共查询到20条相似文献，搜索用时 31 毫秒
1.
2.
Soil erosion and sediment yield modeling using RS and GIS techniques: a case study, Iran 总被引：1，自引：1，他引：0
Water erosion is a serious and continuous environmental problem in many parts of the world. The need to quantify the amount of erosion, sediment delivery, and sediment yield in a spatially distributed form has become essential at the watershed scale and in the implementation of conservation efforts. In this study, an effort to predict potential annual soil loss and sediment yield is conducted by using the Revised Universal Soil Loss Equation (RUSLE) model with adaptation in a geographic information system (GIS). The rainfall erosivity, soil erosivity, slope length, steepness, plant cover, and management practice and conservation support practice factors are among the basic factors that are obtained from monthly and annual rainfall data, soil map of the region, 50-m digital elevation model, remote sensing (RS) techniques (with use of Normalized Difference Vegetation Index), and GIS, respectively. The Ilam dam watershed which is located southeast part of Ilam province in western Iran is considered as study area. The study indicates that the slope length and steepness of the RUSLE model are the most effective factors controlling soil erosion in the region. The mean annual soil loss and sediment yield are also predicted. Moreover, the results indicated that 45.25%, 12.18%, 12.44%, 10.79%, and 19.34% of the study area are under minimal, low, moderate, high, and extreme actual erosion risks, respectively. Since 30.13% of the region is under high and extreme erosion risk, adoption of suitable conservation measures seems to be inevitable. So, the RUSLE model integrated with RS and GIS techniques has a great potential for producing accurate and inexpensive erosion and sediment yield risk maps in Iran. 相似文献
3.
WEPP模型(坡面版)在贵州石漠化地区土壤侵蚀模拟的适用性评价 总被引：6，自引：2，他引：4
文章以贵州花江喀斯特石漠化地区为研究区域,利用WEPP模型(坡面版)分别模拟2006年、2010年土壤侵蚀模数,并将实测数据与WEPP模型模拟值作比较,探讨WEPP软件在喀斯特石漠化地区的适用性。研究表明:WEPP模型对于模拟喀斯特石漠化地区土壤侵蚀有较大误差,对土壤侵蚀模数模拟的有效性系数均为负值,不适用于直接计算该区域土壤侵蚀模数。WEPP模型对微度侵蚀模拟精度不够,但能大体反映不同径流小区之间土壤侵蚀强弱的关系和生态修复过程土壤侵蚀的变化趋势。若要应用WEPP模型对喀斯特地区土壤侵蚀模数模拟计算,必须考虑水土的地下漏失、地表裸岩率、地形高度破碎等环境条件。裸岩率、土壤漏失、地形条件等都是WEPP模型修正所必须注意的内容。 相似文献
4.
西南喀斯特区土层浅薄、成土速率低等特点决定了其允许土壤流失量小,土壤一旦流失,极难恢复,土壤侵蚀及其造成的石漠化现象已成为制约该区可持续发展最严重的生态环境问题。文章首先明晰西南喀斯特区土壤侵蚀特征,从坡面、小流域和区域三个尺度上系统概括西南喀斯特区土壤侵蚀的相关研究进展。针对当前喀斯特区土壤侵蚀研究野外径流小区、小流域及区域空间尺度数据缺少和相关研究模型限制性强等不足,建议从不同尺度深入研究喀斯特区土壤侵蚀发生发展规律及时空演化格局,并结合高新遥感、地球物理探测技术及模型,同步监测坡面—小流域—区域土壤流失,对土壤侵蚀进行定量评估,结合不同空间尺度土壤侵蚀特征构建系统性水土保持生态恢复治理模式和监测系统评价体系。 相似文献
5.
Review and Prospect of the Study on Soil Wind Erosion Process 总被引：2，自引：1，他引：1
Soil wind erosion processes include mechanical process and dynamic changes of the factors affecting soil wind erosion, as well as the corresponding changes of wind erosion rate. The former is rich in experimental and theoretical researches that have clearly defined the process of particle starting, transporting and settling. The latter focuses on the dynamic changes of various wind erosion factors and the response of soil wind erosion rate to the change of the factors, of which systematic research of which is very limited. The difficulties in research of soil wind erosion process include: ①Dynamic parameterization of wind erosion factors; ②Observation and quantitative expression of the dynamic changes of wind erosion factors; ③Scaling problem of wind erosion process; ④Prediction ability of wind erosion models. At present, it is urgent to carry out the following work on soil wind erosion. The first is to establish standard wind erosion observation field in typical regions to obtain continuous and complete data of wind erosion in the field; the second is to study the saturation path of wind sand flow to solve scale problem; and the third is to construct a wind erosion model with solid theoretical foundation and fully consider both mechanical process of soil wind erosion and dynamic changes of the factors. 相似文献
6.
土壤侵蚀量预报模型研究进展 总被引：38，自引：0，他引：38
土壤侵蚀模型是定量评价水土资源发展动态、指导综合治理规划、评价治理方案和措施的技术工具。根据建模的手段和方法，土壤侵蚀量预报模型有经验模型和物理成因模型两大类。根据建模对象的不同，土壤侵蚀模型又有坡面土壤侵蚀模型和流域土壤侵蚀模型之分。主要从这4个方面入手，介绍了国内外土壤侵蚀量预报模型研究的主要成就，指出了现有模型的不足。在总结前人工作的基础上，提出了我国土壤侵蚀模型今后的发展方向。 相似文献
7.
This research selected water soil erosion indicators (land cover, vegetation cover, slope) to assess the risk of soil erosion,
ARCMAP GIS ver.9.0 environments and ERDAS ver.9.0 were used to manage and process satellite images and thematic tabular data.
Landsat TM images in 2003 were used to produce land/cover maps of the study area based on visual interpreting method and derived
vegetation cover maps, and the relief map at the scale of 1:50,000 to calculate the slope gradient maps. The area of water
soil erosion was classified into six grades by an integration of slope gradients, land cover types, and vegetation cover fraction.
All the data were integrated into a cross-tabular format to carry out the grid-based analysis of soil erosion risk. Results
showed that the upper basin of Miyun Reservoir, in general, is exposed to a moderate risk of soil erosion, there is 715,848 ha
of land suffered from water soil erosion in 2003, occupied 46.62% of total area, and most of the soil erosion area is on the
slight and moderate risk, occupied 45.60 and 47.58% of soil erosion area, respectively. 相似文献
8.
G. Matheis 《Journal of Geochemical Exploration》1981,15(1-3)
Geochemical soil surveys in areas underlain by Precambrian volcano-metasedimentary sequences and around rare-metal-bearing pegmatites of southwestern Nigeria demonstrate that residual geochemical soil patterns reflect a wide range of potential source rocks adequately. The secondary geochemical dispersion processes in these typically tropical weathering environments adjust the trace-element distribution during lateritic soil development to narrow fluctuation ranges in comparison to the differing Clarke values of various source rock units.The sample density in these soil surveys, averaging at one sample per square kilometer, favours geochemical inventories even at regional scale and shows great potentials to predict bedrock composition of tropical terrain where rock outcrops are rather scarce. 相似文献
9.
Alireza Arabameri Khalil Rezaei Hamid Reza Pourghasemi Saro Lee Mojtaba Yamani 《Environmental Earth Sciences》2018,77(17):628
Toroud Watershed in Semnan Province, Iran is a prone area to gully erosion that causes to soil loss and land degradation. To consider the gully erosion, a comprehensive map of gully erosion susceptibility is required as useful tool for decreasing losses of soil. The purpose of this research is to generate a reliable gully erosion susceptibility map (GESM) using GIS-based models including frequency ratio (FR), weights-of-evidence (WofE), index of entropy (IOE), and their comparison to an expert knowledge-based technique, namely, Analytic Hierarchy Process (AHP). At first, 80 gully locations were identified by extensive field surveys and Google Earth images. Then, 56 (70%) gully locations were randomly selected for modeling process, and the remaining 26 (30%) gully locations were used for validation of four models. For considering geo-environmental factors, VIF and tolerance indices are used and among 18 factors, 13 factors including elevation, slope degree, slope aspect, plan curvature, distance from river, drainage density, distance from road, lithology, land use/land cover, topography wetness index (TWI), stream power index (SPI), normalized difference vegetation index (NDVI), and slope–length (LS) were selected for modeling aims. After preparing GESMs through the mentioned models, final maps divided into five classes including very low, low, moderate, high, and very high susceptibility. The receiver operating characteristic (ROC) curve and the seed cell area index (SCAI) as two validation techniques applied for assessment of the built models. The results showed that the AUC (area under the curve) in training data are 0.973 (97.3%), 0.912 (91.2%), 0.939 (93.9%), and 0.926 (92.6%) for AHP, FR, IOE, and WofE models, respectively. In contrast, the prediction rates (validating data) were 0.954 (95.4%), 0.917 (91.7), 0.925 (92.5%), and 0.921 (92.1%) for above models, respectively. Results of AUC indicated that four model have excellent accuracy in prediction of prone areas to gully erosion. In addition, the SCAI values showed that the produced maps are generally reasonable, because the high and very high susceptibility classes had very low SCAI values. The results of this research can be used in soil conservation plans in the study area. 相似文献
10.
Arid and semi-arid regions are susceptible to high levels of erosion.A rapid and cost effective methodological erosion assessment for these regions is required to describe and monitor the processes that control erosion.This study uses remote sensing to describe the contribution of several factors that control erosion.Topography,land use,vegetation density,soil properties and climatic proxies are used to determine erosion risk and to provide basic maps of water and soil conservation practices. A hierarchi... 相似文献
11.
Temporal soil erosion risk evaluation: a CORINE methodology application at Elmalı dam watershed,Istanbul 总被引：1，自引：0，他引：1
Geographical information systems (GIS)-based soil erosion risk assessment models continue to play an important role in soil
conservation planning. In the present study, soil erosion risk of Istanbul–Elmalı dam watershed was determined within GIS-based
COoRdination of INformation on the Environment (CORINE) soil erosion risk assessment method. Initially soil texture, soil
depth, and surface stoniness maps were created and were intersected in GIS environment in order to generating erodibility
map. Then, Fournier precipitation and Bagnouls–Gaussen drought indices determined based on meteorological data and erosivity
were calculated. The composed erodibility map was co-evaluated within erosivity value and slope map of the site for composing
potential erosion risk map. At the final step, the previous yearly land use maps which belong to years 1984, 1992, and 2003
intersected with potential erosion risk maps and temporal actual erosion risk alteration were assessed. In conclusion, according
to our results in Elmalı watershed dam in 1984 there have been low, medium, and high erosion risks at rates 29.67, 52.49,
and 17.84%, respectively, whereas in 2003 the erosion risk values have changed from low to high as 26.43, 46.57, and 27.00%,
respectively. Inter-year comparison alteration to the advantage of the high erosion risk could have resulted from over degradation
and high exposure to anthropogenic activities. 相似文献
12.
Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework,Chania, Northwestern Crete,Greece 总被引：7，自引：0，他引：7
Soil erosion is a growing problem in southern Greece and particularly in the island of Crete, the biggest Greek island with
great agricultural activity. Soil erosion not only decreases agricultural productivity, but also reduces the water availability.
In the current study, an effort to predict potential annual soil loss has been conducted. For the prediction, the Revised
Universal Soil Loss Equation (RUSLE) has been adopted in a Geographical Information System framework. The RUSLE factors were
calculated (in the form of raster layers) for the nine major watersheds which cover the northern part of the Chania Prefecture.
The R-factor was calculated from monthly and annual precipitation data. The K-factor was estimated using soil maps available from the Soil Geographical Data Base of Europe at a scale of 1:1,000,000.
The LS-factor was calculated from a 30-m digital elevation model. The C-factor was calculated using Remote Sensing techniques. The P-factor in absence of data was set to 1. The results show that an extended part of the area is undergoing severe erosion.
The mean annual soil loss is predicted up to ∼200 (t/ha year−1) for some watersheds showing extended erosion and demanding the attention of local administrators. 相似文献
13.
Statistical models are one of the most preferred methods among many landslide susceptibility assessment methods. As landslide
occurrences and influencing factors have spatial variations, global models like neural network or logistic regression (LR)
ignore spatial dependence or autocorrelation characteristics of data between the observations in susceptibility assessment.
However, to assess the probability of landslide within a specified period of time and within a given area, it is important
to understand the spatial correlation between landslide occurrences and influencing factors. By including these relations,
the predictive ability of the developed model increases. In this respect, spatial regression (SR) and geographically weighted
regression (GWR) techniques, which consider spatial variability in the parameters, are proposed in this study for landslide
hazard assessment to provide better realistic representations of landslide susceptibility. The proposed model was implemented
to a case study area from More and Romsdal region of Norway. Topographic (morphometric) parameters (slope angle, slope aspect,
curvature, plan, and profile curvatures), geological parameters (geological formations, tectonic uplift, and lineaments),
land cover parameter (vegetation coverage), and triggering factor (precipitation) were considered as landslide influencing
factors. These influencing factors together with past rock avalanche inventory in the study region were considered to obtain
landslide susceptibility maps by using SR and LR models. The comparisons of susceptibility maps obtained from SR and LR show
that SR models have higher predictive performance. In addition, the performances of SR and LR models at the local scale were
investigated by finding the differences between GWR and SR and GWR and LR maps. These maps which can be named as comparison
maps help to understand how the models estimate the coefficients at local scale. In this way, the regions where SR and LR
models over or under estimate the landslide hazard potential were identified. 相似文献
14.
基于GIS重庆岩溶地区生态环境脆弱度评价 总被引：13，自引：3，他引：10
重庆岩溶区属典型的生态环境脆弱区,宜耕地资源不足,土地退化严重,承受自然灾害能力低,使岩溶地区的社会经济发展和生态环境的协调性差,可持续发展能力弱。本文以重庆市岩溶地区为例,选择碳酸盐岩出露面积、山地面积、旱坡耕地面积、石漠化程度(包括轻度、中度和高度)、森林覆盖率、水土流失面积、土壤侵蚀模数、滑坡体积密度、垦殖指数、人均耕地面积、农业人口密度等13项生态环境脆弱度影响因子作为评价指标,利用层次分析法赋予指标权重,然后构建模糊数学模型对岩溶地区生态环境脆弱度进行评价研究,基于GIS技术对评价结果进行等级划分。结果表明: 重庆25个岩溶区县中潜在脆弱区县3个,轻度脆弱区县10个,中度脆弱区县6个,重度脆弱区县6个。 相似文献
15.
Soil erosion is a serious environmental problem in Indravati catchment. It carries the highest amount of sediments compared
with other catchments in India. This catchment spreading an area of 41,285 km2 is drained by river Indravati, which is one of the northern tributaries of the river Godavari in its lower reach. In the
present study, USLE is used to estimate potential soil erosion from river Indravati catchment. Both magnitude and spatial
distribution of potential soil erosion in the catchment is determined. The derived soil loss map from USLE model is classified
into six categories ranging from slight to very severe risk depending on the calculated soil erosion amount. The soil erosion
map is linked to elevation and slope maps to identify the area for conservation practice in order to reduce the soil loss.
From the model output predictions, it is found that average erosion rate predicted is 18.00 tons/ha/year and sediment yield
at the out let of the catchment is 22.30 Million tons per annum. The predicted sediment yield verified with the observed data. 相似文献
16.
Nihat Dipova 《Environmental Earth Sciences》2009,59(3):547-560
Cliff erosion and the consequent instabilities present a significant risk to Antalya city (SW-Turkey). Erosional processes
include the chemical action of mixing zone water, the mechanical action of waves, salt erosion and biological degradation.
The rock properties (lithology, stratification, strength, etc.) are the controlling factors to this erosion. The coastal cliffs
of Antalya are composed of tufa type carbonate rocks which occur in a wide range, from collapsible soil to hard rock. The
instability problems of the cliffs of Antalya tufa commonly involve: rock fall, cave collapse, raveling, washout of weakly
lithified tufa, shear failure and secondary toppling. Secondary toppling type instabilities, Culmann type failures and complex
failures, a combination of these two, are widespread on the cliffs. The occurrence of large failures are usually associated
with heavy rainfall as heavy rainfall causes the saturation of pores, increases pore water pressures and reduces the strength
of the rock. Comparison between aerial photographs and topographic maps of different dates, do not provide evidence of considerable
retreat. According to the historical data there has been little or no cliff retreat for 2,000 years. Therefore the erosion
rate of the Antalya tufa cliffs is said to be so very slow that retreat is valid only in a geological timescale. However in
an engineering timescale these cliffs are subjected to instabilities and to local failures causing local retreats. 相似文献
17.
Li Yunkai Tian Yingjie Ouyang Zhiyun Wang Lingyan Xu Tingwu Yang Peiling Zhao Huanxun 《Environmental Earth Sciences》2010,60(7):1559-1568
Sand production by soil erosion in small watershed is a complex physical process. There are few physical models suitable to
describe the characteristics of the intense erosion in domestic loess plateau. Introducing support vector machine (SVM) oriented
to small sample data and possessing good extension property can be an effective approach to predict soil erosion because SVM
has been applied in hydrological prediction to some extent. But there are no effective methods to select the rational parameters
for SVM, which seriously limited the practical application of SVM. This paper explored the application of intelligence-based
particle swarm optimization (PSO) algorithm in automatic selection of parameters for SVM, and proposed a prediction model
by linking PSO and SVM for small sample data analysis. This method utilized the high efficiency optimization property and
swarm paralleling property of PSO algorithm and the relatively strong learning and extending capacity of SVM. For an example
of Huangfuchuan small watershed, its intensive fragmentation and intense erosion earn itself the name of “worst erosion in
the world”. Using four characteristics selection algorithms of correlation feature selection, the primary affecting factors
for soil erosion in this small watershed were determined to be the channel density, ravine area, sand rock proportion, and
the total vegetation coverage. Based on the proposed PSO–SVM algorithm, the soil erosion modulus in the small watershed was
predicted. The accuracy of the simulation and prediction was good, and the average error was 3.85%. The SVM predicting model
was based on the monitoring data of sand production. The construction of the SVM erosion modulus prediction model for the
small watershed comprehensively reflected the complex mechanism of soil erosion and sand production. It had certain advantage
and relatively high practical value in small sample prediction in the discipline of soil erosion. 相似文献
18.
Assessment of soil erosion risk using SWAT model 总被引：3，自引：2，他引：1
Manel Mosbahi Sihem Benabdallah Mohamed Rached Boussema 《Arabian Journal of Geosciences》2013,6(10):4011-4019
Soil erosion is one of the most serious land degradation problems and the primary environmental issue in Mediterranean regions. Estimation of soil erosion loss in these regions is often difficult due to the complex interplay of many factors such as climate, land uses, topography, and human activities. The purpose of this study is to apply the Soil and Water Assessment Tool (SWAT) model to predict surface runoff generation patterns and soil erosion hazard and to prioritize most degraded sub-catchment in order to adopt the appropriate management intervention. The study area is the Sarrath river catchment (1,491 km2), north of Tunisia. Based on the estimated soil loss rates, the catchment was divided into four priority categories for conservation intervention. Results showed that a larger part of the watershed (90 %) fell under low and moderate soil erosion risk and only 10 % of the watershed was vulnerable to soil erosion with an estimated sediment loss exceeding 10 t?ha?1?year?1. Results indicated that spatial differences in erosion rates within the Sarrath catchment are mainly caused by differences in land cover type and gradient slope. Application of the SWAT model demonstrated that the model provides a useful tool to predict surface runoff and soil erosion hazard and can successfully be used for prioritization of vulnerable areas over semi-arid catchments. 相似文献
19.
Progresses and Prospects of the Research on Soil Erosion in Karst Area of Southwest China* 总被引：1，自引：0，他引：1
The karst area of Southwest China is suffering from serious ecological and environmental problems due to soil erosion while the research on soil erosion is not sufficient. Primary achievement was systematically reviewed in this paper in three aspects: erosion characteristics, current researches about erosion on different spatial scales, and key scientific problems. Based on the review, the authors figured out the shortcomings of the existing studies and pointed out the directions on erosion study in southwest China karst region. The results showed that: ① Due to the existence of a dual structure in karst environment including ground and underground erosion, the process of runoff and sediment production on slope scale and confluence and sediment transportation processes on catchment scale were more complex under the unique geological and hydrological backgrounds; ② At present, most researches about erosion mechanism in karst area focus on slope scale and some achievements on quantitative evaluation of erosion factors have been made. Continuous data with high quality about relationship between water and sediment on catchment scale is limited. When data is scarce, river sediment data can be used as an effective way to study soil erosion intensity and spatial-temporal variation in karst area; ③ It is more reasonable to use 50 t/(km2·a) as the grading standard of soil loss tolerance than the previous grading standard of soil erosion intensity. Given the complex relationship between rocky desertification and soil erosion, more quantitative studies about the effects of rocky desertification on soil erosion are still necessary. There are different viewpoints on soil leakage definitions, leakage mechanism and leakage ratios, and new breakthroughs could be achieved by combining different methods and matching multi-scales. In conclusion, in order to further reveal soil erosion laws and establish and revise available regional soil erosion forecasting models for Southwest China karst areas, synchronous test and monitoring on slope, watershed, and channel spatial scales are urgently needed. The results can provide theoretical and technical support for promoting soil and water conservation work for the karst area of Southwest China. 相似文献
20.
MushtakTalibJabbar 《中国地质大学学报(英文版)》2003,14(4):356-362
Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, developed by FAO, UNEP and UNESCO to assess and evaluate soil degradation at 1 : 250 000 mapping scale. The study area is located in the arid and semi-arid zone of the northern part of Shaanxi Province in China, a region with considerable agricultural potential; Landsat TM images were utilized to provide recent data on land cover and use of the area. ARC/INFO and Arc-View softwares were used to manage and manipulate thematic data, to process satellite images, and tabular data source. ER mapper software is utilized to derive the normalized difference vegetation index (ND VI) values while field data to estimate soil erodibility (SE) factor. A system is established for rating soil parameters, slope, climate factor and human factor activity. The rating values serve as inputs into a modified universal soil loss equation (USLE) to calculate the present state and risk for soil degradation processes, namely soil wind erosion. The produced maps and tabular data show the risk and the present status of different soil degradation processes. The study area, in general, is exposed to high risk of wind erosion and high hazards of water erosion. Several desertification maps were produced, which reflect the desertification types persisting in the study area. Wind erosion, water erosion, vegetation degradation,physical degradation and salinization are the basic desertification maps, and others are combinations of these basic maps. In terms of statistic analysis, 33.75 % of the total land area (120. 330 0 ha) is considered as sand or sand dune, and not included in our analysis of desertification. About 29. 41% of the total land area has slight or moderate desertification and 37. 465 % is facing severe desertification. 相似文献