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.     

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.     

RUSLE2 Model Application for Soil Erosion Assessment Using Remote Sensing and GIS

The study is focused on the estimation of rate of soil erosion, using Revised Universal Soil Loss Eq. 2 (RUSLE2), in the Veppanapalli subwatershed of Krishnagiri catchment located in Tamil Nadu, India. The soil erosion is estimated for each of the hillslope units in the study area. The factors considered are intensity of rainfall, type of soil, land use classification and the existing soil conservation practices. Detailed analysis of soil samples were done to assess the texture, structure, permeability and organic matter content of the soil samples of each hillslope unit. The required data for the other parameters were estimated by carrying out intense field investigations and by the analysis of the satellite imagery of 5.6 m resolution. A data base was created with all the subfactor values for the hillslope units. Incorporation of remote sensing technique and Geographic Information System (GIS) made the spatial analysis of the study more reliable and accurate. The annual average soil erosion rate is estimated as 25 t/ha/year, which is on a higher range. This indicates the immediate need for the adoption of proper conservation strategies in this area to control the eutrophication in the Krishnagiri reservoir and to prevent further watershed degradation.     

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 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.     

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.     

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。     

三峡库区下岸溪小流域水土流失现状评估

 以三峡库区下岸溪小流域为研究区,在GIS软件的支持下,利用2008年SPOT5遥感影像和1∶5万DEM数据,提取坡度因子、植被覆盖度因子和土地利用类型因子作为水土流失风险评估指标因子,结合土壤侵蚀分级标准,生成研究区水土流失风险分级图,利用改进的工程侵蚀模数计算模型,对小流域土壤侵蚀量进行了估算。结果表明：①本流域以水力侵蚀为主,占研究区总面积的88.81%,其中中度侵蚀面积占该流域总面积的38.49%;②开矿等引起的工程侵蚀对该小流域土壤侵蚀量贡献率很大,占该流域水土流失量的41.43%。因此,在开矿和矿区基础设施建设等工程施工时,应采取有效的水土保持措施。     

基于地块间水沙运移的黄土丘陵沟壑区小流域侵蚀产沙模型

根据黄土丘陵沟壑区的侵蚀产沙规律，在晋西羊道沟小流域建立了坡面、沟坡和沟道侵蚀产沙子模型；在GIS的支持下计算出小流域地块间水沙汇流网络，并引入到小流域侵蚀产沙模型中，使小流域侵蚀产沙成为有机结合；模型对羊道沟22次侵蚀性降雨的侵蚀模数具有78．4％的预报精度，对羊道沟1956－1970的年侵蚀模数具有76．1％的预报精度；模型并通过了晋西汾河上游两个小流域的可移植性检验。     

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。     

Assessment of Groundwater Potential in a Semi-Arid Region of India Using Remote Sensing,GIS and MCDM Techniques

Remote sensing (RS) and geographic information system (GIS) are promising tools for efficient planning and management of vital groundwater resources, especially in data-scarce developing nations. In this study, a standard methodology is proposed to delineate groundwater potential zones using integrated RS, GIS and multi-criteria decision making (MCDM) techniques. The developed methodology is demonstrated by a case study in Udaipur district of Rajasthan, western India. Initially, ten thematic layers, viz., topographic elevation, land slope, geomorphology, geology, soil, pre- and post-monsoon groundwater depths, annual net recharge, annual rainfall, and proximity to surface water bodies were considered in this study. These thematic layers were scrutinized by principal component analysis technique to select influential layers for groundwater prospecting. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their relative importance in groundwater occurrence. The assigned weights of the thematic layers and their features were then normalized by using AHP (analytic hierarchy process) MCDM technique and eigenvector method. Finally, the selected thematic maps were integrated by weighted linear combination method in a GIS environment to generate a groundwater potential map. Thus, four groundwater potential zones were identified and demarcated in the study area, viz., ‘good’, ‘moderate’, ‘poor’ and ‘very poor’ based on groundwater potential index values. The area falling in the ‘good’ zone is about 2,113 km² (17% of the total study area), which encompasses major portions of Sarada, Salumber, Girwa, Dhariawad, and Mavli blocks of the study area. The northeast and southwest portions along with some scattered patches fall in the ‘moderate’ zone, which encompasses an area of 3,710 km² (about 29%). The ‘poor’ zone is dominant in the study area which covers an area of 4,599 km² (36% of the total area). The western portion and parts of eastern and southeast portions of the study area are characterized as having ‘very poor’ groundwater potential, and this zone covers an area of 2,273 km² (18%). Moreover, in the ‘good’ zone, the mean annually exploitable groundwater reserve is estimated at 0.026 million cubic metres per km² (MCM/km²), whereas it is 0.024 MCM/km² in the ‘moderate’ zone, 0.018 MCM/km² in the ‘poor’ zone, and 0.013 MCM/km² in the ‘very poor’ zone. The groundwater potential map was finally verified using the well yield data of 39 pumping wells, and the result was found satisfactory.     

基于RS和GIS肇东市生态环境质量综合评价

以2011遥感图像为主要数据源,借助于RS和GIS技术,构造以栅格数据为主多源空间信息,基于GIS空间叠加分析基础上,完成研究区域生态环境的综合评价。研究结果表明,旱地和草地两者比例之和为70.49%,表明旱地和草地是该区域土地利用的主要类型;研究区域生境较差的面积最大,生境一般的区域面积最小,仅为0.14%;研究区域整体生态环境质量不高,多数区域处于较差水平,该生境的评价结果与实际情况基本相符,但具有较高生态价值的林地和湿地对局部区域生态环境的改善具有很积极影响。     

基于GIS技术的贵州省土壤侵蚀危险性评价

针对目前喀斯特区土壤侵蚀潜在危险度研究相对薄弱的现状,以典型喀斯特区贵州省为研究对象,获取研究区土地利用类型、岩性、基岩裸露率等专题因子。基于地理信息系统(GIS)技术,在非喀斯特区和喀斯特区分别采用《土壤侵蚀分类分级标准》和《岩溶地区水土流失综合治理技术标准》解译出研究区土壤侵蚀强度等级分布图。并根据土壤允许流失量和土壤抗蚀年限,利用土壤侵蚀潜在危险度指数(SEPDI)对贵州省土壤侵蚀潜在危险度进行评价,为喀斯特区土壤侵蚀防治提供参考。结果显示:贵州省水土流失面积为47 831.73 km²,以轻度侵蚀为主,侵蚀模数为341 t/(km²·a),SEPDI为2.52,潜在危险等级较高。贵州25.3%行政村的SEPDI位于2~3之间,其中六盘水、黔西南市和毕节市危险度最高,建议将水土流失防治工作纳入SEPDI指标而非单从水土流失强弱等级进行治理,特别加强对SEPDI高但水土流失等级弱的区域的关注。     

长江流域水土流失健康状况评价方法初步研究

 从河流健康的角度出发,介绍了水土流失健康状况评价的单一指标法和综合指标体系法。基于单一指标法和综合指标体系法,并根据长江流域水土流失分区调查资料,对流域中8个片区的水土流失健康状况进行了初步评价。通过对这8个试验区水土流失健康指标的调查和计算,表明他们分别处于3种不同的阶段：3个处于相对稳定阶段(健康指数0.6～0.77);2个处于脆弱阶段;3个处于恶性循环阶段。这说明,长江流域中上游的水土流失情况是比较严峻的。     

Integrated Water Resource Development Plan for Sustainable Management of Mayurakshi Watershed, India using Remote Sensing and GIS

Integrated watershed management requires a host of inter-related information to be generated and studied in relation to each other. Remote sensing technique provides valuable and up-to-date spatial information on natural resources and physical terrain parameters. Geographical Information System (GIS) with its capability of integration and analysis of spatial, aspatial, multi-layered information obtained in a wide variety of formats both from remote sensing and other conventional sources has proved to be an effective tool in planning for watershed development. In this study, area and locale specific watershed development plans were generated for Mayurakshi watershed, India using remote sensing and GIS techniques. Adopting Integrated Mission for Sustainable Development (IMSD) guidelines, decision rules were framed. Using the overlay and decision tree concepts water resource development plan was generated. Indian Remote Sensing Satellite (IRS-1C), Linear Imaging Self Scanner (LISS-III) satellite data along with other field and collateral data on lithology, soil, slope, well inventory, fracture have been utilized for generating land use/land cover and hydro geomorphology of the study area, which are an essential prerequisites for water resources planning and development. Spatial data integration and analyses are carried out in GIS environment.     

基于“3S”技术的南京市水土流失定量监测及分析

为定期对南京市水土流失开展动态监测,利用降雨资料、土地利用资料、环境卫星遥感数据、土壤和地形数据,采用“监测水土流失的定量新方法”,计算2011—2015年南京市水土流失。结果表明:①2011—2015年5 a平均南京市水土流失总量为201.42万t,其中,轻度以上水土流失面积为515.75 km²,水土流失量166.77万t,占全市水土流失总量的82.8%,轻度以上水土流失治理仍是水土流失治理中的重点;②5 a中2015年水土流失最严重,2013年则最轻,其中降雨侵蚀力R_i大小为决定因素;③5 a平均极强烈与剧烈水土流失量为分级侵蚀量中最大;④与2001—2010年10 a平均相比,2011—2015年5 a平均南京市微度水土流失面积增加7.6%,轻度以上水土流失面积减少42.5%,轻度以上年水土流失量减少23.7%,CP值的减小是2011—2015年5 a平均水土流失状况改善的主要原因;⑤3次水土流失定量监测表明,2011—2015年监测强烈、极强烈的水土流失面积和年水土流失量减幅下降,剧烈的水土流失面积和年水土流失量增大,主要原因是2011—2015年降雨侵蚀力R_i (5 a)平均值较大。研究成果为南京市水土保持规划和水土流失防治提供了重要的基础数据支撑和科学参考依据。     

Environmental Monitoring of Spatio-temporal Changes Using Remote Sensing and GIS in a Mediterranean Wetland of Northern Greece

Loss and degradation of terrestrial and aquatic habitats and degraded water quality are major environmental concerns worldwide. Especially wetlands are sensitive ecosystems that are subject to stress from human activities. Remote sensing techniques have been primarily used to generate information on land cover/use changes. Geographical Information Systems (GIS) and remote sensing can be used to provide a rapid or a large-scale understanding of lake change and in developing lake management strategies. The principal objectives of this study are to monitor and assess the spatial and temporal changes in land cover/use by using GIS, and to determine the main environmental factors affecting these changes. This paper presents a case study for the application of integrated remote sensing and GIS data for the classification and monitoring of the spatial and temporal changes in land use types. The study was conducted in a small natural wetland of Lake Cheimaditida, located in the East Mediterranean region of Northern Greece. Data analysis was conducted using GIS software. During the past several decades Lake Cheimaditida wetland has been influenced by many anthropogenic activities. The variables chosen for the assessment included condition of wetland and lake areas, present extent of wetlands relative to historic area, cover of natural habitat, wetland disturbances, etc. These variables address catchments properties that are important for maintaining and improving wetland habitats and water quality and assessment of trends useful for environmental monitoring. Land cover/land use patterns were assessed and compared using aerial photographs taken in 1945, 1969, 1982, and 1996. Over this period, reed beds enormously increased by 1,655.19%, while open-water areas and peat lands decreased by 74.05 and 99.5%, respectively. The significance of the changes in land cover distribution within the Lake Cheimaditida wetland are discussed in relation to the historical pattern of reed beds colonization, the importance of Phragmites australis in the process and the implications for strategic management of freshwater wetland resources.     

Unsteady Flow Simulation and Erosion Assessment in a Ditch Network of a Drained Peatland Forest Catchment in Eastern Finland

We developed and applied a computational model for simulating unsteady flow in a drainage network of a boreal forested peatland site. The input to the model was the hourly runoff produced by a hydrological model. The simulations of the flow in the ditch network were performed using an iterative procedure for solving the Saint-Venant equations that govern the flow in each of the network channels. These equations were solved separately for each ditch branch, and the flow depths at the junctions were corrected using the method of characteristics. The model was applied to the drainage network of a peatland catchment in Eastern Finland over a period of 15 months. Because flow resistance in the ditches depended strongly on flow conditions, flow resistance (Manning’s n) was introduced as a function of discharge. The model was calibrated and validated against field data and the simulation results were further applied to assess erosion risk. The highest risk of erosion occurred during long lasting flows induced by snowmelt at ditch sections with a steep slope and a large upstream area. These model results can aid in the design and siting of water protection measures within the drained area.     

Evaluating Flood Hazard for Land-Use Planning in Greater Dhaka of Bangladesh Using Remote Sensing and GIS Techniques

Floods are a common feature in rapidly urbanizing Dhaka and its adjoining areas. Though Greater Dhaka experiences flood almost in every year, flood management policies are mostly based on structural options including flood walls, dykes, embankments etc. Many shortcomings of the existing flood management systems are reported in numerous literatures. The objective of this paper is to assess flood hazard in Greater Dhaka for the historical flood event of 1998 using Synthetic Aperture Radar (SAR) data with GIS data. Flood-affected frequency and flood depth calculated from the multi-date SAR imageries were used as hydrologic parameters. Elevation heights, land cover classification, geomorphic division and drainage network data generated from optical remote sensing and analogue maps were used through GIS approach. Using a ranking matrix in three dimensional multiplication mode, flood hazard was assessed. All possible combination of flood hazard maps was prepared using land-cover, geomorphology and elevation heights for flood-affected frequency and floodwater depth. Using two hazard maps which produced the highest congruence for flood frequency and flood depth, a new flood hazard map was developed by considering the interactive effect of flood-affected frequency and floodwater depth, simultaneously. This new hazard map can provide more safety for flood countermeasures because pixels belonging to higher hazard degrees were increased due to the consideration of higher degrees of ranks. The estimation of flood hazard areas revealed that a major portion of Greater Dhaka comprised moderate to very high hazard zone. Only a little portion (8.04%) was found to be the least vulnerable to potential flood hazard. Conversely, 28.70% of Greater Dhaka was found within very high hazard zone. Based on this study, comprehensive flood hazard management strategies for land use planning decision were proposed for the efficient management of future flood disasters.     

Integrating Remote Sensing and GIS Techniques with Groundwater Flow Modeling for Assessment of Waterlogged Areas

False Colour Composites (FCC's) of IRS-1A LISS-II sensor pertaining to the dates 9th April 1989 and 7th December 1989 are used to delineate the pre-monsoon and post-monsoon surface waterlogged areas in a region around Habibpur sub-distributary bounded by Vaishali branch canal and Gandak river in North Bihar, India for the year 1989 using visual interpretation technique. Also, digital data of IRS-1C LISS-III sensor pertaining to the dates 7th December 1998 and 6th April 1999 are analyzed in a digital image processing software – ERDAS Imagine 8.3.1, to delineate the pre-monsoon and post-monsoon surface waterlogged areas for the year 1998–1999. Further, for the study area, the waterlogging conditions are delineated for the year 1991–1992 using the groundwater flow modeling software package, MODFLOW. The results obtained using satellite remote sensing data and groundwater flow modeling are integrated in a GIS environment in ERDAS Imagine for assessment of the waterlogging areas.