黑土区典型小流域土壤侵蚀空间格局模拟研究

利用校正后的基于GIS的USLE模型预测了黑土区域土壤侵蚀量的空间分布格局。研究结果表明,研究区小流域年侵蚀量值范围在0~60t/(hm² a),无侵蚀、轻度侵蚀、中度侵蚀和强度侵蚀面积分别占研究区总面积的28.7%,56.2%,18.6%和0.1%。研究区坡顶土壤侵蚀量较少〔0~5t/(hm² a)〕,坡肩和坡背侵蚀量较大〔3~15t/(hm² a)〕。基于GIS的USLE不能够很好地模拟黑土区坡麓和坡足区域土壤沉积和侵蚀沟的空间分布格局,但可以较好地模拟坡顶、坡肩和坡背处的土壤流失状况。     

Cesium‐137‐based erosion‐rate determination of a steep mountainous region

Data on quantification of erosion rates in alpine grasslands remain scarce but are urgently needed to estimate soil degradation. We determined soil‐erosion rates based on ¹³⁷Cs in situ measurements. The method integrates soil erosion over the last 22 y (time after the Chernobyl accident). Measured erosion rates were compared with erosion rates modeled with the Universal Soil Loss Equation (USLE). The comparison was done in order to find out if the USLE is a useful tool for erosion prediction in steep mountainous grassland systems. Three different land‐use types were investigated: hayfields, pasture with dwarf shrubs, and pasture without dwarf shrubs. Our test plots are situated in the Urseren Valley (Central Switzerland) with a mean slope steepness of 37°. Mean annual soil‐erosion rates determined with ¹³⁷Cs of the investigated sites ranged between the minimum of 4.7 t ha^–1 y^–1 for pastures with dwarf shrubs to >30 t ha^–1 y^–1 at hayfields and pastures without dwarf shrubs. The determined erosion rates are 10 to 20 times higher compared to previous measurements in alpine regions. Our measurements integrated over the last 22 y, including extreme rainfall events as well as winter processes, whereas previous studies mostly reported erosion rates based on summer time and short‐term rainfall simulation experiments. These results lead to the assumption that heavy‐rainfall events as well as erosion processes during winter time and early spring do have a considerable influence on the high erosion amounts that were measured. The latter can be confirmed by photographs of damaged plots after snowmelt. Erosion rates based on the USLE are in the same order of magnitude compared to ¹³⁷Cs‐based results for the land‐use type “pasture with dwarf shrubs”. However, erosion amounts on hayfields and pasture without dwarf shrubs are underestimated by the USLE compared to ¹³⁷Cs‐based erosion rates. We assume that the underestimation is due to winter processes that cause soil erosion on sites without dwarf shrubs that is not considered by the USLE. Dwarf shrubs may possibly prevent from damage of soil erosion through winter processes. The USLE is not able to perform well on the affected sites. Thus, a first attempt was done to create an alpine factor for the USLE based on the measured data.     

基于USLE的甘南川西北土壤侵蚀研究

甘南川西北位于黄河和长江上游源区,量化研究该区土壤侵蚀对河源区生态安全保障和地方经济可持续发展具重要意义。论文采用多种数据方法,基于USLE就甘南川西北2000—2015年间土壤侵蚀的时空分布特征及变化规律进行量化评估。结果表明:(1)降雨侵蚀力因子R值介于65~411(MJ·mm)/(hm²·h·a),高值区主要分布在东南部,空间分布与该区降雨格局基本一致;(2)土壤可蚀性因子K值介于0.19~0.41(t·hm²·h)/(hm²·MJ·mm),高值呈斑块状零星分布,与地带性土壤物化性状有关;(3)坡长坡度因子LS值介于0~8.24,高值主要分布在中北部高山地带,低值分布在东北部和西南部地形较平缓区域;(4)植被覆盖管理因子C值介于0~1,高值集中分布在研究区的西北部与西南部,与该区植被覆盖稀疏有关;(5)基于USLE的甘南川西北年侵蚀量为3.3×108 t/a,总体表现为轻度侵蚀;(6)2000—2015年间,研究区土壤侵蚀呈减弱态势,与增温背景下植被活动增强有关。     

GIS/RS集成技术在叙利亚滨海土壤侵蚀评价和模拟研究上的应用

An integrated remote sensing(RS) and geographic informtion system(GIS) technique was employed to characterize the spatial distribution of the risk of soil erosion by water on Lakaia district ,Syria,The universal soil loss equation(USLE)was used to calculate the annual soil loss rates for Latakia soils ,Mainly,remote sensing data soil survey,land use inventory,elevation data and climatic atlases are used as resource data sets to generate USLE facto values ,The results revealed that integration of GIS/RS with USLE was a practical and effective approach for monitoring soil erosion over large areas.     

Empirical reformulation of the universal soil loss equation for erosion risk assessment in a tropical watershed

Efficient intervention to control soil erosion in rural tropical landscapes requires accurate models for predicting the spatial location and intensity of degradation. The Universal Soil Loss Equation (USLE) has commonly been applied for spatial erosion risk assessment in the tropics, but has rarely been validated using ground observations of soil degradation. As with any empirical model, application in new regions requires calibration before results are used for decision support. We evaluated USLE effectiveness for predicting erosion in a small watershed in western Kenya based on 420 georeferenced ground observations of ordinal erosion class (three categories) systematically collected from throughout the basin. Relativized model factors were parameterized using standard remote assessment methods based on interpolated spatial data layers. Inference of degradation status at cultivated sites was estimated by calibration to near infrared diffuse reflectance spectra obtained from sampled soils; diagnostic models based on spectra produced validation accuracies of 78% for three categories. Association between USLE predicted risk and observed erosion, estimated using mixed effects logistic regression to control for within-site variability, correctly classified only 38% of sites into three degradation classes and model sensitivity for delineating regions of severe degradation was only 28%. Graphical modeling was used to identify those USLE risk factors that were conditionally associated with observed degradation, and an ordinal logistic regression model, employing only these factors was developed. This alternative model, which allowed statistical flexibility in estimating effect direction and strength, correctly predicted ordinal degradation class at 54% of field sites, with 55% sensitivity for the severe degradation class. This result suggests a critical need for efficient ground-based sampling schemes to be used in conjunction with flexible statistical models based on USLE factors for future investments in erosion risk assessment in the tropics.     

Validation of a 3-D enhancement of the Universal Soil Loss Equation for prediction of soil erosion and sediment deposition

A study was conducted on three U.S. military training areas to validate the Unit Stream Power Erosion and Deposition (USPED) model, a 3-dimensional enhancement to the Universal Soil Loss Equation (USLE). The USPED model differs from other USLE-based models in the manner in which it handles the influence of topography on the erosion process. As a result, the USPED model predicts both erosion and deposition, while most other USLE-based models are limited to predictions of erosion only. Erosion and deposition from a small watershed at Fort Hood, Texas, USA was quantified using ¹³⁷Cs, a radioactive isotope found in soils around the world as a result of fallout from post-World War II nuclear testing. We compared ¹³⁷Cs-derived erosion/deposition measurements with estimates derived from the USPED model and two applications of the USLE. Soil erosion and sediment deposition estimates generated by the USPED model were more accurate and less biased than results of the USLE applications. Both applications of the USLE consistently and significantly overestimated soil erosion; the USPED model did not. The USPED model was subsequently applied to Camp Guernsey, Wyoming, USA and Fort McCoy, Wisconsin, USA. Model estimates of soil erosion and sediment deposition were compared with field estimates of the same parameters. Based on 3 levels of soil erosion and 3 levels of sediment deposition, the model results agreed with field estimates 76 and 89% of the time at the two locations, respectively.     

福建省水土流失现状分析

[目的]运用遥感技术监测福建省水土流失状况,为研究区的水土保持工作提供一定的科学依据。[方法]利用2014年Landsat-8OLI等遥感数据,基于通用土壤流失方程(USLE)定量计算得到研究区的土壤侵蚀量,并运用GIS空间分析和数理统计的方法分析水土流失在地理空间上分布特征。[结果]福建省2014年的水土流失总面积为10 939.8km2,总流失率为8.93%,其中以轻度流失为主,占总流失面积的82.3%,境内流失等级为强度及以上的区域主要集中在北部的宁德和南平、南部的漳州和西部的龙岩一带;其中22个水土流失重点县流失面积为4 786.65km2,占全省流失总面积的43.76%,平均流失率为10.54%。[结论]水土流失主要发生在海拔高程为200~1 000m的区域,流失面积有8 954.35km2,占流失总面积的81.85%;坡度与水土流失关系密切,水土流失主要发生在坡度为8°~25°的区域,流失面积有69 871.71km2,占总流失面积的57.23%;容易发生水土流失的土地利用类型是裸地和林地,流失比例分别达到30.99%和9.47%。     

基于GIS的慈溪市土壤侵蚀敏感性评价

[目的]对影响浙江省慈溪市土壤侵蚀敏感性的各因素进行评价,为该市进行环境功能区划和各项水土保持措施工程的布局调整提供参考。[方法]借鉴土壤侵蚀流失USLE模型,选取降雨侵蚀力、土壤质地、植被覆盖和地形起伏度4因子构建土壤侵蚀敏感性评价体系,并运用GIS进行土壤侵蚀敏感性分析。[结果]慈溪市土壤侵蚀敏感性在空间格局上呈半圆环状结构分布,并且轻度敏感区面积为733.05km2,占比高达75.70%,广泛分布于平原乡镇地区;不敏感区主要分布于近海滩涂区域,极敏感、高度敏感及中度敏感区则位于南部的丘陵、山地地区。[结论]慈溪市土壤侵蚀敏感性评价结果与水土流失现状空间分布走势大致相符,为此应重视和预防水土保持工作。     

东北地区不同耕作方式农田土壤风蚀特征

为探究不同耕作方式农田土壤风蚀特征,揭示风蚀对表层土壤理化性质及养分含量的影响,以东北地区典型农田土壤(黑土和风沙土)为研究对象,通过野外集沙仪定点监测与室内理化分析等方法,对不同耕作方式(垄作、免耕)和不同地表覆盖措施(无覆盖、留茬、覆盖)下的土壤风蚀特征展开研究。结果表明:(1)风沙土的输沙量显著高于黑土,在0—100cm高度范围内风沙土的输沙量平均为黑土的168倍。随高度的上升输沙量急剧减少,其中0—10cm输沙量最大,占总输沙量的50%以上,40cm以上则无明显风蚀物;(2)不同耕作方式下,免耕农田土壤风蚀输沙量较垄作样地减少了66.0%~94.1%;而相同耕作措施下,不同地表覆盖的输沙量表现为无覆盖>留茬>覆盖,与无覆盖相比,留茬及秸秆覆盖下的输沙量可以减少90.3%~99.4%;(3)受风蚀影响,表层土壤颗粒、有机质及养分流失严重,其中风蚀物的砂粒含量是表层土壤的1.06~1.42倍,且10—20cm风蚀物中有机质、全氮和全磷含量均比表层土壤高;(4)通过修正风蚀方程(RWEQ)估算得出,垄作无覆盖(RTNF)风蚀模数高达181.7~86582.9t/(km^2·a),风蚀剧烈,而免耕覆盖(NTF)的风蚀模数仅为9.89t/(km^2·a),为微度风蚀。研究显示垄作及无覆盖方式下农田土壤风蚀程度剧烈,加剧了表层土壤颗粒和养分流失的风险,而免耕和地表覆盖能有效缓解风蚀危害。     

基于GIS的黑龙江省拉林河流域土壤侵蚀空间特征分析

以黑龙江省拉林河流域为研究区,利用USLE计算土壤侵蚀模数,并建立了基于GIS的空间栅格数据库。采用地统计分析方法,进行研究区的土壤侵蚀模数空间特征分析。对比现行两种土壤侵蚀强度分级标准,分析确定适用的土壤侵蚀强度分级标准。采用空间和趋势分析方法,进行研究区的土壤侵蚀强度空间分布特征分析。结果表明:（1）研究区的土壤侵蚀模数分布具有强烈的空间相关性,自西向东、由北至南呈线型增大的分布趋势;（2）《黑土区水土流失综合防治技术标准标准》中规定的土壤侵蚀强度分级标准适用性更强;（3）研究区的土壤侵蚀面积占总面积的94%,强烈、轻度和中度水力侵蚀为主要的侵蚀强度类型;强烈水力侵蚀主要分布于西部的洪积台地,轻度水力侵蚀主要分布于东部的低山丘陵宽谷,中度水力侵蚀主要分布于中部的地貌过渡带,极强烈和剧烈水力侵蚀主要呈零散状分布于东部的低山丘陵沟壑,中部和西部也有零星分布;随植被覆盖度的降低,土壤侵蚀强度等级自东向西呈增大趋势。