest values found under the forest. The air dose rate in the forest was higher than in open areas and above the average of 0.12 μSv·h−1 on the slope (0.1 μSv·h−1 in the meadow and 0.08 μSv·h−1 on the arable land), with the value increasing from the watershed to the lower part of the slope in all the areas. The γ-background level in the studied ecosystems did not exceed the maximum permissible levels.

Environmental Degradation Analysis of Former Bengawan Solo River Lake Ecosystem

The ecosystem of the former river section lake in the research area formed by the straightening of the river and located in the Sub-Urban area, faces significant environmental degradation such as pollution, erosion, and water shrinkage that threaten its sustainability. The magnitude of environmental degradation that occurs needs to be studied because it can result in a reduction in clean water and shallowing of the lake. Compared with lakes such as Poyang Lake in China, which has experienced a decline in water quantity and quality due to seasonal fluctuations, climate change and waste, this study offers a similar perspective by highlighting the interaction of natural and human factors, and adds a new dimension related to degradation caused by erosion. This study uses a comprehensive approach, namely by combining image analysis, field measurements using measuring sticks, USV, geodetic GPS, laboratory analysis, and interviews. The results of the study indicate that the lake water quality status ranges from "moderately polluted" to "heavily polluted," while the groundwater quality varies from "meets quality standards" to "lightly polluted." The high water quality status is caused by human activities and land conditions, as well as the high rate of erosion around the lake reaching 289.63 tons/ha/year, with an average soil loss of 0.11 tons/year. In addition, the lake in the study area has shrunk by up to 72% due to seasonal fluctuations and climate change. Based on this, effective management is needed to maintain the ecological balance and environmental health of the former river section lake.

Evaluation of WEPP and Its Comparison with USLE and MUSLE in Yozgat-Kadılı Village

The water erosion is a significant environmental issue in arid and semi-arid regions. It leads to soil degradation, reduced agricultural productivity, and desertification. This article used The WEPP, the USLE, and the MUSLE models to estimate the average soil loss in the Yozgat-Kadılı village. Also, The MUSLE model utilized the WEPP model-estimated runoff for soil loss estimation. The USLE model, which estimates soil erosion using six factors (R, K, L, S, P, and C), can be improved by incorporating the Modified Fournier Index (MFI). Results indicated that the MUSLE model (3.66 t/ha) performed well in estimating soil losses close to the observed value (3.15) in the wheat fields between 1986-1996. the MUSLE (5.31 t/ha) and WEPP (5.88 t/ha) models underestimated soil losses to the observed value (8.75 t/ha) in the fallow field for 1986-1996. The WEPP model estimated the highest average soil loss at 5.18 t/ha in a wheat field, while the USLE model yielded the lowest estimate at 1.28 t/ha between 1969 and 2020. The MUSLE model estimated the highest (4.94 t/ha) and The USLE model estimated the lowest (2.53 t/ha) soil loss in the fallow field between 1969-2020. Results also revealed that the WEPP model is needed to calibrate for estimating soil loss in arid and semi-arid regions.

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.

Exploring soil erosion and reservoir sedimentation through the RUSLE model and bathymetric survey

The aim of the paper was to compare the soil erosion in a river catchment with the sediment volume accumulated at the river mouth. Firstly, the sediment yield was estimated in GIS based on the soil loss according to the RUSLE model, and then further integrated into the sediment production equation. Following this, we estimated the sediment volume accumulated at the river mouth based on the diachronic overlap of topographic and bathymetric data. This methodology was validated for the Eselnita catchment exiting into the Iron Gates I Reservoir. The LS factor has an average value of 4, with lower values for the forest cover. The C factor has an average value of 0.057 being statistically correlated with the RUSLE result. The average soil loss was estimated at approximately 1.89 t ha−1 yr −1, a value that is validated by previous studies as a low risk of erosion at national scale. The sediment transfer model indicates a distribution of cells sediment production strongly correlated with the time travel to the discharge channels. Overall, the sediment volume obtained by using the RUSLE model corresponds to about 70% of the sediment volume accumulated at the river mouth during 53 years (1970–2022). The difference in sedimentation may be due to human activities along the river mouth's banks to extend the built-up area and to enjoy the waterscape. This paper is relevant for the topic of reservoir sedimentation and recommends the use of the RUSLE model to predict the sediment contribution, especially for small ungauged catchments.

Harmonizing models and measurements: Assessing soil erosion through RUSLE model.

Soil erosion poses significant ecological and socioeconomic challenges, driven by factors such as inappropriate land use, extreme rainfall events, deforestation, farming methods, and climate change. This study focuses on the Kozhikode district in Kerala, South India, which has seen increased vulnerability to soil erosion due to its unique geographical characteristics, increase in extreme events, and recent land use trends. The research employs RUSLE (Revised Universal Soil Loss Equation), considering multiple contributing factors such as rainfall erosivity (R), slope length and steepness (LS), cover management (C), conservation practices (P), and soil erodibility (K). The study is unique and novel, since it integrates extensive field data collected from agricultural plots across Kozhikode with the RUSLE model predictions, providing a more accurate and context-specific understanding of soil erosion processes and also suggesting management strategies based on risk priority. The study found that Kozhikode experiences an average annual soil loss of 28.7 tons per hectare. A spatial analysis revealed varying erosion risk levels across the district. 52.0% of the area experiences very slight erosion, 10.31% has slight erosion, 6.18% undergoes moderate erosion, 3.88% is moderately severe, 7.34% is at severe erosion risk, 5.6% has very severe erosion, and 14.65% faces extremely severe erosion. Field data collected from agricultural plots across Kozhikode were compared with RUSLE-predicted values, revealing a low root mean square error, indicating a strong correlation between observed and simulated data. Based on these findings, the district was categorized into low, medium, and high-priority regions, with tailored recommendations proposed for each. Implementing these measures could mitigate erosion, preserve soil fertility, and support the long-term sustainability of natural and agricultural ecosystems in Kozhikode. Given the practical challenges in estimating RUSLE factors in Southern India, where data scarcity is a common issue, this preliminary study underscores the need for expanded, long-term field observations to enhance understanding of soil erosion processes at the watershed level.

Estimation of soil loss using RUSLE model and GIS tools: Case study in the Jucusbamba Micro-Watershed (Amazonas, NW Peru)

Human activities have intensified soil erosion globally, negatively impacting the physical, chemical, and microbiological quality of water and soil. This study estimated soil loss in the Jucusbamba Micro-Watershed (Amazonas, northwestern Peru) using the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information Systems (GIS) and remote sensing (RS) data. Meteorological data, soil maps, digital elevation models, and land cover and use maps were integrated into a GIS environment to predict the spatial distribution of erosion. The results showed five classes of soil loss severity: slight (93.34%), moderate (3.94%), high (1.82%), very high (0.61%), and severe (0.29%). Areas with high, very high, and severe erosion levels were mainly located in the middle and lower parts of the micro-watershed. The average annual soil loss was estimated at 23.24 t/ha/year. The information obtained is crucial for the formulation of soil management plans and programs to address erosion problems in the Jucusbamba River Micro-Watershed. Future research should focus on validating these models through field studies and implementing soil conservation practices based on these findings. Keywords: Amazonas, hydrology, RUSLE model, water erosion map, watershed.

Controlling soil erosion and landslides through ecosystem-based adaptation interventions in the hilly landscape of western Rwanda

Ecosystem-based Adaptation interventions such as protective vegetation, soil and water conservation measures and re-vegetation of degraded land have shown promise in reducing soil erosion and landslides occurrence. The western province of Rwanda has experienced destructive natural hazards especially soil erosions, floods and landslides. This study aimed to assess the contribution of Ecosystem-based Adaptation interventions on the reduction of soil erosion and landslides in the hilly landscape of Western Rwanda with a case study of Rubyiro sub-catchment in Rusizi District. Methods used in data collection comprised remote sensing techniques combined with a questionnaire survey to collect perceptions of farmers conducting agricultural activities in the catchment where Rusizi District has implemented Ecosystem-based Adaptation (EbA) interventions. The Revised Universal Soil Loss Equation (RUSLE) model combined with Geographic Information System (GIS) and remote sensing tools were used to assess soil loss pre- and post-EbA interventions. The results of the survey indicated that after four years of EbA interventions, the number of landslide occurrences was reduced at a rate of 62.6 %. The respondents who appreciated forest restoration to minimize landslides were 72.4 %, progressive terraces 26.1 % and bench terraces 1.5 %. The estimated average annual soil losses were 11.9 tons/ha/year, 17.6 tons/ha/year, 10.1 tons/ha/year, 9.3 tons/ha/year in 2017, 2018, 2021 and 2022, respectively. This indicates a reduction of 8.3 tons/ha/year from 2018 to 2022 as opposed to an increase of 5.7 tons/ha/year recorded from 2017 to 2018. Thus, EbA interventions made a great contribution to the reduction of soil erosion and landslides in the Rubyiro sub-catchment, and they can be recommended in other similar hilly landscapes.

Assessing monthly dynamics of agricultural soil erosion risk in Poland

Soil erosion in agricultural landscapes poses a significant threat to soil health and productivity. This study investigates the dynamics of soil erosion across agricultural lands in Poland at monthly scale using the Revised Universal Soil Loss Equation (RUSLE) model. The study utilizes the Global Rainfall Erosivity Dataset (GLOREDA), which provides the most up-to-date and highest resolution rainfall erosivity (R) values, derived from 10-min resolution rainfall records. Additionally, satellite imagery spanning 2003 to 2023 was leveraged to estimate the cover-management (C) factor, capturing the spatial and temporal dynamics of vegetation cover and agricultural practices. Results reveal significant spatio-temporal variations in soil erosion rates, with peak erosion occurring during the summer months following crop harvesting, despite not aligning precisely with peak rainfall erosivity. The lowest erosion rates are observed during the winter seasons, attributed to minimal rainfall erosivity. The findings highlight the critical role of agricultural practices, particularly the timing of crop harvesting and temporary exposure of bare soil, in driving soil erosion dynamics in Poland's agricultural landscapes. Specifically, the average annual soil loss for agricultural areas in Poland was determined to be 0.27 t ha−1 yr−1, with peak monthly soil erosion rates reaching up to 0.08 t ha−1 yr−1 in August. Total monthly soil loss from agricultural lands in Poland was estimated to be approximately 4.87 Mt. annually, with 68 % of the total annual soil loss occurring during the summer months. This study contributes valuable insights into understanding and managing soil erosion risks in agricultural systems, aiding in the development of targeted soil conservation strategies and sustainable land management practices.

Evaluation of soil erosion rate using geospatial techniques for enhancing soil conservation efforts

According to reports, Ethiopia is one of the countries in sub-Saharan Africa with the worst affected by soil erosion. It has both on-site and off-site consequences on biophysical and socioeconomic settings in an area. The study area is heavily affected by soil erosion forming diverse erosion structures, particularly in the upper course of the watershed. Hence, this work seeks to estimate the geographically distributed annual soil loss rate and mapping of soil erosion hazard hotspot areas in the watershed using the Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions. The RUSLE parameters, such as rainfall erosion factor (R-factor), soil erodibility factor (K-factor), slope steepness and slope length factor (LS-factor), land cover factor (C-factor), and conservation practice factor (P-factor) were considered as data input for the analysis to quantify the soil loss rate in the study area. A digital elevation model (DEM) with a 12.5 × 12.5-meter resolution was employed for catchment delineation and determination of the LS factor.The mean yearly rainfall data from the surrounding rain gauge stations was used to analyze the R-factor. The results of the current conditions showed that the average typical soil loss rate from the entire watershed is 23.8 t ha-1 yr-1, and the quantity of soil loss from the study area ranged from 0 to 776.71tan /ha-1 yr-1. Nonetheless, Tiro Afeta experiences mean soil erosion at a rate of roughly 50.2 t ha-1 yr-1, exceeding the acceptable threshold of 11 t ha-1 yr-1. Determining the sustainability of soil production requires assessment, particularly in cases where significant yearly soil erosion occurs. Due to intensive agricultural activities in the Xiro Afeta watershed, significant soil erosion is predominantly occurring in thissteep upper region. Consequently, this area urgently requires appropriate soil protection measures.

Effect of Tillage, Crops Residues and Crops Management Practices on Runoff Erosion, Soil Loss and Soil Properties in Ethiopa: Review

The conducted investigations showed that tillage practices with crop residue and proper cropping systems protect loss of soil from runoff erosion which depletes soil nutrients and affects soil physical and chemical properties. The review was conducted with aim of reviewing the effect of tillage, crops residues and crops management practices on runoff, soil loss and soil properties in Ethiopia. The three years study conducted in the Upper Blue Nile basin of Northwestern Ethiopia showed that reduced tillage reduced soil loss over conventional tillage, row planting reduced soil loss over broadcast planting, without trampling reduced soil loss over with trampling planting, and the sediment concentration was ranged from 0.01 to 5.37g/L and total soil loss was 0.20 to 0.50t/ha. The study conducted in the humid highlands of Ethiopia showed that the lower average soil loss was 16 t/ha.yr under zero tillage with crop residue and maximum was 30 t/ha.yr in conventional tillage without crop residue. The investigation indicated that zero tillage with maize soya bean intercrop, maize rotation, continuous maize and continuous soya bean improved soil properties than conventional tillage system. The investigation which was carried out to evaluate the effects of tillage and cropping system on soil properties showed that enrichment ratio ≤1 under no tillage with intercropping and no tillage with mulch reduce nutrient losses and enrichment ratio. The study conducted at Derashe and Arba Minch Zuriya in Ethiopia showed that some selected properties were statistically significant (P<0.05) and conservation tillage is favored for soil management relative to conventional tillage. Therefore, tillage practices like zero tillage and minimum tillage with crop residue management like mulching and crop management such as intercropping and crop rotation reduce surface runoff erosion, soil loss and soil fertility depletion, but additional continual research is needed to reveal trends in tillage, crops residues and crops management.

Sustainable Land Management for Mitigating Soil Erosion at the Catchment Scale

This study addresses this challenge by focusing on the Revised Universal Soil Loss Equation (RUSLE) to combat excessive soil erosion rates within the Kayacık Dam Basin, located in the semi-arid region of the Tigris-Euphrates Basin in Türkiye. The primary objective is to maintain an average annual soil loss of no more than 10 tons per hectare. To achieve this, the RUSLE model is employed to evaluate sustainable land management (SLM) strategies. These strategies encompass agronomic, vegetative, and structural measures, all of which are intricately linked to RUSLE's C and P factors. Spatial analysis reveals that severe erosion (10-20 t ha-1 y-1) is predominantly concentrated in agricultural areas, spanning 2536.37 hectares. In contrast, very severe erosion (>20 t ha-1 y-1) affects 834.13 hectares of grassland. Statistical analyses underscore the significant contributions of various model factors to predicted soil losses (A). LS, C, K, and R factors account for 80.24%, 44.68%, 0.97%, and 0.27% of the effect, respectively. Remarkably, topography exerts the most substantial influence on agriculture, pasture, and forest/other land uses, contributing 84.46%, 57.29%, and 39.27% to the variation, respectively. These findings highlight the pivotal role of effective agronomic and vegetative practices in ecosystems management, especially within steep-slope landscapes encompassing agriculture, grassland, and forest. Furthermore, the semi-arid regions under investigation contend with the intricate interplay of heightened drought risk and the ramifications of intensive irrigated agriculture on soil erosion. This complex dynamic presents distinct challenges for implementing SLM strategies in the face of evolving climatic conditions and underscores the need for climate-resilient solutions.

Predicting soil erosion risk using the revised universal soil loss equation (RUSLE) model and geo‐spatial methods

AbstractAnthropogenic activities like overgrazing, deforestation and mismanaged land use accelerate soil erosion (SE), causing nutritional and organic matter loss. In this study, we predicted the annual rate of soil loss in the Salt Range, extending south from the Pothohar plateau, Pakistan, using the Revised Universal Soil Loss Equation (RUSLE). The RUSLE model parameters and erosion probability zones were estimated using remote sensing and Geo‐Spatial methods. The annual average soil loss rates were calculated by considering five geo‐environmental factors, that is, slope length and steepness (LS), rainfall erosivity (R), cover management (C), soil erodibility (K), and conservation practice (P) range from 0–559 527, 1404–4431, 0–1, −0.14 to 1.64, and 0.2–122 respectively. This research determined that the yearly average rate of SE in the Salt Range varies from over 50 to above 350 . The distribution of land area across different SE probability zones reveals that a small portion (2.11%) is classified as High, a moderate portion (7.13%) falls under the category of Moderate, while the majority (90.7%) is classified as Low in terms of proneness towards erosion. The land devoid of vegetation and characterized by steep slopes is especially prone to SE. The Salt Range is highly vulnerable to SE risk due to climatic variations and improper land use practices. The result provides a spatial distribution of SE across the salt range, utilized for management planning processes and conservation at the policy level among decision‐makers and land‐use planners.