With the intensification of climate change and the increased frequency of extreme weather events, terraces, as a traditional agricultural practice, are facing severe challenges. This study investigated the characteristics of soil erosion on terraces under extreme rainstorm conditions, the dominant controlling factors influencing soil erosion, and the relationships between these factors in the terrace area of Qiugou watershed on the Loess Plateau. Utilizing high-precision digital elevation model (DEM) data acquired through field surveys and unmanned aerial vehicle (UAV) aerial photogrammetry, topographic and hydrological factors were extracted through visual interpretation and model simulations. High-resolution analysis was carried out on terrace erosion types, soil erosion intensity and the relationships between topographic/hydrological factors and runoff generation/erosion processes during extreme rainstorms. The results indicate that the extreme rainstorm caused five primary forms of terrace damage in the Qiugou watershed: gully erosion, cave erosion, rill erosion, slumping/collapse and shallow landslides. Within the study area, the soil erosion intensity of terrace platform and terrace wall, including channelized erosion and gravitational erosion, were 3732.10 and 27 843.26 t/km2, respectively. The sheet erosion intensities of terrace platform and terrace wall were 2898.56 and 20 143.02 t/km2, respectively. Terrace wall is the primary source of soil erosion in terraces. New terraces suffered significantly more damage, with a soil erosion intensity 1.16 times higher than that of old terraces. Slope gradient emerged as the key factor controlling the terrace soil erosion intensity, which increased with steeper slopes (reaching a peak in the 30 degrees-50 degrees range). Management strategies should therefore prioritize areas with slopes between 30 degrees and 50 degrees, which are commonly distributed within terrace wall. Optimizing terrace design to reduce soil and water loss requires synergistic regulation by combining the LS factor (slope length and steepness factor) and specific catchment area.

Gully erosion severely threatens land resources and agricultural sustainability, yet the role of subsurface erosionresistant soil layers remains poorly understood. This study integrated sub-meter imagery with stratified soil sampling (0-120 cm depth) across 79 gullies with comparable slopes gradient and catchment areas on a farm (570 km2) in the black soil region of northeast China to quantify how erosion-resistant layers control gully sidewall expansion and headcut retreat. Ten soil properties were analyzed to construct a PCA-based comprehensive soil erosion resistance score (CRS), revealing a decline in CRS with profile depth and a hierarchy of soil resistance: Black soil > Black soil-Loess transition layer > Loess > Loess-Sand transition layer > Fluvial sandy. The first two layers were identified as erosion-resistant layers. Through threshold effect analysis, a threshold erosion-resistant layer thickness of 53.88 cm was identified (p < 0.01) for sidewall expansion, revealing a 1.36 cm/yr acceleration in gully sidewall expansion per 1 cm thinning within the threshold thickness. Gullies with erosion-resistant layers below the sensitivity thickness experienced 2.03 times higher expansion rate. Gullies newly formed since 2010 exhibited a lower threshold (34.90 cm) than the pre-existing gullies. Gully headcut retreat rate was 43 % higher if the resistant layer was thinner than 54.28 cm, despite no significant detectable threshold. The threshold erosion-resistant layer thickness is potentially modulated by the depth of soil cracks and needs further investigation. This study highlights the importance of soil-profile features, not just surface properties, in gully erosion research. Integration of this threshold into gully erosion models could revolutionize gully prediction and precision conservation strategies.

The degradation of ‘black soil beach’ (BSB) ecosystems in the Three-River-Source region, characterized by widespread bald patches and severe soil erosion, poses a critical threat to regional ecological security and sustainable pastoralism. This study aims to elucidate the spatial distribution patterns and driving factors of bald patches in BSB degraded grasslands within the Guoluo Tibetan Autonomous Prefecture, providing a scientific basis for targeted restoration strategies. Utilizing multi-source remote sensing data (Landsat 8–9 OLI, UAV imagery, and Google Earth), we employed the Multiple Endmember Spectral Mixture Analysis (MESMA) method to identify bald patches, combined with the landscape pattern index and spatial autocorrelation to quantify their spatial heterogeneity. Geographical detector analysis was applied to assess the influence of natural and anthropogenic factors. The results indicate the following: (1) The patches are bounded by the Yellow River, showing a distribution pattern of ‘high in the west and low in the east’. The total area of patches reached 32,222.11 km2, accounting for 43.43% of the total area of Guoluo Prefecture, among which Maduo County and Dari County had the highest degradation rate. (2) With the aggravation of degradation, the patch density of each county increased first and then decreased, while the aggregation index and landscape shape index continued to decrease. (3) Spatial autocorrelation of bare patches strengthens with degradation severity (Moran’s I index 0.6543→0.7999). LISA identified two clusters: the high–high agglomeration area in the north of Maduo–Dari and the low–low agglomeration area in the southeast of Jiuzhi–Banma, revealing the spatial heterogeneity of the degradation process. (4) The spatial distribution pattern of bare patches was mainly affected by the annual average precipitation and actual stocking capacity, and the synergistic effect was significantly higher than that of a single factor. The combination of a 4491–4708 m high altitude area, 0–5° gentle slope zone, and soil texture (clay 27–31%, silt 43–100%) has the highest degradation risk. This multi-factor coupling effect explains the limitations of traditional single factor analysis and provides a new perspective for accurate repair.

Gully erosion susceptibility (GES) mapping is crucial for controlling gully erosion hazards and has become a significant focus of global research and management efforts. Machine learning models have proven effective in this field. However, in areas with different terrain complexity, the model shows significant variation in optimal resolution and algorithms, factor importance and spatial distribution of the model results, which limits their broader application. This study compares GES mapping in two small watersheds: one located in the complex terrain of the Loess Plateau and the other in the relatively flat terrain of the Northeast China Mollisol region. The model predictive accuracy was evaluated using 30% of the datasets that were excluded from model training. The results revealed that: 1) significant differences in optimal resolution of GES mapping in the two regions, which were 1-2.5 m for the Mollisol region, and 2.5-5 m for the Loess Plateau. The extreme boosting tree (XGBoost) algorithm achieved the best simulation results compared to random forest (RF) and gradient boosting decision tree (GBDT) in both regions. 2) Slope gradient and contributing area influenced gully distribution in both watersheds, with land use being critical in the Loess Plateau and distance from streams more important in the Mollisol region. 3) In the Loess Plateau watershed, 25% of the area was highly susceptible to gully erosion, while only 1% of the Mollisol watershed was highly susceptible. This research compared GES mapping in two watersheds with different terrain complexity, which would be beneficial for better use of machine learning in gully research.

The Digital Elevation Model (DEM) products acquired through traditional approaches, due to the limited spatial resolution, have challenges in representing terrace terrain. Although the Digital Surface Models (DSMs) obtained by Unmanned Aerial Vehicles (UAV) can reflect the finer structural elements (such as flat terrace beds and steep terrace risers) and local variation of terraces, they are often influenced by vegetation. Therefore, in this study, an efficient approach was proposed for constructing a DEM by integrating the GF-7 DEM with the DSM obtained via UAV during the fallow season. The newly generated DEM can present the detailed micro-topography and structural elements of terraces, while also effectively minimizing the interference of vegetation.

The soil erodibility factor (K) is the main data required for regional soil erosion investigation and mapping using soil erosion models. USLE-K, RUSLE2-K, EPIC-K and Dg-K are four widely used methods for calculating soil erodibility factor (K). However, it remains to be studied which algorithm is more suitable to calculate soil erodibility factor (K) in the global scale. While, soil erodibility factor (K) is mostly calculated based on soil physical and chemical property data, which does not involve the content of rock fragments in these algorithms. However, the amount of rock fragments and thier distribution difference have a certain influence on soil physical and chemical properties, and then affect the accuracy of the estimation of soil erodibility factor (K). In this paper, USLE-K, RUSLE2-K, EPIC-K and Dg-K algorithms were used to estimate global soil erodibility factor (K), and its spatial pattern and main controlling factors were analyzed. In this paper, the measured data of soil erodibility factor (K) were retrieved by literature search, and the measured database of K factor value was established. The rationality of the results of the above four algorithms was analyzed, and the above four algorithms for calculating K factor were modified according to the measured database of K factor. At the same time, USLE-K and RUSLE2-K algorithm are taken as an example to calculate the effect of rock fragments in the soil profile and rock fragments on the soil surface. The results showed that (1) The spatial pattern of global K factors estimated by the USLE-K, RUSLE2-K, EPIC-K and Dg-K models is similar, but the values in the K surfaces are different in some extent. (2) Comparing to 106 measured values, the mean value of estimated RUSLE2-K is the closest to the measured K factor, followed by the USLE-K algorithm and the EPIC-K algorithm, while the estimated K by Dg-K algorithm is quite different from the measured K factor. (3) The presence of rock fragment in the soil profile increased the global soil erodibility factor. The rock fragment on the soil surface reduces soil erodibility. This article made the calculation of K more complete and accurate, thereby improving the accuracy of regional soil erosion estimation. And provide the necessary scientific basis for the selection of K algorithms globally.

Mountain hazards threaten ecosystem functions by inducing soil erosion and organic carbon transfer, yet the trait-based microbial strategies remain unclear. This study investigated 168 soils from 18 mountain hazard-affected sites on the northeastern Tibetan Plateau, covering vegetated slopes, eroded slopes, and depositional sediments. We measured six extracellular enzyme activities (EEA) and biomass-specific EEA (normalized by microbial biomass carbon, EEA/MBC), integrating geographic, climatic, topographic, and soil variables to assess their regulatory mechanisms. Results showed that mountain hazards significantly reduced EEA (vegetated > eroded > deposited), primarily due to the deprivation of vegetation inputs and the decrease in MBC. Contrary to the expectation that microbes enhance enzyme investment under resource scarcity, EEA/MBC generally did not increase in nutrient-poor eroded and deposited treatments compared with nutrient-rich vegetated soils. Microbial adaptation in adverse situations (less nutrients, moisture, and high pH) redirected the microbial metabolism from resource acquisition to stress resistance. Inferior mineral stabilization in turn suppressed EEA/MBC with high rock and sand contents in sediments. The significant negative relationship between growth (i.e., MBC) and resource acquisition (i.e., specific enzyme) observed in vegetated soils disappeared in eroded and deposited counterparts, further proving the stress-tolerant strategy under harsh conditions. Soil nutrient, texture, and pH were the primary predictors of EEA spatial distribution (R-2 = 0.69). Predicting biomass-specific EEA was challenging in mountain hazard-disturbed soils (R-2 = 0.28), which would otherwise be improved in vegetated ecosystems. Overall, our study provides evidence of microbial stress-resistant features rather than growth or enzyme production in mountain hazard-disturbed ecosystems, offering insights in other stressful environments under global change.

Gully development is a significant geomorphological and environmental process that affects land degradation worldwide, with ephemeral gullies (EGs) and permanent gullies (PGs) being the two most common types. These two gully types are often spatially connected, and with such EG-PG connectivity can accelerate erosion. However, systematic research on this phenomenon remains limited, particularly at the regional scale. This study focuses on the spatial connectivity between EGs and PGs in the Songnen black soil region of northeast China. An unequal probability stratified sampling was used to establish 977 small watershed units, and a database of gullies and their connectivity was constructed based on sub-meter imagery. Among them, 55 representative units were randomly selected within geomorphic zones for field surveys and UAV validation to ensure data accuracy. Spatial patterns of gully connectivity were analyzed, and dominant controlling factors were identified using the Geodetector, which quantifies spatial stratified heterogeneity and evaluates the explanatory power of potential driving factors. The results are as follows: (1) Gully connectivity varies significantly across the region, with hotspot areas where more than 50% of permanent gullies are connected to ephemeral gullies, and cold spot clusters elsewhere. (2) Permanent gullies connected to ephemeral gullies differ significantly from unconnected ones in both length and width, with the former exhibiting a more elongated morphology. (3) Slope length and mean annual precipitation are the primary drivers of gully connectivity, both showing significant positive effects. Moreover, the interaction between mean annual precipitation and slope length shows the strongest explanatory power, indicating that precipitation, in combination with topographic features, plays a dominant role in shaping gully connectivity. By examining the spatial patterns of gully connectivity, this study contributes to a more refined understanding of gully morphological evolution and offers empirical insights for enhancing gully erosion models and optimizing regional soil and water conservation strategies.

Abstract: Climate change and human activities are seriously affecting the intensity and extent of soil erosion in the Pan-Third Pole region (PTP), which covers an area of approximately 5.14 × 107 km2. Accurate assessment of soil wind and water erosion is crucial for controlling soil degradation. In this study, soil water erosion in the PTP was estimated for 2018 using sampling units and the China Soil Loss Equation (CSLE), and soil wind erosion in the PTP from 1982 to 2020 was simulated using the Revised Soil Wind Erosion Equation (RWEQ), based on meteorological, soils, topographic, and remote sensing data. The results showed that: (1) Soil water erosion in the PTP mainly occurs in East Asia, South Asia, and the Black Sea coastal region, and the average soil wind erosion rate of the whole region is 263.4 t•km-2•a-1, and the average water erosion rate of the key erosion areas with water erosion rates exceeding 2,500 t•km-2•a-1 is 22.6 times higher than the average water erosion rate of the study area, and annual erosion amounted to 57.1×108t, accounting for 38.6% of total erosion amount. The soil water erosion rates of cropland, grassland, and forest were 525.7 t•km-2•a-1, 362.6 t•km-2•a-1, and 185.6 t•km-2•a-1, respectively. (2) Soil wind erosion in the PTP mainly occurs in cropland and grassland in semi-arid areas, and aeolian sand activity primarily occurring in extremely arid and arid areas (deserts), and the average multi-year soil wind erosion rate in regions other than deserts is 633.65 t•km-2•a-1, of which the mean soil wind erosion rate in the area where soil wind erosion rate is greater than 50 t•km-2•a-1 was 4,316.94 t•km-2•a-1, for cropland, grassland, and scrubland were 1,981.14 t•km-2•a-1, 3,815.05 t•km-2•a-1, and 4,010.95 t•km-2•a-1, respectively. (3) From 1982 to 2020, the soil wind erosion rate in the PTP decreased by 10.61 t•km-2•a-1. The proportion of the area with a decreasing trend was 19.53%, while the proportion of the area with an increasing trend was 28.35%. (4) Soil wind and water combined erosion mainly occur in cross-border regions of northern Syria, the Indus River Plain, the northern border of Iran and Afghanistan, the southwestern part of the Qinghai-Tibet Plateau, central Mongolia, the central part of the Loess Plateau, Inner Mongolia, and the bordering areas of the three eastern provinces, the average soil erosion rate of is 4,534.77 t•km-2•a-1, with the average soil erosion rates for grassland and cropland being 4,752.41 t•km-2•a-1 and 1,495.68 t•km-2•a-1, respectively. This study provided a comprehensive understanding of soil erosion (both soil wind and water erosion) in the PTP, and offered valuable data and decision-making support for current and future soil erosion prevention and ecological restoration projects.

With global warming and the increase in extreme precipitation events,floods are becoming more frequent in mountainous areas, and thesafety of lives and property of people is seriously threatened. However, understanding of theflooding process in uninformative mountainousareas is limited due to the lack of high-quality hydrometeorological data. Hence, this study adopts the MIKE21 model to simulateflood inun-dation in the Shadai River basin in the Qilian Mountain region of the northern Tibetan Plateau as an example. This validates the model-simulatedflow and inundation extent using theflow data obtained from the calculation of theflood trace points, extent of inundation,and high-resolution remote sensing images. The results show that theflashflood inundation mainly occurs at 12:00-01:00 AM on 18August 2022, and the simulated and actual maximum inundation areas are 7.9 and 9.5 km2, respectively. ThefittedF-statistic value is0.81, and the relative error between the calculatedflow rate of theflood trace point and the model-simulatedflow rate is 8%, indicatinggood consistency. Furthermore, an in-depth exploration of the model parameter sensitivity reveals that the use of distributed Manning'sroughness coefficient value has higher simulation accuracy.

Ephemeral gully (EG) erosion is an important type of water erosion. Understanding the spatial distribution of EGs and other influencing factors at a regional scale is crucial for developing effective soil and water management strategies. Unfortunately, this area has not been sufficiently studied. The present study visually interpreted the EGs based on Google Earth images in 137 small watersheds uniformly distributed in the Loess Plateau, compared them with measured results, and analyzed the factors influencing EG formation and density using GeoDetector. The results showed that visually interpreting EGs from Google Earth images was suitable for EG regional studies. Out of the 137 small watersheds, 33.6% had EG occurrence with an average density of 3.41 km/km2. Rainfall (R) and slope gradient (S) were the primary factors influencing the formation of EGs, while the area proportion of sloping farmland (APSF) and soil erodibility (K) were the main factors affecting EG density. The interaction of dual factors had a greater influence compared to single factors, with the interaction between S and Normalized Difference Vegetation Index (NDVI) having the greatest impact on EG formation and the interaction between K and NDVI on EG density. Although natural forces significantly influence whether EGs can form in a specific area, human activities greatly affect the density of the gullies that develop. This underscores the importance of proper land management in controlling gully erosion. These findings could provide theoretical support for EG prediction models and a scientific basis for soil and water loss control strategies at the regional scale.

The soil erodibility factor (K) is the main data required for regional soil erosion investigation and mapping using soil erosion models. Fine mapping of K and the study of the applicability of different K estimation methods at the global scale are important to improve the accuracy of global soil erosion evaluation. In this study, the USLE-K, RUSLE2-K, EPIC-K and Dg-K algorithms were used to calculate and compare the global K, and a global measured K database was established by using literature backtracking method and retrieval tool method. Spatial pattern and applicability analysis were carried out on the results of the above four algorithms. The four algorithms were corrected according to the measured K database. The results showed that (1) the global K spatial patterns obtained by the four algorithms were similar but slightly different, with the result of RUSLE2-K being the closest to the measured K, followed by the USLE-K and the EPIC-K, and the result of Dg-K differing significantly from the measured K. (2) The global K distribution characteristics showed some regularity with soil properties, such as soil silt content and sand content, with silt content having the greatest influence on K. (3) The results calculated by the corrected RUSLE2-K and USLE-K algorithms could meet the model applicability conditions and coincided with the results of local K mapping. The results of K mapping in this study on a global scale and the results of the comparative analysis of the applicability of different algorithms provide the necessary scientific basis for the selection of K algorithms globally and quantitative evaluation of soil erosion.

Slope shape as a consequence of erosional landform development plays a prominent role in soil erosion. Clarifying the distribution of soil erosion and deposition patterns on different shaped slopes is crucial for soil erosion control. The aim of this study was to decipher the effects of slope shape on soil erosion and deposition patterns under natural rainfall conditions based on high-resolution unmanned aerial vehicle (UAV) data and geographic information system technology. Structure from motion (SfM)-UAV photogrammetry was carried out in four runoff plots with various slope shapes during the rainy season in 2021. Digital elevation models (DEMs) were developed for each slope shape before and after the rainy season. In addition to collecting runoff and sediment, the DEMs of difference were analyzed to quantify soil erosion and deposition patterns on various slope shapes in the rainy season. Results showed that the runoff volumes and sediment yields induced by rainfall were markedly different among various slope shapes. The mean runoff volume and sediment yield from the concave-convex slope were 1.09 similar to 2.69 and 1.33 similar to 27.16 times those of the other three slopes, respectively, with less sediment loss from the convex-concave slope and its combination slope. Slope shape exhibited a notable effect on the type of slope erosion and deposition. All four slopes showed considerable changes in surface elevation after the rainy season. The increase and decrease in surface elevation were concentrated in the range of -0.02 to -0.007 m and 0.007 to 0.02 m, respectively, with a low proportion of changes less than -0.03 m and greater than 0.03 m. The effectiveness of SfM-UAV in monitoring the microgeomorphic changes of slopes was verified by the consistency of soil erosion amounts based on sediment collection and SfM-UAV measurements. Reference values were provided to solve the threshold problem of slope length cutoff in soil erosion prediction models based on runoff plot experiments. Findings of this study could be useful for decision-making in soil erosion control and slope reconstruction.

在区域尺度研究切沟空间分布特征,对黄土高原切沟防治及黄河中游水土保持工作具有重要意义.研究以系统抽样的方法布设256个小流域抽样单元,基于Google Earth亚米级遥感影像,采用人工目视解译的方法,对黄土高原切沟空间分布特征展开研究,结果表明:(1)92个抽样单元存在切沟,占抽样单元总数35.94％.黄土高原切沟密度均值为1.47 km/km2,以小切沟为主.切沟长度、宽度、距分水岭距离均值分别为43.53 m,6.30 m,71.19 m.(2)黄土高原切沟主要分布在400 mm等降雨量线附近,尤其是延安及其以西至固原一带,榆林及其以北至东胜一带,小切沟分布与切沟总体分布基本一致,大切沟分布相对分散,在天水—定西一带最为突出.(3)黄土高原切沟所在坡面目前土地利用类型主要为草地(48.51％)、耕地(29.76％)、林地(17.27％).研究可为黄土高原侵蚀沟分区治理规划提供理论依据.

Integrated soil management and water loss are important challenges faced by the middle reaches of the Yellow River with regard to high-quality development, and gully erosion is one of the soil erosion types with the largest sediment yield; it severely damages the soil fertility of farmland and is extremely harmful to agricultural production. This study focused on the gully spatial distribution issue in the middle scale of watershed on the Loess Plateau, using Chabagou watershed of northern Shaanxi Province as a case study, based on highresolution unmanned aerial vehicle（UAV） images from 2020. Thirty-two small watersheds were selected, combined with field measurements, to study the spatial distribution patterns of gullies. The results showed that gullies in Chabagou watershed were at its most in the middle reaches; the gully length density was mainly centered around 7-11 km·km -2 , the gully length was mainly within 50 m, and its area was mainly within 500 m~2. There was no significant correlation between ancient valley length density and gully length density. Gully density was significantly positively correlated with slope gradient above the shoulder-line, watershed gradient, and length and was significantly negatively correlated with the ratio of positive and negative topographic area and watershed elevation. The distribution density of gullies in shady slopes was slightly higher than that in sunny slopes. This study clarifies the morphological characteristics and distribution patterns of gullies in the medium watershed scale on the Loess Plateau; thus, providing theoretical basis for gully erosion control and cultivated land protection.

Topography is the main factor influencing soil erosion, but the distribution pattern and influencing factors of topographic factors on the Qinghai-Tibet Plateau（QTP） need to be studied. Based on the 1 arc resolution SRTM（Shuttle Radar Topography Mission） elevation data, we calculated the slope, slope length and LS factor（slope length and steepness factors, LS）, and studied the distribution pattern, statistical distribution characteristics and influencing factors of LS factors on the QTP in combination with area-elevation integration and Hack profile. The results show that:（1） The three topographic indexes of slope, slope length and LS factors all showed the pattern of that small in the center of the plateau and large in the around high mountains, and the average slope gradient of the inner flow area and the outer flow area was 6.55° and 14.3°, the average of slope length was 122.9 and 172.2 m, the mean LS factor was 4.8 and 12.7, respectively.（2） On the whole, the LS factor on the QTP was mainly affected by slope steepness, but the LS factor in the steep areas on the edge of the plateau was mainly affected by slope length.（3） The Hack profiles of the six main rivers in the QTP were convex, and the geomorphic evolution of the region was in its youth stage as a whole.（4） The distribution characteristics of LS factor on the QTP were consistent with soil erosion types and their combinations. The high value in the surrounding area corresponded to Glacier erosion-water erosion, the low value in the northwest corresponded to hydraulic freeze-thaw erosion and wind erosion, and the high value in the transition area from the southeast edge to the interior of the plateau corresponded to hydraulic gravity erosion. The distribution pattern and statistical characteristics of LS factor analyzed in this paper could provide theoretical and data support for the evaluation of soil erosion, and also had great significance for the study of material migration and transformation in the earth system of the QTP.

Soil erosion triggered by water and wind pose a great threat to the sustainable development of Pakistan. In this study, a combination of geographic information systems (GISs) and machine learning approaches were used to predict soil water erosion rates. The Revised Wind Erosion Equation (RWEQ) model was used to evaluate soil wind erosion, map erosion factors, and analyze the soil erosion rates for each land use type. Finally, the maps of soil water and wind erosion were spatially integrated to identify erosion risk regions and recommend land use management in Pakistan. According to our estimates, the Potohar Plateau and its surrounding regions were mostly impacted by water erosion and have a soil erosion rate of 2500–5000 t·km−2·a−1; on the other hand, wind erosion predominated the Kharan Desert and the Thar Desert, with a soil erosion rate exceeding 15,000 t·km−2·a−1. The Sulaiman and Kirthar Mountain Ranges were susceptible to wind–water compound erosion, which was more than 8000 t·km−2·a−1. This study offers new perspectives on the geographic pattern of individual and integrated water–wind erosion threats in Pakistan and provides high-precision data and a scientific foundation for designing rational soil and water conservation practices.

&lt;p&gt;Before the wide application of remote sensing and GIS, ie the pre-GIS era, researchers carried out a series of regional (national to global scale) erosion mapping and research, and group of analog map of soil erosion maps. This manuscript summarizes the achievements and shortcomings of these analog maps, and then discuss the implications of them on today&#039;s digital soil erosion mapping.&lt;/p&gt; &lt;p&gt;From the perspective of geographic information science and digital soil erosion mapping, the main achievements of early soil erosion mapping are summarized in three aspects, including: (1) created the ontology of large regional (national to global) soil erosion research, base on witch, soil erosion can be analysed and control plan can be made. (2) innovatively established the benchmarks and initiation of large regional soil erosion mapping and monitoring; (3) developed a paradigm for for making analog regional soil erosion map. However, the early soil erosion mapping was basically qualitative, static and macro, focusing only on soil and agriculture purpose.&lt;/p&gt; &lt;p&gt;The analog soil erosion map has many implications for the current digital soil erosion mapping, including: (1) It always takes the spatial representation of soil erosion as mission for mappers, but cannot be done as a case of application of remote sensing and other technical methods in soil erosion researches. (2) considering the interaction of various erosion processes such as water erosion, wind erosion, and gully erosion, to represent the comprehensive spatial pattern of various types of soil erosion, and to improve the status quo that the quantitative evaluation of erosion rate is only conducted for a certain erosion type. (3) systematically explore and collect legacy data of soil erosion maps, then establish a free available databased of regional soil erosion maps. (4) considering soil erosion as the driving force of the biogeochemical cycling of essential elements (C, N, P, etc) in earth system, overcome the shortcomings of analog erosion mapping, make a try to develop a new paradigm for digital soil erosion mapping.&lt;/p&gt;

Rock fragments are an important component of soil, and their presence has a significant impact on soil erosion and sediment yield. In this paper, the effects of rock fragments in the topsoil profile (RFP) and rock fragments on the soil surface (RFS) on the soil erodibility factor (K) were assessed at a global scale. The spatial pattern of the relationship between stoniness and erodibility (RS-K) and its predominant factors were explored through correlation analysis, pattern analysis, and random forest model analysis. The results were as followings: (1) The existence of RFP increased K by 2.84%. The RFS of the mountain land and desert/Gobi reduced K by 18.7%; therefore, once the RFP and RFS were taken into account in the calculation, K was 6.98% lower. (2) The predominant factors of the effect of RFS and the joint effect of RFP and RFS were elevation and slope gradient. The predominant factors of the effect of RFP were annual average precipitation and annual average temperature. (3) In assessing and mapping soil erosion in large regions, special attention should be given to areas with large rock fragment contents, a relatively high altitude, and the presence of steep slope. If rock fragments were not taken into consideration, the mapping results of soil erosion may be biased. This article made the calculation of K more complete and accurate, thereby improving the accuracy of regional soil erosion estimation. This research was of significance for the investigation of global hydrological effects and simulation of the global soil carbon budget.

气候变化是影响流域水文循环过程的重要驱动因素,近年来,气候变化导致极端降雨—径流事件的频繁发生对人类社会经济发展构成了严重的威胁.因此,迫切需要开展流域水文模拟和产流特征分析.土壤和水评估工具(SWAT)是一种具有物理机制的分布式水文模型,已被广泛用于评价变化环境下的水文过程.以黄土高原岔巴沟流域为研究区,通过利用与黄土高原地区产流模式更为接近的Green-Ampt下渗法驱动SWAT模型模拟了岔巴沟流域日尺度的水文过程,并以水文响应单元为分析对象,结合4个降雨—径流事件的地表产流量和地表径流系数分析了降雨强度和前期土壤含水量对不同土地覆被产流特征的影响.结果表明:(1)基于Green-Ampt下渗法驱动的SWAT模型率定期和验证期ENS为0.76,0.74,R2为0.78,0.75,模型能够较好地模拟日尺度流域水文过程;(2)流域不同土地覆被下地表径流系数随最大雨强的增加呈显著上升趋势,且最大降雨强度大于16 mm/h后地表径流系数显著增加,当土地覆被为耕地时降雨转化为地表径流的比例最大,其次为草地和林地;(3)前期土壤含水量的大小可以揭示大雨强下部分地表径流系数的变化,不同土地覆被下前期土壤含水量和地表径流系数均有较好的线性关系,从拟合方程的斜率可得耕地和草地地表径流系数对前期土壤含水量的变化敏感程度更高.综上,研究结果可为黄土丘陵沟壑区变化环境下的日径流模拟及产流特征解析提供参考.