河道糙率系数变化对全新世古洪水流量计算的影响研究

洪水流量计算中河道糙率是一个重要的灵敏度参数。以汉江上游郧县尚家河台地前沿记录的四期古洪水流量计算为例,研究河道糙率系数在比降-面积法和HEC-RAS模型中对古洪水流量计算结果的影响。结果表明：其他水文参数一定时,河道糙率系数以±15%变幅,比降-面积法重建的古洪水流量变幅在-13.04%～17.65%,HEC-RAS模型计算的流量变幅在-4.32%～4.57%;若河道糙率系数以±25%变幅,比降-面积法和HEC-RAS模型计算的流量变幅分别为-20%～33.33%和-7.79%～9.18%,说明采用HEC-RAS模型重建古洪水流量,可减少河道糙率系数对计算结果的影响,使古洪水流量计算结果更为可靠。此外,假定其他参数不变,主河槽和左、右岸糙率系数依次变幅±25%,主河槽糙率系数变化对流量计算结果影响最大,说明洪水流量计算时应准确选取主河槽的糙率系数。该结果对水利工程建设具有重要的现实意义。     

Effects of DEM resolution and source on soil erosion modelling: a case study using the WEPP model

Digital elevation models (DEMs) vary in resolution and accuracy by the production method. DEMs with different resolutions and accuracies can generate varied topographic and hydrological features, which can in turn affect predictions by soil erosion models, such as the WEPP (Water Erosion Prediction Project) model. This study investigates the effects of DEMs on deriving topographic and hydrological attributes, and on predicting watershed erosion using WEPP v2006.5. Six DEMs at three resolutions from three sources were prepared for two small forested watersheds located in northern Idaho, USA. These DEMs were used to calculate topographic and hydrological parameters that served as inputs to WEPP. The model results of sediment yields and runoffs were compared with field observations. For both watersheds, DEMs with different resolutions and sources generated varied watershed shapes and structures, which in turn led to different extracted hill slope and channel lengths and gradients, and produced substantially different erosion predictions by WEPP.     

黄土丘陵沟壑区地形定量因子的关联性分析

不同地形因子虽然在语义概念、计算方法等方面均有明显的差异,但各地形因子之间并不是绝对孤立的,它们之间相互关联、相互影响。这种关联的强弱与趋势,都从不同角度揭示着地形起伏变化与地貌发育的本质及内在规律,同时,还在一定程度上映射着地表形态的发育过程。文章以黄土高原丘陵沟壑区的15个样本地区为实验样区,以高分辨率、高精度的1:1万比例尺DEM为基础数据,应用BP神经网络模型,探讨地形定量因子与地面坡度之间的关联性特征,并将神经网络的方法与传统的多元回归方法进行比较。结果表明,相对于传统的多元回归方法,带隐含层的BP神经网络分析方法能更为有效地反映地形因子间隐含的关联特征。该研究方法为进行地貌多定量指标的的选择和多因子之间关联性的量化提供了一种新的方法。     

Hillslope-to-valley transition morphology: New opportunities from high resolution DTMs

The search for the optimal spatial scale for observing landforms to understand physical processes is a fundamental issue in geomorphology. Topographic attributes derived from Digital Terrain Models (DTMs) such as slope, curvature and drainage area provide a basis for topographic analyses. The slope–area relationship has been used to distinguish diffusive (hillslope) from linear (valley) processes, and to infer dominant sediment transport processes. In addition, curvature is also useful in distinguishing the dominant landform process. Recent topographic survey techniques such as LiDAR have permitted detailed topographic analysis by providing high-quality DTMs. This study uses LiDAR-derived DTMs with a spatial scale between 1 and 30 m in order to find the optimal scale for observation of dominant landform processes in a headwater basin in the eastern Italian Alps where shallow landsliding and debris flows are dominant. The analysis considered the scaling regimes of local slope versus drainage area, the spatial distribution of curvature, and field observations of channel head locations. The results indicate that: i) hillslope-to-valley transitions in slope–area diagrams become clearer as the DTM grid size decreases due to the better representation of hillslope morphology, and the topographic signature of valley incision by debris flows and landslides is also best displayed with finer DTMs; ii) regarding the channel head distribution in the slope–area diagrams, the scaling regimes of local slope versus drainage area obtained with grid sizes of 1, 3, and 5 m are more consistent with field data; and iii) the use of thresholds of standard deviation of curvature, particularly at the finest grid size, were proven as a useful and objective methodology for recognizing hollows and related channel heads.     

Assessment of downstream trends in channel gradient, total and specific stream power: a GIS approach

Geographic Information Systems (GIS) analyses of Digital Elevation Models (DEMs) coupled with catchment area based discharge estimation techniques provide a relatively simple means of modelling contiguous downstream trends in channel gradient, total stream power, and in riverscapes conducive to regime analysis, also specific stream power. For a small, high relief, coastal catchment in SE Australia, good agreement was obtained between channel gradients derived from a 25 m cell-size DEM and field survey equivalents over distances of several kilometres, indicating that channel gradients derived from DEMs can have a reasonable degree of absolute as well as relative accuracy over multi-kilometre reach scales. Assessment of downstream rates of change in channel gradient and specific stream power across four river systems suggests that some of the river reaches most responsive to high magnitude floods occur in zones where these variables rapidly decrease downstream. Modelling of downstream trends in channel gradient, total and specific stream power from catchment-wide DEMs has potential to provide a framework with which to investigate conceptual and empirical models between channel gradient, stream power and the form and dynamics of river systems.     

Propagation of vertical and horizontal source data errors into a TIN with linear interpolation

Digital elevation models (DEMs) have been widely used for a range of applications and form the basis of many GIS-related tasks. An essential aspect of a DEM is its accuracy, which depends on a variety of factors, such as source data quality, interpolation methods, data sampling density and the surface topographical characteristics. In recent years, point measurements acquired directly from land surveying such as differential global positioning system and light detection and ranging have become increasingly popular. These topographical data points can be used as the source data for the creation of DEMs at a local or regional scale. The errors in point measurements can be estimated in some cases. The focus of this article is on how the errors in the source data propagate into DEMs. The interpolation method considered is a triangulated irregular network (TIN) with linear interpolation. Both horizontal and vertical errors in source data points are considered in this study. An analytical method is derived for the error propagation into any particular point of interest within a TIN model. The solution is validated using Monte Carlo simulations and survey data obtained from a terrestrial laser scanner.     

Scaling in river corridor widths depicts organization in valley morphology

Landscapes have been shown to exhibit numerous scaling laws from Horton's laws to more sophisticated scaling in topography heights, river network topology and power laws in several geomorphic attributes. In this paper, we propose a different way of examining landscape organization by introducing the “river corridor width” (lateral distance from the centerline of the river to the left and right valley walls at a fixed height above the water surface) as one moves downstream. We establish that the river corridor width series, extracted from 1 m LIDAR topography of a mountainous river, exhibit a rich multiscale statistical structure (anomalous scaling) which varies distinctly across physical boundaries, e.g., bedrock versus alluvial valleys. We postulate that such an analysis, in conjunction with field observations and physical modeling, has the potential to quantitatively relate mechanistic laws of valley formation to the statistical signature that underlying processes leave on the landscape. Such relations can be useful in guiding field work (by identifying physically distinct regimes from statistically distinct regimes) and advancing process understanding and hypothesis testing.     

A study on DEM-derived primary topographic attributes for hydrologic applications: Sensitivity to elevation data resolution

Primary topographic attributes play a critical role in determining watershed hydrologic characteristics for water resources modeling with raster-based digital elevation models (DEM). The effects of DEM resolution on a set of important topographic derivatives are examined in this study, including slope, upslope contributing area, flow length and watershed area. The focus of the study is on how sensitive each of the attributes is to the resolution uncertainty by considering the effects of overall terrain gradient and bias from resampling. Two case study watersheds of different gradient patterns are used with their 10 m USGS DEMs. A series of DEMs up to 200 m grid size are produced from the base DEMs using three commonly used resampling methods. All the terrain variables tested vary with the grid size change. It is found that slope angles decrease and contributing area values increase constantly as DEMs are aggregated progressively to coarser resolutions. No systematic trend is observed for corresponding changes of flow path and watershed area. The analysis also suggests that gradient profile of the watershed presents an important factor for the examined sensitivities to DEM resolution.     

基于不同DEM数据源的数字河网提取对比分析——以韩江流域为例

基于HYDRO1K、SRTM3和ASTER GDEM三种DEM数据,利用BTOPMC地形子模型提取韩江流域河网,并作对比分析。结果表明:①SRTM3提取的河网精度最高,HYDRO1K相对最低。②DEM的垂直精度对提取的河网精度起控制作用。ASTER GDEM的水平分辨率较高,但垂直精度不如SRTM3,因而提取的河网精度不如SRTM3。③HYDRO1K提取大尺度流域河网具有一定的精度,但在地势平坦区域的效果较差,HY-DRO1K不宜用来提取小尺度流域河网。④由DEM提取的数字河网精度与当地的地面坡度以及处理DEM的填洼算法有关。     

Geomorphometric feature analysis using morphometric parameterization and artificial neural networks

This paper presents a semi-automatic method using an unsupervised neural network to analyze geomorphometric features as landform elements. The Shuttle Radar Topography Mission (SRTM) provided detailed digital elevation models (DEMs) for all land masses between 60°N and 57°S. Exploiting these data for recognition and extraction of geomorphometric features is a challenging task. Results obtained with two methods, Wood's morphometric parameterization and the Self Organizing Map (SOM), are presented in this paper.Four morphometric parameters (slope, minimum curvature, maximum curvature and cross-sectional curvature) were derived by fitting a bivariate quadratic surface with a window size of 5 by 5 to the SRTM DEM. These parameters were then used as input to the two methods. Wood's morphometric parameterization provides point-based features (peak, pit and pass), line-based features (channel and ridge) and area-based features (planar). Since point-based features are defined as having a very small slope when their neighbors are considered, two tolerance values (slope tolerance and curvature tolerance) are introduced. Selection of suitable values for the tolerance parameters is crucial for obtaining useful results.The SOM as an unsupervised neural network algorithm is employed for the classification of the same morphometric parameters into ten classes characterized by morphometric position (crest, channel, ridge and plan area) subdivided by slope ranges. These terrain features are generic landform element and can be used to improve mapping and modeling of soils, vegetation, and land use, as well as ecological, hydrological and geomorphological features. These landform elements are the smallest homogeneous divisions of the land surface at the given resolution. The result showed that the SOM is an efficient scalable tool for analyzing geomorphometric features as meaningful landform elements, and uses the full potential of morphometric characteristics.     

Methodological sensitivity of morphometric estimates of coarse fluvial sediment transport

The estimation of fluvial sediment transport rate from measurements of morphological change has received growing recent interest. The revival of the ‘morphological method’ reflects continuing concern over traditional methods of rate determination but also the availability of new survey methods capable of high-precision, high-resolution topographic monitoring. Remote sensing of river channels through aerial digital photogrammetry is a potentially attractive alternative to labour intensive ground surveys. However, while photogrammetry presents the opportunity to acquire survey data over large areas, data precision and accuracy, particularly in the vertical dimension are lower than in traditional ground survey methods. This paper presents results of recent research in which digital elevation models (DEMs) have been developed for a reach of a large braided gravel-bed river in Scotland using both digital photogrammetry and high-resolution RTK GPS ground surveys. A statistical level of change detection is assessed by comparing surfaces with independent check points. The methodological sensitivity of the annual channel sediment budget (1999–2000) to the threshold is presented. Results suggest that while the remote survey methods employed here can be used to develop qualitatively convincing, moderate precision DEMs of channel topography (RMSE=±0.21 m), the remaining errors imply significant limits on reliable change detection which lead to important information losses. Tests at a 95% confidence interval for change detection show that over 60% of channel deposition and 40% of erosion may be obscured by the lower level of precision associated with photogrammetric monitoring when compared to ground survey measurements. This bias reflects the difficulty of detecting the topographic signature of widespread, but shallow deposition on bar tops.     

Sediment flux in a small gravel-bed stream: Response to channel remediation works

Abstract:  Sediment transfers in a short reach of the Kiwitea Stream, near Fielding, lower North Island, New Zealand, are assessed using morphological budgeting based on repeat digital elevation model (DEM) differencing. Field data were acquired using high-precision GPS in October 2004, May and November 2005. Two interpolation methods to construct DEMs were compared. Universal kriging and Triangulation with Linear Interpolation produced consistent results and mean errors of between 4 and 14 mm. DEM error increases where relief changes rapidly. Sediment transfers are derived only from the low-relief active channel and indicate a rapidly changing environment. Remediation works following 2004 flood impacts have reduced bank erosion. A highly mobile bed renders the channel system sensitive to small and frequent flood events.     

Parallel identification and filling of depressions in raster digital elevation models

With the increasing sizes of digital elevation models (DEMs), there is a growing need to design parallel schemes for existing sequential algorithms that identify and fill depressions in raster DEMs. The Priority-Flood algorithm is the fastest sequential algorithm in the literature for depression identification and filling of raster DEMs, but it has had no parallel implementation since it was proposed approximately a decade ago. A parallel Priority-Flood algorithm based on the fastest sequential variant is proposed in this study. The algorithm partitions a DEM into stripes, processes each stripe using the sequential variant in many rounds, and progressively identifies more slope cells that are misidentified as depression cells in previous rounds. Both Open Multi-Processing (OpenMP)- and Message Passing Interface (MPI)-based implementations are presented. The speed-up ratios of the OpenMP-based implementation over the sequential algorithm are greater than four for all tested DEMs with eight computing threads. The mean speed-up ratio of our MPI-based implementation is greater than eight over TauDEM, which is a widely used MPI-based library for hydrologic information extraction. The speed-up ratios of our MPI-based implementation generally become larger with more computing nodes. This study shows that the Priority-Flood algorithm can be implemented in parallel, which makes it an ideal algorithm for depression identification and filling on both single computers and computer clusters.     

不同分辨率DEM提取地面坡度的不确定性模拟:以在黄土高原的试验为例

Slope is one of the crucial terrain variables in spatial analysis and land use planning,especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas,but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Simulation on slope uncertainty derived from DEMs at different resolution levels： a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as(0.0015S2 0.031S-0.0325)X-0.0045S2-0.155S 0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Simulation on slope uncertainty derived from DEMs at different resolution levels: a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

融合多源数字信息的流域水系提取方法研究

由于DEM数据不包括河流、湖泊(水库)及流域边界和堤坝等信息,因此常规仅依靠DEM提取水系的方法不能反映平坦区域及受人类影响强烈区域水系的真实特征。该文建立了融合DEM、河流、湖泊水库、流域边界和堤坝等多源数字信息的流域水系提取方法,对多源信息进行栅格化,采用所提出的高程-距离函数对DEM进行校正,使得提取的数字水系与实际水系精确拟合。将该方法应用于山区太湖西苕溪流域老石坎水库及其上游集水区和平原丘陵分布区的淮河史灌河蒋家集站、梅山、鲇鱼山水库区间流域,提取的河网结构与地图信息拟合较好。     

Analysis of geomorphological conditions for primary streams formation using digital elevation models

A key question of structural-hydrographic analysis of river systems is considered, namely: Is it possible to sufficiently rigorously determine the geomorphological situation that is responsible for the formation of the primary element of the hydrographic network? The objective of this study is to develop an optimal technique for automatic digitizing of the river network in terms of digital elevation models on the basis of searching for an optimal form of the index permitting a separate parameterization of the climatic and geomorphological conditions of the basins. A comparative testing is made of the use of the different variants of the index in the digitizing process as well as analyzing the “slope-area” relations for landscape-hydrological localities.     

Dealing with double vagueness in DEM morphometric analysis

A method is presented to explicitly incorporate spatial and scale vagueness – double vagueness – into geomorphometric analyses. Known limitations of usual practices include using a single fixed set of crisp thresholds for morphometric classification and the imposition of a single arbitrary number of scales of analysis to the entire digital elevation model (DEM). Among the advantages of the proposed method are: fuzzification of morphometric classification rules, scale-dependent adaptive fuzzy set parametrization and an objective definition of maximum scale of analysis on a cell-by-cell basis. The method was applied to several DEMs ranging from the ocean floor to surface landscapes of both Earth and Mars. The result was evaluated with respect to modal morphometric features and to characteristic scales, suggesting a more robust method for deriving both morphometric classifications and terrain attributes. We argue that the method would be preferable to any single-scale crisp approach, at least in the context of preliminary hands-off morphometric analyses of DEMs.