Flow network derivation from a high resolution DEM in a low relief,agrarian landscape

Digital flow networks derived from digital elevation models (DEMs) sensitively react to errors due to measurement, data processing and data representation. Since high‐resolution DEMs are increasingly used in geomorphological and hydrological research, automated and semi‐automated procedures to reduce the impact of such errors on flow networks are required. One such technique is stream‐carving, a hydrological conditioning technique to ensure drainage connectivity in DEMs towards the DEM edges. Here we test and modify a state‐of‐the‐art carving algorithm for flow network derivation in a low‐relief, agricultural landscape characterized by a large number of spurious, topographic depressions. Our results show that the investigated algorithm reconstructs a benchmark network insufficiently in terms of carving energy, distance and a topological network measure. The modification to the algorithm that performed best, combines the least‐cost auxiliary topography (LCAT) carving with a constrained breaching algorithm that explicitly takes automatically identified channel locations into account. We applied our methods to a low relief landscape, but the results can be transferred to flow network derivation of DEMs in moderate to mountainous relief in situations where the valley bottom is broad and flat and precise derivations of the flow networks are needed. Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluating preprocessing methods of digital elevation models for hydrological modelling

With the introduction of high‐resolution digital elevation models, it is possible to use digital terrain analysis to extract small streams. In order to map streams correctly, it is necessary to remove errors and artificial sinks in the digital elevation models. This step is known as preprocessing and will allow water to move across a digital landscape. However, new challenges are introduced with increasing resolution because the effect of anthropogenic artefacts such as road embankments and bridges increases with increased resolution. These are problematic during the preprocessing step because they are elevated above the surrounding landscape and act as artificial dams. The aims of this study were to evaluate the effect of different preprocessing methods such as breaching and filling on digital elevation models with different resolutions (2, 4, 8, and 16 m) and to evaluate which preprocessing methods most accurately route water across road impoundments at actual culvert locations. A unique dataset with over 30,000 field‐mapped road culverts was used to assess the accuracy of stream networks derived from digital elevation models using different preprocessing methods. Our results showed that the accuracy of stream networks increases with increasing resolution. Breaching created the most accurate stream networks on all resolutions, whereas filling was the least accurate. Burning streams from the topographic map across roads from the topographic map increased the accuracy for all methods and resolutions. In addition, the impact in terms of change in area and absolute volume between original and preprocessed digital elevation models was smaller for breaching than for filling. With the appropriate methods, it is possible to extract accurate stream networks from high‐resolution digital elevation models with extensive road networks, thus providing forest managers with stream networks that can be used when planning operations in wet areas or areas near streams to prevent rutting, sediment transport, and mercury export.     

Topographic structure from motion: a new development in photogrammetric measurement

The production of topographic datasets is of increasing interest and application throughout the geomorphic sciences, and river science is no exception. Consequently, a wide range of topographic measurement methods have evolved. Despite the range of available methods, the production of high resolution, high quality digital elevation models (DEMs) requires a significant investment in personnel time, hardware and/or software. However, image‐based methods such as digital photogrammetry have been decreasing in costs. Developed for the purpose of rapid, inexpensive and easy three‐dimensional surveys of buildings or small objects, the ‘structure from motion’ photogrammetric approach (SfM) is an image‐based method which could deliver a methodological leap if transferred to geomorphic applications, requires little training and is extremely inexpensive. Using an online SfM program, we created high‐resolution digital elevation models of a river environment from ordinary photographs produced from a workflow that takes advantage of free and open source software. This process reconstructs real world scenes from SfM algorithms based on the derived positions of the photographs in three‐dimensional space. The basic product of the SfM process is a point cloud of identifiable features present in the input photographs. This point cloud can be georeferenced from a small number of ground control points collected in the field or from measurements of camera positions at the time of image acquisition. The georeferenced point cloud can then be used to create a variety of digital elevation products. We examine the applicability of SfM in the Pedernales River in Texas (USA), where several hundred images taken from a hand‐held helikite are used to produce DEMs of the fluvial topographic environment. This test shows that SfM and low‐altitude platforms can produce point clouds with point densities comparable with airborne LiDAR, with horizontal and vertical precision in the centimeter range, and with very low capital and labor costs and low expertise levels. Copyright © 2012 John Wiley & Sons, Ltd.     

Efficient hybrid breaching‐filling sink removal methods for flow path enforcement in digital elevation models

Digital elevation models (DEMs) that are used in hydrological applications must be processed to remove sinks, mainly topographic depressions. Flow enforcement techniques include filling methods, which raise elevations within depressions, breaching, which carves channels through blockages, and hybrid methods. Despite previous research demonstrating the large impact to DEMs and subsequent analyses of depression filling, it is common practice apply this technique to flow enforcement. This is partly because of the greater efficiency of depression filling tools compared to breaching counterparts, which often limits breaching to applications of small‐ to moderate‐sized DEMs. A new hybrid flow enforcement algorithm is presented in this study. The method can be run in complete breaching, selective breaching (either breached or filled), or constrained breaching (partial breaching) modes, allowing for greater flexibility in how practitioners enforce continuous flow paths. Algorithm performance was tested with DEMs of varying topography, spatial extents, and resolution. The sites included three moderate sized DEMs (52 000 000 to 190 000 000 cells) and three massive DEMs of the Iberian Peninsula, and the Amazon and Nile River basins, the largest containing nearly one billion cells. In complete breaching mode, the new algorithm required 87% of the time needed by a filling method to process the test DEMs, while the selective breaching and constrained breaching modes, operating with maximum breach depth constraints, increased run times by 8% and 27% respectively. Therefore, the new algorithm offers comparable performance to filling and the ability to process massive topographic data sets, while giving practitioners greater flexibility and lowering DEM impact. Copyright © 2015 John Wiley & Sons, Ltd.     

Quantification of braided river channel change using archival digital image analysis

Historical archives of grey‐scale river channel imagery are extensive. Here, we present and test a methodology to extract detailed quantitative topographic data from such imagery of sand‐bed rivers. Extracting elevation information from rivers is difficult as they are characterized by a low relative relief (<4 m); the area of interest may be spatially extensive (e.g. active channel widths >500 m in large braided rivers); the rate of change of surface elevation is generally low except in the vicinity of individual channel banks where the rate of change is very high; there is the complication that comes from inundation; and there may be an added complication caused by blockage of the field of view by vegetation. Here, we couple archival photogrammetric techniques with image processing methods and test these for quantification of sand‐bed braided river dynamics, illustrated for a 500 m wide, 3 km long reach of the South Saskatchewan River, Canada. Digital photogrammetry was used to quantify dry areas and water edge elevations. A methodology was then used to calibrate the spectral signature of inundated areas by combining established two media digital photogrammetric methods and image matching. This allowed determination of detailed depth maps for inundated areas and, when combined with dry area data, creation of complete digital elevation models. Error propagation methods were used to determine the erosion and deposition depths detectable from sequential digital elevation models. The result was a series of elevation models that demonstrate the potential for acquiring detailed and precise elevation data from any historical aerial imagery of rivers without needing associated calibration data, provided that imagery is of the necessary scale to capture the features of interest. We use these data to highlight several aspects of channel change on the South Saskatchewan River, including bar movement, bank erosion and channel infilling. Copyright © 2010 John Wiley & Sons, Ltd.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

无线数字遥测地震台网的信道测试

在无线数字遥测地震台网中,信道测试是台网传输的关键环节,关系到台网的运行率和地震信号的可用率,甚至整个台网建设的成败。信道测试有3方面的内容:中继站背景场强测试、子台信道储备测试和信道误码测试。经测试后得到各种参数柱状图,以此判断每个台站的信道质量情况,及时调整台网信道传输的设计方案,确保成功建成无线数字遥测地震台网。     

A combined algorithm for automated drainage network extraction from digital elevation models

Drainage networks are the basis for segmentation of watersheds, an essential component in hydrological modelling, biogeochemical applications, and resource management plans. With the rapidly increasing availability of topographic information as digital elevation models (DEMs), there have been many studies on DEM‐based drainage network extraction algorithms. Most of traditional drainage network extraction methods require preprocessing of the DEM in order to remove “spurious” sink, which can cause unrealistic results due to removal of real sinks as well. The least cost path (LCP) algorithm can deal with flow routing over sinks without altering data. However, the existing LCP implementations can only simulate either single flow direction or multiple flow direction over terrain surfaces. Nevertheless, terrain surfaces in the real world are usually very complicated including both convergent and divergent flow patterns. The triangular form‐based multiple flow (TFM) algorithm, one of the traditional drainage network extraction methods, can estimate both single flow and multiple flow patterns. Thus, in this paper, it is proposed to combine the advantages of the LCP algorithm and the TFM algorithm in order to improve the accuracy of drainage network extraction from the DEM. The proposed algorithm is evaluated by implementing a data‐independent assessment method based on four mathematical surfaces and validated against “true” stream networks from aerial photograph, respectively. The results show that when compared with other commonly used algorithms, the new algorithm provides better flow estimation and is able to estimate both convergent and divergent flow patterns well regarding the mathematical surfaces and the real‐world DEM.     

Spectral filtering as a method of visualising and removing striped artefacts in digital elevation data

Spectral filtering was compared with traditional mean spatial filters to assess their ability to identify and remove striped artefacts in digital elevation data. The techniques were applied to two datasets: a 100 m contour derived digital elevation model (DEM) of southern Norway and a 2 m LiDAR DSM of the Lake District, UK. Both datasets contained diagonal data artefacts that were found to propagate into subsequent terrain analysis. Spectral filtering used fast Fourier transformation (FFT) frequency data to identify these data artefacts in both datasets. These were removed from the data by applying a cut filter, prior to the inverse transform. Spectral filtering showed considerable advantages over mean spatial filters, when both the absolute and spatial distribution of elevation changes made were examined. Elevation changes from the spectral filtering were restricted to frequencies removed by the cut filter, were small in magnitude and consequently avoided any global smoothing. Spectral filtering was found to avoid the smoothing of kernel based data editing, and provided a more informative measure of data artefacts present in the FFT frequency domain. Artefacts were found to be heterogeneous through the surfaces, a result of their strong correlations with spatially autocorrelated variables: landcover and landsurface geometry. Spectral filtering performed better on the 100 m DEM, where signal and artefact were clearly distinguishable in the frequency data. Spectrally filtered digital elevation datasets were found to provide a superior and more precise representation of the landsurface and be a more appropriate dataset for any subsequent geomorphological applications. Copyright © 2007 John Wiley & Sons, Ltd.     

Suitability of LiDAR point density and derived landform curvature maps for channel network extraction

This study uses landform curvature as an approach for channel network extraction. We considered a study area located in the eastern Italian Alps where a high‐quality set of LiDAR data was available and where channel heads and related channel network were mapped in the field. In the analysis, we derived 1‐m DTMs from different ground LiDAR point densities, and we used different smoothing factors for the landscape curvature calculation in order to test the suitability of the LiDAR point density and the derived curvature maps for the recognition of channel network. This methodology is based on threshold values of the curvature calculated as multiples (1–3 times) of the standard deviation of the curvature. Our analyses suggested that (i) the window size for curvature calculations has to be a function of the size of the features to be detected, (ii) a coarse ground LiDAR point density could be as useful as a finer one for the recognition of main channel network features and (iii) rougher curvature maps are not optimal as they do not explore a sufficient range at which features occur, while smoother curvature maps overcome this problem and are more appropriate for the extraction of surveyed channels. Copyright © 2010 John Wiley & Sons, Ltd.     

Smoothing of digital elevation models and the alteration of overland flow path length distributions

DEM smoothing is a common pre-processing technique used to remove undesirable roughness from a DEM. However, it is hypothesized that smoothing straightens and reduces the length of overland flow paths, which is an important factor controlling modelled time-to-peak flow. Currently, there is a lack of research comparing how different smoothing techniques alter the distribution of overland flow path length. Four low-pass filtering techniques were applied to three fine-resolution LiDAR DEMs of varying relief: the mean filter, the median filter, the Gaussian filter, and the feature-preserving DEM smoothing (FPDEMS) filter, each with different degrees of smoothing. Downslope-distance-to-stream distributions were then derived using D8 and D∞ flow directions and statistically compared to distributions derived from the unsmoothed DEM for each study site. The results indicate that the alteration of flow path length distributions as a result of smoothing is complex. Mean flow path lengths may decrease or increase in response to smoothing, depending on landscape relief and the derivation of flow directions, and generalized flow paths may become longer. The largest increase in mean flow path lengths was 19.2 m using the 21 × 21 median filter and D8 flow directions in the high-relief study site, relative to an unsmoothed mean length of 138.6 m in this site. The largest decrease in mean flow path length was 48.9 m using the 21 × 21 mean filter and D∞ flow directions in the low-relief study site, relative to an unsmoothed mean length of 290.9 m in this site. Furthermore, minimal flow path length alterations were achieved with the Gaussian filter when gentle smoothing is required, and with the FPDEMS filter when moderate to aggressive smoothing is required. These results suggest that an appropriate smoothing method should be chosen based on the relief of the landscape and the degree of smoothing required.     

广西"十五"数字测震台网信道建设与系统集成

通过实施广西"十五"数字测震台网建设项目,在保证地震速报能力的前提下,根据广西区域数字测震台的布局,合理选择台站不同数据传输模式和台网集成方案,以取得系统的优良性价比.     

A comparision of interpolation methods for producing digital elevation models at the field scale

Digital elevation models have been used in many applications since they came into use in the late 1950s. It is an essential tool for applications that are concerned with the Earth's surface such as hydrology, geology, cartography, geomorphology, engineering applications, landscape architecture and so on. However, there are some differences in assessing the accuracy of digital elevation models for specific applications. Different applications require different levels of accuracy from digital elevation models. In this study, the magnitudes and spatial patterning of elevation errors were therefore examined, using different interpolation methods. Measurements were performed with theodolite and levelling. Previous research has demonstrated the effects of interpolation methods and the nature of errors in digital elevation models obtained with indirect survey methods for small‐scale areas. The purpose of this study was therefore to investigate the size and spatial patterning of errors in digital elevation models obtained with direct survey methods for large‐scale areas, comparing Inverse Distance Weighting, Radial Basis Functions and Kriging interpolation methods to generate digital elevation models. The study is important because it shows how the accuracy of the digital elevation model is related to data density and the interpolation algorithm used. Cross validation, split‐sample and jack‐knifing validation methods were used to evaluate the errors. Global and local spatial auto‐correlation indices were then used to examine the error clustering. Finally, slope and curvature parameters of the area were modelled depending on the error residuals using ordinary least regression analyses. In this case, the best results were obtained using the thin plate spline algorithm. Copyright © 2009 John Wiley & Sons, Ltd.     

Investigating the linkage between streamflow recession rates and channel network contraction in a mesoscale catchment in New York state

The rate of recession (dQ/dt) in a given time interval has long been plotted in log–log space against the concurrent mean discharge (Q_avg). Recent interpretations of these dQ/dt–Q_avg plots have sought to look at curves for individual events instead of the data cloud from all the data points together. These individual recession curves have been observed to have near‐constant slope but to have varying intercepts, features hypothesized to possibly be explained by the nature of the contraction of the active channel network during recession. For a steep, 150‐ha forested catchment in central New York state with an 8.8‐km channel network, changes in the active channel network were mapped between April and November 2013. Streamflow recession occurred in a matter of days, but changes in the active channel network occurred over a matter of weeks. Thus, in this catchment, it does not appear that channel contraction directly controls recession. Additionally, field observations indicate that dry down did not occur in a spatially organized, sequential way such that the upper end of higher‐order streams dried first. Instead, the location of groundwater seeps, in part, controlled the active portion of the channel network. Consistent with the presence of different types of flow contributing zones, the paper presents a conceptual model that consists of multiple parallel reservoirs of varying drainage rate and varying degrees of recharge at different times of the year. This conceptual model is able to reproduce a slope of 2 and a seasonal shift in intercept typical of individual recession curves. Copyright © 2015 John Wiley & Sons, Ltd.     

A qualitative and quantitative evaluation of experimental model catchment evolution

Due to the geological time scales required for observation of catchment evolution, surrogates or analogues of field data are necessary to understand long‐term processes. To investigate long‐term catchment behaviour, two experimental model catchments that developed without rigid boundaries under controlled conditions are examined and a qualitative and quantitative analysis of their evolution is presented. Qualitatively, the experimental catchments have the visual appearance of field scale data. Observation demonstrates that changes in catchment shape and network form are conservative. Quantitative analysis suggests that the catchments reach an equilibrium form while a reduction in the channel network occurs. While the catchments are laboratory scale models, the results provide insights into field scale behaviour. Copyright © 2003 John Wiley & Sons, Ltd.     

Variable hillslope-channel coupling and channel characteristics of forested mountain streams in glaciated landscapes

Channel morphology of forested, mountain streams in glaciated landscapes is regulated by a complex suite of processes, and remains difficult to predict. Here, we analyze models of channel geometry against a comprehensive field dataset collected in two previously glaciated basins in Haida Gwaii, B.C., to explore the influence of variable hillslope–channel coupling imposed by the glacial legacy on channel form. Our objective is to better understand the relation between hillslope–channel coupling and stream character within glaciated basins. We find that the glacial legacy on landscape structure is characterized by relatively large spatial variation in hillslope–channel coupling. Spatial differences in coupling influence the frequency and magnitude of coarse sediment and woody material delivery to the channel network. Analyses using a model for channel gradient and multiple models for width and depth show that hillslope–channel coupling and high wood loading induce deviations from standard downstream predictions for all three variables in the study basins. Examination of model residuals using Boosted Regression Trees and nine additional channel variables indicates that ~10 to ~40% of residual variance can be explained by logjam variables, ~15–40% by the degree of hillslope–channel coupling, and 10–20% by proximity to slope failures. These results indicate that channel classification systems incorporating hillslope–channel coupling, and, indirectly, the catchment glacial legacy, may present a more complete understanding of mountain channels. From these results, we propose a conceptual framework which describes the linkages between landscape history, hillslope–channel coupling, and channel form. © 2018 John Wiley & Sons, Ltd.     

Determination of the drainage structure of a watershed using a digital elevation model and a digital river and lake network

Distributed hydrological models require a detailed definition of a watershed's internal drainage structure. The conventional approach to obtain this drainage structure is to use an eight flow direction matrix (D8) which is derived from a raster digital elevation model (DEM). However, this approach leads to a rather coarse drainage structure when monitoring or gauging stations need to be accurately located within a watershed. This is largely due to limitations of the D8 approach and the lack of information over flat areas and pits. The D8 approach alone is also unable to differentiate lakes from plain areas.

To avoid these problems a new approach, using a digital river and lake network (DRLN) as input in addition to the DEM, has been developed. This new approach allows for an accurate fit between the DRLN and the modelled drainage structure, which is represented by a flow direction matrix and a modelled watercourse network. More importantly, the identification of lakes within the modelled network is now possible. The proposed approach, which is largely rooted in the D8 approach, uses the DRLN to correct modelled flow directions and network calculations. For DEM cells overlapped by the DRLN, flow directions are determined using DRLN connections only. The flow directions of the other DEM cells are evaluated with the D8 approach which uses a DEM that has been modified as a function of distance to the DRLN.

The proposed approach has been tested on the Chaudière River watershed in southern Québec, Canada. The modelled watershed drainage structure showed a high level of coherence with the DRLN. A comparison between the results obtained with the D8 approach and those obtained by the proposed approach clearly demonstrated an improvement over the conventionally modelled drainage structure. The proposed approach will benefit hydrological models which require data such as a flow direction matrix, a river and lake network and sub-watersheds for drainage structure information.