首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献，搜索用时 15 毫秒
1.
Effects of land use changes on soil erosion in a fast developing area   总被引：1，自引：0，他引：1  
Land use changes extensively affect soil erosion, which is a great environmental concern. To evaluate the effect of land use change on soil erosion in fast economic developing areas, we studied land use changes of Guangdong, China, from 2002 to 2009 using remote sensing and estimated soil erosion using the Universal Soil Loss Equation. We calculated the areas and percentage of each land use type under different erosion intensity and analyzed soil erosion changes caused by transitions of land use types. In addition, the impact of land use change on soil erosion in different river catchments was studied. Our results show that forest and wasteland land conversions induce substantial soil erosion, while transition from wasteland to forest retards soil loss. This suggests that vegetation cover changes significantly influence soil erosion. Any conversion to wasteland causes soil erosion, whereas expansion of forests and orchards mitigates it. The most significant increase in soil erosion from 2002 to 2009 was found in the Beijiang catchment corresponding to the transition from forest/orchard to built-up and wasteland. Soil erosion in the Xijiang catchment accelerated in this period due to the enormous reduction in orchard land. In Hanjiang catchment, erosion was alleviated and vegetation coverage greatly expanded owing to considerable transitions from wasteland and cropland to orchards. Field investigations validated our estimations and proved the applicability of this method. Measures including protecting vegetation, strict control of mining as well as reasonable urban planning should be taken to prevent successive soil erosion.  相似文献   

2.
桂江流域土壤侵蚀估算及其时空特征分析   总被引：2，自引：1，他引：1  
桂江流域的水土流失现状研究对珠江三角洲的水生态安全有重要的现实意义。采用修正的通用土壤流失方程（RUSLE）估算了桂江流域的土壤侵蚀模数与年侵蚀总量,分析流域内土壤侵蚀的时空分布特征,探讨了影响该区域土壤侵蚀强度的自然与人文因素。结果表明,桂江流域51.8%的地表都在发生不同程度的土壤侵蚀。从全流域平均土壤侵蚀强度来看,属于中度侵蚀。从土壤侵蚀面积来看,约85%的地表处于微度、轻度与中度侵蚀。4-6月的全流域平均土壤侵蚀强度最大,侵蚀总量也是最大的。流域的土壤侵蚀主要发生在高程在30~600m的低山丘陵-高地地貌区内的林地与耕地中。流域内岩溶区的土壤侵蚀强度随着石漠化程度从无到中度逐渐增加,轻、中度石漠化区的土壤侵蚀强度达到强度侵蚀等级。   相似文献   

3.
The devastating effect of soil erosion is one of the major sources of land degradation that affects human lives in many ways which occur mainly due to deforestation, poor agricultural practices, overgrazing,wildfire and urbanization. Soil erosion often leads to soil truncation, loss of fertility, slope instability, etc.which causes irreversible effects on the poorly renewable soil resource. In view of this, a study was conducted in Kelantan River basin to predict soil loss as influenced by long-term land use/land-cover(LULC) changes in the area. The study was conducted with the aim of predicting and assessing soil erosion as it is influenced by long-term LULC changes. The 13,100 km~2 watershed was delineated into four sub-catchments Galas, Pergau, Lebir and Nenggiri for precise result estimation and ease of execution. GIS-based Universal Soil Loss Equation(USLE) model was used to predict soil loss in this study. The model inputs used for the temporal and spatial calculation of soil erosion include rainfall erosivity factor,topographic factor, land cover and management factor as well as erodibility factor. The results showed that 67.54% of soil loss is located under low erosion potential(reversible soil loss) or 0-1 t ha~(-1) yr~(-1) soil loss in Galas, 59.17% in Pergau, 53.32% in Lebir and 56.76% in Nenggiri all under the 2013 LULC condition.Results from the correlation of soil erosion rates with LULC changes indicated that cleared land in all the four catchments and under all LULC conditions(1984-2013) appears to be the dominant with the highest erosion losses. Similarly, grassland and forest were also observed to regulate erosion rates in the area. This is because the vegetation cover provided by these LULC types protects the soil from direct impact of rain drops which invariably reduce soil loss to the barest minimum. Overall, it was concluded that the results have shown the significance of LULC in the control of erosion. Maps generated from the study may be useful to planners and land use managers to take appropriate decisions for soil conservation.  相似文献   

4.
Estimation of soil erosion using RUSLE in Caijiamiao watershed,China   总被引：4，自引：1，他引：3  
Jinghu Pan  Yan Wen 《Natural Hazards》2014,71(3):2187-2205
Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km2. This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha?1 year?1 in 2002 and 70.58 ton ha?1 year?1 in 2010, while the estimated sediment yield was found to be 327.96 × 104 and 293.85 × 104 ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.  相似文献   

5.
Assessment of soil erosion risk using SWAT model   总被引：3，自引：2，他引：1  
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   

6.
Soil degradation resulted from unreasonable land use and erosion has been a serious problem in the black soil region of northeastern China. This paper seeks to understand the relationships between topsoil properties and topography and land use for land management targeting at improving soil quality in this region. A total of 292 soil samples and 81 volumetric rings were taken from a typical small watershed of the region in June 2005 for examining total carbon (TC), total nitrogen (TN), soil texture (classified into gravel, sand, silt, and clay), and bulk density (ρ b), respectively. Spatial variability of these soil properties was evaluated with classical statistics and geostatistics methods. The results of classical statistics indicated that TC, TN, sand, silt, clay content, and ρ b were moderate variables while gravel had great variability. Soil properties were mainly correlated to slope position, elevation and land types. Geostatistical analyses showed that the spatial autocorrelation for TC, TN, and silt was weak, strong for clay and moderate for and ρ b sand, respectively. The spatial variations of soil properties are affected comprehensively by topographic factors, land use, erosion, and erosion control in this watershed. Past erosion, however, is the most important component to induce change of soil properties. In this small watershed, current soil and water conservation measures play an important role in controlling soil loss. But the restoration of soil properties was unsatisfactory. Comparing with untilled soil of this region, TC, TN, silt content are excessively low; whereas ρ b, sand and clay content are excessively high; gravel appears at most sampling locations. It is necessary for improving soil properties to protect forest and grassland and change cultivation system of farmlands.  相似文献   

7.
This study was aimed at predicting soil erosion risk in the Buyukcekmece Lake watershed located in the western part of Istanbul, Turkey, by using Revised Universal Soil Loss Equation (RUSLE) model in a GIS framework. The factors used in RUSLE were computed by using different data obtained or produced from meteorological station, soil surveys, topographic maps, and satellite images. The RUSLE factors were represented by raster layers in a GIS environment and then multiplied together to estimate the soil erosion rate in the study area using spatial analyst tool of ArcGIS 9.3. In the study, soil loss rate below 1 t/ha/year was defined as low erosion, while those >10 t/ha/year were defined as severe erosion. The values between low and severe erosion were further classified as slight, moderate, and high erosion areas. The study provided a reliable prediction of soil erosion rates and delineation of erosion-prone areas within the watershed. As the study revealed, soil erosion risk is low in more than half of the study area (54%) with soil loss <1 t/ha/year. Around one-fifth of the study area (19%) has slight erosion risk with values between 1 and 3 t/ha/year. Only 11% of the study area was found to be under high erosion risk with soil loss between 5 and 10 t/ha/year. The severe erosion risk is seen only in 5% of the study area with soil loss more than 10 t/ha/year. As the study revealed, nearly half of the Buyukcekmece Lake watershed requires implementation of effective soil conservation measures to reduce soil erosion risk.  相似文献   

8.
The installation of a rural settlement complex in the watershed stream Indaiá has promoted changes in land-use and vegetation cover dynamics; however, the effects of intensive agriculture and cattle farming in rural settlements on soil loss rates are not well known. Predictive models implemented in geographic information systems have proven to be effective tools for estimating erosive processes. The erosion predictive model Revised Universal Soil Loss Equation (RUSLE) is a useful tool for analyzing, establishing and managing soil erosion. RUSLE has been widely used to estimate annual averages of soil loss, by both interrill and rill erosion, worldwide. Therefore, the aim of this work was to estimate the soil loss in the watershed stream Indaiá, using the RUSLE model and geoprocessing techniques. To estimate soil loss, the following factors were spatialized: erosivity (R), erodibility (K), topography (LS), land-use and management (C) and conservation practices (P); the annual soil loss values were calculated using the RUSLE model equation. The estimated value of soil loss in the hydrographic basin ranged from 0 to 4082.16 Mg ha?1 year?1 and had an average value of 47.81 Mg ha?1 year?1. These results have demonstrated that 68.16 % of the study area showed little or no soil loss based on the Food and Agriculture Organization’s (FAO 1980) classification. When comparing the average value of soil loss obtained using the RUSLE model with the Natural Potential for Erosion, a 16-fold reduction in soil was found, which highlighted the fact that vegetation cover (C factor) has a greater influence than other factors (R, K and LS) on soil loss prediction attenuation. These results lead to the conclusion that soil loss occurs by different methods in each settlement in the basin and that erosive processes modeled by geoprocessing have the potential to contribute to an orderly land management process.  相似文献   

9.
Soil erosion is one of the serious and urgent issues in the Loss Plateau of China. Chinese government has implemented Grain for Green Project to restore the ecological environment since 1999. In order to explore the spatiotemporal evolution of erosion and sediment yield before and after Grain for Green Project in the Loss Plateau, annual soil loss of Yulin from 2000 to 2013 is estimated by Chinese Water Erosion on Hillslope Prediction Model in conjunction with Remote Sensing and Geographic Information Systems. This model has the characteristics of a simple algorithm and can be applied to predict erosion in the Loss Plateau. The result shows that vegetation cover increased significantly after Grain for Green Project, and the annual average value of NDVI increased from 0.20 to 0.33. The spatiotemporal variations of soil erosion are largely related to rainfall erosion distribution, slope, and land use type. The overall soil erosion categories in the south region are higher than those of the northwest. Mid slopes and valleys are the major topographic contributors to soil erosion. With the growth of slope gradient, soil erosion significantly increased. The soil loss has a decreasing tendency after Grain for Green Project. Although the rainfall of 2002 and 2013 is similar, the soil loss decreased from 5192.86 to 3598.94 t/(km2 a), decreasing by 30.33%. It is also expressed that soil loss appears a reducing trend in the same degree of slope and elevation in 2002, 2007, and 2013. Under the simulation of the maximum and the minimum rainfall, soil erosion amount in 2013 decreased by 29.16 and 30.88%. The study proved that GFG has already achieved conservation of water and soil. The results indicate that the vegetation restoration as part of the Grain for Green Project on the Loss Plateau is effective.  相似文献   

10.
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   

11.
The formulation of watershed management strategies to protect water resources threatened by soil erosion and sedimentation requires a thorough understanding of sediment sources and factors that drive soil movement in the watershed. This paper describes a study of medium-term water-driven soil erosion rates in a mountainous watershed of the Shihmen Reservoir in Taiwan. A total of 60 sampling sites were selected along a hillslope. At each sampling site, the inventory 137Cs activity was determined and then calculated with the diffusion and migration model to derive soil erosion rates. The rates are one to two orders of magnitude lower than estimates using the Universal Soil Loss Equation, a soil erosion model often used in Taiwan. Results of multiple regression analysis indicate that the spatial variability of soil erosion rates is associated with the relative position of a sampling site to the nearest ridge and soil bulk densities (r 2 = 0.33, p < 0.01). Finally, the patterns of soil redistribution rates on the hillslope follow the 137Cs hillslope model as soil erosion increases in the downslope direction. No deposition site is found at footslope because soil deposition is swept away by regular flooding along the stream channel. This study is an important first step in using 137Cs as a tracer of soil redistribution in mountainous watersheds of Taiwan.  相似文献   

12.
The present comparative study is multi-temporal in nature. The Revised Universal Soil Loss Equation (RUSLE), remote sensing, and GIS were used to model the soil loss estimation for soil conservation and vegetation rehabilitation in Nun Nadi watershed for the years 2000 and 2009. The estimated mean soil loss for the year 2000 and 2009 is 3,283.11 and 1,419.39 Mg?ha?1 year?1, respectively. The study finds that about 80 % area has low or least risk of erosion and about 7 % is exposed to high or very high risk which indicates the improvement in terms of soil loss if we compare the data of both the time periods. The findings show that the rainfall, LULC change, and elevation are the main responsible factors for the soil loss in Nun Nadi watershed. Conservation measures have been adopted; however, the problem still remains serious and demands urgent attention.  相似文献   

13.
This paper applied the Revised Universal Soil Loss Equation (RUSLE), remote-sensing technique, and geographic information system (GIS) to map the soil erosion risk in Miyun Watershed, North China. The soil erosion parameters were evaluated in different ways: the R factor map was developed from the rainfall data, the K factor map was obtained from the soil map, the C factor map was generated based on a back propagation (BP) neural network method of Landsat ETM+ data with a correlation coefficient (r) of 0.929 to the field collected data, and a digital elevation model (DEM) with a spatial resolution of 30 m was derived from topographical map at the scale of 1:50,000 to develop the LS factor map. P factor map was assumed as 1 for the watershed because only a very small area has conservation practices. By integrating the six factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the upper watershed of Miyun reservoir was obtained by the RUSLE model. The results showed that the annual average soil loss for the upper watershed of Miyun reservoir was 9.86 t ha−1 ya−1 in 2005, and the area of 47.5 km2 (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.88% very low, 21.90% low, 6.19% moderate, 2.90% severe, and 1.84% very severe. Among all counties and cities in the study area, Huairou County is in the extremely severe level of soil erosion risk, about 39.6% of land suffer from soil erosion, while Guyuan County in the very low level of soil erosion risk suffered from 17.79% of soil erosion in 2005. Therefore, the areas which are in the extremely severe level of soil erosion risk need immediate attention from soil conservation point of view.  相似文献   

14.
In recent times, soil erosion interlocked with land use and land cover (LULC) changes has become one of the most important environmental issues in developing countries. Evaluation of this complex interaction between LULC change and soil erosion is indispensable in land use planning and conservation works. This paper analysed the impact of LULC change on soil erosion in the north-western highland Ethiopia over the period 1986–2016. Rib watershed, the area with dynamic LULC change and severe soil erosion problem, was selected as a case study site. Integrated approach that combined geospatial technologies with revised universal soil loss equation model was utilized to evaluate the spatio-temporal dynamics of soil loss over the study period. Pixel-based overlay of soil erosion intensity maps with LULC maps was carried out to understand the change in soil loss due to LULC change. Results showed that the annual soil loss in the study area varied from 0 to 236.5 t ha?1 year?1 (tons per hectare per year) in 1986 and 0–807 t ha?1 year?1 in 2016. The average annual soil loss for the entire watershed was estimated about 40 t ha?1 year?1 in 1986 comparing with 68 t ha?1 year?1 in 2016, a formidable increase. Soil erosion potential that was estimated to exceed the average soil loss tolerance level increased from 34.5% in 1986 to 66.8% in 2016. Expansion of agricultural land at the expense of grassland and shrubland was the most detrimental factor for severe soil erosion in the watershed. The most noticeable change in soil erosion intensity was observed from cropland with mean annual soil loss amount increased to 41.38 t ha?1 year?1 in 2016 from 26.60 in 1986. Moreover, the most successive erosion problems were detected in eastern, south-eastern and northern parts of the watershed. Therefore, the results of this study can help identify the soil erosion hot spots and conservation priority areas at local and regional levels.  相似文献   

15.
Revised Universal Soil Loss Equation(RUSLE) model coupled with transport limited sediment delivery(TLSD) function was used to predict the longtime average annual soil loss, and to identify the critical erosion-/deposition-prone areas in a tropical mountain river basin, viz., Muthirapuzha River Basin(MRB; area=271.75 km~2), in the southern Western Ghats, India. Mean gross soil erosion in MRB is 14.36 t ha~(-1) yr~(-1), whereas mean net soil erosion(i.e., gross erosion-deposition) is only 3.60 t ha~(-1) yr~(-1)(i.e., roughly 25% of the gross erosion). Majority of the basin area(~86%) experiences only slight erosion(5 t ha~(-1) yr~(-1)), and nearly 3% of the area functions as depositional environment for the eroded sediments(e.g., the terraces of stream reaches, the gentle plains as well as the foot slopes of the plateau scarps and the terrain with concordant summits). Although mean gross soil erosion rates in the natural vegetation belts are relatively higher, compared to agriculture, settlement/built-up areas and tea plantation, the sediment transport efficiency in agricultural areas and tea plantation is significantly high,reflecting the role of human activities on accelerated soil erosion. In MRB, on a mean basis, 0.42 t of soil organic carbon(SOC) content is being eroded per hectare annually, and SOC loss from the 4th order subbasins shows considerable differences, mainly due to the spatial variability in the gross soil erosion rates among the sub-basins. The quantitative results, on soil erosion and deposition, modelled using RUSLE and TLSD, are expected to be beneficial while formulating comprehensive land management strategies for reducing the extent of soil degradation in tropical mountain river basins.  相似文献   

16.
Due to the existence of fragile karst geo-ecological environments, such as environments with extremely poor soil cover, low soil-forming velocity, and fragmentized terrain and physiognomy, as well as inappropriate and intensive land use, soil erosion is a serious problem in Guizhou Province, which is located in the centre of the karst areas of southwestern China; evaluation of soil loss and spatial distribution for conservation planning is urgently needed. This study integrated the revised universal soil loss equation (RUSLE) with a GIS to assess soil loss and identify risk erosion areas in the Maotiao River watershed of Guizhou. Current land use/cover and management practices were evaluated to determine their effects on average annual soil loss and future soil conservation practices were discussed. Data used to generate the RUSLE factors included a Landsat Thematic Mapper image (land cover), digitized topographic and soil maps, and precipitation data. The results of the study compare well with the other studies and local data, and provide useful information for decision makers and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a larger watershed scale in Guizhou.  相似文献   

17.
Tunisia presents many favorable conditions for the outbreak of water erosion because of its climatic and physical characteristics. This phenomenon represents a serious threat to the natural resources of soil and water. The aim of the present study is to identify the most vulnerable areas in order to help managers implement an effective management program. Thematic layers and parameters were integrated in the InVEST (Integrated Valuation of Environmental Services and Trade-offs) SDR (Sediment Delivery Ratio). Soil loss and sediment yield were calculated by the model and compared to observed data. The Rmel river basin was divided into 17 sub-watersheds using the dam axis as the main outlet. Results reveal that approximately 60% of the basin presents soil loss more than 5 ton/ha/year. Soil erosion map demonstrates that soil erosion risk increases with increased slope gradient, especially in agricultural lands. Sub-catchment prioritizations have been fixed based on soil erosion risk. Results show that sub-catchment 16 presents the highest soil loss with a value of 65 ton/ha/year. Sub-catchment presenting high soil erosion risk needs to give a high priority in conservation planning.  相似文献   

18.
http://www.sciencedirect.com/science/article/pii/S1674987111001034   总被引：10，自引：0，他引：10  
A comprehensive methodology that integrates Revised Universal Soil Loss Equation（RUSLE） model and Geographic Information System（GIS） techniques was adopted to determine the soil erosion vulnerability of a forested mountainous sub-watershed in Kerala,India.The spatial pattern of annual soil erosion rate was obtained by integrating geo-environmental variables in a raster based GIS method.GIS data layers including,rainfall erosivity（R）,soil erodability（K）,slope length and steepness（LS）,cover management （C） and conservation practice（P） factors were computed to determine their effects on average annual soil loss in the area.The resultant map of annual soil erosion shows a maximum soil loss of 17.73 t h-1 y-1 with a close relation to grass land areas,degraded forests and deciduous forests on the steep side-slopes（with high LS ）.The spatial erosion maps generated with RUSLE method and GIS can serve as effective inputs in deriving strategies for land planning and management in the environmentally sensitive mountainous areas.  相似文献   

19.
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   

20.
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   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号