Prediction of spatial soil loss impacted by long-term land-use/land-cover change in a tropical watershed

The devastating effect of soil erosion is one of the major sources of land degradation that affects human lives in many ways which occur mainly due to deforestation, poor agricultural practices, overgrazing,wildfire and urbanization. Soil erosion often leads to soil truncation, loss of fertility, slope instability, etc.which causes irreversible effects on the poorly renewable soil resource. In view of this, a study was conducted in Kelantan River basin to predict soil loss as influenced by long-term land use/land-cover(LULC) changes in the area. The study was conducted with the aim of predicting and assessing soil erosion as it is influenced by long-term LULC changes. The 13,100 km~2 watershed was delineated into four sub-catchments Galas, Pergau, Lebir and Nenggiri for precise result estimation and ease of execution. GIS-based Universal Soil Loss Equation(USLE) model was used to predict soil loss in this study. The model inputs used for the temporal and spatial calculation of soil erosion include rainfall erosivity factor,topographic factor, land cover and management factor as well as erodibility factor. The results showed that 67.54% of soil loss is located under low erosion potential(reversible soil loss) or 0-1 t ha~(-1) yr~(-1) soil loss in Galas, 59.17% in Pergau, 53.32% in Lebir and 56.76% in Nenggiri all under the 2013 LULC condition.Results from the correlation of soil erosion rates with LULC changes indicated that cleared land in all the four catchments and under all LULC conditions(1984-2013) appears to be the dominant with the highest erosion losses. Similarly, grassland and forest were also observed to regulate erosion rates in the area. This is because the vegetation cover provided by these LULC types protects the soil from direct impact of rain drops which invariably reduce soil loss to the barest minimum. Overall, it was concluded that the results have shown the significance of LULC in the control of erosion. Maps generated from the study may be useful to planners and land use managers to take appropriate decisions for soil conservation.     

Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed,northwest Turkey

This study was aimed at predicting soil erosion risk in the Buyukcekmece Lake watershed located in the western part of Istanbul, Turkey, by using Revised Universal Soil Loss Equation (RUSLE) model in a GIS framework. The factors used in RUSLE were computed by using different data obtained or produced from meteorological station, soil surveys, topographic maps, and satellite images. The RUSLE factors were represented by raster layers in a GIS environment and then multiplied together to estimate the soil erosion rate in the study area using spatial analyst tool of ArcGIS 9.3. In the study, soil loss rate below 1 t/ha/year was defined as low erosion, while those >10 t/ha/year were defined as severe erosion. The values between low and severe erosion were further classified as slight, moderate, and high erosion areas. The study provided a reliable prediction of soil erosion rates and delineation of erosion-prone areas within the watershed. As the study revealed, soil erosion risk is low in more than half of the study area (54%) with soil loss <1 t/ha/year. Around one-fifth of the study area (19%) has slight erosion risk with values between 1 and 3 t/ha/year. Only 11% of the study area was found to be under high erosion risk with soil loss between 5 and 10 t/ha/year. The severe erosion risk is seen only in 5% of the study area with soil loss more than 10 t/ha/year. As the study revealed, nearly half of the Buyukcekmece Lake watershed requires implementation of effective soil conservation measures to reduce soil erosion risk.     

基于支持向量机的喀斯特山区土壤环境质量评价——以贵州北部一茶叶园区为例

以贵州北部一茶叶园区80个表层土壤样品为研究对象,对其Hg、As、Cd、Pb、Cr和Cu含量进行测定,在MATLAB中应用支持向量机构建土壤环境质量评价模型,并与模糊综合评价法和内梅罗综合污染指数法的评价结果对比分析,探究支持向量机模型在喀斯特山区土壤环境质量评价中的适用性,其结果表明:研究区土壤质量Ⅰ类与Ⅱ类样品比例为33∶7,土壤环境质量大多数为I类;支持向量机方法的评价结果与模糊综合评价法和内梅罗综合污染指数法结果的相同率分别达到82.5%和80.0%,并分析结果有差异的样品,发现支持向量机评价结果更符合实际情况,这说明该模型适用于土壤环境质量的评价。      

Spatio-temporal changes in rate of soil loss and erosion vulnerability of selected region in the tropical forests of Borneo during last three decades

An attempt has been made to analyze the spatial-temporal characteristics of soil erosion vulnerability and soil loss from the forested region in the north-eastern Borneo, Sarawak, Malaysia during the last three decades (1991–2015) using the revised universal soil loss equation (RUSLE) and geographical information systems (GIS). The components of RUSLE such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS), cover management (C) and conservation practice (P) factors were grouped into two categories by keeping one set as temporally changing and others as static. Among them the R and C factors are calculated for the years 1991, 2001 and 2015 whereas the K and LS factors are considered for the single time frame. Because of the forested nature of the study area, the P factor is kept constant for the whole analysis. The R factor and C factor is shown changes in values and its distribution over the years, which reflected in the final soil loss and erosion vulnerability map as a change in the rate of erosion and spatial domain. The analysis of three time slices has shown that the maximum value of the soil loss per unit area i.e. at erosion hotspots, is relatively similar throughout at around 1636 to 1744 t/ha/y. This is the result of maximum values of R factor and C factor i.e. high rainfall erosivity combined with lack of vegetation cover in those hotspots, which are generally steeply sloping terrain. The reclassification of annual soil loss map into erosion vulnerability zones indicated a major increase in the spatial spread of erosion vulnerability from the year 1991 to 2015 with a significant increase in the high and critical erosion areas from 2.3% (1991) to 31.5% (2015). In 1991, over 84% of the study area was under low erosion vulnerability class but by the year 2015 only 12% was under low erosion vulnerability class. Moreover, a dynamic nature in the erosion pattern was found from the year 1991 to 2015 with more linear areas of land associated with higher rate of soil loss and enhanced erosion vulnerability. The linearity in the spatial pattern is correlated with the development of logging roads and logging activities which has been confirmed by the extraction of exposed areas from satellite images of different years of analysis. The findings of the present study has quantified the changes in vegetation cover from dense, thick tropical forest to open mixed type landscapes which provide less protection against erosion and soil loss during the severe rainfall events which are characteristic of this tropical region.     

Spatial prediction of soil erosion risk by remote sensing,GIS and RUSLE approach: a case study of Siruvani river watershed in Attapady valley,Kerala, India

Siruvani watershed with a surface area of 205.54 km² (20,554 hectare), forming a part of the Western Ghats in Attapady valley, Kerala, was chosen for testing RUSLE methodology in conjunction with remote sensing and GIS for soil loss prediction and identifying areas with high erosion potential. The RUSLE factors (R, K, LS, C and P) were computed from local rainfall, topographic, soil classification and remote sensing data. This study proved that the integration of soil erosion models with GIS and remote sensing is a simple and effective tool for mapping and quantifying areas and rates of soil erosion for the development of better soil conservation plans. The resultant map of annual soil erosion shows a maximum soil loss of 14.917 t h⁻¹ year⁻¹ and the computations suggest that about only 5.76% (1,184 hectares) of the area comes under the severe soil erosion zone followed by the high-erosion zone (11.50% of the total area). The dominant high soil erosion areas are located in the central and southern portion of the watershed and it is attributed to the shifting cultivation, and forest degradation along with the combined effect of K, LS and C factor. The RUSLE model in combination with GIS and remote sensing techniques also enables the assessment of pixel based soil erosion rate.     

Soil erosion assessment on hillslope of GCE using RUSLE model

A new method for obtaining the C factor (i.e., vegetation cover and management factor) of the RUSLE model is proposed. The method focuses on the derivation of the C factor based on the vegetation density to obtain a more reliable erosion prediction. Soil erosion that occurs on the hillslope along the highway is one of the major problems in Malaysia, which is exposed to a relatively high amount of annual rainfall due to the two different monsoon seasons. As vegetation cover is one of the important factors in the RUSLE model, a new method that accounts for a vegetation density is proposed in this study. A hillslope near the Guthrie Corridor Expressway (GCE), Malaysia, is chosen as an experimental site whereby eight square plots with the size of \(8\times 8\) and \(5\times 5\) m are set up. A vegetation density available on these plots is measured by analyzing the taken image followed by linking the C factor with the measured vegetation density using several established formulas. Finally, erosion prediction is computed based on the RUSLE model in the Geographical Information System (GIS) platform. The C factor obtained by the proposed method is compared with that of the soil erosion guideline Malaysia, thereby predicted erosion is determined by both the C values. Result shows that the C value from the proposed method varies from 0.0162 to 0.125, which is lower compared to the C value from the soil erosion guideline, i.e., 0.8. Meanwhile predicted erosion computed from the proposed C value is between 0.410 and \(3.925\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\) compared to 9.367 to \(34.496\, \hbox {t ha}^{-1}\,\hbox {yr}^{-1 }\) range based on the C value of 0.8. It can be concluded that the proposed method of obtaining a reasonable C value is acceptable as the computed predicted erosion is found to be classified as a very low zone, i.e. less than \(10\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\) whereas the predicted erosion based on the guideline has classified the study area as a low zone of erosion, i.e., between 10 and \(50\, \hbox {t ha}^{-1 }\,\hbox {yr}^{-1}\).     

http://www.sciencedirect.com/science/article/pii/S1674987111001034

A comprehensive methodology that integrates Revised Universal Soil Loss Equation（RUSLE） model and Geographic Information System（GIS） techniques was adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala,India.The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method.GIS data layers including,rainfall erosivity（R）,soil erodability（K）,slope length and steepness（LS）,cover management （C） and conservation practice（P） factors were computed to determine their effects on average annual soil loss in the area.The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h^-1 y^-1 with a close relation to grass land areas,degraded forests and deciduous forests on the steep side-slopes（with high LS ）.The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.     

遥感与GIS支持下的南桐矿区水土流失评价与区划

以重庆市南桐矿区为研究对象,运用遥感和GIS技术获取对水土流失影响较大的植被覆盖度、地形坡度、土地利用类型等信息并进行空间叠加分析,计算了水土流失类型及面积。研究结果表明,南桐矿区水土流失面积262.91km2,侵蚀模数2281t/(km2?a),水土流失强度以轻度和中度为主,其中轻度流失132.37km2,中度流失108.95km2。根据区域地貌类型以及水土流失特征,将研究区水土流失划分为盆边低山丘陵中强度流失区、北部坪状低山中轻度流失区和盆边中山轻度流失区三个类型区,盆边低山丘陵中强度流失区以中度流失为主;北部坪状低山中轻度流失区以轻度流失为主;盆边中山轻度流失区虽然以轻度流失为主,但微度流失也占有相当部分的比重。      

桂江流域土壤侵蚀估算及其时空特征分析

桂江流域的水土流失现状研究对珠江三角洲的水生态安全有重要的现实意义。采用修正的通用土壤流失方程（RUSLE）估算了桂江流域的土壤侵蚀模数与年侵蚀总量,分析流域内土壤侵蚀的时空分布特征,探讨了影响该区域土壤侵蚀强度的自然与人文因素。结果表明,桂江流域51.8%的地表都在发生不同程度的土壤侵蚀。从全流域平均土壤侵蚀强度来看,属于中度侵蚀。从土壤侵蚀面积来看,约85%的地表处于微度、轻度与中度侵蚀。4-6月的全流域平均土壤侵蚀强度最大,侵蚀总量也是最大的。流域的土壤侵蚀主要发生在高程在30~600m的低山丘陵-高地地貌区内的林地与耕地中。流域内岩溶区的土壤侵蚀强度随着石漠化程度从无到中度逐渐增加,轻、中度石漠化区的土壤侵蚀强度达到强度侵蚀等级。      

Geospatial assessment of soil erosion intensity and sediment yield: a case study of Potohar Region,Pakistan

Estimation of spatial extent of soil erosion, one of the most serious forms of land degradation, is critical because soil erosion has serious implications on soil fertility, water ecosystem, crop productivity and landscape beauty. The primary objective of the current study was to assess and map the soil erosion intensity and sedimentation yield of Potohar region of Pakistan. Potohar is the rainfed region with truncated and complex topography lying at the top of the Indus Basin, the world’s largest irrigation networks of canals and barrages. Spatially explicit Revised Universal Soil Loss Equation (RUSLE) Model integrated with Remote Sensing-GIS techniques was used for detecting/mapping of erosion prone areas and quantification of soil losses. The results show that the Potohar region is highly susceptible to soil erosion with an average annual soil loss of 19 tons ha^?1 year^?1 of which the maximum erosion (70–208 tons ha^?1 year^?1) was near the river channels and hilly areas. The sediment yield due to the erosion is as high as 148 tons ha^?1 year^?1 with an average of 4.3 tons ha^?1 year^?1. It was found that 2.06% of the total area falls under severe soil erosion, 13.34% under high erosion, 15.35% under moderate soil erosion while 69.25% of the area lies in the low (tolerable) soil erosion. Chakwal and Jhelum districts of the region are seriously affected by erosion owing to their topography and soil properties. The information generated in this study is a step forward towards proper planning and implementation of strategies to control the erosion and for protection of natural resources. It is, hence, necessary that suitable water harvesting structures be made to control water to prevent soil erosion and provision of water in the lean season in this region. Tree plantation and other erosion control practices such as strip cropping can also minimize soil erosion in this region.     

Spatial estimation of soil erosion risk using RUSLE/GIS techniques and practices conservation suggested for reducing soil erosion in Wadi Mina watershed (northwest,Algeria)

The Wadi Mina Watershed, western area of Algeria is characterized by rare and irregular rains and a fragile and weak vegetable cover. The sediments resulting from erosion are transported and contributed to silting dam Sidi Mhamed Benaouda. The combination of the thematical maps of the various erosive factors according to the Revised Universal Soil Loss Equation (RUSLE) in SIG by ArcGIS 10.2 software provided a reliable forecast of the annual rates of soil loss by delimiting the areas prone to erosive risk in the catchment above mentioned. The estimated potential average annual soil loss is 11.2 t/ha/yr., and the potential erosion rates from recognized erosion classes ranged from 0.0 to plus 100 t/ha/yr. About 50% of the catchment area was predicted to have very low to low erosion risk, with soil loss between 0 and 7.4 t/ha/yr. Erosion risk is moderate over 13.9% of the catchment, where calculated soil loss is between 7.4 and 12 t/ha/yr. Erosion risk is high to dangerous over 36.1% of the catchment, where calculated soil loss is more than 12 t/ha/yr. According to this study, it appeared clearly that we must intervene quickly by using reliable and effective conservation techniques.     

Estimating of water erosion in semiarid regions using RUSLE equation under GIS environment

Water erosion is one of the main forms of land degradation in Algeria, with a serious repercussion on agricultural productivity. The purpose of this study is to estimate the soil loss of Wadi El-Ham watershed in the center of Algeria, this study aims also to evaluate the effectiveness and reliability of the use of the Revised Universal Soil Loss Equation (RUSLE) under a Geographic Information System in this field. The RUSLE model involves the main factors of erosion phenomena, namely, rain aggressiveness, soil erodibility, topographic factor, land cover index and the anti-erosive practices factor. Using this approach, the specific erosion in Wadi El-Ham watershed is estimated as 5.7 (t/ha/yr) in the entire watershed area. This result is compared to the measured suspended sediment at the Rocade-Sud gauging station situated outlet the watershed. These data consist of 1293 instantaneous measures of the water discharge and the suspended sediment concentration recorded during 21 years. Through this comparison, the used approach of RUSLE under GIS estimates the soil loss in Wadi El-Ham in Hodna region of Algeria with an error of 7.5%. Consequently, the results obtained in cartographic format make it possible to target the areas requiring priority action for a larger scale analysis to find appropriate solutions to combat erosion and to protect the natural environment.     

Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado

The installation of a rural settlement complex in the watershed stream Indaiá has promoted changes in land-use and vegetation cover dynamics; however, the effects of intensive agriculture and cattle farming in rural settlements on soil loss rates are not well known. Predictive models implemented in geographic information systems have proven to be effective tools for estimating erosive processes. The erosion predictive model Revised Universal Soil Loss Equation (RUSLE) is a useful tool for analyzing, establishing and managing soil erosion. RUSLE has been widely used to estimate annual averages of soil loss, by both interrill and rill erosion, worldwide. Therefore, the aim of this work was to estimate the soil loss in the watershed stream Indaiá, using the RUSLE model and geoprocessing techniques. To estimate soil loss, the following factors were spatialized: erosivity (R), erodibility (K), topography (LS), land-use and management (C) and conservation practices (P); the annual soil loss values were calculated using the RUSLE model equation. The estimated value of soil loss in the hydrographic basin ranged from 0 to 4082.16 Mg ha^?1 year^?1 and had an average value of 47.81 Mg ha^?1 year^?1. These results have demonstrated that 68.16 % of the study area showed little or no soil loss based on the Food and Agriculture Organization’s (FAO 1980) classification. When comparing the average value of soil loss obtained using the RUSLE model with the Natural Potential for Erosion, a 16-fold reduction in soil was found, which highlighted the fact that vegetation cover (C factor) has a greater influence than other factors (R, K and LS) on soil loss prediction attenuation. These results lead to the conclusion that soil loss occurs by different methods in each settlement in the basin and that erosive processes modeled by geoprocessing have the potential to contribute to an orderly land management process.     

RETRACTED ARTICLE: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed,Guizhou Province,China

Due to the existence of fragile karst geo-ecological environments, such as environments with extremely poor soil cover, low soil-forming velocity, and fragmentized terrain and physiognomy, as well as inappropriate and intensive land use, soil erosion is a serious problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China; evaluation of soil loss and spatial distribution for conservation planning is urgently needed. This study integrated the revised universal soil loss equation (RUSLE) with a GIS to assess soil loss and identify risk erosion areas in the Maotiao River watershed of Guizhou. Current land use/cover and management practices were evaluated to determine their effects on average annual soil loss and future soil conservation practices were discussed. Data used to generate the RUSLE factors included a Landsat Thematic Mapper image (land cover), digitized topographic and soil maps, and precipitation data. The results of the study compare well with the other studies and local data, and provide useful information for decision makers and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a larger watershed scale in Guizhou.     

Erosional effects on terrestrial resources over the last millennium in Reykjanes, southwest Iceland

The study presents the effect of soil erosion on vegetation, soil accumulation (SA), SA rate (SAR), soil quality, soil mass, and the soil organic carbon (SOC) pool in Brown Andosols and Histosols in a 24-km² area in southwest Iceland. Undisturbed prehistoric soils were distinguished from disturbed historic soils using tephrochronology. Soil erosion has been severe during historic time (last 1135 yr), resulting in the increase of the soil mass deposited in soils covered by vegetation by a factor of 7.3-9.2 and net loss of soil in unvegetated areas. The SAR correlated positively with SOC sequestration. SOC is easily transported and, given the extensive accumulation of soil, the net effect of burial and subsequent reduction in decomposition is to increase SOC storage. Nevertheless, the increased accumulation and soil depletion has decreased soil quality, including the SOC, and reduced soil resistance to erosion with the depleted SOC contributing to enrichment of atmospheric CO₂. The initial terrestrial disturbance was triggered by anthropogenic land use during the Medieval Warm Period, followed by volcanic activity approximately three centuries later. The combination of harsh climate during the Little Ice Age and drastic anthropogenic perturbations has led to land degradation at a catastrophic scale.     

Impact of fractional vegetation cover change on soil erosion in Miyun reservoir basin,China

It is well known that soil erosion at the watershed scale is the result of interactions between various factors. Among these environmental factors, vegetation is the most important and plays a major role in the soil erosion process. The impact of fractional vegetation cover change (FVCC) on soil erosion in non-contributing areas is a heavily discussed topic. In this paper, the fractional vegetation cover (FVC) in 2002 and 2005 was calculated by using a backpropagation neural network based on remote sensing (RS) data. Then the impacts of FVCC on sediment loads at the outlets of two Miyun reservoir sub-basins were evaluated by integrating RS and geographic information system with statistical analysis. The Miyun reservoir basin (MRB) is characterized by hilly and mountainous topographies and seasonal rainy weather. The primary goal of this paper is to gain a better understanding of FVCC, its driving forces, and its impact on regional soil erosion. We discuss spatiotemporal variations in precipitation and soil erosion, identify which factors contribute to those variations, analyze the influences of FVCC on climate change and human activities and, finally, conclude that changes in FVC and climate regimes are primary factors for soil erosion in MRB. We also discuss how sediment loads may be used to quantitatively separate biophysical and anthropogenic influences and to identify critical thresholds that might have dramatic consequences for the watershed ecosystem. These findings should be quite helpful for sensible watershed development and management planning.     

Soil erosion risk assessment of the Keiskamma catchment,South Africa using GIS and remote sensing

This paper examines the soil loss spatial patterns in the Keiskamma catchment using the GIS-based Sediment Assessment Tool for Effective Erosion Control (SATEEC) to assess the soil erosion risk of the catchment. SATEEC estimates soil loss and sediment yield within river catchments using the Revised Universal Soil Loss Equation (RUSLE) and a spatially distributed sediment delivery ratio. Vegetation cover in protected areas has a significant effect in curtailing soil loss. The effect of rainfall was noted as two pronged, higher rainfall amounts received in the escarpment promote vegetation growth and vigour in the Amatole mountain range which in turn positively provides a protective cover to shield the soil from soil loss. The negative aspect of high rainfall is that it increases the rainfall erosivity. The Keiskamma catchment is predisposed to excessive rates of soil loss due to high soil erodibility, steep slopes, poor conservation practices and low vegetation cover. This soil erosion risk assessment shows that 35% of the catchment is prone to high to extremely high soil losses higher than 25 ton ha⁻¹ year⁻¹ whilst 65% still experience very low to moderate levels of soil loss of less than 25 ton ha⁻¹ year⁻¹. Object based classification highlighted the occurrence of enriched valley infill which flourishes in sediment laden ephemeral stream channels. This occurrence increases gully erosion due to overgrazing within ephemeral stream channels. Measures to curb further degradation in the catchment should thrive to strengthen the role of local institutions in controlling conservation practice.     

Estimation of soil erosion using RUSLE in Caijiamiao watershed,China

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km². This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha^?1 year^?1 in 2002 and 70.58 ton ha^?1 year^?1 in 2010, while the estimated sediment yield was found to be 327.96 × 10⁴ and 293.85 × 10⁴ ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.     

Dynamics of soil organic carbon following land-use change: insights from stable C-isotope analysis in black soil of Northeast China

Intensive soil tillage is a significant factor in soil organic matter decline in cultivated soils. Both cultivation abandonment and foregoing tillage have been encouraged in the past 30 years to reduce greenhouse gas emissions and soil erosion. However, the dynamic processes of soil organic carbon (SOC) in areas of either continuous cultivation or abandonment remain unclear and inconsistent. Our aims were to assess and model the dynamic processes of SOC under continuous tillage and after cultivation abandonment in the black soil of Northeast China. Soil profiles were collected of cultivated or abandoned land with cultivation history of 0–100 years. An isotope mass balance equation was used to calculate the proportion of SOC derived from corn debris (C₄) and from natural vegetation (C₃) to deduce the dynamic process. Approximately 40% of SOC in the natural surface soil (0–10 cm) was eroded in the first 5 years of cultivation, increasing to about 75% within 40 years, before a slow recovery. C₄ above 30 cm soil depth increased by 4.5%–5% or 0.11–0.12 g·kg^?1 on average per year under continuous cultivation, while it decreased by approximately 0.34% annually in the surface soil after cultivation abandonment. The increase in the percentage of C₄ was fitted to a linear equation with given intercepts in the upper 30 cm of soil in cultivated land. A significant relationship between the change of C₄ and time was found only in the surface soil after abandonment of cultivation. These results demonstrate the loss and accumulation of corn-derived SOC in surface black soil of Northeast China under continuous tillage or cultivation abandonment.     

Soil erosion risk and its spatial pattern in upstream area of Guanting reservoir

The spatial pattern of soil erosion can provide valuable insights into the soil erosion processes that require a rapid assessment in practical applications. Generally, quantitative technique is expensive and time-consuming. The objective of this paper is to reveal the spatial pattern of erosion with a rapid assessment method. The affecting factors such as land cover, vegetation fraction and slope gradient are integrated into this method using a qualitative means. Beijing-1 images in 2006 were used to produce land-cover and vegetation fraction, and 1:50,000 topographic maps were used to calculate slope gradient. The study area was classified into six grades. Results show that the upstream area of Guanting Reservoir, in general, is exposed to a moderate risk; there are 17,740.33 km² of land that suffered from water soil erosion in 2006, occupied 40.69% of the total area, and most of the soil erosion area is on the light and moderate risk, which occupied 25.05 and 62.83% of the eroded area, respectively. Eight elevation zones and six slope gradient zones were overlaid with the assessed risk. The analyzed results show that: (1) the areas above 2,000 m have the lowest erosion risk, which is only 0.75% of the eroded area; 1,250–1,500 m elevation zone has the highest erosion risk, which is 34.72% of the eroded area. (2) The slope gradient zone less than 5 degrees and greater than 35 degrees have the lowest erosion risk, which is 0.02 and 0.75% of the eroded area, respectively; the slope gradient zone with 8–15 degrees has the highest erosion risk, which is 36.40% of the eroded area. These results will be useful for water and soil conservation management and the planning of mitigation measures.