基于实地和遥感调查的离子型轻稀土尾砂土壤侵蚀对植被修复措施响应

稀土开采产生大量尾砂,导致严重土壤侵蚀,伴生水质和地质灾害,评价植被修复措施对稀土尾砂土壤侵蚀治理效果可为措施优选提供理论依据。以寻乌县离子型轻稀土尾砂区为研究区,基于1982—2015年GIMMS NDVI 3 g、DEM等遥感和尾砂理化性状现场调查数据,采用空间代时间方法,结合RUSLE模型及其全微分公式探究不同修复年限土壤侵蚀量对植被修复措施的响应机理。结果表明:1982—2015年研究区土壤侵蚀模数显著下降,倾向率为-60 t/(km~2·10a),突变年份为2008年;在植被修复措施实施年(2008年)前后,多年平均土壤侵蚀量减幅超过60%;土壤侵蚀模数呈现上升、平稳、上升、平稳、上升和下降的阶段性变化,与NDVI时程变化呈负相关;水土保持措施、植被覆盖、土壤可蚀性和降雨变化对土壤侵蚀量减小的贡献率分别为33.18%,32.19%,19.95%,13.19%。植被修复过程中,矿区土壤侵蚀量减少的主要影响因子为水土保持措施因子和植被覆盖因子。     

基于GIS和RUSLE的滇池流域土壤侵蚀敏感性评价及其空间格局演变

土壤侵蚀是滇池流域重要的生态问题之一,掌握滇池流域土壤侵蚀敏感性的时空变化特征有助于水土保持工作的实施和改进。以降雨量、DEM、土壤类型和Landsat影像为数据源,选择降雨、土壤、坡度坡长、植被覆盖4个因子建立土壤侵蚀敏感性评价体系,对滇池流域进行土壤侵蚀敏感性评价。结果表明:滇池流域土壤侵蚀敏感性以轻度敏感和中度敏感为主。空间分布上,轻度敏感区主要分布在滇池周边。中度敏感区主要分布在滇池流域山地区域,地形陡峭。时间变化上,1999—2014年滇池流域土壤侵蚀敏感程度呈下降趋势。轻度敏感区域面积增加20.18%,中度敏感区域面积减少20.31%,轻度敏感区的增加来源于中度敏感区的转变,转变区域分布于滇池流域西北部和东南部。在土壤侵蚀敏感性影响因子中,降雨是影响滇池流域土壤侵蚀敏感性的关键因子。研究滇池流域土壤敏感性时空变化,识别滇池流域易发生土壤侵蚀的区域,有助于该区域水土保持措施实施、生态治理和土地利用优化。     

Assessing spatial variability and erosion susceptibility of soils in hilly agricultural areas in Southern Italy

Soil erosion is one of the main environmental problems in the Mediterranean area. This problem is becoming even more important especially in Italy, in the Apennines, where severe erosive processes occur due to the action of concentrated running water. The erodibility (K-Factor) of a soil, estimated using the Revised Universal Soil Loss Equation (RUSLE), is a measure of its susceptibility to erosion and depends on several soil properties such as organic matter, texture and permeability and structure.To assess the spatial variability of soil properties and soil erodibility in hilly agricultural areas and to investigate the relationships between soil features and landscape morphodynamics, a detailed study in Molise region (southern Italy), in a small drainange basin located along its hilly Adriatic flank, was carried out. In this catchment, 63 topsoil samples (A horizons) were collected and 10 soil profiles, forming a catena crossing 3 land units, were sampled. The calculated K-Factors ranges between 0.012 and 0.048 t ha h ha⁻¹ MJ⁻¹ mm⁻¹ indicating a complex spatial distribution, due to the several local pedological and geomorphological factors affecting soil erodibility. The results give clear evidence about the relationships among soil characteristics, soil erodibility and landscape morpho-dynamics (land units).Comparing the soil loss rates estimated for the study area with those reported in literature, a good correspondence can be observed only for the more stable land unit, not characterized by intense erosive processes. The proposed methodology is suitable to highlight areas characterized by similar morphodynamics features, and comparable soil erodibility, for a more effective spatialization of K factor.     

Modelling soil erodibility in mountain rangelands of southern Kyrgyzstan

Soil erosion in mountain rangelands in Kyrgyzstan is an emerging problem due to vegetation loss caused by overgrazing. It is further exacerbated by mountain terrain and high precipitation values in Fergana range in the south of Kyrgyzstan. The main objective of this study was to map soil erodibility in the mountainous rangelands of Kyrgyzstan. The results of this effort are expected to contribute to the development of soil erodibility modelling approaches for mountainous areas. In this study, we mapped soil erodibility at two sites, both representing grazing rangelands in the mountains of Kyrgyzstan and having potentially different levels of grazing pressure. We collected a total of 232 soil samples evenly distributed in geographical space and feature space. Then we analyzed the samples in laboratory for grain size distribution and calculated soil erodibility values from these data using the Revised Universal Soil Loss Equation (RUSLE) K-factor formula. After that, we derived different terrain indices and ratios of frequency bands from ASTER GDEM and LANDSAT images to use as auxiliary data because they are among the main soil forming factors and widely used for prediction of various soil properties. Soil erodibility was significantly correlated with channel network base level (geographically extrapolated altitude of water channels), remotely sensed indices of short-wave infrared spectral bands, exposition, and slope degree. We applied multiple regression analysis to predict soil erodibility from spatially explicit terrain and remotely sensed indices. The final soil erodibility model was developed using the spatially explicit predictors and the regression equation and then improved by adding the residuals. The spatial resolution of the model was 30 m, and the estimated mean adjusted coefficient of determination was 0.47. The two sites indicated different estimated and predicted means of soil erodibility values (0.035 and 0.039) with a 0.05 significance level, which is attributed mainly to the considerable difference in elevation.     

基于RUSLE的2010年商南县土壤侵蚀特征分析

[目的]以长江源头陕西省商南县为例,分析县域土壤侵蚀空间分布,为正确认识与防治长江上游水土流失和做好水土保持防治工作提供科学依据。[方法]基于Landsat TM7和ETM+影像,获取商南县2010年土地利用信息,采用修正通用土壤流失方程(RUSLE)确定方程中各影响因子,对商南县土壤侵蚀现状进行定量评价。[结果]林地是商南县主要土地利用类型,占县域总面积的87.05%,其次是耕地(9.43%)、居民地(2.82%)、水体(0.64%)、未利用地和草地(0.06%)。受坡耕地和低覆盖林草地的影响,商南县2010年土壤侵蚀较严重,平均侵蚀模数4 953.76t/(km2·a)。受侵蚀(轻度以上)面积1 319.3km2,占总面积的57.03%。强度和极强度侵蚀级别面积所占比例为24.10%,其次为轻度侵蚀级别,面积为14.31%,中度和剧烈侵蚀级别面积分别为6.23%,12.39%。剧烈和强度侵蚀主要分布在北部、中部及东南部的山区地段的坡耕地。虽然强度和剧烈侵蚀级别面积比例不是很高,但对该县总侵蚀量的贡献最大,达到52.29%。[结论]不适宜的土地利用是引起严重土壤侵蚀的主要原因;应将县域北部、中部及东南部山区的坡耕地作为防治的重点。     

生产建设项目区土壤侵蚀研究进展简

生产建设活动导致生产建设项目区土壤侵蚀发生深刻变化,生产建设项目区土壤侵蚀的研究对于区域土壤侵蚀控制,改善项目区及其周边地区生态环境具有重大意义;因此,生产建设项目区土壤侵蚀的研究亦应形成其完善的理论体系,从而为生产建设项目区的土壤侵蚀控制提供科学指导.从生产建设项目土壤侵蚀的基本概念、影响因素、产流产沙规律等方面总结生产建设项目土壤侵蚀的研究现状,并对研究中存在的部分问题进行评述,以期为今后生产建设项目区土壤侵蚀的相关研究提供参考.     

基于RUSLE的蔗区小流域土壤侵蚀特征研究

[目的] 探讨广西壮族自治区典型赤红壤集约化蔗区小流域的土壤侵蚀状况,以及土壤侵蚀强度与不同坡度、土地利用类型的关系,为广西集约化蔗区小流域防治土壤侵蚀提供科学参考。[方法] 在GIS空间分析技术支持下,利用修正的通用土壤流失方程（revised universal soil loss equation,RUSLE）对其进行定量估算。[结果] ①那辣小流域坡度在0°~35°之间,坡耕地（甘蔗）、林地（桉树）分别占土地利用总面积的82.85%,10.99%,道路和沟渠共占6.16%。2020年流域平均土壤侵蚀速率为22.97 t/（hm²·a）,属轻度侵蚀水平,是水利部规定的南方红壤丘陵区土壤允许流失量5 t/（hm²·a）的4.6倍;②流域土壤侵蚀主要发生在5°~25°的坡度范围内,是预防和治理水土流失的重点区域;③不同土地利用类型中,平均侵蚀速率最大的是林地（桉树）,为53.59 t/（hm²·a）,分别是坡耕地（甘蔗）、道路、沟渠的2.84,2.12,27.91倍。[结论] 应用RUSLE模型通过借助软件输入相关参数和处理数据,即可估算出蔗区土壤侵蚀及不同坡度、土地利用类型的土壤侵蚀强度分布特征,应合理规划并利用管理好流域的坡耕地（甘蔗）、林地（桉树）、道路等土地利用类型,采取具有针对性的、有效的水土保持措施。     

区域尺度喀斯特区石漠化强度对土壤流失的影响

石漠化和水土流失是西南喀斯特区突出的生态问题,制约着社会经济的发展。目前,石漠化与土壤流失的耦合关系尚未系统探明,石漠化强度评价因子植被盖度、土层厚度和基岩裸露率的交互作用如何影响土壤流失知之甚少。基于石漠化现状的调查,采用RUSLE模型、Getis?OrdGi*、地理探测器等方法,测算了贵州喀斯特区土壤侵蚀状况并识别了冷热区分布,量化了石漠化强度评价因子与土壤侵蚀之间的关系,解析了因子组合对土壤流失的交互影响。结果表明：1）贵州喀斯特区土壤侵蚀以中度和微度侵蚀为主,平均土壤流失率17.69 t/(hm2·a),侵蚀热区（重点防治区）主要集中在贵州西部经济相对欠发达区,侵蚀冷区（轻微区）则主要集中在黔北遵义市和黔中贵阳市等经济相对发达区。2）土壤流失随石漠化强度评价指标植被盖度、土层厚度的增加呈降低趋势,随基岩裸露率的增加则呈增加趋势;石漠化与土壤流失之间并非简单的线性关系,而呈复杂的非线性关系,3个评价因子分别以三次曲线函数、指数函数和反正弦函数拟合优度最高。3）石漠化强度评价因子对土壤流失空间分异的解释力依次为植被盖度、基岩裸露率和土层厚度,且因子组合对土壤流失的交互影响均呈非线性增强,其中基岩裸露率与植被盖度的交互作用起主导作用,其次是土层厚度与植被盖度,基岩裸露率与土层厚度的解释力最小。研究结果可为喀斯特区水土流失、石漠化的协同防治提供理论参考。     

澜沧江中下游流域土壤侵蚀时空演变特征

为了探究土壤侵蚀演变机制,以澜沧江中下游流域为研究区域,利用改进的土壤流失方程(RUSLE)模型,开展流域内土壤侵蚀时空演变特征研究,引入随机森林算法探讨了流域内土壤侵蚀因子的相对重要程度。结果表明:澜沧江中下游流域2005—2015年土壤侵蚀量为0～1.89万t/(km²·a),平均土壤侵蚀模数为0.252万t/(km²·a),中下游子流域平均土壤侵蚀模数处于较低风险以上和中风险侵蚀以下级别。自2005年以后,澜沧江中下游流域土壤侵蚀空间分布特征呈现中度侵蚀风险区域扩张,高度和低度侵蚀风险收缩的趋势。随机森林算法结果发现植被覆盖管理因子和地形因子是影响澜沧江中下游流域土壤侵蚀的主要因素,土壤可蚀性因子、降雨侵蚀因子和水土保持措施因子的相对重要程度偏低,均未超过20%。可见,土壤侵蚀的时空异质性主要是由于植被覆盖和地形影响改变了局部气候而导致的。     

基于GIS和RUSLE的粤东黄冈河流域土壤侵蚀评估

以TM影像图、数字高程模型DEM、土地利用类型图、土壤数据为信息源,以GIS技术和RUSLE模型为研究方法,对粤东黄冈河流域土壤侵蚀进行了评估,并分析了影响土壤侵蚀的主要因素。结果表明,降雨是影响土壤侵蚀的最主要因素,该流域多年平均土壤侵蚀模数为1 745.5 t/(km2.a),属轻度侵蚀;地形地貌是影响土壤侵蚀的显著因素,随着地形坡度的增加土壤侵蚀模数显著增大;不同土地利用类型的土壤侵蚀量差异较大。根据研究结果,指出15°—25°、25°—35°两个坡度带和居民点及交通用地、草地为黄冈河流域土壤侵蚀防治的重点区域。