Evaluation of ASTER GDEM and SRTM and their suitability in hydraulic modelling of a glacial lake outburst flood in southeast Tibet

The resolution and accuracy of digital elevation models (DEMs) can affect the hydraulic simulation results for predicting the effects of glacial lake outburst floods (GLOFs). However, for the Tibetan Plateau, high‐quality DEM data are often not available, leaving researchers with near‐global, freely available DEMs, such as the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) and the Shuttle Radar Topography Mission data (SRTM) for hydraulic modelling. This study explores the suitability of these two freely available DEMs for hydraulic modelling of GLOFs. Our study focused on the flood plain of a potentially dangerous glacial lake in southeastern Tibet, to evaluate the elevation accuracy of ASTER GDEM and SRTM, and their suitability for hydraulic modelling of GLOFs. The elevation accuracies of ASTER GDEM and SRTM were first validated against field global position system (GPS) survey points, and then evaluated with reference to the relatively high precision of 1:50 000 scale DEM (DEM5) constructed from aerial photography. Moreover, the DEM5, ASTER GDEM and SRTM were used as basic topographic data to simulate peak discharge propagation, as well as flood inundation extent and depth in the Hydrologic Engineering Center's River Analysis System one‐dimensional hydraulic model. Results of the three DEM predictions were compared to evaluate the suitability of ASTER GDEM and SRTM for GLOF hydraulic modelling. Comparisons of ASTER GDEM and SRTM each with DEM5 in the flood plain area show root‐mean‐square errors between the former two as ± 15·4 m and between the latter two as ± 13·5 m. Although SRTM overestimates and ASTER GDEM underestimates valley floor elevations, both DEMs can be used to extract the elevations of required geometric data, i.e. stream centre lines, bank lines and cross sections, for flood modelling. However, small errors still exist in the cross sections that may influence the propagation of peak discharge. The flood inundation extent and mean water depths derived from ASTER GDEM predictions are only 2·2% larger and 2·3‐m deeper than that of the DEM5 predictions, whereas the SRTM yields a flood zone extent 6·8% larger than the DEM5 prediction and a mean water depth 2·4‐m shallower than the DEM5 prediction. The modelling shows that, in the absence of high‐precision DEM data, ASTER GDEM or SRTM DEM can be relied on for simulating extreme GLOFs in southeast Tibet. Copyright © 2011 John Wiley & Sons, Ltd.     

Impact of grid resolution on the integrated and distributed response of a coupled surface–subsurface hydrological model for the des Anglais catchment,Quebec

Digital elevation models (DEMs) at different resolutions (180, 360, and 720 m) are used to examine the impact of different levels of landscape representation on the hydrological response of a 690‐km² catchment in southern Quebec. Frequency distributions of local slope, plan curvature, and drainage area are calculated for each grid size resolution. This landscape analysis reveals that DEM grid size significantly affects computed topographic attributes, which in turn explains some of the differences in the hydrological simulations. The simulations that are then carried out, using a coupled, process‐based model of surface and subsurface flow, examine the effects of grid size on both the integrated response of the catchment (discharge at the main outlet and at two internal points) and the distributed response (water table depth, surface saturation, and soil water storage). The results indicate that discharge volumes increase as the DEM is coarsened, and that coarser DEMs are also wetter overall in terms of water table depth and soil water storage. The reasons for these trends include an increase in the total drainage area of the catchment for larger DEM cell sizes, due to aggregation effects at the boundary cells of the catchment, and to a decrease in local slope and plan curvature variations, which in turn limits the capacity of the watershed to transmit water downslope and laterally. The results obtained also show that grid resolution effects are less pronounced during dry periods when soil moisture dynamics are mostly controlled by vertical fluxes of evaporation and percolation. Copyright © 2010 John Wiley & Sons, Ltd.     

Effect of elevation resolution on evapotranspiration simulations using MODFLOW

Surface elevations represented in MODFLOW head-dependent packages are usually derived from digital elevation models (DEMs) that are available at much high resolution. Conventional grid refinement techniques to simulate the model at DEM resolution increases computational time, input file size, and in many cases are not feasible for regional applications. This research aims at utilizing the increasingly available high resolution DEMs for effective simulation of evapotranspiration (ET) in MODFLOW as an alternative to grid refinement techniques. The source code of the evapotranspiration package is modified by considering for a fixed MODFLOW grid resolution and for different DEM resolutions, the effect of variability in elevation data on ET estimates. Piezometric head at each DEM cell location is corrected by considering the gradient along row and column directions. Applicability of the research is tested for the lower Rio Grande (LRG) Basin in southern New Mexico. The DEM at 10 m resolution is aggregated to resampled DEM grid resolutions which are integer multiples of MODFLOW grid resolution. Cumulative outflows and ET rates are compared at different coarse resolution grids. Results of the analysis conclude that variability in depth-to-groundwater within the MODFLOW cell is a major contributing parameter to ET outflows in shallow groundwater regions. DEM aggregation methods for the LRG Basin have resulted in decreased volumetric outflow due to the formation of a smoothing error, which lowered the position of water table to a level below the extinction depth.     

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 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.     

Spatial analysis of sand dunes with a new global topographic dataset: new approaches and opportunities

On June 29, 2009, version 1 of the ASTER GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) was made available at no cost or restrictions to users worldwide via electronic download. The ASTER GDEM provides expanded spatial coverage and better resolution than other global digital elevation models (DEMs). In this paper we demonstrate how the ASTER GDEM provides new opportunities for investigating large aeolian sand dunes in three‐dimensions. Two dune‐specific spatial analysis methods are presented to illustrate potential applications of these data for discriminating dune generations and quantifying spatial variations of sediment supply. Moreover, we review how existing and emerging fields of dune pattern analysis and simulation modeling will be able to make significant advances through application of these data, potentially leading to future progress in studies of dune morphodynamics, environmental controls, and paleoenvironmental reconstructions. Copyright © 2010 John Wiley & Sons, Ltd.     

Satellite Data for a Rapid Assessment of Tsunami Inundation Areas after the 2011 Tohoku Tsunami

The M _w = 9.0 earthquake that occurred off the coast of Japan’s Tohoku region produced a great tsunami causing catastrophic damage and loss of life. Within hours of the tsunami event, satellite data were readily available and massive media coverage immediately circulated thousands of photographs and videos of the tsunami. Satellite data allow a rapid assessment of inundated areas where access can be difficult either as a result of damaged infrastructure (e.g., roads, bridges, ports, airports) or because of safety issues (e.g., the hazard at Nuclear Power Plant at Fukushima). In this study, we assessed in a day tsunami inundation distances and runup heights using satellite data (very high-resolution satellite images from the GeoEye1 satellite and from the DigitalGlobe worldview, SRTM and ASTER GDEM) of the Tohoku region, Northeast Japan. Field survey data by Japanese and other international scientists validated our results. This study focused on three different locations. Site selection was based on coastal morphologies and the distance to the tsunami source (epicenter). Study sites are Rikuzentakata, Oyagawahama, and Yagawahama in the Oshika Peninsula, and the Sendai coastal plain (Sendai City to Yamamoto City). Maximum inundation distance (6 km along the river) and maximum runup (39 m) at Rikuzentakata estimated from satellite data agree closely with the 39.7 m inundation reported in the field. Here the ria coastal morphology and horn shaped bay enhanced the tsunami runup and effects. The Sendai coastal plain shows large inundation distances (6 km) and lower runup heights. Natori City and Wakabayashi Ward, on the Sendai plain, have similar runup values (12 and 16 m, respectively) obtained from SRTM data; these are comparable to those obtained from field surveys (12 and 9.5 m). However, at Yagawahama and Oyagawahama, Miyagi Prefecture, both SRTM and ASTER data provided maximum runup heights (41 to 45 m and 33 to 34 m, respectively), which are higher than those measured in the field (about 27 m). This difference in DEM and field data is associated with ASTER and SRTM DEM’s pixel size and vertical accuracy, the latter being dependent on ground coverage, slope, aspect and elevation. Countries with less access to technology and infrastructure can benefit from the use of satellite imagery and freely available DEMs for an initial, pre-field surveys, rapid estimate of inundated areas, distances and runup, and for assisting in hazard management and mitigation after a natural disaster.     

基于迭代融合的InSAR技术获取数字高程模型研究

数字高程模型是重要的地理空间数据,可以提供丰富的地形信息.为了获得时效性好、分辨率高的数字高程模型,本文以南京市为实验区域,利用德国宇航局TerraSAR-X卫星同一轨道上的两幅StripMap模式SAR影像对,主从影像时间间隔只有66天,空间分辨率为3 m.采用InSAR技术,通过迭代的方法来提高获取DEM的分辨率,并结合JAXA/EORC提供的AW3D30数字表面模型与迭代后的DEM进行融合来解决阴影等问题,最终获取了南京地区的高精度数字高程模型.将实验结果分别与90 m分辨率的SRTM、30 m分辨率的ASTER GDEM、30 m分辨率的AW3D30进行相互对比分析.结果表明,相比三种常用的DEM而言,本文获取的DEM能够更精确的获取地面的细节信息,特别是对于分布稀疏的大型单体建筑物,能够很好的恢复其三维信息,但是对于建筑物分布较为密集的区域,由于传感器视线受阻,不能观测建筑物的全貌,阴影分布较多,导致此类区域的DEM结果不理想,还需进一步深入研究,提高精度及可靠性.     

Topographic accuracy assessment of bare earth lidar-derived unstructured meshes

This study is focused on the integration of bare earth lidar (Light Detection and Ranging) data into unstructured (triangular) finite element meshes and the implications on simulating storm surge inundation using a shallow water equations model. A methodology is developed to compute root mean square error (RMSE) and the 95th percentile of vertical elevation errors using four different interpolation methods (linear, inverse distance weighted, natural neighbor, and cell averaging) to resample bare earth lidar and lidar-derived digital elevation models (DEMs) onto unstructured meshes at different resolutions. The results are consolidated into a table of optimal interpolation methods that minimize the vertical elevation error of an unstructured mesh for a given mesh node density. The cell area averaging method performed most accurate when DEM grid cells within 0.25 times the ratio of local element size and DEM cell size were averaged. The methodology is applied to simulate inundation extent and maximum water levels in southern Mississippi due to Hurricane Katrina, which illustrates that local changes in topography such as adjusting element size and interpolation method drastically alter simulated storm surge locally and non-locally. The methods and results presented have utility and implications to any modeling application that uses bare earth lidar.     

Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases

Presently, the application of digital elevation or surface models have increasing relevance in all areas of scientific research and in practical engineering applications. The ASTER GDEM and SRTM databases are the most widely used digital surface models, due to their free accessibility and global coverage. The SRTM model was produced using a radar-based technique and the ASTER GDEM was developed using optical stereo image-pairs. Therefore, as all models contain errors (i.e. differences stemming from real surface or vertical biases), errors in these models will also differ. Our aim was to examine these vertical biases and to calculate the rate of error variance. A TIN (Triangulated Irregular Network) model was used as a reference surface, derived from the contour lines of a large scale topographic map. Errors were evaluated with statistical and geoinformation techniques. We discovered significant differences between the surfaces. The mean difference between topographic elevations minus the SRTM-V2 is +2.6 ± 4 m, while the mean difference between topographic elevations minus the SRTM-V3 is +2.7 ± 2.5 m. With the GDEM, the mean difference was 2.7 ± 9.1 m. Furthermore, we found that in the case of SRTM, the differences were significant considering the aspects and the steepness of the slopes: southern and eastern directions and larger slope angles showed greater differences compared to the reference data. The GDEM V2 DEM had a larger error variance, but the error did not vary significantly with slope angle.     

Morphometric analysis of aeolian bedforms in the Namib Sand Sea using ASTER data

The ASTER Global Digital Elevation Model (GDEM) has made elevation data at 30 m spatial resolution freely available, enabling reinvestigation of morphometric relationships derived from limited field data using much larger sample sizes. These data are used to analyse a range of morphometric relationships derived for dunes (between dune height, spacing, and equivalent sand thickness) in the Namib Sand Sea, which was chosen because there are a number of extant studies that could be used for comparison with the results. The relative accuracy of GDEM for capturing dune height and shape was tested against multiple individual ASTER DEM scenes and against field surveys, highlighting the smoothing of the dune crest and resultant underestimation of dune height, and the omission of the smallest dunes, because of the 30 m sampling of ASTER DEM products. It is demonstrated that morphometric relationships derived from GDEM data are broadly comparable with relationships derived by previous methods, across a range of different dune types. The data confirm patterns of dune height, spacing and equivalent sand thickness mapped previously in the Namib Sand Sea, but add new detail to these patterns. 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.     

Modeling and visualizing uncertainties of flood boundary delineation: algorithm for slope and DEM resolution dependencies of 1D hydraulic models

As flood inundation risk maps have become a central piece of information for both urban and risk management planning, also a need to assess the accuracies and uncertainties of these maps has emerged. Most maps show the inundation boundaries as crisp lines on visually appealing maps, whereby many planners and decision makers, among others, automatically believe the boundaries are both accurate and reliable. However, as this study shows, probably all such maps, even those that are based on high-resolution digital elevation models (DEMs), have immanent uncertainties which can be directly related to both DEM resolution and the steepness of terrain slopes perpendicular to the river flow direction. Based on a number of degenerated DEMs, covering areas along the Eskilstuna River, Sweden, these uncertainties have been quantified into an empirically-derived disparity distance equation, yielding values of distance between true and modeled inundation boundary location. Using the inundation polygon, the DEM, a value representing the DEM resolution, and the desired level of confidence as inputs in a new-developed algorithm that utilizes the disparity distance equation, the slope and DEM dependent uncertainties can be directly visualized on a map. The implications of this strategy should benefit planning and help reduce high costs of floods where infrastructure, etc., have been placed in flood-prone areas without enough consideration of map uncertainties.     

EFFECT OF DIGITAL ELEVATION MODEL RESOLUTION ON EMPIRICAL ESTIMATION OF SOIL LOSS AND SEDIMENT TRANSPORT WITH GIS

The horizontal accuracy of topographic data represented by digital elevation model (DEM) resolution brings about uncertainties in landscape process modeling with raster GIS. This paper presents a study on the effect of topographic variability on cell-based empirical estimation of soil loss and sediment transport. An original DEM of 10m resolution for a case watershed was re-sampled to three realizations of higher grid sizes for a comparative examination. Equations based on the USLE are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams. The study found that the calculated total soil loss from the watershed decreases with the increasing DEM resolution with a linear correlation as spatial variability is reduced by cell aggregation. The USLE topographic factors (LS) extracted from applied DEMs represent spatial variability, and determine the estimations as shown in the modeling results. The commonly used USGS 30m DEM appears to be able to reflect essential spatial variability and suitable for the empirical estimation. The appropriateness of a DEM resolution is dependent upon specific landscape characteristics, applied model and its parameterization. This work attempts to provide a general framework for the research in the DEM-based empirical modeling.     

‘Out with the Old?’ Why coarse spatial datasets are still useful for catchment‐scale investigations of sediment (dis)connectivity

The increasing popularity of remote sensing techniques has created numerous options for researchers seeking spatial datasets, especially digital elevation models (DEMs), for geomorphic investigations. This yields an important question regarding what DEM resolution is most appropriate when answering questions of geomorphic significance. The highest possible resolution is not always the best choice for a particular research aim, and DEM resolution should be tailored to fit both the scale of investigation and the simplicity/complexity of modelling processes applied to the dataset. We find that DEM resolution has a significant effect on a simple model of bed load sediment connectivity in the Lockyer Valley, Queensland. We apply a simple bed load transport threshold to catchment DEMs at three different resolutions – 1 m, 5 m, and 25 m. We find that using a 1 m resolution DEM generates numerous disconnections along tributary channel networks that underestimates the sediment contributing area, i.e. effective catchment area (ECA), of seven tributary basins of Lockyer Creek. Utilizing a coarser (lower‐resolution) DEM helps eliminate erroneous disconnections, but can reduce the detail of stream network definition. We find that the 25 m resolution DEM provides the best measure of ECA for comparing sediment connectivity between tributary catchments. The utility of simple models and coarse‐resolution datasets is important for undertaking large, catchment‐scale geomorphic investigations. As catchment‐scale investigations are becoming increasingly entwined with river management and rehabilitation efforts, scientists need not embrace an ‘out with the old’ philosophy. Simple models and coarse‐resolution datasets can help better integrate geomorphic research with management strategies and provide inexpensive and quick first‐order insights into catchment‐scale processes that can help focus future management efforts. Copyright © 2017 John Wiley & Sons, Ltd.     

Assessment of the Accuracy of SRTM C- and X-Band High Mountain Elevation Data: a Case Study of the Polish Tatra Mountains

Global digital elevation models (DEMs) are an invaluable source of information in large area studies. Of particular interest are shuttle radar topography mission (SRTM) data that are freely available for the scientific community worldwide. Prior to any application, global datasets should be evaluated using reference data of higher accuracy. Therefore, the main objective of this study was to assess the accuracy of the SRTM C-band (version 4) DEM and SRTM X-band DEM of mountainous areas located in Poland and to examine the quality of data in relation to topographic parameters, radar beam geometry, initial voids in data and the presence of forest cover. A DEM from the Central National Geodetic and Cartographic Inventory, Poland, served as a reference. The study consisted of three steps: (i) the computation of vertical errors of the SRTM C- and X-band DEMs, (ii) the examination of any systematic bias in the data, and (iii) the analysis of the relationships between the elevation errors and terrain slope, aspect, local incidence angle, occurrence of voids and land cover. We found that the SRTM C- and X-band DEMs have mean errors equal to 4.31 ± 14.09 and 9.03 ± 37.40 m and root mean square errors equal to 14.74 and 38.47 m, respectively. Only 82 % of the C-band DEM and 74 % of the X-band DEM vertical errors had absolute values below 16 m. We found that the most important factors determining the occurrence of high errors were the distribution of initial voids and high slope angles for the C-band DEM, and local incidence angle, slope, aspect and radar beam geometry for the X-band DEM. In both cases, the presence of forest cover increased the mean error by approximately 10 m.     

Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) IV: Model sensitivity to data aggregation and spatial (re-)distribution

This paper analyses the effect of spatial resolution and distribution of model input data on the results of regional-scale land use scenarios using three different hydrological catchment models. A 25 m resolution data set of a mesoscale catchment and three land use scenarios are used. Data are systematically aggregated to resolutions up to 2 km. Land use scenarios are spatially redistributed, both randomly and topography based. Using these data, water fluxes are calculated on a daily time step for a 16 year time period without further calibration. Simulation results are used to identify grid size, distribution and model dependent scenario effects. In the case of data aggregation, all applied models react sensitively to grid size. WASIM and TOPLATS simulate constant water balances for grid sizes from 50 m to 300–500 m, SWAT is more sensitive to input data aggregation, simulating constant water balances between 50 m and 200 m grid size. The calculation of scenario effects is less robust to data aggregation. The maximum acceptable grid size reduces to 200–300 m for TOPLATS and WASIM. In case of spatial distribution, SWAT and TOPLATS are slightly sensitive to a redistribution of land use (below 1.5% for water balance terms), whereas WASIM shows almost no reaction. Because the aggregation effects were stronger than the redistribution effects, it is concluded that spatial discretisation is more important than spatial distribution. As the aggregation effect was mainly associated with a change in land use fraction, it is concluded that accuracy of data sets is much more important than a high spatial resolution.     

Capturing the essential spatial variability in distributed hydrological modelling: Infiltration parameters

Selecting the correct resolution in distributed hydrological modelling at the watershed scale is essential in reducing scale-related errors. The work presented herein uses information content (entropy) to identify the resolution which captures the essential variability, at the watershed scale, of the infiltration parameters in the Green and Ampt infiltration equation. A soil map of the Little Washita watershed in south-west Oklahoma, USA was used to investigate the effects of grid cell resolution on the distributed modelling of infiltration. Soil-derived parameters and infiltration exhibit decreased entropy as resolutions become coarser. This is reflected in a decrease in the maximum entropy value for the reclassified/derived parameters vis a vis the original data. Moreover, the entropy curve, when plotted against resolution, shows two distinct segments: a constant section where no entropy was lost with decreasing resolution and another part which is characterized by a sharp decrease in entropy after a critical resolution of 1209 m is reached. This methodology offers a technique for assessing the largest cell size that captures the spatial variability of infiltration parameters for a particular basin. A geographical information system (GIS) based rainfall-runoff model is used to simulate storm hydrographs using infiltration parameter maps at different resolutions as inputs. Model results up to the critical resolution are reproducible and errors are small. However, at resolutions beyond the critical resolution the results are erratic with large errors. A major finding of this study is that a large resolution (1209 m for this basin) yields reproducible model results. When modelling a river basin using a distributed model, the resolution (grid cell size) can drastically affect the model results and calibration. The error structure attributable to grid cell resolution using entropy as a spatial variability measure is shown.     

Improvement of streams hydro‐geomorphological assessment using LiDAR DEMs

Hydro‐geomorphological assessments are an essential component for riverine management plans. They usually require costly and time‐consuming field surveys to characterize the spatial variability of key variables such as flow depth, width, discharge, water surface slope, grain size and unit stream power throughout the river corridor. The objective of this research is to develop automated tools for hydro‐geomorphological assessments using high‐resolution LiDAR digital elevation models (DEMs). More specifically, this paper aims at developing geographic information system (GIS) tools to extract channel slope, width and discharge from 1 m‐resolution LiDAR DEMs to estimate the spatial distribution of unit stream power in two contrasted watersheds in Quebec: a small agricultural stream (Des Fèves River) and a large gravel‐bed river (Matane River). For slope, the centreline extracted from the raw LiDAR DEM was resampled at a coarser resolution using the minimum elevation value. The channel width extraction algorithm progressively increased the centerline from the raw DEM until thresholds of elevation differences and slopes were reached. Based on the comparison with over 4000 differential global positioning system (GPS) measurements of the water surface collected in a 50 km reach of the Matane River, the longitudinal profile and slope estimates extracted from the raw and resampled LiDAR DEMs were in very good agreement with the field measurements (correlation coefficients ranging from 0 · 83 to 0 · 87) and can thus be used to compute stream power. The extracted width also corresponded very well to the channel as seen from ortho‐photos, although the presence of bars in the Matane River increased the level of error in width estimates. The estimated maximum unit stream power spatial patterns corresponded well with field evidence of bank erosion, indicating that LiDAR DEMs can be used with confidence for initial hydro‐geomorphological assessments. Copyright © 2013 John Wiley & Sons, Ltd.     

When does spatial resolution become spurious in probabilistic flood inundation predictions?

Advances in remote sensing have enabled hydraulic models to run at fine scale resolutions, producing precise flood inundation predictions. However, running models at finer resolutions increase their computational expense, reducing the feasibility of running the multiple model realizations required to undertake uncertainty analysis. Furthermore, it is possible that precision gained by running fine scale models is smoothed out when treating models probabilistically. The aim of this paper is to determine the level of spatial complexity that is required when making probabilistic flood inundation predictions. The Imera basin, Sicily is used as a case study to assess how changing the spatial resolution of the hydraulic model LISFLOOD‐FP impacts on the skill of conditional probabilistic flood inundation maps given model parameter and boundary condition uncertainties. We find that model performance deteriorates at resolutions coarser than 50 m. This is predominantly caused by changes in flow pathways at coarser resolutions which lead to non‐stationarity in the optimum model parameters at different spatial resolutions. However, although it is still possible to produce probabilistic flood maps that contain a coherent outline of the flood extent at coarser resolutions, the reliability of these maps deteriorates at resolutions coarser than 100 m. Additionally, although the rejection of non‐behavioural models reduces the uncertainty in probabilistic flood maps the reliability of these maps is also reduced. Models with resolutions finer than 50 m offer little gain in performance yet are more than an order of magnitude computationally expensive which can become infeasible when undertaking probabilistic analysis. Furthermore, we show that using deterministic, high‐resolution flood maps can lead to a spurious precision that would be misleading and not representative of the overall uncertainties that are inherent in making inundation predictions. Copyright © 2015 The Authors Hydrological Processes Published by John Wiley & Sons Ltd.