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1.
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。 相似文献
2.
基于遥感和GIS的宣化县水土流失定量空间特征分析 总被引：4，自引：0，他引：4
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%。 相似文献
3.
黄土高原典型区土壤保持服务效应研究 总被引：2，自引：0，他引：2
黄土高原生态屏障区是我国"两屏三带"的重要组成部分,不仅对当地居民具有重要的屏障作用,同时也对黄河中下游具有重要的影响。本研究以土壤侵蚀量为评估指标,应用修正的通用土壤流失方程,利用2000—2010年间土地覆被、气象站点和泥沙站点等多源数据,定量评估了黄土高原生态屏障区退耕还林还草生态工程的土壤保持效应。结果表明,2000—2010年间,尽管黄土高原降雨量明显增多,降雨侵蚀力在增强,但研究区以退耕还草为主,退耕还草面积达到3 287. 01 km2,研究区植被覆盖在以1. 29%/a速率递增;土壤侵蚀状况发生明显改善,土壤侵蚀模数由2000年的6 579. 55 t·km-2·a-1降低到了2010年的1 986. 66 t·km-2·a-1,土壤侵蚀等级由剧烈侵蚀向微度侵蚀转变,侵蚀等级在逐渐降低,低覆盖度-烈度土壤侵蚀面积在大幅度降低,而高覆盖度-微度土壤侵蚀类型面积在大幅度提升;并且流域土壤侵蚀强度与相关站点含沙量和输沙量呈正相关,黄土高原生态屏障效应在不断加强。该研究对加强生态安全格局建设,促进我国生态文明建设具有一定的借鉴意义。 相似文献
4.
《地理空间信息》2016,(4)
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。 相似文献
5.
基于知识库和空间信息耦合模型的北川县震后土壤侵蚀分析 总被引：1，自引：0，他引：1
基于土壤水力侵蚀分级标准,考虑地震造成的特殊土壤侵蚀类型,构建了地震重灾区土壤侵蚀强度分级知识库;综合利用RS和GIS技术,结合专家知识判断,快速提取了四川省北川县土地利用、地面坡度、植被盖度、特殊侵蚀类型等土壤侵蚀因子空间信息;基于EcoHAT系统中的知识库和空间信息耦合型土壤侵蚀模型,快速完成了北川县震后土壤侵蚀强度的判定与分析.结果表明,地震使北川县土壤侵蚀加剧,相比2000年全国土壤侵蚀遥感调查成果,震后土壤侵蚀面积增加了275.13km2,增长量为23.83%;特殊侵蚀类型面积占北川县面积的2.48%;林地土壤侵蚀面积最大,占总侵蚀面积的一半以上;耕地土壤侵蚀比例为98.95%;坡度是北川县土壤侵蚀的主要贡献因子,植被则是主要控制因子,坡耕地治理是今后北川县土壤侵蚀控制的重点. 相似文献
6.
孤山川流域近30年土壤侵蚀时空动态特征分析 总被引：2，自引：0，他引：2
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。 相似文献
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为了研究黄土高原南部植被覆盖较高地区在退耕还林后的土壤侵蚀变化特征,利用RUSLE模型,结合GIS、RS技术,定量估算了2000～2013年石川河流域的土壤侵蚀量,分析了不同植被覆盖条件和不同土地利用类型的土壤侵蚀时空变化特征。结果表明:①土壤侵蚀等级与降雨侵蚀力、地貌和土地利用类型关系密切;②土地利用类型变化显著,耕地所占比重由51.44%减少到48.37%,草地所占比重由24.51%减少到12.48%,林地所占比重由19.45%增加到33.20%;③土壤侵蚀模数由退耕还林初期(2000年)的1 473.7 t/(km~2·a)减少到2013年的806.12 t/(km~2·a),总侵蚀量减少到217.91×10~4 t。土地利用类型的水土保持效益从大到小分别为林地、草地和耕地,说明还林还草工程后石川河流域土壤侵蚀呈总量减少、侵蚀强度降低的趋势,还林还草工程取得了水土保持效益。石川河流域的土壤侵蚀强度可以代表相似水热条件地区的土壤侵蚀情况,相同纬度地区的土壤侵蚀还有进一步下降的空间。 相似文献
11.
Integrated approach of using remote sensing and GIS to study watershed prioritization and productivity 总被引：1，自引：0，他引：1
Soil data obtained from soil resource inventory, land and climate were derived from the remote sensing satellite data (Landsat
TM, bands 1 to 7) and were integrated in GIS environment to obtain the soil erosion loss using USLE model for the watershed
area. The priorities of different sub-watershed areas for soil conservation measures were identified. Land productivity index
was also used as a measure for land evaluation. Different soil and land attribute maps were generated in GIS, and R,K,LS,C
and P factor maps were derived. By integrating these soil erosion map was generated. The mapping units, found not suitable
for agriculture production, were delineated and mapped as non-arable land. The area suitable for agricultural production was
carved out for imparting the productivity analysis; the land suitable for raising agricultural crops was delineated into different
mapping units as productivity ratings good, fair, moderate and poor. The analysis performed using remote sensing and GIS helped
to generate the attribute maps with more accuracy and the ability of integrating these in GIS environment provided the ease
to get the required kind of analysis. Conventional methods of land evaluation procedures in terms of either soil erosion or
productivity are found not comparable with the out put generated by using remote sensing and GIS as the limitations in generating
the attribute maps and their integration. The results obtained in this case study show the use of different kinds of data
derived from different sources in land evaluation appraisals. 相似文献
12.
This study is aimed at evolving a watershed prioritization of reservoir catchment based on vegetation, morphological and topographical parameters, and average annual soil loss using geographic information system (GIS) and remote sensing techniques. A large multipurpose river valley project, Upper Indravati reservoir, situated in the state of Orissa, India, has been chosen for the present work. Watershed prioritization is useful to soil conservationist and decision makers. This study integrates the watershed erosion response model (WERM) and universal soil loss equation (USLE) with a geographic information system (GIS) to estimate the erosion risk assessment parameters of the catchment. The total catchment is divided into 15 sub-watersheds. Various erosion risk parameters are determined for all the sub-watersheds separately. Average annual soil loss is also estimated for the sub-watersheds using USLE. The integrated effect of all these parameters is evaluated to recommend the priority rating of the watersheds for soil conservation planning. 相似文献
13.
Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models 总被引：1，自引：0，他引：1
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. 相似文献
14.
Rainfall-runoff and soil erosion modeling using Remote Sensing and GIS technique — a case study of tons watershed 总被引：1，自引：0，他引：1
A S Jasrotia S D Dhiman S P Aggarwal 《Journal of the Indian Society of Remote Sensing》2002,30(3):167-180
In the present study, the rainfall-runoff relationship is determined using USDA Soil Conservation Service (SCS) method. The coefficient of determination (R2) is 0.99, which indicates a high correlation between rainfall and runoff. The runoff potential map was prepared by assigning individual class weight and scores input map. Annual spatial soil loss estimation was computed using Morgan, Morgan and Finney mathematical model in conjunction with remote sensing and GIS techniques. Higher soil erosion was found to occur in the northern part of the Tons watershed. The soil texture in the affected area is coarse loamy to loamy skeletal and soil detachment is higher. Moreover the land use has open forests, which does not reduce the impact of rainfall. The average soil loss for all the four sub-watersheds was calculated, and it was found that the maximum average soil loss of 24.1 t/ha occurred in the sub-watershed 1. 相似文献
15.
Mushtak Jabbar 《地球空间信息科学学报》2013,16(1):34-37
This paper describes the use of the Arc/Info and ArcView GIS tools to estimate soil erosion with Universal Soil Loss Equation (USLE). Calculations are be done by using capabilities available. This study start with a digital elevation model (DEM) of Shaanxi, which was created by digitizing contour and spot heights from the topographic map on 1∶250 000 scale and grid themes for the USLEK andC factors. It is note worthy that USLEK can be obtained by adding the K factor as an attribute to a soil theme's table. TheC can be obtained from tables or using the information about land use and management given by USLE program. A land use theme can be used to add theC factors as an attribute field. The purpose of this study is to establish spatial information of soil erosion using USLE and GIS and discuss the analysis of the soil erosion and slope failures in GIS and formulate the possible framework. 相似文献
16.
Quantitative Determination of Soil Erosion and Prioritization of Micro-Watersheds Using Remote Sensing and GIS 总被引：5，自引：0，他引：5
Vipul Shinde Arabinda Sharma Kamlesh N. Tiwari Manjushree Singh 《Journal of the Indian Society of Remote Sensing》2011,39(2):181-192
Soil erosion which occurs at spatially varying rate is a widespread threat to sustainable resource management at watershed scale. Thus estimation of soil loss and identification of critical area for implementation of best management practice is central to success of soil conservation programme. The present study focuses application of most widely used Universal Soil Loss Equation (USLE) to determine soil erosion and prioritization of micro-watersheds of Upper Damodar Valley Catchment (UDVC) of India. Annual average soil loss for the entire basin is 23.17 t/ha/yr; for micro-watersheds. High soil loss is observed in 345 micro-watersheds, medium in 159 micro-watersheds and low soil loss is observed in 201 micro-watersheds. It is found that, out of 705 micro-watersheds of UDVC, 453 micro-watersheds are in agreement with AISLUS suggested priority which is based on observed sediment yield, 116 micro-watersheds under predict and 136 micro-watersheds over predict the priority. Geographic Information System (GIS) is applied to prepare various layers of USLE parameters which interactively estimate soil erosion at micro-watershed level. The main advantage of the GIS methodology is in providing quick information on the estimated value of soil loss for any part of the investigated area. 相似文献
17.
Application of GIS to estimate soil erosion using RUSLE 总被引：9，自引：0，他引：9
Mushtak Talib Jabbar 《地球空间信息科学学报》2003,6(1):34-37
This paper describes the use of the Arc/Info and ArcView GIS tools to estimate soil erosion with Universal Soil Loss Equation (USLE).Calculations are be done by using capabilities available.This study start with a digital elevation model(DEM) of Shaanxi,which was created by digitizing contour and spot heights from the topographic map on 1:250000 scale and grid themes for the USLE K and C factors.It is note worthy that USLE K can be obtained by adding the K factor as an attribute to a soil theme‘s table.The C can be obtained from tables or using the information about land use and management given by USLE program.A land use theme can be used to add the C factors as an attribute field.The purpose of this study is to establish spatial information of soil erosion using USLE and GIS and discuss the analysis of the soil erosion and slope failures in GIS and formulate the possible framework. 相似文献
18.
The quantitative assessment of spatial soil erosion is valuable information to control the erosion. The study area in a part of Narmada river in central India is selected. The main objective is to assess and compare the results obtained from three soil erosion models using GIS platform. Variation in the rate of erosion of the three models is compared considering varying slope, soil and land use of the area. Three models selected are Morgan–Morgan–Finney (MMF), Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The best fit or the most reliable model for the study area is selected after validation with the observed sedimentation data. The results give –39.45%, –9.60% and 4.80% difference in the values of sedimentation by MMF, USLE and RUSLE, respectively, from the observed data. Finally, RUSLE model has been found to be most reliable for the study area. 相似文献
19.
Pallavi Behera K. H. V. Durga Rao K. K. Das 《Journal of the Indian Society of Remote Sensing》2005,33(1):165-176
Hardly any part of the world has remained unchanged since the arrival of the speciesHomo sapiens including the mountain ecosystems. Himalayan physiographic unit of India in due course has become populated and is tolerating
all kinds of human interventions. Soil erosion in this region has been identified as a major problem due to both natural and
anthropogenic factors. Remote sensing and Geographical Information system (GIS) techniques hold great promises in the assessment
and conservation of natural resources including the surface soil. The major objective of the present study was to apply a
process based model to quantify soil erosion and to prioritize the sub-watershed on this basis. The sub-watershed located
at Jakhan rao area of Western Dun in lower Himalayan belt was taken as the test site for the study at 1: 50,000 scale. Deforestation,
unscientific agricultural practices, terrace farming, cattle grazing and land degradation in the sub-watershed are some of
the anthropogenic factors causing soil erosion in the area. Here, MMF model was used for estimation of soil erosion by incorporating
layers derived from both remote sensing and ancillary data. IRS 1C LISS III satellite data was used for the preparation of
land use map that was used to derive RD map, BD map and K map. Digital Elevation Model (DEM) provided slope map, an intermediate
layer used in equation 6 to generate G map, and soil map provided MS map, BD map and K map. The above intermediate layers
generated were then integrated in GIS domain to estimate the amount of soil erosion in the sub-watershed area. Results show
high values 4572.333 kg/m2 for G map, which depicted transport capacity of overland flow. Comparatively lower values 13.15, and 7.98 kg/m2were observed for F map, which depicted soil detachment by raindrop impact. The subtracted image of the aforesaid layers produced
the real picture, where in the highest value 3.770 kg/m2 was found in the midland region of the site. The crossed erosion map was then classified into different erosion classes for
sub-watershed area. This study illustrates the applications of remote sensing and GIS techniques for soil erosion modeling. 相似文献
20.
Temporal and spatial relationships between soil erosion and ecological restoration in semi-arid regions: a case study in northern Shaanxi,China 总被引：1，自引：0，他引：1
Xin Wen 《地理信息系统科学与遥感》2020,57(4):572-590
ABSTRACTTo 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. 相似文献