北京市平原区小流域划分技术研究

流域是水利现代化管理与精细化管理的重要基础,小流域是对流域的进一步细化。本文首先阐述了小流域的概念,接着结合实际需求,分析讨论了北京市平原区内小流域划分技术及原则,最后对北京市平原区的小流域划分结果进行展示和讨论,并分析了小流域成果应用方向。     

基于DEM的不同地貌类型区小流域划分及分布特征研究——以贵州省赤水河流域为例

小流域已经成为水土流失治理、生态系统修复等研究工作的重要地理单元。本文以贵州省赤水河流域为研究对象,探索我国西南典型喀斯特与非喀斯特地貌混合分布区小流域划分方法及小流域分布特征,基于DEM提取小流域边界,利用1∶5万地形图进行修正,并结合野外调查和地质、水文数据验证,最终将贵州省赤水河流域划定了753个小流域。其中,喀斯特地貌区小流域个数358个,喀斯特+非喀斯特地貌区小流域个数182个,非喀斯特地貌区213个;就不同流域类型小流域划分结果看,完整型小流域530个,区间型小流域180个,坡面型小流域43个;这些小流域中面积小于3km²的有9个,面积在3～10km²的有310个,面积在10～30km²的有348个,面积在30～50km²的有86个。贵州省赤水河流域小流域划分研究可为小流域治理工作提供依据,为区域制定水土保持方案和生态建设措施提供辅助决策,促进喀斯特地区水土保持与生态环境建设。     

基于排水管网中心城区小流域划分方法研究

流域边界提取是流域精细化管理和分析的基础,由于平原河网区域地势平坦,地形的起伏较小,很难按照基于数字高程模型(DEM)提取流域边界。针对此技术问题,在梳理平原河网水系的基础上,提出利用排水管网的汇水特性辅助划分平原区小流域,可以解决平原区流域划分困难的问题,生成的小流域与实际情况比较接近。将此方法应用于北京市中心城区的小流域划分工作中,取得了较好的效果,为平原区流域划分提供了一个有效途径。     

基于Landsat TM/ETM+影像的面状水体特征研究——以巢湖流域面状水体为例

通过对研究区2001年10月和2007年1月Lnadsat TM/ETM+的遥感影像进行光谱特征分析,利用归一化差异水体指数(NDWI)、阈值法和谱间关系法提取研究区面状水体形态信息,在此基础上,利用分形几何理论计算不同时相巢湖流域研究区影像的各小流域面状水体的分形维数.结果表明,巢湖流域研究区各小流域面状水体明显具有分形特征,2007年各小流域面状水体的分维值相应都比2001年各小流域面状水体分维值有所降低.说明整个流域的面状水体的稳定性增大.反映了研究区人类工农业生产活动开始注重与周围地理环境的和谐发展.     

基于数字地形分析的小流域分割技术

小流域是具有相对完整自然生态过程的区域单元，适宜尺度的小流域可作为生态评价、地理过程的基本单元。基于数字地形分析技术的小流域分割技术，既是建立这种地学分析单元的关键技术，同时也实现了流域制图自动化。     

遥感技术在小流域水土流失快速调查中的应用——以老高川地区为例

以SPOT与TM融合图像为遥感信息源,对孤山川流域老高川地区进行1:5万比例尺水土流失遥感调查,分析了小流域水土流失的主要影响因素,指出了遥感技术与地理信息系统结合是遥感技术在小流域水土流失快速调查的发展方向.     

基于DEM的黄土小流域侵蚀监测与输沙过程模拟研究EI北大核心CSCD

黄土高原是地表物质交换最频繁、形态变化最剧烈的区域之一。小流域既是天然的地理单元,又是流域管理的基本单元,更是水沙治理等工程措施的重点试验单元。前人在黄土小流域侵蚀产沙机制与建模方面开展了一系列研究,但是受研究数据和方法的限制,目前仍没有提出一套从小流域侵蚀监测到反演输沙过程的方法体系。     

基于GIS的数字小流域系统设计与实践——以南小河沟数字小流域系统为例

以南小河沟数字小流域系统为例,介绍了基于GIS技术构建数字小流域系统的主要技术和方法。系统采用三层架构设计方法,在ArcGIS软件平台基础上,利用Visual Studio和JavaServer Pages进行二次开发,实现南小河沟数字小流域系统建设,将长期积累的各级各类数据进行充分整合和集成,将各类试验研究成果进行形象直观展示。数字小流域系统的建设,为进一步开展流域水土流失预测预报模型及水土保持综合治理效益分析评价模型研究奠定了坚实的基础。     

基于PostGIS的小流域数据库设计与应用研究

针对小流域数据种类多、数据量大的特点,利用PostgreSQL的空间扩展插件PostGIS实现对小流域的空间数据以及影像数据的存储与管理,并利用Python和JDBC技术实现对小流域基本属性数据及长时间序列的小流域降雨、径流数据的存储与管理。本文提出了对小流域不同数据类型数据存储的数据库设计思路,实现了小流域多类型数据的统一管理;同时,本文结合WebGIS技术发布相应的网络服务,实现数据的可视化以及管理应用。     

基于GIS与RS的中小流域洪水风险图研究

以苏鲁皖三省交界处的复新河流域为研究区,在多源数据集成与融合的基础上,利用GIS与RS技术分析了流域地形地貌,提取了水文模型参数,集成了洪水模拟,从而进行洪水淹没与影响分析,并对洪水模拟结果进行自动可视化处理与发布。系统地阐述了运用GIS与RS技术快速制作中小流域洪水风险图的关键技术,并构建了洪水风险可视化模型,可实现快速一体化成图,提高中小流域洪水风险图的动态适应性。     

Risk assessment of soil erosion in semi-arid mountainous watershed in Saudi Arabia by RUSLE model coupled with remote sensing and GIS

Soil erosion is the most important factor in land degradation and influences desertification in semi-arid areas. A comprehensive methodology that integrates revised universal soil loss equation (RUSLE) model and GIS was adopted to determine the soil erosion risk (SER) in semi-arid Aseer region, Saudi Arabia. Geoenvironmental factors viz. rainfall (R), soil erodibility (K), slope (LS), cover management and practice factors were computed to determine their effects on average annual soil loss. The high potential soil erosion, resulting from high denuded slope, devoid of vegetation cover and high intensity rainfall, is located towards the north western part of the study area. The analysis is investigated that the SER over the vegetation cover including dense vegetation, sparse vegetation and bushes increases with the higher altitude and higher slope angle. The erosion maps generated with RUSLE integrated with GIS can serve as effective inputs in deriving strategies for land planning/management in the environmentally sensitive mountainous areas.     

A comparative study of soil erosion modelling by MMF,USLE and RUSLE

The quantitative assessment of spatial soil erosion is valuable information to control the erosion. The study area in a part of Narmada river in central India is selected. The main objective is to assess and compare the results obtained from three soil erosion models using GIS platform. Variation in the rate of erosion of the three models is compared considering varying slope, soil and land use of the area. Three models selected are Morgan–Morgan–Finney (MMF), Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). The best fit or the most reliable model for the study area is selected after validation with the observed sedimentation data. The results give –39.45%, –9.60% and 4.80% difference in the values of sedimentation by MMF, USLE and RUSLE, respectively, from the observed data. Finally, RUSLE model has been found to be most reliable for the study area.     

Prediction of soil loss differences and sediment accumulation at the Nilufer creek watershed,Turkey, using multiyear satellite data in a GIS

This study integrates the RUSLE, remote sensing and GIS to assess soil loss and identify sensitive areas to soil erosion in the Nilufer creek watershed in Bursa province, Turkey. The annual average soil loss was generated separately for years 1984 and 2011, in order to expose possible soil loss differences occurred in 27 years. In addition, sediment accumulation and sediment yield of the studied watershed was also predicted and discussed. The results indicated that very severe erosion risk areas in 1984 was 13.4% of the area, but it was increased to 15.3% by the year 2011, which needs immediate attention from soil conservation point of view. Furthermore, the estimated annual sediment yield of the Nilufer creek watershed was increased from 903 to 979 Mg km^?2 y^?1 in 27 years period. The study also provides useful information for decision-makers and planners to take appropriate land management practices in the area.     

Estimating the rainfall erosivity for management planning in the Eastern Desert,Egypt

Soil erosion is one of the major causes of land degradation in arid areas. Soil erosion models, e.g. the revised universal soil loss equation (RUSLE), use arithmetical expressions to explore relationships among various processes occurring in the terrain. The established model includes soil parameters, slope, climate and human activities to estimate the water erosion rate and sediment yield. In this study, an approach was adopted to integrate RUSLE model and geographic information system to detect erosion vulnerability and determine the soil erosion risk in the study area. The study area is situated in the Eastern Desert, Egypt. Ground truth data were examined to represent two regions: Luxor-Suhag and Suhag–ElMinya. These regions are exampled by four dry valleys named Sannor, Tarfa, Asyut and Qena, which are planned for agricultural development. The results indicate high risk of water erosion and sediment load discharge into the cultivated land in Luxor–Suhag region. The other region of Suhag–ElMinya is moderately affected by water and sediment load discharge. A higher soil erosion rate was found in Qena wadi followed by Asyut, then Tarfa and Sannur, respectively.     

An integrated approach for prioritization of reservoir catchment using remote sensing and geographic information system techniques

This study is aimed at evolving a watershed prioritization of reservoir catchment based on vegetation, morphological and topographical parameters, and average annual soil loss using geographic information system (GIS) and remote sensing techniques. A large multipurpose river valley project, Upper Indravati reservoir, situated in the state of Orissa, India, has been chosen for the present work. Watershed prioritization is useful to soil conservationist and decision makers. This study integrates the watershed erosion response model (WERM) and universal soil loss equation (USLE) with a geographic information system (GIS) to estimate the erosion risk assessment parameters of the catchment. The total catchment is divided into 15 sub-watersheds. Various erosion risk parameters are determined for all the sub-watersheds separately. Average annual soil loss is also estimated for the sub-watersheds using USLE. The integrated effect of all these parameters is evaluated to recommend the priority rating of the watersheds for soil conservation planning.     

雅鲁藏布江中游流域水土流失动态变化

以雅鲁藏布江中游流域作为研究区域,运用遥感和地理信息系统技术对2000年、2005年、2009年3个时期的遥感影像处理并提取水土流失因子,通过转移概率矩阵对雅鲁藏布江中游流域的水土流失动态变化进行深入研究,并运用马尔科夫模型预测了2010年-2020年雅鲁藏布江中游流域水土流失变化情况。研究发现：2000年-2005年...     

Effect of cover management factor in quantification of soil loss: case study of Sungai Akah subwatershed,Baram River basin Sarawak,Malaysia

The present study evaluates the effectiveness and suitability of cover management factors (C factor) generated through different techniques like land use/land cover-based arbitrary value (C_LULC), Normalised Different Vegetation Index-based methods C_NDVI1 and C_NDVI2 and Modified Soil Adjusted Vegetation Index 2-based method (C_MSAVI2). The C factors generated using these four methods were tested in the calculation and assessment of annual average soil loss from an upland forested subwatershed in the Baram river basin using the Revised Universal Soil Loss Equation (RUSLE). The four cover management factor maps generated by this analysis show some variation among the results. The LULC method uses a single arbitrary value for each LULC type mapped in the subwatershed. The other three methods show a range of C values within each mapped LULC type. The effects of these variations were tested in the RUSLE by keeping the factors such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS) constant. The maximum annual average soil loss is 1191 t. ha^?1. y^?1 based on the C_LULC. Soil losses estimated with other three methods are very different compared to those estimated with the C_LULC method. The highest calculated soil loss values were 1832, 1674 and 1608 t. ha^?1. y^?1 in the study area based, respectively, on C_NDVI1, C_NDVI2 and C_MSAVI2 C factors. These maximum values represent the worst pixel scenario values of soil loss in the region. The statistical analysis performed indicates different relationship between the parameters and suggests the acceptance of the methodology based on C_NDVI2 for the study area, instead of a single value method such as C_LULC. Among the other two methods, the C_MSAVI2 was found to be more consistent than the C_NDVI1 method, but both methods lead to over-prediction of annual soil loss rate and therefore need to be reconsidered before applied in the RUSLE.     

基于GIS、RS的黄土高原USLE模型改进方法

结合地理信息系统技术、遥感技术,探讨美国通用土壤流失方程（USLE）在我国黄土高原土壤侵蚀产沙模型应用中的改进方法。USLE属于因子分析模型,由于USLE考虑因素全面,因子具有物理意义,形式简单,所用资料广泛,统一了土壤侵蚀模型形式,故在全世界得到了广泛应用。但是我国黄土高原地区土壤流失严重,影响流失的因素极其多样,使得USLE模型不能很好的应用于该地特殊的地理条件。基于此,采用GIS方法探讨USLE模型在黄土高原改进方法问题。     

长江上游小流域土壤侵蚀动态模拟与分析

以长江上游甘肃省尚沟流域为研究区,在遥感影像和GIS空间分析技术支撑下,根据USLE因子算法生成各因子栅格图,借助地图代数运算,估算了尚沟流域1998年和2004年的土壤侵蚀量,并对2004年土壤侵蚀与其环境背景因子进行叠加和空间统计分析。在此基础上,构建了与GIS软件平台集成的地理元胞自动机,模拟了该流域2004年、2010年和2020年土壤侵蚀空间演化情形。结果表明:研究区平均侵蚀量从1998年的6598.1t/km2下降到2004年的5923.3t/km2,侵蚀面积净减少172.3hm2,输沙量减少9.15×104t;1300～1400m的海拔高程带、25～35°坡度带、南坡和旱耕地是发生水土流失的主要区域;经模拟,2010年总侵蚀面积为93.49km2,侵蚀总量73.15×104t,侵蚀模数为5126t/km2,土壤侵蚀状况总体上将有所减缓。     

近30年来密云水库上游水土流失动态监测

使用修正的通用土壤流失方程RUSLE,综合考虑降雨、土壤可蚀性、地形、土地覆盖和水土保持措施等因素,计算得密云水库上游地区1990年、2000年和2008年3期的土壤侵蚀数据,并对土壤侵蚀变化结果及其原因进行分析,发现：①研究区近20年水土流失状况经历由加剧到减轻的过程,但总体来说是减轻的,1990～2008年减轻区面积和加剧区面积分别为3083．11km。和2287．71km2;②研究区水土流失变化的原因主要为以土地利用类型变化为特征的人为因素,降雨也有影响,而与坡度没有关系。