基于GIS和RUSLE的滇西北山区土壤侵蚀空间特征分析——以云南省丽江县为例

土壤侵蚀空间分布特征,是进行土壤侵蚀防治规划、实践的重要基础与依据。研究以云南省丽江县为例,应用RUSLE估算了县域土壤侵蚀量,并基于G IS的空间统计分析功能,分析了土壤侵蚀在海拔、坡度与土地利用类型等方面的空间分布特征。结果表明,全县平均土壤侵蚀模数为52.50 t/(hm2.a),属于强度侵蚀,县域东部的金沙江沿岸、3 500~6 000 m高程带、25°~90°坡度带,以及裸地与荒草地、旱地等不同类型区域是研究区土壤侵蚀治理的重点地区。     

RETRACTED ARTICLE: Assessment of soil erosion using RUSLE and GIS: a case study of the Maotiao River watershed,Guizhou Province,China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

陕北地区退耕还林还草工程土壤保护效应的时空特征

This paper looks at the Green for Grain Project in northern Shaanxi Province.Based on remote sensing monitoring data,this study analyzes the locations of arable land in northern Shaanxi in the years 2000,2010 and 2013 as well as spatio-temporal changes over that period,and then incorporates data on the distribution of terraced fields to improve the input parameters of a RUSLE model and simulate and generate raster data on soil erosion for northern Shaanxi at different stages with a accuracy verification.Finally,combined with the dataset of farmland change,compared and analyzed the characteristics of soil erosion change in the converted farmland to forest(grassland)and the unconverted farmland in northern Shaanxi,so as to determine the project’s impact on soil erosion over time across the region.The results show that between 2000 and 2010,the soil erosion modulus of repurposed farmland in northern Shaanxi decreased 22.7 t/ha,equivalent to 47.08%of the soil erosion modulus of repurposed farmland in 2000.In the same period,the soil erosion modulus of non-repurposed farmland fell 10.99 t/ha,equivalent to 28.6%of the soil erosion modulus of non-repurposed farmland in 2000.The soil erosion modulus for all types of land in northern Shaanxi decreased by an average of 14.51 t/ha between 2000 and 2010,equivalent to 41.87%of the soil erosion modulus for the entire region in 2000.This suggests that the Green for Grain Project effectively reduced the soil erosion modulus,thus helping to protect the soil.In particular,arable land that was turned into forest and grassland reduced erosion most noticeably and contributed most to soil conservation.Nevertheless,in the period 2010 to 2013,which was a period of consolidation of the Green for Grain Project,the soil erosion modulus and change in volume of soil erosion in northern Shaanxi were significantly lower than in the previous decade.     

Capacity of soil loss control in the Loess Plateau based on soil erosion control degree

The capacity of soil and water conservation measures, defined as the maximum quantity of suitable soil and water conservation measures contained in a region, were determined for the Loess Plateau based on zones suitable for establishing terraced fields, forestland and grassland with the support of geographic information system (GIS) software. The minimum possible soil erosion modulus and actual soil erosion modulus in 2010 were calculated using the revised universal soil loss equation (RUSLE), and the ratio of the minimum possible soil erosion modulus under the capacity of soil and water conservation measures to the actual soil erosion modulus was defined as the soil erosion control degree. The control potential of soil erosion and water loss in the Loess Plateau was studied using this concept. Results showed that the actual soil erosion modulus was 3355 t?km^-2?a^-1, the minimum possible soil erosion modulus was 1921 t?km^-2?a^-1, and the soil erosion control degree was 0.57 (medium level) in the Loess Plateau in 2010. In terms of zoning, the control degree was relatively high in the river valley-plain area, soil-rocky mountainous area, and windy-sandy area, but relatively low in the soil-rocky hilly-forested area, hilly-gully area and plateau-gully area. The rate of erosion areas with a soil erosion modulus of less than 1000 t?km^-2?a^-1 increased from 50.48% to 57.71%, forest and grass coverage rose from 56.74% to 69.15%, rate of terraced fields increased from 4.36% to 19.03%, and per capita grain available rose from 418 kg?a^-1 to 459 kg?a^-1 under the capacity of soil and water conservation measures compared with actual conditions. These research results are of some guiding significance for soil and water loss control in the Loess Plateau.     

Exploring the potential of perennial crops in reducing soil erosion: A GIS-based scenario analysis in southern Tuscany,Italy

Preserving soils is a major challenge in ensuring sustainable agriculture for the future. Soil erosion by water is a critical issue in the Mediterranean regions and usually occurs when high-erosive precipitation is in temporal association with poor vegetation cover and density. Modelling soil erosion risks over large spatial scales suffers from the scarcity of accurate information on land cover, rainfall erosivity and their intra-annual dynamics. We estimated the soil erosion risk on arable land in a Mediterranean area (Grosseto Province, southern Tuscany, Italy) and investigated its potential reduction as a response to the change in intra-annual distribution of land cover due to the increase of perennial forage crops. A GIS-based (R)USLE model was employed and a scenario analysis was performed by setting criteria for raising the performance of perennial forage crops. Statistical data on agricultural crops provided an insight into current intra-annual land cover dynamics. Rainfall erosivity was computed on the basis of 22-year hourly precipitation data. The model was used to: i) quantify the potential soil losses of arable land in the study area, ii) identify those areas highly affected by erosion risks iii) explore the potential for soil conservation of perennial crops, thereby enabling appropriate preventive measures to be identified. The erosion rates, averaged over an area of about 140’000 ha, are estimated to 33.42 Mg ha⁻¹ y⁻¹. More than 59% of the study area was subjected to soil losses higher than 11 Mg ha⁻¹ y⁻¹ (from moderate to severe erosion) and the highest rates are estimated for steep inland areas. Arable land with severe soil erosion rates (higher than 33 Mg ha⁻¹ y⁻¹) represent about 35% of the whole study area. The risk of soil loss by water erosion in the study area is estimated to be reduced on average by 36% if perennial crops are increased in terms of 35% of the total arable land. The soil erosion data produced compared well with the published local and regional data. This study thus provides useful preliminary information for landscape planning authorities and can be used as a decision support tool in quantifying the implications of management policies.     

Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy)

Soil erosion by water is a serious problem in southern Italy, particularly in Sicily which is one of the Italian administrative regions prone to desertification. Soil erosion not only affects soil quality, in terms of agricultural productivity, but also reduces the availability of water in reservoirs. This study was conducted in the Comunelli catchment in south-central Sicily, to predict potential annual soil loss using the revised universal soil loss equation (RUSLE) and to test the reliability of this methodology to predict reservoirs siltation. The RUSLE factors were calculated for the catchment using survey data and rain gauge measurement data. The R-factor was calculated from daily, monthly and annual precipitation data. The K-factor was calculated from soil samples collected in May and November 2004. The LS topographic factor was calculated from a 20 m digital elevation model. The C- and P-factors, in absence of detailed data, were set to 1. The results were compared with those obtained from another soil loss estimation method based on ¹³⁷Cs and with the soil loss estimated from the sediment volume stored in the Comunelli reservoir between 1968 and 2004.     

陕北地区退耕还林还草工程土壤保护效应的时空特征

以中国退耕还林生态工程重点区域陕北地区作为研究区,基于耕地遥感监测数据集,分析了陕北地区2000-2013年耕地的时空变化特征;基于梯田空间分布,对RUSLE模型进行改进,模拟生成陕北地区土壤侵蚀模数栅格数据并进行精度验证;最后结合耕地变化数据集对陕北地区退耕还林（草）地及未退耕地的土壤侵蚀变化特征进行对比分析,以明确工程对全区土壤侵蚀变化的影响。结果表明,2000-2010年,陕北退耕农田内部侵蚀模数减少了22.70 t/hm ²,是退耕农田区2000年土壤侵蚀模数的47.08%。同期,陕北地区未退耕农田侵蚀模数减少了10.99 t/hm ²,占未退耕农田区域2000年土壤侵蚀模数的28.60%。从陕北全区的角度看,各种土地利用类型2000-2010年土壤侵蚀模数平均减少了14.51 t/hm ²,占2000年全区土壤侵蚀模数的41.87%。由此可见,退耕还林还草工程可以有效减少土壤侵蚀模数,达到土壤保护的作用。其中,由耕地转为林草所导致的侵蚀减少最为显著,对土壤保护的贡献作用最大。但是,2010年以后（2010-2013年）为退耕还林还草巩固时期,因此该阶段陕北地区土壤侵蚀模数和土壤侵蚀量变化较前10年显著降低。     

Quantitative attribution analysis of soil erosion in different geomorphological types in karst areas: Based on the geodetector method

Journal of Geographical Sciences - The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the...     

Effects of rock fragment cover on hydrological processes under rainfall simulation in a semi‐arid region of China

Rock fragment cover has long been an important agricultural crop production technique on the Loess Plateau, China. Although this approach plays an important role in controlling hydrological processes and preventing soil erosion, inconsistent results have been recovered in this field. In this study, we investigated the effects of rock fragment cover on infiltration, run‐off, soil erosion, and hydraulic parameters using rainfall simulation in the field in a semi‐arid region of China. Two field plots encompassing 6 rock fragment coverages (0%, 10%, 20%, 25%, 30%, and 40%), as well as 2 rock fragment positions and sizes were exposed to rainfall at a particular intensity (60 mm h^?1). The results of this study showed that increasing the rock fragment coverage with rock fragments resting on the soil surface increased infiltration but decreased run‐off generation and sediment yield. A contrasting result was found, however, when rock fragments were partially embedded into the soil surface; in this case, a positive relationship between rock fragment coverage and run‐off rate as well as a nonmonotonic relationship with respect to soil loss rate was recovered. The size of rock fragments also exerted a positive effect on run‐off generation and sediment yield but had a negative effect on infiltration. At the same time, both mean flow velocity and Froude number decreased with increasing rock fragment coverage regardless of rock fragment position and size, whereas both Manning roughness and Darcy–Weisbach friction factor were positively correlated. Results show that stream power is the most sensitive hydraulic parameter affecting soil loss. Combined with variance analysis, we concluded that the order of significance of rock fragment cover variables was position followed by coverage and then size. We also quantitatively incorporated the effects of rock fragment cover on soil loss via the C and K factors in the Revised Universal Soil Loss Equation. Overall, this study will enable the development of more accurate modelling approaches and lead to a better understanding of hydrological processes under rock fragment cover conditions.     

Effect of cover management factor in quantification of soil loss: case study of Sungai Akah subwatershed,Baram River basin Sarawak,Malaysia

The present study evaluates the effectiveness and suitability of cover management factors (C factor) generated through different techniques like land use/land cover-based arbitrary value (C_LULC), Normalised Different Vegetation Index-based methods C_NDVI1 and C_NDVI2 and Modified Soil Adjusted Vegetation Index 2-based method (C_MSAVI2). The C factors generated using these four methods were tested in the calculation and assessment of annual average soil loss from an upland forested subwatershed in the Baram river basin using the Revised Universal Soil Loss Equation (RUSLE). The four cover management factor maps generated by this analysis show some variation among the results. The LULC method uses a single arbitrary value for each LULC type mapped in the subwatershed. The other three methods show a range of C values within each mapped LULC type. The effects of these variations were tested in the RUSLE by keeping the factors such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS) constant. The maximum annual average soil loss is 1191 t. ha^?1. y^?1 based on the C_LULC. Soil losses estimated with other three methods are very different compared to those estimated with the C_LULC method. The highest calculated soil loss values were 1832, 1674 and 1608 t. ha^?1. y^?1 in the study area based, respectively, on C_NDVI1, C_NDVI2 and C_MSAVI2 C factors. These maximum values represent the worst pixel scenario values of soil loss in the region. The statistical analysis performed indicates different relationship between the parameters and suggests the acceptance of the methodology based on C_NDVI2 for the study area, instead of a single value method such as C_LULC. Among the other two methods, the C_MSAVI2 was found to be more consistent than the C_NDVI1 method, but both methods lead to over-prediction of annual soil loss rate and therefore need to be reconsidered before applied in the RUSLE.