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GIS与RUSLE模型的喀斯特地区土壤侵蚀研究——以贵州省为例

[目的]对贵州省土壤侵蚀进行快速定量研究,为土壤侵蚀治理工作和土地利用决策提供科学依据。[方法]在GIS技术的支持下,利用日降雨量、土壤类型、土地利用、DEM,MODIS-NDVI等数据,结合RUSLE模型估算研究区土壤侵蚀量。[结果]研究区的2010年年均土壤侵蚀模数为880.81t/(km~2·a),属轻度侵蚀。大部分区域主要以小于500t/(km~2·a)的微度侵蚀为主,占研究区总面积的59.60%。土壤侵蚀面积(轻度侵蚀以上)达71 164.14km~2,占总面积的40.40%。强度以上土壤侵蚀面积达10 431.60km~2,占总面积的5.91%,主要分布在研究区西北部和东北部,以及北部大楼山、武陵山、东南部苗岭以及西部乌蒙山等地势较高以及中东部乌江,西南部北盘江等河流流域。[结论]林地、耕地和草地以及海拔在600~1 600m之间的区域是今后水土流失防治的重点区域。     

基于GIS和RUSLE的高山峡谷区土壤侵蚀研究——以云南省泸水县为例

[目的]研究区域土壤侵蚀,揭示水土流失的空间分异规律,为区域水土保持和生态农业建设提供理论指导依据。[方法]应用GIS和RUSLE模型对云南省泸水县的土壤侵蚀进行研究。RUSLE模型中的因子包括降雨侵蚀力、土壤可蚀性、坡度坡长因子、植被覆盖和水土保持措施因子,运用GIS空间分析模块,获取泸水县土壤侵蚀模数空间分布图,根据SL 190-2007的分级标准进行土壤侵蚀强度分级,并分析该区土壤侵蚀强度空间分布格局。[结果](1)从各强度侵蚀面积上看,泸水县2014年土壤侵蚀以微度侵蚀为主,占总面积的86.86%,但从平均土壤侵蚀模数看,土壤侵蚀量为4.24×10~6 t,平均侵蚀模数为1 373.1t/(km~2·a),土壤侵蚀强度属于轻度侵蚀;(2)土壤侵蚀较严重区与未利用地、耕地空间分布基本一致,在坡度25°~50°的范围内,侵蚀面积占总侵蚀面积的75%,并且在该坡度段上的耕地面积占总耕地的63%,剧烈侵蚀集中分布在未利用地上,中度以上剧烈以下强度侵蚀集中分布在该坡度段上的耕地上,说明该坡耕地、未利用地对土壤侵蚀的贡献最大,要加强对未利用地的生态治理。[结论]坡度大,陡坡垦殖和未利用地的不合理利用是该区土壤侵蚀加重的主要原因,坡度在25°以上的地区不适宜耕种,应优化农业产业结构如实施退耕还林还草等措施,才能有效的保持水土。     

深圳市土地利用对土壤侵蚀的影响研究

运用修正通用土壤流失方程(RUSLE)对深圳市土壤侵蚀进行定量计算,并依据城市水土流失标准进行分级,应用并修正土壤侵蚀强度综合指数和区域土壤侵蚀强度综合指数,对深圳市全市及下辖各区的土地利用和土壤侵蚀关系进行比较分析.结果表明:深圳市较少侵蚀等级以上土壤侵蚀面积为81.588 km2;全市平均土壤侵蚀模数为3570.676 t/(hm2·a),土壤侵蚀模数最大值为447621.594 t/(hm2·a);以土地利用类型划分,最易引起侵蚀的三种土地利用类型是采矿地、未利用地以及工地和推平未建地,最不易引起土壤侵蚀的三种土地利用类型是林地、草地和水田,最易引起土壤侵蚀并造成最大影响的用地类型是果园;而从区域分异来看,南山区和龙岗区发生土壤侵蚀的可能性较大,应及早预防.     

Assessing soil erosion after fire and rehabilitation treatments in NW Spain: Performance of rusle and revised Morgan–Morgan–Finney models

Although the Revised Universal Soil Loss Equation (RUSLE) and the revised Morgan–Morgan–Finney (MMF) are well‐known models, not much information is available as regards their suitability in predicting post‐fire soil erosion in forest soils. The lack of information is even more pronounced as regards post‐fire rehabilitation treatments. This study compared the soil erosion predicted by the RUSLE and the revised MMF model with the observed values of soil losses, for the first year following fire, in two burned areas in NW of Spain with different levels of fire severity. The applicability of both models to estimate soil losses after three rehabilitation treatments applied in a severely burned area was also tested. The MMF model presented reasonable accuracy in the predictions while the RUSLE clearly overestimated the observed erosion rates. When the R and C factors obtained by the RUSLE formulation were multiplied by 0·7 and 0.865, respectively, the efficiency of the equation improved. Both models showed their capability to be used as operational tools to help managers to determine action priorities in areas of high risk of degradation by erosion after fire. Copyright © 2010 John Wiley & Sons, Ltd.     

基于GIS的福建省将乐县土壤侵蚀及保持定量分析

【目的】对福建省将乐县土壤侵蚀及保持量现状进行定量分析,为该地区制定森林经营方案及水土保持工作提供依据。【方法】以福建省将乐县为研究区,首先建立降雨侵蚀力因子(R)图层、土壤可蚀性因子(K)图层、坡长坡度因子(LS)图层,然后依据实际土地覆盖类型和植被覆盖度构建植被覆盖或作物管理因子(C)图层和水土保持措施因子(P)图层。基于地理信息系统(GIS)和修正的土壤通用侵蚀方程(RUSLE)估算土壤侵蚀量和保持量,定量分析坡度(0°,90°)、土地覆盖类型与土壤侵蚀强度之间的相关关系。【结果】2015年研究区的现实侵蚀量为42.64×10~4t/年,平均土壤侵蚀模数为189.07t/(km~2·年)。从6种土壤侵蚀类型来看,微度侵蚀面积占研究区总面积的88.31%,轻度侵蚀面积占10.36%,中度侵蚀面积占1.13%,这3种侵蚀类型的侵蚀量占侵蚀总量的比例分别为12.43%,60.44%和19.79%;强度、极强度、剧烈侵蚀面积及侵蚀量所占比例均较小。各侵蚀等级在研究区内的空间分布较为均匀,总体来说中部、北部地区侵蚀量较大。7个坡度带中,土壤侵蚀量所占比例较大的是[15°,25°)、[8°,15°)和[25°,35°)坡度带,其面积所占比例分别为35.63%,23.95%和17.53%,侵蚀量所占比例分别为44.68%,24.63%和20.90%。研究区年均土壤保持量为6.98×10~6 t,每km~2土壤保持量为3 099.36t/年;有林地和稀疏植被的每km~2土壤保持量均较高,分别为3 773.58和22 254.39t/年,明显高于其他土地覆盖类型。【结论】将乐县微度侵蚀面积所占比例最大,轻度侵蚀的侵蚀量所占比例最大;森林和稀疏植被对将乐县的土壤保持量贡献最大,进行皆伐作业设计时应该尽量减小皆伐面积。     

广西壮族自治区土地利用与土壤侵蚀的关系

[目的]对广西壮族自治区的土壤侵蚀现状进行定量分析,分析土地利用类型与土壤侵蚀的关系,为科学防治土壤侵蚀提供决策依据。[方法]以RUSLE模型为基础,引入喀斯特石漠化修正因子M,构建适合广西地区的土壤侵蚀模型。[结果](1)2015年,研究区土壤侵蚀模数为135.51t/(km~2·a),土壤侵蚀厚度达0.08mm/a,土壤侵蚀面积2.52×10~4 km~2,土壤侵蚀量3.21×10~7 t。其中,喀斯特地区土壤侵蚀面积1.86×10~4 km~2,占土壤侵蚀面积的73.81%,占总侵蚀量的31.01%。(2)土壤侵蚀量占总侵蚀量的大小顺序为:耕地(37.58%)林地(30.94%)草地(16.10%)园地(6.39%)工矿用地(4.09%)裸地(2.16%)。[结论]人类活动干扰强烈的土地利用影响全区土壤侵蚀空间分布格局。