长江流域土壤侵蚀预报模型研究进展

土壤侵蚀模型是定量评价土壤侵蚀影响,进行土地利 用和水土保持规划的科学工具。总结了长江流域土壤侵蚀模型的主要成果,对长江流域国外 物理模型的应用、USLE模型的应用、经验性模型、物理过程性模型作了详细介绍,以期为今 后长江流域的土壤侵蚀模型研究提供一定的参考意见。     

Modelling Watershed Scale Soil Loss Prediction and Sediment Yield Estimation

Computer simulation models are becoming increasingly popular in predicting soil loss for various land use and management practices. A GIS-based system, GeoUSLE, was developed in this study for soil loss prediction and sediment yield estimation in the watershed scale. The Universal Soil Loss Equation (USLE) and watershed analysis models are incorporated in the system. The required watershed information and USLE factors are derived from digital elevation models (DEMs) and remote sensing data. The GIS-based system can flexibly delineate drainage networks and watersheds and rapidly query the sediment yield at any point or watershed outlet via the point-and-click interface. The study presents an example application of the system to an agricultural reservoir watershed in central Taiwan. The estimated result shows that the developed system scales up USLE applications from the slope to the watershed, which can be used to assess the erosion hot spots in a watershed for the management decision making.     

Estimation of Potential Soil Erosion for River Perkerra Catchment in Kenya

River Perkerra catchment with an area of 1207 km² is drained by River Perkerra, which is one of the rivers flowing into Lake Baringo whose drainage area is 6820 km². The lake is in a semi-arid area of Kenya. Its depth has reduced from 8 m in 1972 to 2.5 m in 2003 due to siltation resulting from high erosion rates in the catchment. The entire catchment is characterised by very steep slopes on the hillsides and gentle slopes in the middle and lower reaches where the surface is bare with very little undergrowth. Interventions to control soil erosion in this fragile ecosystem have been limited partly because of lack of data on erosion and its spatial distribution. In the present study, Universal Soil Loss Equation (USLE) was used in conjunction with GIS Arc/Info and Integrated Land and Water Information Systems (ILWIS) to estimate potential soil loss from River Perkerra catchment. Various physical parameters of the equation were derived by analysing spatial data and processing Landsat TM satellite imagery of the catchment. The estimated potential soil erosion from the catchment was 1.73 million tonnes/year while the sediment yield at the catchment outlet was found to be 1.47 million tonnes/year. The sediment delivery ratio derived using an empirical equation was 0.83. This figure indicates that a higher proportion of sediments generated in the catchment is delivered at the outlet. The use of GIS enabled the results of erosion potential to be mapped back onto the catchment. This is useful in identifying priority areas that require urgent management interventions in controlling soil erosion.     

流域侵蚀产沙模型研究动态评述

土壤侵蚀模型是水土保持效益评价的有效工具.本文将流域土壤侵蚀模型分为经验模型、理论模型和随机模型,并从这三方面进行了分析总结,着重介绍了国内外流域土壤侵蚀经验模型、理论模型的发展历程以及随机模型的研究现状,以期能吸收国内外已有经验,促进我国土壤侵蚀模型研究,并依此为基础对我国土壤侵蚀模型的发展趋势提出了自己的见解.     

基于RS和GIS的乌东德水电站坝址区土壤侵蚀预测研究

 选取乌东德水电站坝区一典型区为试验示范区,以通用土壤流失方程（USLE）为评价模型,运用GIS和RS对各指标因子赋值,对试验区的土壤侵蚀量进行估算与分析。结果表明,试验区平均土壤侵蚀模数为6 088.58t/(km2·a),属于强度侵蚀。试验区中度以下的侵蚀面积占总面积的57.91%,土壤侵蚀量的贡献率仅为8.85%;而91.15%的侵蚀泥沙来自于面积42.09%的强度侵蚀以上的区域,其中,占11.53%的剧烈侵蚀区域贡献了43.83%的侵蚀泥沙。     

Identification of critical erosion prone areas in the small agricultural watershed using USLE,GIS and remote sensing

In the present study, Karso watershed of Hazaribagh, Jharkhand State, India was divided into 200 × 200 grid cells and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion prone areas of watershed for prioritization purpose. Average annual sediment yield data on grid basis was estimated using Universal Soil Loss Equation (USLE). In general, a major limitation in the use of hydrological models has been their inability to handle the large amounts of input data that describe the heterogeneity of the natural system. Remote sensing (RS) technology provides the vital spatial and temporal information on some of these parameters. A recent and emerging technology represented by Geographic Information System (GIS) was used as the tool to generate, manipulate and spatially organize disparate data for sediment yield modeling. Thus, the Arc Info 7.2 GIS software and RS (ERDAS IMAGINE 8.4 image processing software) provided spatial input data to the erosion model, while the USLE was used to predict the spatial distribution of the sediment yield on grid basis. The deviation of estimated sediment yield from the observed values in the range of 1.37 to 13.85 percent indicates accurate estimation of sediment yield from the watershed.     

Estimation of Soil Erosion and Sediment Yield During Individual Rainstorms at Catchment Scale

Lushi basin, named after the Lushi County, is one of the sub-basins of the Yellow River basin in China. The basin is suffering from severe soil erosion problems, especially during the “wet” season. In order to identify the proper soil management approaches for the basin, an erosion model is designed to estimate the soil erosion and sediment yield during single events. The hydrological model used for the estimations in the study is the BTOPMC model, which is developed based on the TOPMODEL. Under the model structure of BTOPMC, a modified form of the Universal Soil Loss Equation (USLE) was incorporated as a core module of the erosion component. In the modification, the runoff ratio, an important determinant of soil erosion, was brought into the USLE equation and consequent modifications were made to the soil erodibility and slope length factors. A concept of total sediment transport capacity for single events is applied in the model to route the surface erosion from each discrete cell to the basin outlet. The BTOPMC model was used in simulating the river discharges and sediment yields for 29 events in the Lushi basin. Its acceptable performance validates the model’s predictive ability in simulating the basin-scale erosions during individual rainstorms.     

不确定性信息下流域土壤侵蚀量计算

根据流域土壤、地形、降雨、植被、管理技术等因素存在的多种不确定性特点，运用盲数来描述和处理通用土壤流失方程USLE中各参数的不确定性，尝试性地提出了不确定性信息下流域土壤侵蚀量计算的新方法。根据这一方法，不仅可以求得研究区域土壤潜在侵蚀量的各种可能取值区间，也可以得到各区间相应的主观可信度。再由盲数均值计算公式，最终得到整个研究区域土壤潜在侵蚀总量。在此基础上，结合区域土壤中氮、磷含量资料，可以计算出吸附态氮、磷的流失量。实例研究表明，运用盲数理论研究流域土壤侵蚀量和吸附态氮、磷流失量，理论上是可行的，计算结果是可信的。     

Catchment Erosion and Sediment Delivery in a Limno-Reservoir Basin Using a Simple Methodology

Accelerated soil erosion is a threat for the societies due to the loss of ecosystems services. Soil erosion and sediment delivery have been assessed in a small catchment of Central Spain with a new water body, the Pareja Limno-reservoir, located in its outlet. This limno-reservoir was created in 2006 with environmental and recreational purposes in the riverine zone of a large reservoir. Sedimentation risk is an issue of concern regarding limno-reservoirs environmental feasibility. Thus, the study of the soil erosion in the Pareja Limno-reservoir catchment and its sediment delivery seemed of the utmost importance. In this paper we establish an affordable and simple methodology to address it. A soil erosion and deposition monitoring network was installed in the Ompólveda River basin (≈88 km²), which flows into the Pareja Limno-reservoir. Results obtained were related with those from a sedimentation study previously carried out in the limno-reservoir. Gross hillslope erosion in the catchment was 6.0 Mg ha^?1 year^?1, which is in agreement with values reported for Mediterranean areas. After subtraction of the deposition measured, a soil loss of 1.2 Mg ha^?1 year^?1 was found in the catchment. Sediment delivery ratio (SDR) was estimated to be 3.8 %. SDR is low as a result of the low connectivity between the stream network and the limno-reservoir. Some local characteristics may also have a secondary influence in the low SDR value. Results obtained support the environmental feasibility of the Pareja Limno-reservoir from the sedimentation risk perspective. They also demonstrate that the methodology followed allows the assessment of soil loss and sediment delivery at a catchment scale, and the identification of areas where the erosion problems are most severe.     

Quantification of soil erosion and sediment yield for ungauged catchment using the RUSLE model: Case study for Lake Basaka catchment in Ethiopia

Soil erosion is a monumental land degradation problem in many parts of the world, threatening the well‐being of humans and ecosystems. The Lake Basaka catchment is heavily affected by serious land degradation problems related to land use–land cover changes (LULC), population dynamics and settlement, introduction of large‐scale irrigation schemes, etc. Accordingly, the objective of the present study was to quantify the magnitude of soil lost from the Lake Basaka catchment and the sediment subsequently delivered to the lake on the basis of the limited available dataset in a distributed manner using the RUSLE model in a GIS environment. The results indicated about 36 million m³ of soil were lost from the catchment between 1973 and 2007. Soil erosion and sedimentation in the lake catchment continue to increase from time to time, being attributed to the significant LULC occurring in the catchment. About 23 cm of the economically productive top soil in the catchment was lost during the study period (1960–2015), which translates into a significant degradation of the catchment (e.g. further reduction of infiltration capacity, thereby accelerating run‐off and erosion rates). Similarly, about a 1.3 m deep sediment layer was deposited in the lake during the same period. The computed sediment yield indicates about 14% of the lake incremental volume and depth in recent periods (post‐2000s) is attributable to sedimentation. Certain coincidental changes are also occurring in the catchment, including organic matter declines, soil nutrient depletion and soil depth decrement, which may lead to decreased production and productivity and associated ecosystem imbalances. The present study identified the potential areas that contribute significantly to erosion and sedimentation, thereby providing guidance regarding where land use/cover practices must be implemented to limit/reduce, if not avoid, the impacts of erosion and subsequent sedimentation in Lake Basaka.     

Estimation of Sediment Yield and Areas of Soil Erosion and Deposition for Watershed Prioritization using GIS and Remote Sensing

A Geographical Information System (GIS) based method is proposed and demonstrated for the identification of sediment source and sink areas and the prediction of sediment yield from watersheds. Data from the Haharo sub-catchment having an area of 565 km² in the Upper Damodar Valley in Jharkhand State in India was taken up for the present study due to availability of gauged data at multiple locations within watershed area. The watershed was discretized into hydrologically homogeneous grid cells to capture the watershed heterogeneity. The cells thus formed were then differentiated into cells of overland flow regions and cells of channel flow regions based on the magnitude of their flow accumulation areas. The gross soil erosion in each cell was calculated using the Universal Soil Loss Equation (USLE). The parameters of the USLE were evaluated using digital elevation model, soil and landuse information on cell basis. The concept of transport limited sediment delivery (TLSD) was formulated and used in ArcGIS for generating the transport capacity maps. An empirical relation is proposed and demonstrated for its usefulness for computation of land vegetation dependent transport capacity factor used in TLSD approach by linking it with normalized difference vegetation index (NDVI) derived from satellite data. Using these maps, the gross soil erosion was routed to the watershed outlet using hydrological drainage paths, for derivation of transport capacity limited sediment outflow maps. These maps depict the amount of sediment rate from a particular grid in spatial domain and the pixel value of the outlet grid indicates the sediment yield at the outlet of the watershed. Up on testing, the proposed method simulated the annual sediment yield with less than ±40% error.     

Integration of GIS with USLE in Assessment of Soil Erosion

A Geographic Information System (GIS) has been integrated with the USLE (Universal Soil Loss Equation) model in identification of rainfall-based erosion and the transport of nonpoint source pollution loads to the Gediz River, which discharges into the Aegean Sea along the western coast of Turkey. The purpose of the study is to identify the gross erosion, sediment loads, and organic N loads within a small region of the Gediz River basin. Similar studies are available in literature, ranging from those that use a simple model such as USLE to others of a more sophisticated nature. The study presented here reflects the difficulties in applying the methodology when the required data on soil properties, land use and vegetation are deficient in both quantity and quality, as the case is with most developing countries.     

Sediment TMDL Development for the Amite River

The Amite River is recognized as one of the 15 water bodies impaired by sediments in Louisiana, USA. Based on US EPA’s Protocol sediment TMDL (Total Maximum Daily Load) development is conducted for the Amite River and described in this paper. The TMDL development consists of four components: (1) development of a new model for cohesive sediment transport, (2) estimation of sediment loads (sources) due to watershed erosion, (3) river flow computation, and (4) determination of sediment TMDL for the Amite River. Using the mass conservation principle and Reynolds transport theorem a new 1-D model has been developed for computation of suspended cohesive sediment transport. Sediment erosion in the Amite River Basin is calculated by combining the USLE (Universal Soil Loss Equation) model with GIS and the digital elevation model of the Amite River Basin. Digital elevation data was imported into the GIS which generated inputs for USLE. The calculated average annual rate of soil erosion in the Amite River Basin is 13.368 tons per ha, producing a nonpoint sediment load of 103 mg/L to the Amite River. The flow computation is performed using the HEC-RAS software. The computed sediment concentration in the Amite River varies in the range of 3–114 mg/L and sediment TMDL is 281.219 tons/day. The reduction necessary to support beneficial uses of the river is 55% or 275.946 tons/day. Results indicate that the combined application of the new 1-D sediment transport model, GIS, USLE model, and HEC-RAS is an efficient and effective approach to sediment TMDL development.     

水电建设项目水土流失预测程序化研究

在分析大量国内外水土流失预测相关资料并走访国内专家的基础上,认为修正参数后的通用水土流失方程(USLE)仍是目前预测坡面水土流失的可行办法,程序提供了R、L、S等主要因子的多种计算方法,也提供了专家预测法对渣场外其他区域的预测,计算结果保存到EXCEL工作表中。此外,程序还提供了大量的参考参数值。程序对水电工程的水土流失预测有很强的针对性,可大大节省预测时间。     

基于GIS的粤北青莲水流域水土流失成因分析

随着人类社会经济活动的加强,水土流失有持续恶化趋势,青莲水流域内土壤肥力下降,河道泥沙淤积,影响河流行洪安全。本文选用通用土壤流失方程,利用ArcGIS的空间叠加分析等功能,分别计算分析研究区内与土壤侵蚀相关的降雨、土壤、植被、地形、土地利用等因子,经叠加分析后生成流域水土流失现状图。结果表明,地形地貌因子和土地利用因子是影响流域水土流失的关键因子,研究结果可为广东省中小流域治理提供水土保持方面的理论支撑。     

The Economics of Reservoir Sedimentation: A Case Study of Mahaweli Reservoirs in Sri Lanka

Benefits of water resource projects often fall short of original expectations owing to sedimentation of reservoirs. This study estimates the cost of reservoir sedimentation in Mahaweli reservoirs including impact on hydropower production, irrigation water supply, extra cost of water purification and loss of fisheries yields. The present value of the cost of sedimentation is estimated to be US$26 406 620. Of the different types of costs, lost hydropower production is the most significant as it accounts for 66.6% of the total cost. The benefits of prevention of reservoir sedimentation alone are inadequate to compensate for the costs involved. Using soil erosion control measures at farm level offers a better solution for reservoir sedimentation compared with de-silting. Among the available erosion control methods, stoned terrace is the least-cost solution to reservoir sedimentation.     

Modelling Sediment Input to Surface Waters for German States with MEPhos: Methodology, Sensitivity and Uncertainty

Soil erosion on arable land and on steep vineyards is a major problem in the state of Hesse (21,115 km2) in central Germany. The aim of a joint study between the Research Centre Jülich, the Hessian Agency for the Environment and Geology and the Hessian Ministry for the Environment, Energy, Agriculture and Consumer Protection was to delineate parcels which are severely affected by erosion and to identify sediment source areas. For this purpose, the ABAG, an adaptation of the USLE approach to German conditions, has been employed with the best available data sets on K-, C-, R- and LS-factor. Model results at the field scale show that soil losses in Hesse vary between <0.5 and >15 tonnes/hectare/year. The mean loss amounts to ca. 4.3 tonnes/hectare/year. The sediment delivery ratios for 450 sub-catchments range between 0.5 and 78% with a mean of 18%. Further analysis showed that LS- and C-factor are of highest sensitivity for the model output. Therefore, the effects of alternative algorithms or sources for LS- and C-factor on the results were assessed. An uncertainty analysis based on Gaussian error propagation and Monte Carlo simulation showed that the uncertainty of model results induced by input parameters is 1.7 tonnes/hectare/year or 34% of the mean annual soil loss. The model results are a good basis for further works concerning a soil erosion atlas and internet-based soil data viewer.     

Estimation of Soil Erosion and Sediment Yield Using GIS at Catchment Scale

A GIS-based method has been applied for the determination of soil erosion and sediment yield in a small watershed in Mun River basin, Thailand. The method involves spatial disintegration of the catchment into homogenous grid cells to capture the catchment heterogeneity. The gross soil erosion in each cell was calculated using Universal Soil Loss Equation (USLE) by carefully determining its various parameters. The concept of sediment delivery ratio is used to route surface erosion from each of the discritized cells to the catchment outlet. The process of sediment delivery from grid cells to the catchment outlet is represented by the topographical characteristics of the cells. The effect of DEM resolution on sediment yield is analyzed using two different resolutions of DEM. The spatial discretization of the catchment and derivation of the physical parameters related to erosion in the cell are performed through GIS techniques.     

A Modified LAPSUS Model to Enhance the Effective Rainfall Estimation by SCS-CN Method

In this study, LAPSUS model is modified to enhance the effective rainfall estimation by SCS curve number method. The LAPSUS model calculates discharge based on effective rainfall and routs it towards lower neighbouring grid cells following the multiple flow direction principle. Then, the sediment transport capacity and sediment transport rate are calculated in each grid cell. Finally, erosion or sedimentation is calculated by comparing the sediment transport rate with the sediment already in the transport of each grid cell. The amount of rainfall, curve number, convergence factor, discharge exponent, slope exponent, erodibility factor, and sedimentation ability factor are inputted to the application page of the modified model that was created in the C⁺⁺ programming. The outputs of the model are runoff and erosion maps in ASCII format. Evaluating performance of the modified model showed a high accuracy of its results. The value of the coefficient of determination (R²) calculated 0.99 for runoff and 0.97 for erosion. The Nash-Sutcliffe efficiency was 0.96 for runoff and 0.97 for erosion. The value of the precision index calculated 0.81 for both runoff and erosion. Also, the nRMSE calculated 3% for both runoff and erosion. The result showed that the modified model capable to estimate the runoff and erosion on a landscape in a micro sub-catchment scale.     

近廿年来官厅水库流域水土保持拦沙量估算

自1983年官厅水库永定河上游流域被列为国家重点水土流失治理区以来，在近廿年的时间内，流域内进行了大量的水土流失治理工作，据调查截止2000年年底，山西省大同地区治理水土流失面积4205．8km^2，河北省张家口地区治理水土流失面积6449．11km^2，北京市延庆县妫水河流域治理水土流失面积435．33km^2，三省市共治理流失面积ll090．24km^2，其中治理面积保存率在90％以上。对不同治理措施拦沙量的估算结果表明各类水土保持措施拦沙总量为3．51亿t，水土保持拦沙量占流域总产沙量的20．53％，水土保持措施拦沙对减少官厅水库泥沙的淤积起到了积极的作用。