Soil Erosion Intensity Research Articles

Mapping Potential Soil Water Erosion and Flood Hazard Zones in the Yarlung Tsangpo River Basin, China

The ubiquity of soil water erosion in the Yarlung Tsangpo River Basin leads to a series of natural hazards, including landslides, debris flows and floods. In this study, the Revised Universal Soil Loss Equation model (RUSLE) was used to quantify potential soil water erosion, while the Height Above Nearest Drainage model (HAND) was used to delimit potential flood hazard zones. Remote sensing and geographic information system technologies were employed to spatialize the results, which showed that the annual soil loss from water erosion was less than 1239 t ha−1 y−1. The total soil loss was estimated to be over 108 × 106 tons, of which about 13 × 106 tons (12.04% of the total) occurred from the agricultural land in the downstream valley. Soil erosion mapping was performed using six levels of soil erosion intensity and the effects of precipitation, land use/land cover and topography on soil erosion were revealed. Increases in precipitation and slope gradient significantly increased the soil loss rate, while the maximum rate of soil loss occurred from densely vegetated land, reaching 9.41 t ha−1 y−1, which was inconsistent with erosion preconceptions for this land type. This may be due to a combination of the region’s unique climate of high intensity rainfall and steep slopes. Flood hazard mapping showed that all regional cities were located in a flood hazard zone and that, within the total basin area (~258 × 105 ha), 9.84% (2,537,622 ha) was in a high flood occurrence area, with an additional 1.04% in aa vulnerable to moderate flood hazard area. Approximately 1.54% of the area was in a low flood risk area and 4.15% was in a very low flood risk area. The results of this study provide an initial identification of high-risk soil water erosion and flood hazard locations in the basin and provide a foundation upon which decision-makers can develop water and soil conservation and flood prevention policies.

Variability in mollic epipedon thickness in response to soil erosion–deposition rates along slopes in Northeast China

The Mollisol region of Northeast China is one of the most significant grain-producing areas. Intense soil erosion has led to a sharp decline in both the mollic epipedon (ME) thickness and soil quality, and these processes have in turn resulted in a serious threat to the national food security. Soil erosion–deposition processes influence the soil thickness. However, the quantitative relationship between the ME thickness and soil erosion–deposition rate along slopes remains unclear. In this study, the ME thickness and soil erosion–deposition rate along three typical long, gentle slopes in Heilongjiang Province were investigated by using ground-penetrating radar (GPR) and 137Cs tracing technology. Variations in the spatial characteristics of the ME thickness and soil erosion–deposition rate on slopes were obtained. Wavelet analysis was employed to analyse the soil erosion–deposition rate on these slopes. The results indicated that the soil erosion rate along the three slopes was periodic and oscillated between high and low values. The range of primary cycle variation was 73–80 m, and the range of secondary cycle variation was 44–47 m. A negative correlation was found between the soil erosion–deposition rate and ME thickness within each cycle. The periodic variability in the soil erosion rate on these slopes also yielded a periodic variability in the ME thickness. Fitted equations were derived based on the ME thickness, slope length and soil erosion–deposition rate. The error range for soil thickness prediction was 0.30–9.40 %. This study could provide an efficient and accurate method to predict ME thickness change patterns along slopes and to help arrange soil erosion control measures at appropriate locations.

A new framework to identify most suitable priority areas for soil-water conservation using coupling mechanism in Guwahati urban watershed, India, with future insight

The urban watershed of Guwahati, Assam, has witnessed a rapid urbanization in recent years, making it to one of the most deteriorated cities in terms of environmental issues. Therefore, this work focused on finding the most suitable soil-water conservation areas at a micro-scale using coupling coordination mechanism. Principal component analysis (PCA) was used to create a priority model for sub-watershed basin based on nineteen morphometric parameters. We then quantified the soil erosion using the revised universal soil loss equation (RUSLE) for current and future scenarios based on the representative concentration pathway (RCP) 2.6 and 8.5 models (RCP2.6 and 8.5). In addition, we proposed the fuzzy logic and analytical hierarchy process (AHP) model-based soil-water conservation suitability (SWPC) model for current and future scenarios. Finally, the most suitable soil-water conservation areas for current and future scenarios were identified using coupling coordination degree model (CCD). To the author's knowledge, this is the first in-depth study that identifies the most suitable conservation areas by analyzing the watershed prioritization, soil erosion, and topographic, hydrologic, land cover, and climatic parameters-based soil-water conservation suitability models. Sub-watersheds comprising Silsako, Bharalu, Deepor Beel, and North Guwahati have been identified as high-priority sub-watersheds. According to the current RUSLE model, soil erosion in the study area varies from 140 to 181.64 tonnes per hectare per year. In contrast, soil erosion would continue to increase in the future as per the RCP8.5 model, which varies from 305 to 332 tonnes per hectare per year. The current SWPC model predicted 46.92 km2 area as high and 54.40 km2 area as very high suitable zones. However, under the RCP 2.6 and RCP 8.5 models, the high and very high SWPC zones will experience extended areas in the future due to increased soil erosion intensity. According to the CCDM results, Bharalu, Deepor Beel, and North-Guwahati sub-watersheds have observed a very high to medium coupling degrees, which are considered the most suitable areas for conservation. The findings of this study will significantly help stakeholders and experts in long-term land-water resource management and effectively address environmental degradation issues in urban watersheds around the world.

Quantitative analysis and spatial distribution of landform spatial structure on Loess Plateau

The Loess Plateau is the largest gully geomorphic region in the world, characterized by the most intense soil erosion in a typical loess-covered area. Previous studies have focused on the terrain and texture of this region; however, there have been no systematic studies on the gully spatial structure of the Loess Plateau. Therefore, the present study investigated the characteristics and spatial distribution of landform spatial structure over the Loess Plateau. Specifically, gully weighted complex networks (GWCNs) were applied to simulate the gully spatial structure of loess landforms, and a series of quantitative indices were introduced to delineate these. Using 57 geomorphological units uniformly distributed across the Loess Plateau as test areas and six typical loess landforms as sample areas, GWCNs were constructed, and using these GWCNs, the spatial structure and internal mechanisms of typical loess landforms were explored. From a series of fresh insights, such as the regional scale-free distribution, homologous structure, tightness, community effect, connectivity, stability, and complexity, regular variations in quantitative indices delineate the spatial distribution of the characteristics of landform spatial structure over the plateau. Moreover, the spatial distribution of complex network indices exhibited strong spatial coupling with loess landforms. Overall, GWCNs could be effectively used for landform recognition and performed well. In conclusion, these experimental results suggest that introducing complex networks into landform studies can offer novel insights into landform quantitative analyses. The present work is of great significance, as it proposes a new methodology for describing the spatial structure and terrain features of landforms in quantitative analyses and furthers our understanding of landform genesis.

Mercury Speciation, Distribution, and Potential Sources in Surface Waters of the Yangtze and Yellow River Source Basins of Tibetan Plateau During Wet Season

To understand the mercury (Hg) biogeochemical cycle in alpine regions under global warming, it is critical to identify the distribution and sources of Hg in aquatic ecosystems of the Tibet Plateau. The spatial distribution pattern and potential sources of Hg species including total mercury (THg), particulate mercury (PHg), and dissolved mercury (DHg) were investigated in surface waters of the Yangtze and Yellow River source basins during the wet season. The results showed that average ρ(DHg) in surface water of the Yangtze and Yellow River source basins were comparable[(2.96±1.26) ng·L-1 and (2.47±0.83) ng·L-1, respectively], whereas the average ρ(THg)[(10.69±11.14) ng·L-1] and ρ(PHg)[(8.46±11.41) ng·L-1] in the source basin of the Yangtze River were significantly higher than that in surface water of the Yellow River source basin[(3.37±2.03) ng·L-1 and (1.13±1.02) ng·L-1, respectively]. It is worth noting that the ecological risk of Hg in the study area was limited because of low Hg concentration and methylation level. In addition, the correlation analysis illustrated that the THg was mainly concentrated by PHg in the source basin of the Yangtze River. Specifically, the concentration variations in Hg were mainly affected by the input of glacier meltwater, soil erosion, and precipitation. By contrast, the main species of Hg in the source basin of the Yellow River was DHg, the distribution pattern of which was mainly controlled by DOC. Spatially, a significant negative correlation was found between ρ(PHg) and longitude in the source basin of the Yangtze River (R2=0.46, P<0.01). The spatial distribution differences of river slope and soil erosion intensity were identified as the key factors leading to the decreasing trend of ρ(PHg) and ρ(THg) along the river flow in the source basin of the Yangtze River. The results of the PMF model further demonstrated that in the surface waters of the source regions of the Yangtze and Yellow Rivers, 51.4% of Hg derived from long-distance atmospheric deposition, 38.8% from erosion of soil rock or sediment via stream flow, and 9.7% from soil runoff or seepage input.

Effect of land use–land cover and projected rainfall on soil erosion intensities of a tropical catchment in Sri Lanka

Effect of land use–land cover and projected rainfall on soil erosion intensities of a tropical catchment in Sri Lanka

Spatiotemporal patterns and drivers of soil erosion in Yunnan, Southwest China: RULSE assessments for recent 30 years and future predictions based on CMIP6

Soil erosion is a critical driving force of regional-scale ecosystem dynamics. Quantifying soil erosion and its responses to climate and land cover changes comprise an important part of regional ecological security assessment. Taking account of rainfall and vegetation cover changes in Yunnan Province, Southwest China, from 1986 to 2015, this study explored the spatiotemporal patterns of soil erosion intensity in Yunnan over this 30-year period, using the Revised Universal Soil Loss Equation. Sensitivity analyses were performed to evaluate the roles of rainfall (R) and vegetation cover (C) changes in soil erosion. Based on the climate model CMIP6, the carbon emission socio-economic sharing scenarios SSP126 and SSP585 were compared, using a random forest model, to predict soil erosion risk in Yunnan in different future periods. The results indicated the following: (1) During 1986–2015, soil erosion was detected in 33.55% of the land area of Yunnan, among which the areas of slight, moderate, severe, very severe, and extremely severe erosion accounted for 19.55%, 7.64%, 3.23%, 2.08%, and 1.04%, respectively; the 30-year mean annual soil erosion modulus over Yunnan was 1289.72 t km−2 a−1. (2) The area percentage change of five soil erosion intensity levels consistently showed a generally declining trend of soil erosion during the 30-year period. Comparing 1995–2006 vs. 1986–1995 and 2006–2015 vs. 1996–2005, area percentages were 1.56% and 2.4% for intensively reduced, respectively, and correspondingly 16.65% and 22.12% for reduced, 68.11% and 71.15% for no significant change, 12.79% and 4.02% for enhanced, and 0.08% and 0.03% for intensively enhanced. (3) Factor C was a more sensitive driver than R for soil erosion in this period. (4) Under the SSP126 and SSP585 scenarios, soil erosion risk was predicted to rise in the 21st century; and the provincial average soil erosion risk was larger for the SSP585 than the SSP126 scenario. Compared with the average of the 30-year period, predicted soil erosion in the SSP585 and SSP126 scenarios in 2100 would increase in western and southern Yunnan, while the SSP585 scenario predicted more severe soil erosion in southern and southwestern regions than SSP126. Our historical assessments and future forecasts suggest vegetation protection in karst areas and restoration in southern Yunnan will be critical for future soil erosion control and regional ecological security in Yunnan.

Soil erosion rates on sloping cropland fragment underlain by contrasting lithologies

This study examines the pattern of soil erosion rates in a cropland fragment underlain by limestone and purple sandstone (referred to as the CLP) in the Three Gorges Reservoir Region (TGRR) using the 137Cs and 210Pbex techniques. A total of 96 bulk cores and 18 sectioned cores were collected from the CLP. In addition, 4 bulk and 4 sectioned cores were extracted from each of two reference sites. Based on the 137Cs and 210Pbex inventories obtained from these cores, the soil erosion rates were assessed. The results indicate that the 137Cs and 210Pbex inventories both increase downslope, while the calculated soil erosion rates both decrease. This implies that the intensity of soil erosion decreases downslope, which is a combined response to the effect of gravity, the short slope length, and the gentle gradient of the cropland. The soil erosion rates derived from 137Cs were generally higher than those determined using 210Pbex. This shows that soil erosion was more intense from 1954 onward than during the period between 1920 and 1954, reflecting the impact of disturbance by cultivation, which has increased rapidly over the past 60 years. The soil erosion rate on the limestone area was similar to that in the purple sandstone area, but higher than that reported from karst regions experiencing rocky desertification. This suggests that, providing that there is no evidence of karst rocky desertification, the soil erosion intensity in cropland underlain by limestone is similar to that underlain by purple sandstone. This result provides a new insight into the pattern of soil erosion intensity on the cultivated hillslopes of karst and non-karst regions at the scale of the cropland fragment. It will also help to improve our understanding of surface processes in karst and non-karst areas subject to intense cultivation.

Spatiotemporal characteristics of soil erosion in a typical watershed consisting of different landscape: A case study of the Qin River Basin.

Soil erosion has a severe impact on habitat and productivity. It is considered to be a major environmental threat prevalent in ecosystems. However, few researchers have studied the spatial distribution of soil erosion intensity among different geographic environmental factors. The Qin River Basin is a geographical unit consisting of mountains, hills, and plains with significant regional characteristics, and it has a basin area of 14,810.91 km2. This study uses the Geographical Information Systems, Revised Universal Soil Loss Equation model to analyze the spatiotemporal changes in the soil-erosion intensity in the Qin River Basin from 1990 to 2018. Different environmental factors of land use, slope and altitude on erosion intensities of 19 secondary land types were analyzed. It can better reflect the soil erosion under different environmental factors and different land use types. Results show that the soil erosion modulus of Qin River Basin were 10.25 t hm−2 a−1, and it belong to slight erosion from 1990 to 2018. Soil erosion intensity is greater in grassland and woodland than in cropland. The strongest soil erosion occurred in the sparse forestland, and the lowest was in beach land. Soil erosion was the highest for a slope of 15~25° and an altitude of 1200~1500 m. Rainfall and slope are important factors lead to soil erosion, indicating weak water and soil conservation implemented in these areas. Therefore, priority should be given to these geomorphic units to formulate and implement soil-erosion control and ecological restoration policies in the Qin River Basin. This study provides a good reference for preventing and controlling soil erosion in river basins.

Soil Loss Potential Assessment for Natural and Post-Fire Conditions in Evia Island, Greece

A devastating forest fire in August 2021 burned about 517 km2 of the northern part of Evia Island, affecting vegetation, soil properties, sediment delivery and the hydrological response of the catchments. This study focuses on the estimation of the annual soil loss in the study area under natural (pre-fire) and post-fire conditions. The assessment of the soil loss potential was conducted with the application of the Universal Soil Loss Equation (USLE), which is an empirical equation and an efficient way to predict soil loss. The USLE factors include rainfall erosivity (R), soil erodibility (K), the slope and slope length factor (LS), the cover management factor (C) and the erosion control practice factor (P). The USLE quantified the annual soil erosion (in t/ha/year) for both pre- and post-wildfire conditions, and the study area has been classified into various soil loss categories and soil erosion intensity types. The results showed that the annual soil loss before the forest fires ranged from 0 to 1747 t/ha, with a mean value of 253 t/ha, while after the fire the soil loss significantly increased (the highest annual soil loss was estimated at 3255 t/ha and the mean value was 543 t/ha). These values demonstrate a significant post-fire change in mean annual soil loss that corresponds to an increase of 114% compared to the pre-fire natural condition. The area that is undergoing high erosion rates after the extreme wildfire event increased by approximately 7%, while the area of moderate rates increased by 2%. The calculated maximum potential of soil erosion, before and after the 2021 extreme wildfire event, has been visualized on spatial distribution maps of the average annual soil loss for the study area. The present study underlines the significant post-fire increase in soil loss as part of the identification of the more vulnerable to erosion areas that demand higher priority regarding the protective/control measures.

Degradation of traditional vineyards in Slovakia by abandonment and soil erosion: A case‐study of Vráble

AbstractWe evaluated the effect of increased erosion events and decreased management intensity on the degradation of traditional vineyards. The study area is located near Vráble, Slovakia, in an area with warm dry climate with mild winters, and Luvisol and Regosol soils. For the erosion measurements, we used the pole height method, which uses vineyard poles as a passive soil‐surface marker. The erosion of a tilled vineyard increased from 33.47 Mg ha−1 yr−1 in the period 1983–2010 to 55.34 Mg ha−1 yr−1 in the period 2010–2021. In comparison, the erosion of the hoed and grassed vineyard has not changed significantly. We also quantified the regeneration of soil in abandoned vineyards. An average increase in level of the soil surface level after abandonment in 2010 was 0.56 mm yr−1. A control plot showed minimal change in the average exposed pole height over 10 years and confirmed the reliability of the pole height method. Land cover and management practices have dramatically changed in the study area over the last decade. Only 27.16% of the total vineyard area is currently tilled and potentially threatened by soil erosion. On the other hand, 35.73% of the vineyards are abandoned; abandonment is expected to continue into the future. Therefore, the loss of management associated with vineyard abandonment is more strongly linked to their degradation than increased soil erosion intensity.

Simulation of Holocene soil erosion and sediment deposition processes in the Yellow River basin during the Holocene

The Yellow River Basin is ideal for studying fluvial landscape evolution under climate change and human activities. Quantitative reconstruction of soil erosion, sediment transport, and delta deposition in the basin enhances understanding of the dynamic mechanisms of fluvial surface processes. This study reconstructs the spatial and temporal distribution of precipitation and vegetation cover based on geological profile records, paleoclimatic datasets, and historical documentation in the Yellow River basin during the Holocene. A landscape evolution model (Landlab) is introduced to simulate soil erosion and sediment deposition processes. Modeling results show that soil erosion intensity in the middle reaches of the Yellow River was weak during the early and middle Holocene. Since the late Holocene, soil erosion has increased due to vegetation degradation, as the climate became drier, but with more fluctuations. Since 2.0 ka (1 ka = 1,000 calibrated a B.P.), and especially since 1.0 ka, soil erosion in the middle reaches of the Yellow River increased rapidly due to strong human activity, with the intensity-six times higher than the average level before the late Holocene. Average sediment deposition thickness in the lower reach of the Yellow River (North China Plain) was about 2.4 m, and sediment volume was about 3.6 × 1011 m3. The deposition rate and soil erosion intensity showed synchronous changes during the Holocene. Since 2.0 ka, the sediment load and deposition rate have increased rapidly, to 6–10 times higher than in the early and middle Holocene. On this basis, the effects of climate change and human activities on the evolution of the fluvial landscape are discussed.

Dynamic Changes and Precision Governance of Soil Erosion in Chengde City Using the GIS Techniques and RUSLE Model

Soil erosion is one of the major environmental problems facing the world. The multi-scale characteristics of soil erosion and the complexity of its influencing factors put forward higher requirements for soil erosion prevention and control. Based on GIS technology and the RUSLE model, this paper quantitatively studies the temporal and spatial variation characteristics of soil erosion intensity in Chengde City(CC) from 2003 to 2018 and analyzes the temporal and spatial characteristics of R, K, LS, C, P factors according to the model calculation results, and analyzes the formation mechanism of key units of soil erosion in CC. The results show that: The area of tolerable erosion in CC in 2018 was 35152.19 km2 (accounting for 90.22% of the total area), which was at the level of tolerable erosion on the whole. The average soil erosion modulus of CC in 2003, 2006, 2009, 2012, 2015, and 2018 were 41.38, 45.06, 46.58, 83.66, 27.67, and 73.34 t.km-2.y-1, reaching the maximum value of 83.66 t.km-2.y-1 in 2012, showing a rising trend and then declining trend in the research period. Soil erosion deteriorated in some areas of CC and regional differences increased, which caused serious environmental problems. Fitting results showed that the R factor was one of the important factors for the increase of regional differences and average erosion modulus. According to the characteristics of the problem, a precise governance model of soil erosion prevention based on the intensity and causes of soil erosion was put forward, and a “landing” scheme of soil erosion prevention and control measures was put forward. Furthermore, the control of soil and water loss in key areas should be strengthened in the future.

Satellite observations reveal decreasing soil erosion in Northeast Inner Mongolia, China, over the past four decades

Knowledge regarding the soil erosion change patterns in Northeast Inner Mongolia (NIM) is essential for ecological security and sustainable development. Multisource satellite remote sensing with auxiliary data, including meteorology, land use, vegetation coverage, and digital elevation, was collected to establish a distributed soil erosion model to quantify the soil erosion intensity in Northeast Inner Mongolia. The results showed that soil erosion in Northeast Inner Mongolia, China, decreased by 100,654 km2 from 1978 to 2018. The area change rates of the mild, moderate, strong, intensive and severe soil erosion intensities were −48.91%, −41.41%, 32.63%, −91.15%, and −91.14%, respectively. The decrease in soil erosion was mainly located in the Hulunbuir and Tongliao regions. Our findings from satellite observations provide information about the soil erosion intensity and spatial distribution required for policy-making and the management of soil erosion prevention in Northeast Inner Mongolia.

Spatial Pattern of Soil Erosion in Relation to Land Use Change in a Rolling Hilly Region of Northeast China

The black soil region in Northeast China is one of the major grain-producing areas of China. Soil erosion in the black soil region caused by natural factors and anthropic activities has attracted much attention, especially in a rolling hilly region. Compared with natural factors, the land use factor of cropland encompasses the most easily optimized measures. Jiutai County of Changchun City, located in the hilly areas of Northeast China, was taken as an example to calculate the soil erosion modulus using the Revised Universal Soil Loss Equation model. The overall soil erosion status of cultivated land in the study area was mainly slight and light, the proportion of cultivated land affected by extremely intensive and severe erosion was relatively small, and the average soil erosion modulus was 7.09 t·hm−2·a−1 in 2019. In view of spatial distribution characteristics of soil erosion revealed by the spatial aggregation and hot spot analysis, the most serious soil erosion intensity was concentrated in the southeast and northeast sloping farmland over 8°. With the increase in elevation and topographic slope, the proportion of slight and light soil erosion gradually decreased, which was closely related to the increase in soil erodibility caused by the space–time migration of soil organic carbon caused by the interaction of hydraulic and tillage erosion in complex topographic areas. The Geographically Weighted Regression model was introduced to explore the driving factors and superposition mechanism of farmland soil erosion in the hilly region of Northeast China. Based on the relationship between soil erosion and landscape fragmentation, landscape fragmentation was an important driving force promoting soil erosion, sediment yield, and sediment transport. This paper is committed to providing a basis for accurately deploying regional soil and water conservation measures and formulating macro land management policies.

Study on Dynamic Changes of Soil Erosion in the North and South Mountains of Lanzhou

The North and South Mountains of Lanzhou City are the ecological protection barriers and an important part of the ecological system of Lanzhou City. This study takes the North and South Mountains as the study area, calculates the soil erosion modulus of the North and South Mountains of Lanzhou City based on the five major soil erosion factors in the RUSLE model, and analyses the spatial and temporal dynamics of soil erosion in the North and South Mountains of Lanzhou City and the soil erosion characteristics under different environmental factors. The results of the study show that: The intensity of soil erosion is dominated by slight erosion, which was distributed in the northwestern and southeastern parts of the North and South Mountains in 1995, 2000, 2005, 2010, 2015 and 2018. Under different environmental factors, the soil erosion modulus increased with elevation and then decreased; the soil erosion modulus increased with a slope; the average soil erosion modulus of grassland was the largest, followed by forest land, cultivated land, unused land, construction land, and it was the smallest for water; except for bare land, the average soil erosion modulus decreases with the increase of vegetation cover; Soil erosion modulus was the greatest in the pedocal of the North and South Mountains, and the least in the alpine soil.

The nexus between land use, land cover dynamics, and soil erosion: a case study of the Temecha watershed, upper Blue Nile basin, Ethiopia.

At the current times, soil erosion is the major problem that affects land and water resources, especially in Ethiopia's highlands. Due to the dynamics of land use land cover change, land degradation, and soil erosion increase significantly and result in a loss of fertile soil every year and lead reduction in agricultural production. This study was therefore designed to explore the land use land cover (LULC) dynamics from 1986 to 2020, to estimate mean annual soil erosion rates and identify erosion hotspot areas from 1986 to 2020, and finally, to evaluate the impacts of land use land cover change on soil loss of 1986 to 2020. For this, Landsat imageries of 4 years from 1986 to 2020 were used. Maximum likelihood supervised classification methods were used to classify LULCs. The dynamics of LULC change were used as an input for measuring soil loss by employing the combination of geospatial technologies with the revised universal soil loss equation (RUSLE). The LULC maps of 1986, 1997, 2009, and 2020 were used for identifying crop management (C) factor and conservation practice (P) factor. Rainfall erosivity factor (R), soil erodibility factor (K), and slope length and steepness factor (LS) were also used as sources of data. Based on the five factors, soil erosion intensity maps were prepared for each year. Results showed that the annual soil loss in the watershed ranged from 0 to 3938.66 t/ha/year in 1986, 0 to 4550.94 t/ha/year in 1997, 0 to 5011.21 t/ha/year in 2009, and 0 to 6953.23 t/ha/year in 2020. The annual soil loss for the entire watershed was estimated at 36.889, 42.477, 47.805, and 48.048 t/ha/year in 1986, 1997, 2009, and 2020, respectively. The mean soil loss of 1986, 1997, 2009, and 2020 was higher in cultivated land followed by shrub land, grazing land, and forest land. Mean soil loss increased from 1986 to 1997, from 1997 to 2009, and from 2009 to 2020. This is because of the expansion of agricultural land at the expense of grazing land and shrub land. Therefore, urgent soil and water conservation practices should be made in hotspot areas.

Spatial Modelling of Vineyard Erosion in the Neszmély Wine Region, Hungary Using Proximal Sensing

Intense soil erosion in the northern part of the Gerecse Hills, Hungary, is causing significant damage to vineyards in the area. Three vineyards in the Neszmély Wine Region were investigated to quantify the amount of eroded soils. The method was based on monitoring vineyards for one-year between July 2019 and June 2020. Every season, a set of photographs of the vineyards were taken from an unmanned aerial vehicle. The images were processed in a photogrammetric workflow to produce high-resolution digital terrain models (DTMs) and orthophotos, which were used to estimate the soil loss using the Universal Soil Loss Equation (USLE) model. Particular attention was paid to the effect of seasonal variation in vegetation cover and rainfall, and the erosion control effect of the inter-row grassing already applied in the vineyards was also modelled. The results confirm and quantify the extent to which intense summer rainfall has a more significant effect on erosion compared to autumn or winter rainfall.

Spatio-Temporal Evolution of Sandy Land and its Impact on Soil Wind Erosion in the Kubuqi Desert in Recent 30 Years

Continuous remote-sensing monitoring of sand in desert areas and the exploration of the spatio–temporal evolution characteristics of soil–wind erosion has an important scientific value for desertification prevention and ecological restoration. In this study, the Kubuqi Desert was selected as the study area, and the Landsat series satellite remote sensing data, supplemented by satellite remote sensing data such as GE images, SPOT-5, ZY-3, GF-1/2/6, etc., integrated object-oriented, decision tree, and auxiliary human–computer interaction interpretation methods, developed the Kubuqi Desert area dataset from 1990 to 2020, and established a soil erosion intensity database of the past 30 years based on the soil–wind erosion correction equation. The results show that the application of the training samples obtained by a high-score collaborative ground sampling to land use/cover classification in desert areas can effectively improve the efficiency of remote-sensing mapping of sand changes and the accuracy of change information identification, and the overall accuracy of the classification results is 95%. In general, the sandy area of the Kubuqi Desert area has decreased year by year, during which the mobile sand in the hinterland of the desert has expanded in a scattered distribution. The overall soil–wind erosion intensity showed a downward trend, especially since 2000; the ecological improvement trend after the implementation of desertification control projects is obvious. Changes in the sand type contributed the most to the reduction of soil–wind erosion intensity (contribution 81.14%), ecological restoration played a key role in reducing the soil–wind erosion intensity (contribution 14.42%), and the increase of forest and grass vegetation covers and agricultural oases played a positive role in solidifying the soil- and wind-proof sand fixation. The pattern of sandy land changes in desert areas is closely related to the national ecological civilization construction policy and the impact of climate change.

RUSLE Model Evaluation of the Soil and Water Conservation Ratio of the Guizhou Province in China between 2000 and 2019

The soil and water conservation ratio (SWCR), which is a quantitative index for measuring the control degree of soil and water loss, is equal to the percentage of the land areas with a slight erosion intensity in the study area. The dynamic change in the SWCR reflects the dynamic process of realizing a specific soil and water conservation goal in a certain stage. The objectives of this study were to evaluate the change in the SWCR in the Guizhou Province in this century and to analyze its causes. The temporal and spatial variations of soil erosion intensity and SWCR were measured based on GIS technology and revised universal soil loss equation (RUSLE). The results showed that the spatial pattern of soil erosion intensity in the Guizhou Province was high in the west and low in the southeast, and that the soil erosion characteristics were obviously different between karst and non-karst areas. In the karst areas, the land with a moderate and above erosion intensity (&gt;3 t hm−2 y−1 in the karst area; &gt;25 t hm−2 y−1 in the non-karst area) accounted for 28.20–34.78% of the total area, while only accounting for 2.39–2.72% in the non-karst areas. From 2000 to 2019, the mean intensity of soil erosion decreased from 13.97 to 10.83 t hm−2 y−1, and the SWCR increased from 32.95% to 35.31%. According to the change in erosion intensity grades, 22.30% of the whole province’s erosion grade changed from high to low, especially in the west, with a high erosion intensity. Meanwhile, about 11.99% of the land in the central, eastern and southeastern regions, was where the erosion intensity showed a slight increase and the spatial distribution showed sporadic patch distribution characteristics, which may be related to an increase in infrastructure investment in the Guizhou Province in recent years. A large number of production and construction projects caused the destruction of surface vegetation and also caused patchy soil erosion. The spatial and temporal characteristics of the soil erosion and the SWCR in the Guizhou Province between 2000 and 2019 were mastered through this study, and our results provide an important basis for further scientific and reasonable soil and water conservation planning work.