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.     

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.     

岷江镇江关流域分布式水文及泥沙侵蚀模型研究

基于空间地理信息系统的流域分布式水文泥沙模型为研究流域产流产沙及在河道中的汇流、输移过程提供了,科学有效的手段.针对岷江上游镇江关流域土壤易受降雨侵蚀的问题,采用水沙耦合的流域分布式水文综合模型,对该流域1990年后典型年的径流及泥沙侵蚀输移过程进了数值模拟,并结合镇江关水文站的实测资料对模型进行了验证,计算成果令人满意.分析表明,近年来岷江上游地区的年径流和输沙量均呈现出下降的趋势,且后者下降速率更快,说明泥沙侵蚀输移与径流相比对流域环境变化的反应更为敏感,今后水土保持工作应注重坡面治理.     

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。     

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。     

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.     

东湾流域BTOPMC模型和新安江模型的应用比较

对BTOPMC模型的原理、结构以及参数进行了详细介绍,利用东湾流域DEM资料、土地覆盖资料、土壤组成资料、NDVI数据、月平均气候资料及1982—2000年的实测水文资料,对BTOPMC模型与新安江模型的模拟性能进行了比较研究。结果表明,新安江模型整体的模拟精度较BTOPMC模型的模拟精度要高。     

Simulation of Runoff and Suspended Sediment Transport Rate in a Basin with Multiple Watersheds

Accurate runoff and suspended sediment transport rate models are critical for watershed management. In this study, a physiographic soil erosion–deposition (PSED) model is used in conjunction with GIS, to simulate the runoff and sediment transport process during storm events in a multi-watershed basin. This PSED model is verified using three typhoon events and 33 storm events in Cho-Shui River Basin, located in central Taiwan. Cho-Shui River Basin has 11 sub-watersheds displaying a variety of hydrologic and physiographic conditions as well as high concentrations of suspended sediment in river flow and a steep average channel bed slope of 2%. The results show the capability, applicability, and accuracy of the PSED model for multi-watershed basins.     

Estimation of Soil Erosion for a Himalayan Watershed Using GIS Technique

The fragile ecosystem of the Himalayas has been an increasing cause of concern to environmentalists and water resources planners. The steep slopes in the Himalayas along with depletedforest cover, as well as high seismicity have been major factors in soil erosion and sedimentation in river reaches. Prediction ofsoil erosion is a necessity if adequate provision is to be madein the design of conservation structures to offset the ill effects of sedimentation during their lifetime.In the present study, two different soil erosion models, i.e. theMorgan model and Universal Soil Loss Equation (USLE) model, have been used to estimate soil erosion from a Himalayan watershed.Parameters required for both models were generated using remotesensing and ancillary data in GIS mode. The soil erosion estimated by Morgan model is in the order of 2200 t km^-2 yr^-1 and is within the limits reported for this region.The soil erosion estimated by USLE gives a higher rate. Therefore, for the present study the Morgan model gives, for area located in hilly terrain, fairly good results.     

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.     

应用输沙量推演流域侵蚀量的方法探讨

鉴于至今还没有一个有效获取流域侵蚀产沙量的方法,在分析悬移质泥沙与侵蚀泥沙之间的数量与粒配关系的基础上,阐述了应用输沙量推演流域侵蚀量在理论上的可能性,但却存在着难点,且主要表现在水文站数量不足与区域分布不均、流域内的生态环境复杂与区域差异大、水文站输沙量观测记录起始时间不同步、及新技术应用存在时空条件的局限性。结合与侵蚀产沙和泥沙输移比相关的定性与定量指标,提出了应用输沙量推演流域侵蚀量的方法,即"层次类剔法",来计算与评估流域侵蚀量和泥沙输移比,具体的操作过程是首先制作一幅流域地貌类型地块图,然后是逐类型、逐类型地块的侵蚀量计算和沟道流域泥沙输移比的判断,最终获取流域不同地块的侵蚀强度和流域泥沙输移比。本研究结果可为水土流失监测点的选择提供科学依据,同时对解决流域的泥沙问题也有重要的启迪作用。     

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.     

Finite Element Method and GIS Based Distributed Model for Soil Erosion and Sediment Yield in a Watershed

The objective of this study is to develop a soil erosion and sediment yield model based on the kinematic wave approximation using the finite element method, remote sensing and geographical information system (GIS) for calculating the soil erosion and sediment yield in a watershed. Detachment of soil particles by overland flow occurs when the shear stress at the surface overcomes the gravitational forces and cohesive forces on the particles. Deposition occurs when the sediment load is greater than the transport capacity. Beasley et al.’s (Trans ASAE 23:938–944, 1980) transport equations for laminar and turbulent flow conditions are used to calculate the transport capacity. The model is capable of handling distributed information about land use, slope, soil and Manning’s roughness. The model is applied to the Catsop watershed in the Netherlands and the Harsul watershed in India. Remotely sensed data has been used to extract land use/land cover map of the Harsul watershed, and other thematic maps are generated using the GIS. The simulated results for both calibration and validation events are compared with the observed data for the watersheds and found to be reasonable. Statistical evaluation of model performance has been carried out. Further, a sensitivity analysis has also been carried out to study the effect of variation in model parameter values on computed volume of sediment, peak sediment and the time to peak sediment. Sensitivity analysis has also been carried out for grid size variation and time step variation of the Catsop watershed. The proposed model is useful in predicting the hydrographs and sedigraphs in the agricultural watersheds.     

GIS Based Estimation of Sediment Discharge and Areas of Soil Erosion and Deposition for the Torrential Lukovska River Catchment in Serbia

In the present study the SHETRAN river basin modelling system was used in conjunction with Geographic Information System (GIS) to estimate potential erosion and deposition rates within the catchment and the concentrations of sediment in a flow at the catchment outlet on the example of the 114.31 km² mountainous torrential Lukovska River catchment in Serbia. The streams in the Lukovska River catchment are short, steep and often produce hazardous torrential floods as a consequence of strong rainfall of short duration. The soil erosion and sediment discharge were analysed in view of the catchment response to physical characteristics of the catchment. Considering that the most of total annual sediment discharge in watersheds of torrential character is achieved during storm events, the SHETRAN modelling system was calibrated on the example of a storm event in 1986 and validated for three other storm events in 1974, 1976 and 1979. The simulated results of discharges and sediment concentrations at the catchment outlet for both calibration and validation events were compared with the observed data and found to be reasonable. The changes of erosion and deposition rates within the catchment and in the course of time were estimated for the calibration event in 1986. The simulated erosion rates were within the range of 1 to 10.5 t/ha and corresponded to the observed rates of erosion in Europe during extreme rain events. The presented methodology is useful in identifying the erosion vulnerable regions in a catchment where erosion control measures should be implemented.     

流域产沙量预测的神经网络模型

流域产沙量演变规律的研究对于工程设计、水土流失规划与治理具有重要作用。由于其影响因素多、演变过程复杂,目前,对流域产沙量的研究主要侧重于定性分析,这就造成了缺乏理论基础及精度不高的缺陷。人工神经网络能以非显式表示产沙量与其影响因素之间的非线性复杂关系,将其应用到流域产沙量的拟合与预测中,在改进BP网络不足及优化确定网络结构的基础上,建立了云南楚雄州龙川江流域产沙量预测模型,通过对预测样本的检验,表明其具有比较高的精度,基本能够反映龙川江流域产沙量的演变规律。     

基于栅格新安江模型的淮河上游土壤侵蚀预测

将栅格新安江模型与改进通用土壤侵蚀方程进行耦合,建立基于栅格尺度的水沙模拟模型,以淮河上游息县水文站以上为研究区域,基于研究流域DEM数据、土地利用数据、土壤数据以及息县站2000年-2010年水文数据,模拟了淮河上游2000年-2010年输沙过程。并基于构建的水沙模型,结合流域2020年和2030年土地利用远景规划数据设定两种土地利用模式情景,定量分析了不同土地利用模式情景对流域土壤侵蚀的影响。研究结果表明:基于栅格新安江模型的水沙耦合模型在淮河上游具有较好的模拟精度,模拟的输沙量相对误差小于15%,确定性系数0.6以上,满足泥沙模拟精度要求;林地用地面积增加5%,流域土壤侵蚀量减少8.78%,城镇用地面积增加8%,流域土壤侵蚀量减少12.73%。研究成果可为淮河水土保持治理和规划提供参考。     

Soil Erosion Assessment in a Hilly Catchment of North Eastern India Using USLE, GIS and Remote Sensing

In the present study, soil erosion assessment of Dikrong river basin of Arunachal Pradesh (India) was carried out. The river basin was divided into 200 × 200 m grid cells. The Arc Info 7.2 GIS software and RS (ERDAS IMAGINE 8.4 image processing software) provided spatial input data and the USLE was used to predict the spatial distribution of the average annual soil loss on grid basis. The average rainfall erositivity factor (R) for Dikrong river basin was found to be 1,894.6 MJ mm ha⁻¹ h⁻¹ year⁻¹. The soil erodibility factor (K) with a magnitude of 0.055 t ha h ha⁻¹ MJ⁻¹ mm⁻¹ is the highest, with 0.039 t ha h ha⁻¹ MJ⁻¹ mm⁻¹ is the least for the watershed. The highest and lowest value of slope length factor (LS) is 53.5 and 5.39 respectively for the watershed. The highest and lowest values of crop management factor (C) were found out to be 0.004 and 1.0 respectively for the watershed. The highest and lowest value of conservation factor (P) were found to be 1 and 0.28 respectively for the watershed. The average annual soil loss of the Dikrong river basin is 51 t ha⁻¹ year⁻¹. About 25.61% of the watershed area is found out to be under slight erosion class. Areas covered by moderate, high, very high, severe and very severe erosion potential zones are 26.51%, 17.87%, 13.74%, 2.39% and 13.88% respectively. Therefore, these areas need immediate attention from soil conservation point of view.     

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.     

Combination of Runoff Simulation with Sediment Modeling in Rivers and Its Application in the Lower Yellow River

Abstract

Previous research on runoff show flow and sediment movement in rivers, and river bed variations are usually separated. This paper, from the point of view of the basin as a whole system, presents an integrated approach by combining runoff simulation with numerical model of sediment transport in rivers to simulate the whole processes of hydrological variables and flow-caused bed variations from the very upper part of the basin to the river mouth. To accomplish this purpose, BTOPMC, a rainfall-runoff model, and NUSTM-1D, a well-developed numerical model for sediment transport and river bed variations, are selected to form a combined model. The application of the proposed model to the lower Yellow River shows that it can properly simulate rainfall-caused runoff, the change of suspended sediment concentration along the river, and river bed variation.     

基于径流侵蚀功率的流域次暴雨输沙模型研究——以岔巴沟流域为例

流域次暴雨侵蚀产沙模型研究是国内外土壤侵蚀研究的重点领域之一。提出了基于径流深和洪峰流量模数两个流域次暴雨洪水特征参数的径流侵蚀功率的概念;利用岔巴沟曹坪水文站1959至1990年间历年实测的次暴雨洪水径流泥沙资料,系统研究了该流域次暴雨径流侵蚀功率与流域输沙模数之间的相关关系,建立和验证了基于径流侵蚀功率的岔巴沟流域次暴雨输沙模型。结果表明,岔巴沟流域次暴雨径流侵蚀功率与流域输沙模数之间具有极显著的幂函数相关关系;模型验证期的次暴雨输沙模数模拟值与实测值之间具有较好的一致性。