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1.
The objective of this study was to assess the lake sediment budget of land use changes using the Universal Soil Loss Equation (USLE), sediment delivery ratio (SDR), and trap efficiency (TE). The geographic information system was combined with the USLE to estimate the soil erosion of the Lake Asan watershed. Spatial data for each of the USLE factors were obtained from the land use, soil, and 1/25,000 scale digital contour maps. Landsat-5 TM images were selected for analyzing soil erosion changes due to land use changes. The sediment yield to Lake Asan was estimated using the SDR and TE. The estimated sediment budget was compared with observed data from the Lake Asan watershed between 1974 and 2003. The total estimated annual mean sediment budgets from Lake Asan in 1986, 1992, and 2000 were 0.267, 0.301, and 0.339 × 106 ton, respectively, with an average of 0.302 × 106 ton. The average measured sediment budget was 3.15 × 106 ton year?1. The average estimated value shows reasonable agreement with the observed sediment balance. The average estimated and measured sediment budgets contain uncertainties due to both the methods and the approach used by the observers. The simulated results indicated that soil erosion in the Lake Asan watershed increased at a rate of approximately 2 % per year from 1986 to 2000 due to land use change. This study may be useful for managers to identify reservoir rehabilitation management methods for stable irrigation water supply.  相似文献   

2.
Undulating landscapes of Chhotanagpur plateau of the Indian state of Jharkhand suffer from soil erosion vulnerability of varying degrees. An investigation was undertaken in some sections of the Upper Subarnarekha River Basin falling within this state. An empirical equation known as Universal Soil Loss Equation (USLE) was utilized for estimating the soil loss. Analysis of remote sensing satellite data, digital elevation model (DEM) and geographical information system (GIS)–based geospatial approach together with USLE led to the soil erosion assessment. Erosion vulnerability assessment was performed by analyzing raster grids of topography acquired from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM data. LANDSAT TM and ETM+ satellite data of March 2001 and March 2011 were used for inferring the land use–land cover characteristics of the watershed for these years, respectively. USLE equation was computed within the GIS framework to derive annual soil erosion rates and also the areas with varying degrees of erosion vulnerability. Erosion vulnerability units thus identified covered five severity classes of erosion ranging from very low (0–5 ton ha?1 yr?1) to very severe (> 40 ton ha?1 yr?1). Results indicated an overall increase of erosion in the year 2011 as compared to the erosion computed for the year 2001. Maximum soil erosion rate during the year 2001 was found up to 40 ton ha?1 yr?1, whereas this went up to 49.80 ton ha?1 yr?1 for the year 2011. Factors for the increase in overall erosion could be variation in rainfall, decrease in vegetation or protective land covers and most important but not limited to the increase in built-up or impervious areas as well.  相似文献   

3.
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   

4.
Mapping heatwave vulnerability in Korea   总被引：1，自引：0，他引：1  
Analysis of event-based soil erosion magnitude with special return periods is essential to appropriately design strategies and adopt soil conservation practices. However, the spatiotemporal variations of soil erosion with different return periods, especially at national level, have not been adequately considered. Therefore, the present study aimed to zone rainfall erosivity index (R factor) as the most dynamic factor affecting variability of soil erosion rate, with different return periods in monthly, seasonal and annual time scales in Iran. Toward this attempt, the kinetic energy and maximum 30-min intensity (I 30) over 12,000 available and accessible events of 70 stations were calculated during the common period of 1984–2004 and the corresponding R factor of the Universal Soil Loss Equation was then computed. Subsequently, the best-fitted frequency distributions were determined in all stations in three time scales using the EasyFit Software. The R factor was accordingly estimated for 2-, 5-, 10-, 25- and 50-year return periods. In addition, the inverse distance weighting technique was employed to determine and analyze the spatial variability patterns of R factor in different time scales using geographic information system. The results indicated that the frequency distributions fitted to study data were different in study time scales due to variability of spatiotemporal patterns of R factor. In addition, no specific spatial pattern of R factor could be recognized for different return periods and time scales. The average annual R factor was also found 1.41 MJ mm ha?1 h?1, whereas the respective R factor for different respective return periods of 2, 5, 10, 25 and 50 years was obtained 1.47, 2.62, 3.35, 4.48 and 5.54 MJ mm ha?1 h?1. These findings can be used for suitable decision making and effective environmental planning for land management Iran countrywide.  相似文献   

5.
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   

6.

In this work, a dynamic GIS modeling approach is presented that incorporates: a) geoinformatic techniques, b) 55-year historical meteorological data, and c) field measurements, in order to estimate soil erosion risk in intensively cultivated regions. The proposed GIS-based modeling approach includes the estimation of soil erosion rates due to surface water flow under current and future climate change scenarios A2 and B1 for the years 2030 and 2050. The soil erosion was estimated using the Universal Soil Loss Equation (USLE). The proposed soil erosion model was validated using field measurements at different sites of the study area. The results show that an extended part of the study area is under intense erosion with the mean annual loss to be 4.85 t/ha year−1. Moreover, an increase in rainfall intensity, especially for scenario B1, can generate a significant increase (32.44 %) in soil loss for the year 2030 and a much more (50.77 %) for the year 2050 in comparison with the current conditions. Regarding the scenario A2, a slight decrease (1.85 %) in soil loss was observed for the year 2030, while for 2050 the results show an adequate increase (7.31 %) in comparison with the present. All these approaches were implemented at one of the most productive agricultural areas of Crete in Greece dominated by olive and citrus crops.

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7.
Estimation of spatial extent of soil erosion, one of the most serious forms of land degradation, is critical because soil erosion has serious implications on soil fertility, water ecosystem, crop productivity and landscape beauty. The primary objective of the current study was to assess and map the soil erosion intensity and sedimentation yield of Potohar region of Pakistan. Potohar is the rainfed region with truncated and complex topography lying at the top of the Indus Basin, the world’s largest irrigation networks of canals and barrages. Spatially explicit Revised Universal Soil Loss Equation (RUSLE) Model integrated with Remote Sensing-GIS techniques was used for detecting/mapping of erosion prone areas and quantification of soil losses. The results show that the Potohar region is highly susceptible to soil erosion with an average annual soil loss of 19 tons ha?1 year?1 of which the maximum erosion (70–208 tons ha?1 year?1) was near the river channels and hilly areas. The sediment yield due to the erosion is as high as 148 tons ha?1 year?1 with an average of 4.3 tons ha?1 year?1. It was found that 2.06% of the total area falls under severe soil erosion, 13.34% under high erosion, 15.35% under moderate soil erosion while 69.25% of the area lies in the low (tolerable) soil erosion. Chakwal and Jhelum districts of the region are seriously affected by erosion owing to their topography and soil properties. The information generated in this study is a step forward towards proper planning and implementation of strategies to control the erosion and for protection of natural resources. It is, hence, necessary that suitable water harvesting structures be made to control water to prevent soil erosion and provision of water in the lean season in this region. Tree plantation and other erosion control practices such as strip cropping can also minimize soil erosion in this region.  相似文献   

8.
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   

9.
Watershed degradation due to soil erosion and sedimentation is considered to be one of the major environmental problems in Iran. In order to address the critical conditions of watershed degradation in arid and semiarid regions, a study based on the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model was carried out at Golestan watershed, northeast of Iran. The model information layers comprising nine effective factors in erosion and sedimentation at the watershed site were obtained by digitalization and spatial interpolation of the basic information data in a GIS program. These factors are geology, soil, climate, runoff, topography, land cover, land use, channel, and upland erosion. The source data for the model were obtained from available records on rainfall and river discharge and sediment, topography, land use, geology, and soil maps as well as field surveys and laboratory analysis. The results of the MPSIAC model indicated that 60.75 % (194.4 km2) and 54.97 % (175.9 km2) of the total watershed area were classified in the heavy sedimentation and erosion classes, and the total basin sediment yield and erosion were calculated as 4,171.1 and 17,813.4 m3 km?2 year?1, respectively. In the sensitivity analysis, it was found that the most sensitive parameters of the model in order of importance were topography (slope), land cover and use, runoff, and channel erosion (R 2?=?0.92–0.94), while geology, climate (rainfall), soil, and upland erosion factors were found to have moderate effect to the model output (R 2?=?0.74–0.59).  相似文献   

10.
The particle size distribution in small watershed changes under different land uses and affects soil erodibility. The aims of this study were (1) to investigate the volume fractal dimension of particle size distribution under different land uses in a typical small watershed of purple soil, (2) to estimate soil erodibilities of various land uses utilizing the Erosion-Productivity Impact Calculator (EPIC) model and the nomogram (NOMO) model, and (3) to relate volume fractal dimension with the soil erodibility used in the Universal Soil Loss Equation (USLE) in purple soil areas. Laser diffractions and double-logarithmic model were used to measure and calculate volume fractal dimension values. The results show that soil volume fractal dimensions were well linearly fitted to the double-logarithmic model with high correlation coefficients of 0.902–0.936 under six land uses in the small watershed. The averaged volume fractal dimension values under different land uses, from high to low were in the order of Zea mays L, Ipomoea batatas, Citrus reticulata Blanco, Setaria viridis, Robinia pseudoacacia L, Pinus massoniana Lamb. The volume fractal dimension was positively correlated to clay particle fraction (R = 0.933). The average soil erodibility values under different land uses from high to low were in the order of Setaria viridis, Citrus reticulata Blanco, Pinus massoniana Lamb, Zea mays L, Ipomoea batatas, Robinia pseudoacacia L while average soil erodibilities from high to low values were in the order of Setaria viridis, Citrus reticulata Blanco, Zea mays L, Ipomoea batatas, Pinus massoniana Lamb, Robinia pseudoacacia L. The soil erodibilities calculated by the two models were similar, and positively correlated (R = 0.630–0.877). The volume fractal dimension values of six land uses were negatively correlated to both soil erodibility estimated by EPIC and by NOMO models. Moreover, the correlations of the volume fractal dimension values of Zea mays L, Ipomoea batatas and Citrus reticulata Blanco estimated by EPIC or NOMO were lower than those of Pinus massoniana Lamb, Robinia pseudoacacia L and Setaria viridis. Further research is needed to determine the influence of volume fractal dimension on the soil erodibility under different land use and managements.  相似文献   

11.
This study is aimed at the evaluation of the hazard of soil erosion and its verification at Boun, Korea, using a Geographic Information System (GIS) and remote sensing. Precipitation, topographic, soil, and land use data were collected, processed, and constructed into a spatial database using GIS and remote sensing data. Areas that had suffered soil erosion were analysed and mapped using the Universal Soil Loss Equation (USLE). The factors that influence soil erosion are rainfall erosivitiy (R) from the precipitation database, soil erodibility (K) from the soil database, slope length and steepness (LS) from the topographic database, and crop and management (C) and conservation supporting practices (P) from the land use database. Land use was classified from Landsat Thematic Mapper satellite images. The soil erosion map verified use of the landslide location data. Landslide locations were identified in the Boun area from interpretation of aerial photographs and field surveys.  相似文献   

12.
The universal soil loss equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices by the effective integration of the GIS-based procedures to estimate the factor values on a grid cell basis. This study was performed for five different lands uses of Indağı Mountain Pass, Cankırı to predict the soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Of the USLE factors, rainfall-runoff erosivity factor (USLE-R) and topographic factor (USLE-LS) were greatly involved in GIS. These were surfaced by correcting USLE-R site-specifically using DEM and climatic data and by evaluating USLE-LS by the flow accumulation tool using DEM and watershed delineation tool to consider the topographical and hydrological effects on the soil loss. The study assessed the soil erodibility factor (USLE-K) by randomly sampled field properties by geostatistical analysis. Crop management factor for different land-use/land cover type and land use (USLE-C) was assigned to the numerical values from crop and flora type, canopy and density of five different land uses, which are plantation, recreational land, cropland, forest and grassland, by means of reclassifying digital land use map available for the site. Support practice factor (USLE-P) was taken as a unit assuming no erosion control practices. USLE/GIS technology together with the geostatistics combined these major erosion factors to predict average soil loss per unit area per unit time. Resulting soil loss map revealed that spatial average soil loss in terms of the land uses were 1.99, 1.29, 1.21, 1.20, 0.89 t ha−1 year−1 for the cropland, grassland, recreation, plantation and forest, respectively. Since the rate of soil formation was expected to be so slow in Central Anatolia of Turkey and any soil loss of more than 1 ton ha−1 year−1 over 50–100 years was considered as irreversible for this region, soil erosion in the Indağı Mountain Pass, to the great extent, attained the irreversible state, and these findings should be very useful to take mitigation measures in the site.  相似文献   

13.
Soil erosion modeling of a Himalayan watershed using RS and GIS   总被引：5，自引：1，他引：4  
Employing the remote sensing (RS) and geographical information system (GIS), an assessment of sediment yield from Dikrong river basin of Arunachal Pradesh (India) has been presented in this paper. For prediction of soil erosion, the Morgan-Morgan and Finney (MMF) model and the universal soil loss equation (USLE) have been utilized at a spatial grid scale of 100 m × 100 m, an operational unit. The average annual soil loss from the Dikrong river basin is estimated as 75.66 and 57.06 t ha−1 year−1 using MMF and USLE models, respectively. The watershed area falling under the identified very high, severe, and very severe zones of soil erosion need immediate attention for soil conservation.  相似文献   

14.
Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m3 km?2 year?1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m3 km?2 year?1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.  相似文献   

15.
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   

16.
Remote sensing data and Geographical Information System (GIS) has been integrated with the weighted index overlay (WIO) method and E 30 model for the identification and delineation of soil erosion susceptibility zones and the assessment of rate of soil erosion in the mountainous sub-watershed of River Manimala in Kerala (India). Soil erosion is identified as the one of the most serious environmental problems in the human altered mountainous environment. The reliability of estimated soil erosion susceptibility and soil loss is based on how accurately the different factors were estimated or prepared. In the present analysis, factors that are considered to be influence the soil erosion are: land use/land cover, NDVI, landform, drainage density, drainage frequency, lineament frequency, slope, and relative relief. By the WIO analysis, the area is divided into zones representing low (33.30%), moderate (33.70%), and high (33%) erosion proneness. The annual soil erosion rate of the area under investigation was calculated by carefully determining its various parameters and erosion for each of the pixels were estimated individually. The spatial pattern thus created for the area indicates that the average annual rate of soil erosion in the area was ranging from 0.04 mm yr−1 to 61.80 mm yr−1. The high soil erosion probability and maximum erosion rate was observed in areas with high terrain alteration, high relief and slopes with the intensity and duration of heavy precipitation during the monsoons.  相似文献   

17.
Gravely calcareous soils cover approximately most of arid lands (in percent); however, the solute transport behavior in these soils remains a current issue. This research aimed at estimating and correlating the solute transport parameters in gravely calcareous soils as being affected by different land uses through the knowledge of the soil morphological, physical, and chemical properties. Four different land use sites were selected: irrigated trees and bare, range, and alluvial sediment lands. Solute transport parameters of soil pore water velocity (V), dispersion coefficient (D), and retardation factor (R) were estimated using bromide breakthrough curve tests for surface soil columns. In addition, field Brilliant Blue FCF dye tracing experiment was conducted to determine the maximum dimensional movements. Soil morphological analysis was able to explain the heterogeneity in the solute transport parameters. Conductive solute transport mechanism with V of 17.99 m/day was favored in a high continuous pore system observed under tree lands. Presence of high gravel and CaCO3 contents under range lands increased pore system tortuosity and thus increased D magnitude up to 1,339.88 cm2/day. Existence of thin surface crusts at both bare soils and alluvial sediments had considerably restricted V down to 1.46 m/day. Dye staining technique aided the explanation of the existing variations by providing visual evidence on the preferential flow paths and patterns governing the solute transport mechanism at each site.  相似文献   

18.
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   

19.
Mapping of erosion risk areas is an important tool for the planning of natural resources management, allowing researchers to propose the modification of land use properly and implement more sustainable long-term management strategies. The objective of this study was to assess and identify critical sub-catchments for soil conservation management using the USLE, GIS, and remote sensing techniques. The Tapacurá catchment is one of the planning units for water resource management of the Recife Metropolitan Region. Maps of the erosivity (R), erodibility (K), slope (LS), cover-management (C), and support practice (P) factors were derived from the climate database, digital elevation model, and soil and land-use maps. In order to validate the simulation process, total sediment delivery ratio was estimated. The results showed a mean sediment delivery ratio (SDR) of around 11.5?% and a calculated mean sediment yield of 0.108?t?ha?1?year?1, which is close to the observed one, 0.169?t?ha?1?year?1. The obtained soil loss map could be considered as a useful tool for environmental monitoring and water resources management. The methodology applied showed acceptable precision and allowed the identification of the most susceptible areas to soil erosion by water, constituting an important predictive tool for soil and environmental management in this region, which is highly relevant for the prediction of varying development scenarios for Tapacurá catchment. This approach can be applied to other areas for simple and reliable identification of critical areas of soil erosion in catchments.  相似文献   

20.
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   

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