Soil Loss Rates Research Articles

Estimation of climate and watershed management-induced potential soil loss using the USLE in Demjer watershed, Blue Nile basin, Ethiopia

ABSTRACT This study aimed to predict future soil loss under different climatic scenarios in the Demjer watershed, Blue Nile River Basin. The soil loss was calculated using USLE. The GCMs derived under the RCP4.5 and RCP8.5 for the period 2020–2049 were used. Three LULC scenarios were considered and the projection of the change in rainfall was estimated under the RCP4.5 and RCP8.5 scenarios. The projected mean annual precipitation increased by 6.42 and 5.95% under the RCP4.5 and RCP8.5 scenarios, respectively. The soil loss rate in the future ranged from 0 to 144.7 t ha−1y−1 and from 0 to 142.4 t ha−1y−1 for RCP4.5 and RCP8.5, respectively. Compared to the base period, the soil loss rates increased by 7.6% (RCP4.5) and 7.4% (RCP8.5). This is attributed to increase in rainfall erosivity. The LULC scenario is a major variable in reducing soil erosion rates in the future. That means, soil loss would reduce up to 33.6% of the present soil loss rate, if all the current cultivated lands with slopes >35% are covered by plantations and if open grazing land controlled. Estimation of future soil loss risk could provide evidence for preparing site-specific conservation plans, thereby enabling sustainable use of land.

Soil erosion assessment and identification of erosion hotspot areas in the upper Tekeze Basin, Northern Ethiopia

Soil erosion is a major environmental problem in Ethiopia, reducing topsoil and agricultural land productivity. Soil loss estimation is a critical component of sustainable land management practices because it provides important information about soil erosion hotspot areas and prioritizes areas that require immediate management interventions. This study integrates the Revised Universal Soil Loss Equation (RUSLE) with Google Earth Engine (GEE) to estimate soil erosion rates and map soil erosion in the Upper Tekeze Basin, Northern Ethiopia. SoilGrids250 m, CHIRPS-V2, SRTM-V3, MERIT Hydrograph, NDVI from sentinel collections and land use land cover (LULC) data were accessed and processed in the GEE Platform. LULC was classified using Random forest (RF) classification algorithm in the GEE platform. Landsat surface reflectance images from Landsat 8 Operational land imager (OLI) sensors (2021) was used for LULC classification. Besides, different auxiliary data were utilized to improve the classification accuracy. Using the RUSLE-GEE framework, we analyzed the soil loss rate in different agroecologies and LULC types in the upper Tekeze basin in Waghimra zone. The results showed that the average soil loss rate in the Upper Tekeze basin is 25.5 t ha−1 yr−1. About 63 % of the basin is experiencing soil erosion above the maximum tolerable rate, which should be targeted for land management interventions. Specifically, 55 % of the study area, which is covered by unprotected shrubland is experiencing mean annual soil loss of 34.75 t ha−1 yr−1 indicating the need for immediate soil conservation intervention. The study also revealed evidence that this high mean soil loss rate of the basin can be reduced to a tolerable rate by implementing integrative watershed management and exclosures. Furthermore, this study demonstrated that GEE could be a good source of datasets and a computing platform for RUSLE, in particular for data scarce semi-arid and arid environments. The results from this study are reliable for decision-making for rapid soil erosion assessment and intervention prioritization.

Mapping and quantifying medium-term soil loss rates in mountain olive groves using unmanned aerial vehicle technology

Olive groves are one of the main agroecosystems in the Mediterranean region, but water erosion, aggravated by inappropriate soil management, is compromising the environmental sustainability of these crops. National and international public organisations, including the European Union via its Common Agricultural Policy, have acknowledged the problem and recognise the need to quantify the effects of this process. However, the variability of currently available short-term soil erosion measurements, together with limited understanding of the underlying processes, mean there is considerable uncertainty about the long-term effects of soil erosion. This paper presents an innovative procedure called SERHOLIVE4.0 designed to measure and model long-term soil erosion rates in olive groves, by means of structure-from-motion (SfM) techniques by which image information is obtained from unmanned aerial vehicles (UAVs). For the present study, the procedure was evaluated in mountain olive groves, where the erosion rate was calculated from historical surface reconstructions. Overall, this approach was found to be practical and effective. The method includes the following steps: [1] measure the current relief using UAV technology; [2] reconstruct the historical relief from field measurements; [3] calculate soil truncation (h) and obtain a soil erosion rate map; [4] determine the erosive dynamics of the slope and establish the relation between tree truncation, slope and mounds. The method we describe presents the following advantages:•it quantifies soil losses by reference to existing tree mounds;•it is straightforward to apply;•its application enhances the calibration of erosion models.

Modelling, quantification and estimation of the soil water erosion using the Revised Universal Soil Loss Equation with Sediment Delivery Ratio and the analytic hierarchy process models

AbstractThis research used the Revised Universal Soil Loss Equation (RUSLE) with Sediment Delivery Ratio (SDR) model. The analytic hierarchy process (AHP) method, while also incorporating the use of a geographic information system (GIS) and remote sensing (RS) to predict the annual soil loss rate and spatialise the processes of water erosion at the scale of the Loukkos Watershed, Morocco. The RUSLE model and AHP parameters were estimated using RS data, and the erosion vulnerability zones were determined using GIS. We used five parameters, including precipitation erosivity, soil erodibility, slope length and steepness, vegetation cover, and soil erosion control practices in the RUSLE. For the AHP technique, we used seven geo‐environmental factors, including annual average precipitation, drainage density, lineament density, slope, soil texture, land use/land cover and landform maps. The results of RUSLE indicated that the average annual soil loss varied from 0 to 2388.27 . The total estimated annual potential soil loss was approximately 40 790 220.11 , and a sediment yield estimated by RUSLE‐SDR was 8 647 526.66 , equivalent to 6.65 Mm3. This value is very close to the measured value of 6.81 Mm3, for a difference of 0.16 Mm3. Furthermore, the results of the AHP indicate that the soil erosion potential index varies from 0 to 0.205315 . Overall, nearly 13.7% of the area suffered from severe soil erosion exceeding 50 . Approximately 80% of the Loukkos Watershed area experienced only slight erosion, while the remaining 6% incurred moderate erosion. Integrating GIS and RS into the RUSLE model and AHP helped us robustly estimate the extent and degree of erosion risk. Territorial decision‐makers should adopt our results to develop soil conservation strategies, water management plans and other necessary soil and water conservation measures for this region.

Quantifying soil erosion and soil organic carbon conservation services in indian forests: A RUSLE-SDR and GIS-based assessment

Indian forests, having sixteen types of vegetation, provide various ecosystem services. Forests reduce water erosion of soil, reduce floods and conserve low river flow during dry seasons. Present study estimated annual sedimentation, texture, soil organic carbon control service of forests of India using the Revised Universal Soil Loss Equation (RUSLE) and Sediment Delivery Ratio (SDR) approach through GIS technique along with identifying important drivers responsible for erosion in forests. The soil erosion control service was based on five factors viz., rainfall erosivity, soil erodibility, slope, crop management, conservation practice factor and SDR across the various forest dominated river basins. Geo-detector modelling was performed to evaluate environmental drivers responsible for soil erosion. Valuation of soil control service of the India’s forests was estimated based on damage and replacement cost method. Annual soil loss rate was maximum in Tropical Thorn Forest and in Ganga River basin. Maximum sediment control and SOC conservation against the soil erosion control service by India’ forests were due to Tropical Dry Deciduous Forest with a total annual sedimentation control and SOC conservation of 33,056,560 tonnes and 3,31,115.06 tonnes, respectively. The conservative estimate of the economic value of soil conservation service by the forests of India was US$ 535.6 M with an average of 4.40 US$ ha−1 and a maximum share of value for Tropical Dry Deciduous Forest i.e. 294.18 million US$ and average maximum value for Littoral and Swamp Forest (28.91 US$ ha−1). The soil erosion in Tropical and Sub-tropical Forest was influenced by the interactive effects between NDVI and Bulk Density. In contrast, soil erosion in the temperate and alpine area was influenced by anthropogenic activity in combination with climatic factors. Present study accounts the role of India’s forests for the soil conservation service and may provide inputs to implement forest and reservoir management strategies besides providing information for Integrated Watershed management and Catchment Treatment Plans.

High-resolution soil erosion mapping in croplands via Sentinel-2 bare soil imaging and a two-step classification approach

Erosion-induced lateral soil redistribution leads to spatially heterogenous soil composition, which can be captured through the distinctive spectral reflectance of soils under varying levels of erosion influence. This points to the potential of using remotely sensed soil spectra to detect severe erosion and deposition hotspots in exposed croplands and, importantly, further differentiate the intra-class spectral variability of moderate erosion that often occupies the largest proportion. Here, we aim to develop a two-step erosion classification and mapping approach based on multitemporal compositing of Sentinel-2 bare soil images of a typical agricultural region (11,500 km2) of northeast China. A random forest classifier was firstly trained against the ground-truth data derived from very high resolution (VHR) imagery in Google Earth, with an overall accuracy of 91 % that allowed for clear delineation of severe erosion and deposition areas based on their distinct topographic and spectral features particularly in the red and red-edge bands. In the second step, the remaining area of moderate erosion (60.30 %) was further differentiated using Iterative Self-Organizing cluster unsupervised classification to yield a five-class soil erosion map at 10 m spatial resolution. The accuracy of the predicted map was successfully validated by independent Caesium-137 (137Cs) and soil organic carbon observations at catchment and regional scales, as revealed by significant inter-class differences in soil redistribution rates estimated from 137Cs inventory. The severe erosion class had a soil loss rate of 5.5 mm yr−1, suggesting that previous assessments have underestimated erosion severity. The spatial accordance of crop growth with soil erosion intensity, particularly in localized settings, further highlighted the potential of bare soil imaging for mapping the spatiotemporal development of soil erosion and its response to targeted sustainable cropland management efforts.

Rainfall intensity profile induced changes in surface‒subsurface flow and soil loss as influenced by surface cover type: A long-term in situ field study

Due to global warming, changes in the rainfall intensity profile (i.e., the temporal intensity distribution within a rainfall event) increase the difficulty of accurate erosion prediction and control. Surface cover has been widely used as a critical measure to control soil erosion worldwide. However, the effects of the rainfall intensity profile (RIP) on soil erosion under different surface covers are not fully understood. In this study, long-term in situ field observations of the rain hyetograph, surface runoff coefficient (SRC), subsurface flow rate (SFR), and soil loss rate (SLR) from bare land, litter cover and grass cover were conducted over 11 consecutive years in the red soil hilly region of southern China. According to the occurrence time of the most intense rainfall, 226 erosive events were classified into four RIP patterns: advanced, intermediate, delayed, and uniform patterns. The results indicated that the advanced pattern with short duration–high intensity and the delayed pattern with long duration–high depth contributed to 73.45% of the total erosive events. For bare land, advanced events were the dominant pattern producing surface runoff and soil erosion, accounting for 57.24% and 75.17%, respectively, of the total surface runoff and erosion. The average SRC and SLR from the advanced pattern were 1.29–2.42 times and 2.52–39.78 times greater than those from the other patterns, respectively. The delayed pattern contributed to subsurface flow, and the average SFR was 1.27–2.17 times greater than that of the other patterns. Furthermore, surface cover significantly reduced surface runoff and erosion and increased subsurface flow, especially under the advanced pattern. Both surface cover measures were equally effective in controlling surface runoff and erosion, but the increase in subsurface flow caused by litter cover was 1.38–2.67 times greater than that caused by grass cover. Advanced pattern events increase the erosion risk on red soil slopes, and surface cover effectively weakens the effect of variation in the RIP pattern on soil erosion. Moreover, surface cover significantly alters the surface‒subsurface flow distribution pattern for all the RIP patterns. This study highlights the crucial importance of rain intensity profiles on water erosion and provides a basis for optimizing measures to effectively control soil and water loss under climate change.

Morphometric Characteristics of the Lower Orashi River, Niger Delta Region, Nigeria

The study examined the spatial analysis of the morphometric characteristics of the Lower Orashi River, Niger Delta Region, Nigeria. The river course was segmented into 30 equal distances of 4.8m from each other and at each point, the morphometric parameters like width, depth, and flow velocity. The discharge was measured from these parameters. Descriptive and inferential statistics were employed for data analysis while results are presented using tables and graphs. Results showed that width of the river ranged from 77.90m to 2788.00m with the mean width of 318.83m. The depth ranged from 2.10 to 7.60m with the mean depth recording 4.14m as it was higher at the upper section of the river while it becomes lower as it is entering the Atlantic Ocean. Furthermore, width was significantly correlated with the depth (r= -0.556, p<0.05), cross sectional area (r= 0.989, p<0.05) and discharge (r= 0.987, p<0.05). Also, elevation was significantly correlated with cross sectional area (r= -0.506, p<0.05) and discharge (r = -0.511, p<0.05). More importantly, the cross sectional area was correlated with discharge (r=0.995, p<0.05). The study concluded that there is significant variation existing in the morphometric parameters namely width, elevation, cross sectional area and discharge among the segments along Orashi River. The study therefore recommended that the water course should be reduced of human activities to reduce the rate of soil loss or discharge and to boost the river floor with adequate morphological property.

Estimation of Soil Loss in the Nanoi River Basin using Geospatial Techniques

Objectives: The main purpose of this research is to identify severe soil loss areas in the Nanoi river basin of Assam, India to suggest appropriate soil management planning in the river basin. Methods: The Revised Universal Soil Loss Equation (RUSLE) integrates geospatial technologies to assess overall soil loss in the Nanoi river basin which provides a faster and more accurate estimation. It is possible to understand soil erosion patterns more thoroughly using RUSLE which makes sustainable soil management easier. Findings: According to the RUSLE equation, the Nanoi river basin experiences an estimated total soil loss of 18,562.5 tons per year, with an average annual soil loss of 0.32 t/h/y. This suggests that approximately 0.64 km2 of the area falls into the Moderate, high and Extreme soil erosion sensitivity zones. Furthermore, a final map is generated to display different areas with varying levels of soil loss rates. Novelty: The geospatial approaches used produce precise findings at a reasonable price and demonstrate the severity of soil loss in the river basin. If soil loss continues at the current rate, there is a high likelihood that certain areas on both sides of the river, particularly in the downstream region of the basin, will experience fluvial hazards, such as drainage congestion and floods. Hence, the results generated will be helpful in the management practices of the river basin. Keywords: Soil loss, Soil erosion, Geospatial, Revised universal soil loss equation, River basin

Perennial Baki™ Bean Safety for Human Consumption: Evidence from an Analysis of Heavy Metals, Folate, Canavanine, Mycotoxins, Microorganisms and Pesticides.

Global food production relies on annual grain crops. The reliability and productivity of these crops are threatened by adaptations to climate change and unsustainable rates of soil loss associated with their cultivation. Perennial grain crops, which do not require planting every year, have been proposed as a transformative solution to these challenges. Perennial grain crops typically rely on wild species as direct domesticates or as sources of perenniality in hybridization with annual grains. Onobrychis spp. (sainfoins) are a genus of perennial legumes domesticated as ancient forages. Baki™ bean is the tradename for pulses derived from sainfoins, with ongoing domestication underway to extend demonstrated benefits to sustainable agriculture. This study contributes to a growing body of evidence characterizing the nutritional quality of Baki™ bean. Through two studies, we investigated the safety of Baki™ bean for human consumption. We quantified heavy metals, folate, and canavanine for samples from commercial seed producers, and we quantified levels of mycotoxins, microorganisms, and pesticides in samples from a single year and seed producer, representing different varieties and production locations. The investigated analytes were not detectable or occurred at levels that do not pose a significant safety risk. Overall, this study supports the safety of Baki™ bean for human consumption as a novel pulse crop.

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.

Ecological flexible protection method of expansive soil slope under rainfall

In this study, a new ecological slope protection method—Anchor Reinforced Vegetation System (ARVS) was applied to the newly excavated expansive soil slope. To explore the effect and mechanism of ARVS protection of newly excavated expansive soil slopes, expansive soil slopes with three different protection methods (bare slopes, grassed slopes, and ARVS slopes) were built. The continuous natural rainfall test and artificial rainfall tests were carried out. The results show that: compared with the bare slope and the grassed slope, ARVS could effectively adjust the moisture and heat balance of newly excavated expansive soil slopes and achieve a satisfactory soil and water conservation performance. Under different rainfall intensities, the runoff and soil loss rates of the ARVS-protected slope were smallest. Under the combined action of vegetation, high-performance turf reinforcement mats (HPTRMs) and anchors, the ARVS provided a superior erosion resistance. The higher the rainfall intensity is, the more significant the anti-erosion effect of the ARVS compared to that of grass protection technology. The ARVS could also effectively limit vertical and horizontal deformation of newly excavated expansive soil slopes. Therefore, the ARVS could effectively reduce the negative influences of the atmospheric environment on newly excavated expansive soil slopes and provide a new solution for shallow protection of newly excavated expansive soil slopes.

Comparison of SWAT and WEPP for Modeling Annual Runoff and Sediment Yield in Agewu - Mariyam Watershed, Northern Ethiopia

The Soil and Water Assessment Tool (SWAT) and the Geographic Water Erosion Prediction Project (Geo-WEPP) were applied to compare modeling of annual runoff and sediment yield in the Agewmariam watershed, eastern Amhara Region, Ethiopia. Spatial and temporal data distributions were required as inputs to run both models. Soil texture and other soil properties were measured in the field and in the laboratory, and soil maps were generated from global digital soil maps. Land use maps were created by manually digitizing Google Earth images. Watersheds were defined using watershed DEMs and gradient maps were created for each runoff event. Runoff samples were collected and analyzed for sediment concentrations in the laboratory; average annual runoff and sediment volumes were estimated using the WEPP and SWAT models. The results were satisfactory compared to the observed values, with R2 values of 0.86 and 0.91 for the SWAT and WEPP models, respectively, and NSE values of 0.54 and 0.71 for the monthly runoff. The estimated annual mean runoff and sediment yield at the watershed outlets were 65.54 mm, 146.14 mm, 43t/ha/yr and 41.7t/ha/yr for the WEPP and SWAT models, respectively. Several sub watersheds were determined to be susceptible to soil erosion and were prioritized, so more attention was given to this area to reduce runoff and soil erosion. Therefore, the SWAT and WEPP models were suitable for estimating annual runoff and sediment volumes. Sediment yields simulated from both models were high and alarming and far exceeded the allowable rate of soil loss.

Serra da Canastra National Park: Influence of forest fires on the RUSLE C factor and its impact on water erosion

The adverse impacts of soil degradation and nutrient loss resulting from water erosion are significant environmental concerns that have profound implications for both water quality and biodiversity. This study aims to evaluate the impact of forest fires on soil loss through water erosion in the Serra da Canastra National Park, in Minas Gerais state, Brazil. Using the Revised Universal Soil Loss Equation (RUSLE), which considers rainfall erosivity, soil erodibility, slope length and slope and vegetation cover, the C factor (vegetation cover) values were obtained from data from literature and methods based on the Normalized Differential Vegetation Index (NDVI). Validation was carried out using data on total sediment, water flow and daily runoff from the hydrosedimentological station and the InVEST software. The results highlight the significant impact of wildfires on soil loss through water erosion and indicate that areas recently affected by wildfires, especially on steep slopes and with more erodible soils, are subject to the highest rates of soil loss. Soil loss rates varied from 0.75 to 12.55 Mg ha-1 yr-1, in part due to the different ways of obtaining factor C. The research emphasizes the need to conserve vegetation cover to prevent soil erosion, particularly in regions impacted by forest fires. This study offers valuable insights that can contribute to enhancing the sustainable environmental management of the Serra da Canastra National Park.

Unraveling soil filling and transport in fissures on karst slopes using multiple tracers

The fragile ecological environment and unique surface–subsurface geological duality of karst regions have led to complex processes and rates of underground soil loss, which is subject to much controversy. However, to ensure the ecological sustainability of karst areas, it is imperative to address this issue systematically using innovative study methods. With focuses on ten fissures and fivecross-sections in a typical karst area in southwestern China, this study applied unmanned aerial vehicles for field surveys and indoor modeling techniques to investigate the distribution density of fissures in typical karst areas, which is crucial for calculating underground soil loss. By measuring magnetic susceptibility, organic carbon content, and particle size of fissure soils, the primary sources of soil in the fissures were identified. Additionally, the rate of soil loss passing through karst fissure was calculated using 137Cs tracing and 14C dating techniques. Results indicate that (1) the proportion of fissure area per square kilometer of land is 1.59 %; (2) the soil in the fissures is mainly filled with the topsoil outside the fissures, and (3) the average rate of soil filling into the fissures is 16.13 t km−2 yr−1, account for only 5.8 % of the total soil erosion modulus. The study shows that soil filling into fissures is the main process of underground soil loss on karst slopes, and the rate of soil loss through fissures is very small. This study offers valuable insights into soil movement processes and quantification of soil erosion in karst regions, thus aiding in the preservation and sustainable management of these unique ecosystems.

Does century-old biochar affect soil interrill erodibility on cropland soils? A study on pre-industrial kiln sites

Adding biochar to soils is being advocated to mitigate soil erosion. However, given biochar aging and persistency in soils, the effects of biochar on soil in the long-term are important to investigate yet remain largely unknown. The objective was therefore to determine the long-term effect of biochar on interrill erosion on cropland soils. Experiments were conducted using topsoil from three fields of different textures (silt loam, loam and sandy loam). Each field was characterized by the presence of kiln sites containing century-old charcoal used as proxy to investigate the long-term impact of biochar. Aggregate stability was measured using the method of Le Bissonnais (1996), whereas interrill erosion was studied using two successive (24-h apart) rainfall simulation experiments (84 mm h−1, 90 min.). The presence of historical charcoal in kiln sites did not affect soil aggregate stability, irrespective of charcoal-C content or soil type. For the first rainfall simulation only, the century-old charcoal reduced both the final runoff and soil loss rates by, respectively, 15.4 mm h−1 and 12.1 g m−2 h−1 for each percent increase in charcoal-C content. As a result, Meyer’s interrill erodibility decreased with increasing charcoal-C content. However, because the final runoff and soil loss rates decreased to a similar extent with increasing charcoal-C content, Kinnell’s interrill erodibility was unaffected by charcoal-C content. These effects on interrill erosion parameters were independent of soil type and could not be related to changes in soil chemical properties. The measured reduction in runoff and soil loss were attributed to delayed crust development, which could be related to increasing proportions of clods in the soil samples with increasing charcoal-C content. Further research may be needed to confirm the observed trends and underlying mechanisms over a wider range of soil types.

Effect of rainfall parameters on soil erosion in Chwalimski Brook catchment, NW Poland

Soil erosion by water is one of the most important factors affecting contemporary landscape changes within the lowland geoecosystems in Central Europe. Soil erosion mainly depends on rainfall (especially its intensity and erosivity), length of slope and its inclination, type of cultivation and usage of the land, antierosion treatments, and susceptibility of soils to erosion. The main goal of this research was to evaluate the impact of rainfall on soil erosion processes. This was realized by stationery observations and quantitative research conducted within the Chwalimski Brook catchment (NW Poland) since the early 90s. Additionally, the rainfall characteristics such as intensity, kinetic energy, and erosivity (represented by the rainfall erosivity indices EI5, EI10, EI15, EI20, EI30 and EI60) were computed. The presented results contain data on runoff, soil loss, and rainfall collected at a testing plot over 16 years (2001–2016 hydrological years). Annual rainfall erosivity (EI30) ranged from 144.7 to 782.1 MJ mm ha−1 h−1, precipitation totals varied from 524.9 to 919.7 mm, and soil loss ranged from 0.074 to 4.471 kg m−2. The greatest rates of soil loss were established in the most rainy years, although significant soil loss also occurred in below-average rainfall years, such as in 2013 and 2014. Consequently, the achieved results show that annual soil erosion primarily depends on individual rainfall and erosive events. Hence, the magnitude of soil erosion cannot be solely estimated based on the rainfall totals, but it is also necessary to consider the intensity and erosivity of each rainfall event.

Effects of Landscape Fragmentation on Soil Loss in the Cerrado Biome, Brazil

Soil loss stands as a critical global challenge, posing economic and environmental threats to soil and water conservation. This study aimed to assess the impact of landscape changes on soil loss in the Descoberto River basin, encompassing 62 watersheds in the Cerrado biome in central Brazil. We analysed a 32-year time series (1985-2017) of land use and land cover data based on geostatistical techniques and spatiotemporal weighted regression analysis. Principal component analysis condensed 16 landscape metrics into three factors: aggregation/diversity, dispersion/adjacency, and patchiness. The average annual total soil loss across all 62 analysed watersheds was estimated at 73.3 ± 78.2 (standard deviation) ton ha−1. A significant positive correlation was observed between landscape fragmentation and soil erosion, indicating that, as fragmentation increases, soil losses also increase. Furthermore, our analysis revealed a decreasing trend in soil loss rates in recent years, primarily attributed to the recovery of native vegetation since no significant soil management practices were widely implemented in the study area during the study period.

Prioritization of Sub-Watershed Based on Soil Loss Estimation Using RUSLE Model

Soil erosion is one of the most crucial land degradation problems and is considered the most critical environmental hazard worldwide. The present study uses remote sensing data integrated with the geographical information system (GIS) technique and the revised universal soil loss equation (RUSLE) model for assessing the annual average soil loss of the Digaru watershed of India for 1999 and 2020. The estimated mean gross yearly soil loss from the entire watershed was 102716 t yr-1 in 1999 and 178931.6 t yr-1 in 2020. The overall average soil loss rate increased significantly between 1999 and 2020, rising from 4.73 t—ha-1yr-1 to 8.43 t—ha-1yr-1. The sub-watersheds are prioritized as high (≥ 40 t ha−1yr−1), moderate (20–40 t ha−1yr−1), and low (<20 t ha−1yr−1) based on the spatial distribution of soil erosion. Seven sub-watersheds have been grouped under low priority, followed by seven under moderate priority and one under high priority. This study demands instant attention for soil and water conservation efforts in highly eroded watershed areas.

Relationship among runoff, soil erosion, and rill morphology on slopes of overburdened stockpiles under simulated rainfall

Overburdened stockpiles are difficult to achieve natural stability in a short period time because of their complex and diverse composition of materials and significant differences in physical and chemical properties, causing numerous cases of water loss and soil loss events. We conducted a series of experiments at different rainfall intensities (30, 60, 90, and 120 mm h−1) and different gravel contents (0 %, 10 %, 20 %, 30 %, and 40 %) to study the runoff, soil erosion, and rill morphology characteristics and relationship among three of overburdened stockpiles in production and construction projects with simulated rainfall. The runoff rate and soil loss rate basically showed a trend of increasing and then decreasing with gravel content and lower gravel content had a certain degree of inhibition on the flow velocity. 20 %, 0 %, 0 %, and 20 % gravel contents had the most significant inhibition on the flow velocity at 30, 60, 90, and 120 mm h−1 rainfall intensities, respectively. Flow shear stress, stream power, unit energy of water cross-section, maximum rill length, width and depth all increased with increasing rainfall intensity. The stream power, unit stream power, and unit energy of water cross-section were larger at higher gravel content. The maximum rill length and depth were positively correlated with gravel content, which were the minimum at 0 % gravel content and all rainfall intensities. Gravel content played a more important role in the runoff, soil loss, and rill morphology. The relationship between runoff rate and soil loss rate, flow velocity and rill morphology parameters were all expressed as linear functions, and flow velocity and soil loss rate was quadratic function, with a correlation coefficient of 0.339. In contrast, runoff rate and rill morphology parameters, soil loss rate and rill morphology parameters, erosion dynamics parameters and rill morphology parameters were all expressed as power functions. In addition, the runoff rate can better describe the process of soil loss (R2 = 0.798, P < 0.05). The unit energy of water cross-section was more suitable to describe the development of maximum rill length and depth (with rill length was R2 = 0.781, and with rill depth was R2 = 0.723, P < 0.05). At the same time, the stream power was more suitable to describe the development of maximum rill width on the slope of overburdened stockpiles (R2 = 0.841, P < 0.05). These results contributed to preventing soil loss on overburdened stockpiles and helping the development of estimation models for soil erosion.