土壤侵蚀时空动态分析——以黑龙江省宾县为例

利用1990年和2010年两期Landsat TM数据,基于RS和GIS技术及通用土壤侵蚀方程(RUSLE),完成黑龙江省宾县两个时期的土壤侵蚀动态变化分析,以期揭示该区域土壤侵蚀空间分布格局与时空动态演变规律。结果表明:两个时期土壤侵蚀总体格局基本一致,都是以微度和轻度侵蚀为主,面积比例分别为80.68%和74.71%;微度和极强度侵蚀的变化率呈缩小趋势,轻度、中度和重度侵蚀呈增加趋势,土壤侵蚀有加剧的趋势;轻度和强度侵蚀的主要流向为中度侵蚀,中度和极强度侵蚀的主要流向为强度侵蚀。     

地理国情监测在秦岭山地土壤侵蚀中的应用

利用国情监测成果,分析了2010~2014年秦岭山地丹江流域土地利用类型变化特征,并探讨了土地利用类型方式转变对流域土壤侵蚀的影响。结果表明,微度侵蚀和轻度侵蚀面积在波动中呈减少趋势;中度侵蚀至剧烈侵蚀面积呈上升趋势,在一定程度上,流域的侵蚀状况加剧。土壤侵蚀较严重的土地利用类型是耕地和裸地。     

基于GIS与RUSLE的土壤侵蚀量时空变化分析

基于修正的土壤流失方程(RUSLE),运用RS和GIS技术对葫芦岛市的土壤侵蚀状况进行分析。结果表明,葫芦岛市年均土壤侵蚀量17 867 598.32 t,年均土壤侵蚀模数为16.13 t/(hm2×a),属于轻度侵蚀。葫芦岛市中度侵蚀以上的土壤侵蚀面积占总侵蚀面积的11.31%,土壤侵蚀模数占总侵蚀量的40.17%。中度侵蚀以下的土壤侵蚀面积占总侵蚀面积的88.96%,土壤侵蚀量占总侵蚀量的59.83%,研究区土壤侵蚀空间差异性大。分析土壤侵蚀与坡度和土地利用之间的关系表明,6°~25°为研究区主要侵蚀坡度段,裸土地、旱地、林地和草地是研究区土壤侵蚀的主要发生区,葫芦岛市应将其列为水土保持重点治理对象,采取有效措施,改善土壤侵蚀现状。     

湖南省典型区域土壤侵蚀监测方法研究与应用

土壤侵蚀的变化受到地表覆盖、植被覆盖度、地形地貌等多种因素的影响。本文选取新化县作为湖南省典型区域进行研究,基于土地利用数据、数字高程模型,依据土壤侵蚀面蚀分级指标、通用土壤流失模型、坡度因子,建立土壤侵蚀风险评价方案,完成2020年新化县土壤侵蚀强度计算,并结合2008年土壤侵蚀数据进行时空分析。结果表明：2020年新化县土壤侵蚀量略有增加,但均属于轻度土壤侵蚀;两个年度的轻度、强度、极强度、剧烈土壤侵蚀空间分布基本相同;相比2008年,由于荒山造林,2020年土壤侵蚀强度为强度、极强度、剧烈的地区得到了一定改善,同时由于灌木林和旱地面积的增加,2020年部分地区的中度水土流失加剧。本文方法利用遥感影像与土地利用数据可快速监测土壤侵蚀的变化趋势,为相关部门提供方法依据与数据支持,为生态环境改善提供有利服务。     

综合137Cs，RS和GIS的土壤侵蚀评估和预测——以云南小江流域为例

综合应用137Cs技术、RS技术和GIS技术,进行云南小江流域土壤侵蚀的评估和预测研究,探索中国西部山区观测资料缺乏、USLE(Universal Soil Loss Equation)方程不适宜区域土壤侵蚀评估与预测方法。通过137Cs技术,采用非农耕地与农耕地土壤侵蚀模型确定区内林地、灌丛、草地、坡耕地和裸地的年均侵蚀模数分别为356—1531 t/(km2·a),330—1709 t/(km2·a),886—3885 t/(km2·a),5197—12454 t/(km2·a)和15000 t/(km2·a)以上。解译小江流域1987年(Landsat TM)、1995年(Landsat TM)和2005年(Landsat ETM)遥感影像,获得流域不同时期土地利用图,将其与1∶50000 DEM模型进行叠置分析,建立小江流域土地利用的空间分布图,结合利用137Cs确定的土壤侵蚀速率数据,进行土壤侵蚀分区与制图,分析土壤侵蚀的时空变化。结果表明:1987年—2005年流域轻度以上侵蚀面积占总面积的66.0%—67.3%,变化不大,但侵蚀强度明显加剧,1987年—1995年间尤为明显;中度侵蚀、强度侵蚀、极强度侵蚀区面积分别增加30%、23%和26%;小江流域1987年、1995年和2005年土壤侵蚀量分别为7.51×106t/a,8.19×106t/a和8.18×106t/a。进而选用1995年和2005年的土壤侵蚀数据构建Markov-CA(马尔可夫—元胞自动机)预测模型,获得2015年流域土壤侵蚀分区图,并预测2015年土壤侵蚀量为8.17×106t,与2005年侵蚀量接近。研究结果真实地反映了小江流域土壤侵蚀的变化过程与主要驱动因子,研究方法适合中国西部山区土壤侵蚀评估与预测。     

大理河流域土壤侵蚀风险及其空间格局分析

本文利用遥感影像提取大理河流域相关信息,采用水利部部颁标准评价土壤侵蚀风险等级,并与地形特征进行叠加分析。结果显示:研究区侵蚀风险以中度和轻度为主;坡度是主要影响因素,坡度越大侵蚀风险区越集中,尤其是强度及以上区域,集中程度达到90%以上;侵蚀主要分布在1000m—1400m的两个高程带内。研究结果可以辅助管理部门进行侵蚀治理决策。     

基于遥感和GIS的宣化县水土流失定量空间特征分析

以遥感和GIS技术为支撑,利用通用的土壤流失方程(USLE)的修正模型(RUSLE)定量评估宣化县2000年的水土流失量和土壤侵蚀强度,并对宣化县水土流失空间分布特征进行了分析。结果表明,宣化县2000年土壤侵蚀(轻度侵蚀以上)面积为982.85 km2,占宣化县总面积的39.25%,平均土壤侵蚀模数为13.92 t/hm2.a,属于轻度侵蚀;坡度越大,极强度及剧烈侵蚀越有可能发生,从整体来看,15°~25°是侵蚀比例最大的坡度带。宣化县土壤侵蚀主要集中于灌草地和旱地两种土地类型,两者土壤侵蚀面积占宣化县2000年总土壤侵蚀面积的93.897%。     

孤山川流域近30年土壤侵蚀时空动态特征分析

针对区域水土保持效益评价、土壤流失治理的需求,选择黄土高原土壤侵蚀较为严重的孤山川流域为研究区,定量研究了孤山川流域近30a的土壤侵蚀时空变异特征。结果表明,1975~2006年间,研究区土壤侵蚀的变化分两个阶段。第一阶段为1975~1986年,土壤侵蚀强度加剧,侵蚀面积增加了138.13km2,流域东南部增加最多;第二阶段为1986~2006年,全流域土壤侵蚀强度减弱,侵蚀面积减少了163.09km2,1986年和1997年,东部地区减弱趋势更明显。中度以上的土壤侵蚀主要发生在高程1 070~1 300m处,都对应于18°~35°的陡坡地;1975年和2006年,中度以上侵蚀分别集中在900~1 150和1 300~1 800,单位为MJ·mm·hm-2·h-1。流域土壤侵蚀主要发生在耕地和林地。1975~2006年,耕地面积减少,林草地面积增加,土地利用向良性循环发展。可为认识黄土丘陵沟壑区I副区土壤侵蚀规律和该区土壤侵蚀防治宏观决策提供科学支撑。     

长江上游小流域土壤侵蚀动态模拟与分析

以长江上游甘肃省尚沟流域为研究区,在遥感影像和GIS空间分析技术支撑下,根据USLE因子算法生成各因子栅格图,借助地图代数运算,估算了尚沟流域1998年和2004年的土壤侵蚀量,并对2004年土壤侵蚀与其环境背景因子进行叠加和空间统计分析。在此基础上,构建了与GIS软件平台集成的地理元胞自动机,模拟了该流域2004年、2010年和2020年土壤侵蚀空间演化情形。结果表明:研究区平均侵蚀量从1998年的6598.1t/km2下降到2004年的5923.3t/km2,侵蚀面积净减少172.3hm2,输沙量减少9.15×104t;1300～1400m的海拔高程带、25～35°坡度带、南坡和旱耕地是发生水土流失的主要区域;经模拟,2010年总侵蚀面积为93.49km2,侵蚀总量73.15×104t,侵蚀模数为5126t/km2,土壤侵蚀状况总体上将有所减缓。     

神东矿区土壤侵蚀时空特征及驱动力分析

针对神东矿区土壤侵蚀生态破坏及煤炭开采对矿井采区土壤侵蚀的影响问题,该文基于RUSLE模型,提出一种基于矿区和矿井尺度探究矿区土壤侵蚀演变特征并结合地理探测器进行驱动力分析的研究方法。结果表明:(1)矿区尺度上土壤侵蚀呈加重趋势,1989—2019年土壤侵蚀量增加30.28×10~5 t,空间上以微度和轻度侵蚀散布全区,中度和强度侵蚀次之,极强度和剧烈侵蚀最少;(2)矿井尺度上,补连塔、榆家梁矿井受到采矿的负面影响,大柳塔矿井受到生态措施的正面影响,活鸡兔、石圪台矿井受到的负面影响被正面影响消除;(3)各因子对土壤侵蚀的解释力为:坡度>土地利用类型>降雨量>植被覆盖度,因子交互作用的解释力强于单因子,坡度>35°,降雨为416.10～420.69 mm、植被覆盖度为0.5～0.6及未利用地的区域为土壤侵蚀高风险区。该研究方法可摸清矿区的土壤侵蚀变化规律以及矿井受采矿活动的干扰,为矿区实行生态管理提供决策支持。     

Temporal and spatial relationships between soil erosion and ecological restoration in semi-arid regions: a case study in northern Shaanxi,China

ABSTRACT

To assess the effects of the Grain for Green Program (GGP) on soil erosion is essential to support better land management policies in the Chinese Loess Plateau. Studies on the evaluation of the effects of the GGP on soil erosion have garnered heightened attention. However, few studies examined the efficiency of GGP on soil erosion control through spatial relationship analysis. Thus, this study focuses on analyzing the spatial variation relationship between soil erosion and GGP in northern Shaanxi, Chinese Loess Plateau, from 1988 to 2015. The Universal Soil Loss Equation was used to quantify changes in soil erosion at the regional and watershed scales, and the Geographically Weighted Regression model was used to analyze the spatial relationships between land use and land cover (LULC) and soil erosion. Our results indicated that the major characteristic of LULC change during the GGP was a rapid increase of vegetation area and a rapid decrease of cropland. Bare lands contributed to the most serious soil loss, followed by croplands and sparse grasslands. The GGP had a globally positive influence on the decrease in soil erosion over the study area, but the amount of soil erosion in western and northern regions maintained a severe level. Spatial heterogeneity in the nature of the relationships among different vegetation, croplands, and soil erosion was also observed. The change rate of wood and the change rate of soil erosion in northern sub-watershed represented a negative relationship, while the change rate of sparse grassland was negatively correlated to the change rate of soil erosion in 21 sub-watersheds, account for 72% of the study area. The GGP implemented in northern sub-watersheds were more effective for soil erosion control than southern sub-watersheds. We propose that current areas of vegetation can support soil erosion control in the whole northern Shaanxi, but local-scale ecological restoration can be considered in northern sub-watersheds.     

Assessment of soil erosion using remote sensing and GIS in Nagpur district, Maharashtra for prioritisation and delineation of conservation units

In the present study, soil loss in Nagpur district of Maharashtra is predicted employing USLE method and adopting integrated analysis in GIS to prioritise the tahsils for soil conservation and for delineation of suitable conservation units. Remote sensing techniques are applied to delineate the land cover of the district and to arrive at annual cover factors. Results indicate that potential soil loss of very slight to slight (>5–10 tons/ha/year) exist in the valleys in north western, northern and in the plains of central and eastern parts of the district. Moderate to moderately severe erosion rates (10 to 20 tones/ha/year) is noticed in the southeastern and some central parts. Severe, very severe and extremely severe erosion types (20 to 80 tons/ha/year) are noticed in the northern, western, southwestern and southern parts of the district. The average soil loss is estimated to be 23.1 and 15.5 tons/ha/yr under potential and actual conditions respectively. Slight, moderate, moderately severe and extremely severe potential erosion covering about 41 per cent area of the district is reduced to negligible and very slight rates of actual erosion under the influence of present land cover leading to a reduction of 7421.2 tones of potential soil loss. Priority rating of the tahsils is evaluated from the area weighted mean quantum of soil loss. Multi-criteria overlay analysis with the parameters of soil erosion, slope, soil depth, land cover and surface texture with rating for the constituent classes has resulted in delineation of nine conservation units. Appropriate agronomic and mechanical practices are suggested in the identified units for minimizing the erosion hazard.     

Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models

This study attempts to identify and forecast future land cover (LC) by using the Land Transformation Model (LTM), which considers pixel changes in the past and makes predictions using influential spatial features. LTM applies the Artificial Neural Networks algorithm) in conducting the analysis. In line with these objectives, two satellite images (Spot 5 acquired in 2004 and 2010) were classified using the Maximum Likelihood method for the change detection analysis. Consequently, LC maps from 2004 to 2010 with six classes (forest, agriculture, oil palm cultivations, open area, urban, and water bodies) were generated from the test area. A prediction was made on the actual soil erosion and the soil erosion rate using the Universal Soil Loss Equation (USLE) combined with remote sensing and GIS in the Semenyih watershed for 2004 and 2010 and projected to 2016. Actual and potential soil erosion maps from 2004 to 2010 and projected to 2016 were eventually generated. The results of the LC change detections indicated that three major changes were predicted from 2004 to 2016 (a period of 12 years): (1) forest cover and open area significantly decreased at rates of almost 30 and 8 km², respectively; (2) cultivated land and oil palm have shown an increment in sizes at rates of 25.02 and 5.77 km², respectively; and, (3) settlement and Urbanization has intensified also by almost 5 km². Soil erosion risk analysis results also showed that the Semenyih basin exhibited an average annual soil erosion between 143.35 ton ha^?1 year^?1 in 2004 and 151 in 2010, followed by the expected 162.24 ton ha^?1 year^?1. These results indicated that Semenyih is prone to water erosion by 2016. The wide range of erosion classes were estimated at a very low level (0–1 t/ha/year) and mainly located on steep lands and forest areas. This study has shown that using both LTM and USLE in combination with remote sensing and GIS is a suitable method for forecasting LC and accurately measuring the amount of soil losses in the future.     

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.     

区域尺度海河流域水土流失风险评估

借鉴USLE的因子选择及综合方法,在遥感和GIS的支撑下对海河流域的水土流失风险进行评估,并对其空间分布特征进行分析.结果表明:海河流域山区水土流失风险显著高于平原地区,北三河山区水土流失风险最低,太行山区最高,永定河上游介于两者之间;水土流失风险"很低"等级主要分布在小于5°的平坦地区,"中"、"高"水土流失风险面积...     

Change of river channel and bank erosion of the burhi dihing river (assam), assessed using remote sensing data and gis

The Burhi Dining river flows in a meandering course for about 220 km through alluvial plains of Assam including a short rocky and hilly tract in between. Sequential changes in the position of banklines of the river due to consistent bank erosion have been studied from Survey of India topographic maps of 1934 and 1972, and digital satellite data of 2001 and 2004 using GIS. Two broad kinds of changes have been observed, e.g. alteration of direction of flow due to neck cut-off and progressive gradual change of the meander bends that accounts for translational, lateral, rotational, extensional and other types of movement of the meander bends. Study of bankline shift due to the bank erosion has been carried out for the periods 1934–1972, 1972–2001, 2001–2004 and 1934–2004 at 13 segments spaced at 5′ longitude interval (average 15 km) as the river course trends nearly east to west. The amounts of the bank area lost due to erosion and gained due to sediment deposition are estimated separately. The total area eroded in both banks during 1934–1972 was more (26.796 km²) as compared to sediment deposition (19.273 km²), whereas total sediment deposition was more (34.61 km²) during 1972-2001 as compared to erosion (23.152 km²). Erosion was again more in 2001–2004 (7.568 km²) as compared to sediment deposition (2.493 km²). During the entire period (1934–2004) of study the overall erosion on the both banks was 31.169 km² and overall sediment deposition was 30.101 km². The highest annual rates of bank erosion as well as bank building of the river are 21055.47 m²/km in 2001–2004 and 9665.81 m²/km in 1972-2001, respectively. Similarly the highest average annual rates of erosion as well as sediment deposition in both banks are observed during 2001–2004 and 1972–2001, respectively. The hard rocks of the hilly tract situated in between result in development of entrenched meandering and this tract has suffered minimum bank erosion.     

Land degradation mapping in the upper catchment of river Tons

A study on land degradation in the upper catchment of river Tons, a tributary of Yamuna river, in Uttarkashi district of the Uttarakhand state, was carried out using on-screen visual interpretation of IRS LISS-III + PAN merged data. The study area, which is largely mountainous, includes Govind Wildlife Sanctuary and National Park. Vegetation cover, slope and erosion status were used as criteria for the delineation of four major land degradation categories viz., undegraded, moderately degraded, degraded and severely degraded. More than 50 per cent of the study area is reported to be covered with snow and grassland. The moderate to severely degraded area worked out to be 42.4 per cent of the total area. The 32.8 per cent of area was found to be moderately degraded, followed by degraded (6.63%) and severely degraded (2.88%) areas. The depletion of vegetation cover on mountainous terrain and subsequent cultivation without proper protection measures is the reason for severe soil erosion and land degradation. In view of the existing land degradation situation, the catchment requires immediate treatment on priority for the sustenance of agriculture and wild life. It is expected that these measures will reduce the silt load in the river Tons and eventually, in river Yamuna.     

Integrating terrain and vegetation indices for identifying potential soil erosion risk area

The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.     

一种黄土区土壤侵蚀强度遥感调查新方法

通过对TM图像的线性纹理提取和密度统计,首先获得了黄土丘陵区沟谷密度图,然后由沟谷密度反演区域土壤侵蚀强度。这种方法避开了影响土壤侵蚀量的诸多复杂因子。可直接从水土流失的外在表现---沟谷密度来反推土壤侵蚀强度。研究结果证明,这种方法对快速调查大范围黄土丘陵区的土壤侵蚀强度是十分有效的。