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.     

A comparison of hillslope drainage area estimation methods using high-resolution DEMs with implications for topographic studies of gullies

Topographic models provide a useful tool for understanding gully occurrence in the landscape but require reliable estimates of gully head drainage areas. Modern high-resolution topography data (collected using structure from motion photogrammetry or light detection and ranging) is increasingly used for topographic studies of gullies, but little work has been done to assess the variability of gully head drainage area estimates using different methods. This study evaluated alternative approaches to using high-resolution digital elevation models (DEMs) so that gully topographic models can be more readily applied to any area with suitably high-resolution data. Specifically, we investigated the impact of single- or multiple-direction flow routing algorithms, DEM hydrologic-enforcement procedures and spatial resolution on gully head drainage area estimation. We tested these methods on a 40 km² site centred on Weany Creek, a low-relief semi-arid landscape draining towards the Great Barrier Reef, Australia. Using a subroutine to separate gully heads into those with divergent or convergent flow patterns upslope, we found that divergent flow conditions occurred at half of 484 studied gullies. Drainage areas estimated by different flow routing algorithms were more variable in these divergent cases than for convergent cases. This variation caused a significant difference between topographic threshold parameters (slope b and intercept k) derived from single- or multiple-direction flow routing algorithms, respectively. Different methods of hydrologic enforcement (filling or breaching) also affected threshold analysis, resulting in estimates of the exponent b being ~188% higher if the DEM was filled than if breached. The testing of the methods to date indicates that a finer resolution (≤2 m) DEM and a multiple-direction flow routing algorithm achieve the most realistic drainage area estimates in low-relief landscapes. For Weany Creek we estimated threshold parameters k = 0.033 and b = 0.189, indicating that it is highly susceptible to gully erosion.     

The effects of topographic depressions on multiscale overland flow connectivity: A high‐resolution spatiotemporal pattern analysis approach based on connectivity statistics

In watershed modelling, the traditional practice of arbitrarily filling topographic depressions in digital elevation models has raised concerns. Advanced high‐resolution remote sensing techniques, including airborne scanning laser altimetry, can identify naturally occurring depressions that impact overland flow. In this study, we used an ensemble physical and statistical modelling approach, including a 2D hydraulic model and two‐point connectivity statistics, to quantify the effects of depressions on high‐resolution overland flow patterns across spatial scales and their temporal variations in single storm events. Computations for both models were implemented using graphic processing unit‐accelerated computing. The changes in connectivity statistics for overland flow patterns between airborne scanning laser altimetry‐derived digital elevation models with (original) and without (filled) depressions were used to represent the shifts of overland flow response to depressions. The results show that depressions can either decrease or increase (to a lesser degree and shorter duration) the probability that any two points (grid locations) are hydraulically connected by overland flow pathways. We used macro‐connectivity states (Φ) as a watershed‐specific indicator to describe the spatiotemporal thresholds of connectivity variability caused by depressions. Four states of Φ are identified in a studied watershed, and each state represents different magnitudes of connectivity and connectivity changes (caused by depressions). The magnitude of connectivity variability corresponds to the states of Φ, which depend on the topological relationship between depressions, the rising/recession limb, and the total rainfall amount in a storm event. In addition, spatial distributions of connectivity variability correlate with the density of depression locations and their physical structures, which cause changes in streamflow discharge magnitude. Therefore, this study suggests that depressions are “nontrivial” in watershed modelling, and their impacts on overland flow should not be neglected. Connectivity statistics at different spatial scales and time points within a watershed provide new insights for characterizing the distributed and accumulated effects of depressions on overland flow.     

A physically-based method for removing pits in digital elevation models

Spurious pits in digital elevation models (DEMs) are traditionally removed by filling depressions, often creating flat regions that lead to inaccurate estimation of landscape flow directions. In this study, a physical approach based on a simple landscape evolution model is proposed for DEM pit removal. This method, an alternative to traditional geometrical procedures, enforces more realistic slopes and flow directions on topography. The procedure is compared with the method most commonly used in the literature and distributed with commercial GIS software where, generally, elevations of a depression are increased up to the lowest value among neighbouring cells. Several tests are performed and parameters sensitivity is carried out in order to demonstrate the performance of the proposed model as compared to traditional methods.     

A new depression‐dominated delineation (D‐cubed) method for improved watershed modelling

Prior to hydrologic modelling, topographic features of a surface are derived, and the surface is divided into sub‐basins. Surface delineation can be described as a procedure, which leads to the quantitative rendition of surface topography. Different approaches have been developed for surface delineation, but most of them may not be applicable to depression‐dominated surfaces. The main objective of this study is to introduce a new depression‐dominated delineation (D‐cubed) method and highlight its unique features by applying it to different topographic surfaces. The D‐cubed method accounts for the hierarchical relationships of depressions and channels by introducing the concept of channel‐based unit (CBU) and its connection with the concept of puddle‐based unit (PBU). This new delineation method implements a set of new algorithms to determine flow directions and accumulations for puddle‐related flats. The D‐cubed method creates a unique cascaded channel‐puddle drainage system based on the channel segmentation algorithm. To demonstrate the capabilities of the D‐cubed method, a small laboratory‐scale surface and 2 natural surfaces in North Dakota were delineated. The results indicated that the new method delineated different surfaces with and without the presence of depressional areas. Stepwise changes in depression storage and ponding area were observed for the 3 selected surfaces. These stepwise changes highlighted the dynamic filling, spilling, and merging processes of depressions, which need to be considered in hydrologic modelling for depression‐dominated areas. Comparisons between the D‐cubed method and other methods emphasized the potential consequences of use of artificial channels through the flats created by the depression‐filling process in the traditional approaches. In contrast, in the D‐cubed method, sub‐basins were further divided into a number of smaller CBUs and PBUs, creating a channel‐puddle drainage network. The testing of the D‐cubed method also demonstrated its applicability to a wide range of digital elevation model resolutions. Consideration of CBUs, PBUs, and their connection provides the opportunity to incorporate the D‐cubed method into different hydrologic models and improve their simulation of topography‐controlled runoff processes, especially for depression‐dominated areas.     

Thresholds for run‐off generation in a drained closed depression

Hydrological threshold behaviour has been observed across hillslopes and catchments with varying characteristics. Few studies, however, have evaluated rainfall–run‐off response in areas dominated by agricultural land use and artificial subsurface drainage. Hydrograph analysis was used to identify distinct hydrological events over a 9‐year period and examine rainfall characteristics, dynamic water storage, and surface and subsurface run‐off generation in a drained and farmed closed depression in north‐eastern Indiana, USA. Results showed that both surface flow and subsurface tile flow displayed a threshold relationship with the sum of rainfall amount and soil moisture deficit (SMD). Neither surface flow nor subsurface tile flow was observed unless rainfall amount exceeded the SMD. Timing of subsurface tile flow relative to soil moisture response on the shoulder slope of the depression indicated that the formation and drainage of perched water tables on depression hillslopes were likely the main mechanism that produced subsurface connectivity. Surface flow generation was delayed compared with subsurface tile flow during rainfall events due to differences in soil water storage along depression hillslopes and run‐off generation mechanisms. These findings highlight the substantial impact of subsurface tile drainage on the hydrology of closed depressions; the bottom of the depression, the wettest area prior to drainage installation, becomes the driest part of the depression after installation of subsurface drainage. Rapid connectivity of localized subsurface saturation zones during rainfall events is also greatly enhanced because of subsurface drainage. Thus, less fill is required to generate substantial spill. Understanding hydrologic processes in drained and farmed closed depressions is a critical first step in developing improved water and nutrient management strategies in this landscape.     

Effect of microrelief on water erosion and their changes during rainfall

Soil surface roughness contains two elementary forms, depressions and mounds, which affect water flow on the surface differently. While depressions serve as temporary water storage, mounds divert water away from their local summits. Although roughness impacts on runoff and sediment production have been studied, almost no studies have been designed explicitly to quantify the evolution of depressions and mounds and how this impacts runoff generation and sediment delivery. The objectives of this study were to analyze how different surface forms affect runoff and sediment delivery and to measure the changes in surface depressions and mounds during rainfall events. A smooth surface was used as the control. Both mounds and depressions delayed the runoff initiating time, but to differing degrees; and slightly reduced surface runoff when compared to the runoff process from the smooth surface. Surface mounds significantly increased sediment delivery, whilst depressions provided surface storage and hence reduced sediment delivery. However, as rainfall continued and rainfall intensity increased, the depression effect on runoff and erosion gradually decreased and produced even higher sediment delivery than the smooth surface. Depressions and mounds also impacted the particle size distribution of the discharged sediments. Many more sand‐sized particles were transported from the surface with mounds than with depressions. The morphology of mounds and depressions changed significantly due to rainfall, but to different extents. The difference in change had a spatial scale effect, i.e. erosion from each mound contributed to its own morphological change while sediments deposited in a depression came from a runoff contributing area above the depression, hence a much greater source area than a single mound. The results provide a mechanistic understanding of how soil roughness affects runoff and sediment production. Copyright © 2015 John Wiley & Sons, Ltd.     

Modelling rating curves using remotely sensed LiDAR data

Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage‐discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics‐based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m‐wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90‐m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a ‘hybrid model’ rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see ‘below’ the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics‐based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations. Copyright © 2012 John Wiley & Sons, Ltd.     

Land cover controls on depression‐focused recharge on the Oak Ridges Moraine,southern Ontario,Canada

The Oak Ridges Moraine (ORM) is a key hydrogeologic feature in southern Ontario. Previous research has emphasized the importance of depression‐focused recharge (DFR) for the timing and location of water recharge to the ORM's aquifers. However, the significance of DFR has not been empirically demonstrated, and the ORM's permeable surficial deposits imply that rainfall and snowmelt will largely recharge vertically rather than move laterally to topographic depressions. The exception may be during winter and spring, when concrete soil frost limits infiltration and encourages overland flow. The potential for DFR was examined for closed depressions under forest and agricultural land covers with similar soils and surficial geology. Air temperatures, precipitation, snow depth and water equivalent, soil water contents, soil freezing, and depression surface‐water levels were monitored during the winter and spring of 2012–2013 and 2013–2014. Recharge (R) was estimated at the crest and base of each depression using a 1‐dimensional water balance approach and surface‐applied Br^? tracing. Both forest and agricultural land covers experienced soil freezing; however, forest soils did not develop concrete frost. Conversely, agricultural fields saw concrete frost, overland flow, episodic ponding, and subsequent drainage of rain‐on‐snow and snowmelt inputs in open depressions. Recharge at the base of open depressions exceeded that in surrounding areas by an order of magnitude, suggesting that DFR is a significant hydrologic process during winter and spring under agricultural land cover on the ORM. Closed topographic depressions under agricultural land cover on the ORM crest may serve as critical recharge “hot spots” during winter and spring, and the ability of the unsaturated zone beneath these depressions to modify the chemistry of recharging water deserves further attention.     

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.     

How does DEM resolution affect microtopographic characteristics,hydrologic connectivity,and modelling of hydrologic processes?

The resolution of a digital elevation model (DEM) is a crucial factor in watershed hydrologic and environmental modelling. DEM resolution can cause significant variability in the representation of surface topography, which further affects quantification of hydrologic connectivity and simulation of hydrologic processes. The objective of this study is to examine the effects of DEM resolution on (1) surface microtopographic characteristics, (2) hydrologic connectivity, and (3) the spatial and temporal variations of hydrologic processes. A puddle‐to‐puddle modelling system was utilized for surface delineation and modelling of the puddle‐to‐puddle overland flow dynamics, surface runoff, infiltration, and unsaturated flow for nine DEM resolution scenarios of a field plot surface. Comparisons of the nine modelling scenarios demonstrated that coarser DEM resolutions tended to eliminate topographic features, reduce surface depression storage, and strengthen hydrologic connectivity and surface runoff. We found that reduction in maximum depression storage and maximum ponding area was as high as 97.56% and 76.36%, respectively, as the DEM grid size increased from 2 to 80 cm. The paired t‐test and fractal analysis demonstrated the existence of a threshold DEM resolution (10 cm for the field plot), within which the DEM‐based hydrologic modelling was effective and acceptable. The effects of DEM resolution were further evaluated for a larger surface in the Prairie Pothole Region subjected to observed rainfall events. It was found that simulations based on coarser resolution DEMs (>10 m) tended to overestimate ponded areas and underestimate runoff discharge peaks. The simulated peak discharge from the Prairie Pothole Region surface reduced by approximately 50% as the DEM resolution changed from 2 to 90 m. Fractal analysis results elucidated scale dependency of hydrologic and topographic processes. In particular, scale analysis highlighted a unique constant–threshold–power relationship between DEM scale and topographic and hydrologic parameters/variables. Not only does this finding allow one to identify threshold DEM but also further develop functional relationships for scaling to achieve valid topographic characterization as well as effective and efficient hydrologic modelling. Copyright © 2016 John Wiley & Sons, Ltd.     

The impact of depression removal on catchment geomorphology,soil erosion and landscape evolution

The current generation of landscape evolution models use a digital elevation model for landscape representation. These programs also contain a hydrological model that defines overland flow with the drainage network routed to an outlet. One of the issues with landscape evolution modelling is the hydrological correctness of the digital elevation model used for the simulations. Despite the wide use and increased quality of digital elevation models, data pits and depressions in the elevation data are a common feature and their removal will remain a necessary step for many data sets. This study examines whether a digital elevation model can be hydrologically correct (i.e. all depressions removed so that all water can run downslope) before use in a landscape evolution model and what effect depression removal has on long‐term geomorphology and hydrology. The impact on sediment transport rates is also examined. The study was conducted using a field catchment and a proposed landform for a post‐mining landscape. The results show that there is little difference in catchment geomorphology and hydrology for the non‐depression removed and depression removed data sets. The non‐depression removed and depression removed digital elevation models were also evaluated as input to a landscape evolution model for a 50 000 year simulation period. The results show that after 1000 years there is little difference between the data sets, although sediment transport rates did vary considerably early on in the simulation. Copyright © 2007 John Wiley & Sons, Ltd.     

Application of globally available,coarse-resolution digital elevation models for delineating valley bottom segments of varying length across a catchment

The worldwide availability of digital elevation models (DEMs) has enabled rapid (semi-)automated mapping of earth surface landforms. In this paper, we first present an approach for delineating valley bottom extent across a large catchment using only publicly available, coarse-resolution DEM input. We assess the sensitivity of our results to variable DEM resolution and find that coarse-resolution datasets (90 m resolution) provide superior results. We also find that LiDAR-derived DEMs produce more realistic results than satellite-derived DEMs across the full range of topographic settings tested. Satellite-derived DEMs perform more effectively in moderate topographic settings, but fail to capture the subtleties of valley bottom extent in mild gradient, low-lying topography and in narrow headwater reaches. Second, we present a semi-automated technique within ArcGIS for delineating valley bottom segments using DEM-derived network scale metrics of valley bottom width and slope. We use an unsupervised machine-learning technique based on the k-means clustering algorithm to solve a conundrum in GIS-based geomorphic analysis of rivers: the delineation of valley bottom segments of variable length. The delineation of valley bottom segments provides a coarse-scale entry point into automated geomorphic analysis and characterization of river systems. © 2020 John Wiley & Sons, Ltd.     

Spatial variability of soils developing on basalt flows in the Potrillo volcanic field,southern New Mexico: prelude to a chronosequence study

If the systematic spatial variability of soils in a chronosequence is identified and accounted for, the accuracy of quantitative data derived from soil chronosequence studies will be increased. A sample design using landscape positions with minimal variability could result in more accurate chronofunctions from these studies. Four basalt flows in the Potrillo volcanic field, southern New Mexico, with ages ranging between 20 ka and 260 ka (⁴⁰Ar/³⁹Ar and/or cosmogenic ³He methods) provide a sound basis for a soil chronosequence study. Basalt flow surface relief in the Potrillos reduces with time as depressions fill with basalt rubble and aeolian dust. Soil variability is primarily a function of landscape position with respect to ridges and swales in the original basalt flow topography. Soils developing over original topographic lows (swale soils) form primarily in aeolian dust, have larger amounts of total carbonate and soluble salts, and display greater variability than soils developing over original topographic highs (ridge soils). It is thus concluded that ridge soils, which have minimal variability, should be employed for a soil chronosequence study of basalt surfaces in the Potrillo volcanic field. The spatial variability of swale soils results in part from the significant hydrologic variability of low-lying landscape positions. Depth profiles of chloride concentrations suggest that hydrologic variability systematically correlates with the size and shape of depressions in which soils are forming. The infilling of depressions with aeolian material results in increasingly arid hydrologic conditions both by increasing the volume of aeolian material that is being drained and by reducing the catchment area for runoff into the depression. Depressions fill at different rates, however, depending on their size, shape and catchment area. Small, narrow depressions fill quickly, and their associated soils form under more arid conditions and have stronger development than soils in large depressions. Therefore, a number of geomorphic surfaces of varying age may develop on a single isochronous basalt flow. Each of these surfaces will have unique hydrologic characteristics and consequently different degrees of soil development. The pre-burial high water flux evident in depressions suggests that basalt flows may play an important role in aquifer recharge in this area of New Mexico. Copyright © 1999 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.     

Digital landscapes of deglaciation: identifying Late Quaternary glacial lake outburst floods using LiDAR

High resolution DEMs obtained from LiDAR topographic data have led to improved landform inventories (e.g. landslides and fault scarps) and understanding of geomorphic event frequency. Here we use airborne LiDAR mapping to investigate meltwater pathways associated with the Tweed Valley palaeo ice‐stream (UK). In particular we focus on a gorge downstream of Palaeolake Milfield, previously mapped as a sub‐glacial meltwater channel, where the identification of abandoned headcut channels, run‐up bars, rock‐cut terrace surfaces and eddy flow features attest to formation by a sub‐aerial glacial lake outburst flood (GLOF) caused by breaching of a sediment dam, likely an esker ridge. Mapping of these landforms combined with analysis of the gorge rim elevations and cross‐section variability revealed a two phase event with another breach site downstream following flow blockage by higher elevation drumlin topography. We estimate the magnitude of peak flow to be 1–3 × 10³ m³/s, duration of the event to range from 16–155 days, and a specific sediment yield of 10⁷–10⁹ m³/km²/yr. We identified other outburst pathways in the lower Tweed basin that help delineate an ice margin position of the retreating Tweed Valley ice stream. The results suggest that low magnitude outburst floods are under‐represented in Quaternary geomorphological maps. We therefore recommend regional LiDAR mapping of meltwater pathways to identify other GLOFs in order to better quantify the pattern of freshwater and sediment fluxes from melting ice sheets to oceans. Despite the relatively low magnitude of the Till outburst event, it had a significant impact on the landscape development of the lower Tweed Valley through the creation of a new tributary pathway and triggering of rapid knickpoint retreat encouraging new regional models of post‐glacial fluvial landscape response. Copyright © 2015 John Wiley & Sons, Ltd.     

Influence of pit removal methods on river network position

Digital elevation models often contain depressions that result in areas described as having no drainage, referred to as sinks or pits. These depressions disrupt the drainage surface, which disrupt routing of flow over the surface. Most of the attributes that can be extracted from a digital elevation model rely on flow‐routing algorithms to calculate the upslope contributing area. There is little information on the influence of the various algorithms on the position and on the connectivity of the extracted networks. The aim of this study was to assess the effects of pit removal methods, data sources and flow‐routing algorithms on the position of river networks. The results show that all factors and methods have an impact on the position of the extracted networks. The pit removal method combining filling and carving extracted river networks closer to the reference, as well the elevation models with higher resolution. Single‐flow direction methods provided more accurate positioning of river network, in this test area where the drainage is generally well defined. Copyright © 2011 John Wiley & Sons, Ltd.     

Evaluation of on-line DEMs for flood inundation modeling

Recent and highly accurate topographic data should be used for flood inundation modeling, but this is not always feasible given time and budget constraints so the utility of several on-line digital elevation models (DEMs) is examined with a set of steady and unsteady test problems. DEMs are used to parameterize a 2D hydrodynamic flood simulation algorithm and predictions are compared with published flood maps and observed flood conditions. DEMs based on airborne light detection and ranging (LiDAR) are preferred because of horizontal resolution, vertical accuracy (∼0.1 m) and the ability to separate bare-earth from built structures and vegetation. DEMs based on airborne interferometric synthetic aperture radar (IfSAR) have good horizontal resolution but gridded elevations reflect built structures and vegetation and therefore further processing may be required to permit flood modeling. IfSAR and shuttle radar topography mission (SRTM) DEMs suffer from radar speckle, or noise, so flood plains may appear with non-physical relief and predicted flood zones may include non-physical pools. DEMs based on national elevation data (NED) are remarkably smooth in comparison to IfSAR and SRTM but using NED, flood predictions overestimate flood extent in comparison to all other DEMs including LiDAR, the most accurate. This study highlights utility in SRTM as a global source of terrain data for flood modeling.     

The practice of DEM stream burning revisited

Stream burning is a common flow enforcement technique used to correct surface drainage patterns derived from digital elevation models (DEM). The technique involves adjusting the elevations of grid cells that are coincident with the features of a vector hydrography layer. This paper focuses on the problematic issues with common stream burning practices, particularly the topological errors resulting from the mismatched scales of the hydrography and DEM data sets. A novel alternative stream burning method is described and tested using five DEMs of varying resolutions (1 to 30 arc‐seconds) for an extensive area of southwestern Ontario, Canada. This TopologicalBreachBurn method uses total upstream channel length (TUCL) to prune the vector hydrography layer to a level of detail that matches the raster DEM grid resolution. Network pruning reduces the occurrence of erroneous stream piracy caused by the rasterization of multiple stream links to the same DEM grid cell. The algorithm also restricts flow within individual stream reaches, further reducing erroneous stream piracy. In situations where two vector stream features occupy the same grid cell, the new tool ensures that the larger stream, designated by higher TUCL, is given priority. TUCL‐based priority minimizes the impact of the topological errors that occur during the stream rasterization process on modeled regional drainage patterns. The test data demonstrated that TopologicalBreachBurn produces highly accurate and scale‐insensitive drainage patterns and watershed boundaries. The drainage divides of four large watersheds within the study region that were delineated from the TopologicalBreachBurn‐processed DEMs were found to be highly accurate when compared with the official watershed boundaries, even at the coarsest grid resolutions, with Kappa index of agreement values ranging from 0.952 to 0.921. The corresponding Kappa coefficient values for a traditional stream burning method (FillBurn) ranged from 0.953 to 0.490, demonstrating a significant decrease in mapping accuracy at coarser DEM grid resolutions. Copyright © 2015 John Wiley & Sons, Ltd.