Perspectives on Digital Elevation Model (DEM) Simulation for Flood Modeling in the Absence of a High-Accuracy Open Access Global DEM

Open-access global Digital Elevation Models (DEM) have been crucial in enabling flood studies in data-sparse areas. Poor resolution (>30m), significant vertical errors and the fact that these DEMs are over a decade old continue to hamper our ability to accurately estimate flood hazard. The limited availability of high-accuracy DEMs dictate that dated open-access global DEMs are still used extensively in flood models, particularly in data-sparse areas. Nevertheless, high-accuracy DEMs have been found to give better flood estimations, and thus can be considered a ‘must-have’ for any flood model. A high-accuracy open-access global DEM is not imminent, meaning that editing or stochastic simulation of existing DEM data will remain the primary means of improving flood simulation. This article provides an overview of errors in some of the most widely used DEM data sets, along with the current advances in reducing them via the creation of new DEMs, editing DEMs and stochastic simulation of DEMs. We focus on a geostatistical approach to stochastically simulate floodplain DEMs from several open-access global DEMs based on the spatial error structure. This DEM simulation approach enables an ensemble of plausible DEMs to be created, thus avoiding the spurious precision of using a single DEM and enabling the generation of probabilistic flood maps. Despite this encouraging step, an imprecise and outdated global DEM is still being used to simulate elevation. To fundamentally improve flood estimations, particularly in rapidly-changing developing regions, a high-accuracy open-access global DEM is urgently needed, which in turn can be used in DEM simulation.

[1]  E. Rodríguez,et al.  A Global Assessment of the SRTM Performance , 2006 .

[2]  Paul D. Bates,et al.  A high‐resolution global flood hazard model† , 2015, Water resources research.

[3]  Wenkai Li,et al.  SRTM DEM Correction in Vegetated Mountain Areas through the Integration of Spaceborne LiDAR, Airborne LiDAR, and Optical Imagery , 2015, Remote. Sens..

[4]  P. Gamba,et al.  SRTM data Characterization in urban areas , 2012 .

[5]  David J. Harding,et al.  SRTM C-band and ICESat Laser Altimetry Elevation Comparisons as a Function of Tree Cover and Relief , 2006 .

[6]  L. Martz,et al.  An outlet breaching algorithm for the treatment of closed depressions in a raster DEM , 1999 .

[7]  S. Wechsler Uncertainties associated with digital elevation models for hydrologic applications: a review , 2006 .

[8]  J. N. Callow,et al.  How does modifying a DEM to reflect known hydrology affect subsequent terrain analysis , 2007 .

[9]  Dan Watt,et al.  Quality Assessment , 2009, Encyclopedia of Database Systems.

[10]  P. Bates,et al.  Evaluating the effect of scale in flood inundation modelling in urban environments , 2008 .

[11]  P. Kyriakidis,et al.  Error in a USGS 30-meter digital elevation model and its impact on terrain modeling , 2000 .

[12]  Thomas A. Hennig,et al.  The Shuttle Radar Topography Mission , 2001, Digital Earth Moving.

[13]  Thierry Toutin,et al.  Impact of terrain slope and aspect on radargrammetric DEM accuracy , 2002 .

[14]  David W. S. Wong,et al.  Effects of DEM sources on hydrologic applications , 2010, Comput. Environ. Urban Syst..

[15]  Liang-pei Zhang,et al.  High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations , 2017 .

[16]  Richard Barnes,et al.  Priority-Flood: An Optimal Depression-Filling and Watershed-Labeling Algorithm for Digital Elevation Models , 2015, Comput. Geosci..

[17]  J. Bryan Blair,et al.  Validation of SRTM Elevations Over Vegetated and Non-vegetated Terrain Using Medium-Footprint Lidar , 2006 .

[18]  Nicholas J. Tate,et al.  Improving user assessment of error implications in digital elevation models , 2008, Comput. Environ. Urban Syst..

[19]  Philippe J. J. Desmet,et al.  Effects of Interpolation Errors on the Analysis of DEMs , 1997 .

[20]  Ashton Shortridge Shuttle Radar Topography Mission Elevation Data Error and Its Relationship to Land Cover , 2006 .

[21]  F. O'Loughlin,et al.  A multi-sensor approach towards a global vegetation corrected SRTM DEM product , 2016 .

[22]  Mike J. Smith,et al.  Methods for the visualization of digital elevation models for landform mapping , 2005 .

[23]  Robert P. Guralnick,et al.  EarthEnv-DEM90: A nearly-global, void-free, multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data , 2014 .

[24]  Paul D. Bates,et al.  Perspectives on Open Access High Resolution Digital Elevation Models to Produce Global Flood Hazard Layers , 2016, Front. Earth Sci..

[25]  Sajid Ghuffar,et al.  DEM Generation from Multi Satellite PlanetScope Imagery , 2018, Remote. Sens..

[26]  Scott Kulp,et al.  CoastalDEM: A global coastal digital elevation model improved from SRTM using a neural network , 2018 .

[27]  P. Bates,et al.  Effects of spatial resolution on a raster based model of flood flow , 2001 .

[28]  Paul D. Bates,et al.  Implications of Simulating Global Digital Elevation Models for Flood Inundation Studies , 2018, Water Resources Research.

[29]  Alfred J. Kalyanapu,et al.  Accounting digital elevation uncertainty for flood consequence assessment , 2018 .

[30]  Q. Guo,et al.  Effects of Topographic Variability and Lidar Sampling Density on Several DEM Interpolation Methods , 2010 .

[31]  Trevor J. Davis,et al.  Modelling Uncertainty in Natural Resource Analysis Using Fuzzy Sets and Monte Carlo Simulation: Slope Stability Prediction , 1997, Int. J. Geogr. Inf. Sci..

[32]  Paul D. Bates,et al.  When does spatial resolution become spurious in probabilistic flood inundation predictions? , 2016 .

[33]  C. Sampson,et al.  Benchmarking urban flood models of varying complexity and scale using high resolution terrestrial LiDAR data , 2011 .

[34]  S. Coveney,et al.  Lightweight UAV digital elevation models and orthoimagery for environmental applications: data accuracy evaluation and potential for river flood risk modelling , 2017 .

[35]  P. Bates,et al.  Quantifying the importance of spatial resolution and other factors through global sensitivity analysis of a flood inundation model , 2016 .

[36]  Qiuhua Liang,et al.  Hydraulic correction method (HCM) to enhance the efficiency of SRTM DEM in flood modeling , 2018 .

[37]  Keiko Saito,et al.  An urgent case for higher resolution digital elevation models in the world's poorest and most vulnerable countries , 2015, Front. Earth Sci..

[38]  Takahiro Sayama,et al.  CORRECTION OF SRTM DEM ARTEFACTS BY FOURIER TRANSFORM FOR FLOOD INUNDATION MODELING , 2013 .

[39]  P. Burrough,et al.  Principles of geographical information systems , 1998 .

[40]  Ian T. Jolliffe,et al.  Evaluating Rank Histograms Using Decompositions of the Chi-Square Test Statistic , 2008 .

[41]  Venkatesh Merwade,et al.  Incorporating the effect of DEM resolution and accuracy for improved flood inundation mapping , 2015 .

[42]  Christian Hirt,et al.  Artefact detection in global digital elevation models (DEMs): The maximum slope approach and its application for complete screening of the SRTM v4.1 and MERIT DEMs , 2018 .

[43]  Stephen Wise,et al.  Cross-validation as a means of investigating DEM interpolation error , 2011, Comput. Geosci..

[44]  Tommaso Moramarco,et al.  Exploring the Potential of SRTM Topography and Radar Altimetry to Support Flood Propagation Modeling: Danube Case Study , 2015 .

[45]  T. Hamill Interpretation of Rank Histograms for Verifying Ensemble Forecasts , 2001 .

[46]  P. Bates,et al.  A subgrid channel model for simulating river hydraulics and floodplain inundation over large and data sparse areas , 2012 .

[47]  Michelle L. Murillo,et al.  Assessing uncertainty due to elevation error in a landslide susceptibility model , 1997 .

[48]  Michael F. Hutchinson,et al.  Digital elevation models and representation of terrain shape , 2000 .

[49]  Michael J. Collins,et al.  The effect of error in gridded digital elevation models on the estimation of topographic parameters , 2006, Environ. Model. Softw..

[50]  Takeo Tadono,et al.  Quality updates of ‘AW3D’ global DSM generated from ALOS PRISM , 2017, 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[51]  P. Bates,et al.  Distributed whole city water level measurements from the Carlisle 2005 urban flood event and comparison with hydraulic model simulations , 2009 .

[52]  M. Hutchinson A new procedure for gridding elevation and stream line data with automatic removal of spurious pits , 1989 .

[53]  Maxim Neumann,et al.  NASADEM GLOBAL ELEVATION MODEL: METHODS AND PROGRESS , 2016 .

[54]  Peter F. Fisher,et al.  Causes and consequences of error in digital elevation models , 2006 .

[55]  P. Bates,et al.  Evaluation of 1D and 2D numerical models for predicting river flood inundation , 2002 .

[56]  Suzanne P. Wechsler,et al.  Perceptions of Digital Elevation Model Uncertainty by DEM Users , 2003 .

[57]  K. Holmesa,et al.  Error in a USGS 30-meter digital elevation model and its impact on terrain modeling , 2000 .

[58]  Stephen Wise,et al.  Assessing the quality for hydrological applications of digital elevation models derived from contours , 2000 .

[59]  Joseph P. Messina,et al.  The Influence of Land Cover on Shuttle Radar Topography Mission (SRTM) Elevations in Low‐relief Areas , 2010, Trans. GIS.

[60]  Paul D. Bates,et al.  SRTM vegetation removal and hydrodynamic modeling accuracy , 2013 .

[61]  A. Edwards,et al.  Characterizing errors in digital elevation models and estimating the financial costs of accuracy , 2010, Int. J. Geogr. Inf. Sci..

[62]  Paul D. Bates,et al.  Technology: Fight floods on a global scale , 2014, Nature.

[63]  Thomas M. Hamill,et al.  Verification of Eta–RSM Short-Range Ensemble Forecasts , 1997 .

[64]  Lucy Marshall,et al.  A method for combining SRTM DEM and ASTER GDEM2 to improve topography estimation in regions without reference data , 2018, Remote Sensing of Environment.

[65]  W. Tobler A Computer Movie Simulating Urban Growth in the Detroit Region , 1970 .

[66]  Gergely Szabó,et al.  Slope angle and aspect as influencing factors on the accuracy of the SRTM and the ASTER GDEM databases , 2015 .

[67]  Michael F. Goodchild,et al.  Geostatistics for conflation and accuracy assessment of digital elevation models , 1999, Int. J. Geogr. Inf. Sci..

[68]  S. M. Wise,et al.  Effect of differing DEM creation methods on the results from a hydrological model , 2007, Comput. Geosci..

[69]  K. Verdin,et al.  New Global Hydrography Derived From Spaceborne Elevation Data , 2008 .

[70]  F. Dottori,et al.  Detailed data is welcome, but with a pinch of salt: Accuracy, precision, and uncertainty in flood inundation modeling , 2013 .

[71]  Abdollah A. Jarihani,et al.  Satellite-derived Digital Elevation Model (DEM) selection, preparation and correction for hydrodynamic modelling in large, low-gradient and data-sparse catchments , 2015 .

[72]  Seth J Wenger,et al.  The influence of land cover on the sensitivity of streams to metal pollution. , 2018, Water research.

[73]  Guohe Huang,et al.  A study on DEM-derived primary topographic attributes for hydrologic applications: Sensitivity to elevation data resolution , 2008 .

[74]  P. Atkinson,et al.  Prediction uncertainty in elevation and its effect on flood inundation modelling , 2003 .

[75]  H. Veregin The Effects of Vertical Error in Digital Elevation Models on the Determination of Flow-path Direction , 1997 .

[76]  Tapani Sarjakoski,et al.  Error propagation of DEM-based surface derivatives , 2005, Comput. Geosci..

[77]  Ashton Shortridge,et al.  Spatial structure and landscape associations of SRTM error , 2011 .

[78]  Q. Guo,et al.  A global corrected SRTM DEM product for vegetated areas , 2018 .

[79]  Ø. Dick,et al.  SRTM DEM accuracy assessment over vegetated areas in Norway , 2007 .

[80]  Aaron A. Berg,et al.  Evaluating DEM conditioning techniques, elevation source data, and grid resolution for field-scale hydrological parameter extraction , 2016 .

[81]  J. I. House,et al.  Comparing TanDEM‐X Data With Frequently Used DEMs for Flood Inundation Modeling , 2018, Water Resources Research.

[82]  S. Kanae,et al.  A high‐accuracy map of global terrain elevations , 2017 .

[83]  Josef Kellndorfer,et al.  Quality assessment of SRTM C- and X-band interferometric data: Implications for the retrieval of vegetation canopy height , 2007 .

[84]  Theodore A. Endreny,et al.  Representing elevation uncertainty in runoff modelling and flowpath mapping , 2001 .

[85]  Kevin Amaratunga,et al.  Analysis and characterization of the vertical accuracy of digital elevation models from the Shuttle Radar Topography Mission , 2005 .

[86]  Frédérique Seyler,et al.  Correction of Interferometric and Vegetation Biases in the SRTMGL1 Spaceborne DEM with Hydrological Conditioning towards Improved Hydrodynamics Modeling in the Amazon Basin , 2015, Remote. Sens..

[87]  A. S. Toprak,et al.  DEM generation with UAV Photogrammetry and accuracy analysis in Sahitler hill , 2015 .

[88]  Takeo Tadono,et al.  PRECISE GLOBAL DEM GENERATION BY ALOS PRISM , 2014 .

[89]  Nicholas C. Coops,et al.  Evaluating error associated with lidar-derived DEM interpolation , 2009, Comput. Geosci..

[90]  Peter Bunting,et al.  Enhancing digital elevation models for hydraulic modelling using flood frequency detection , 2018, Remote Sensing of Environment.

[91]  Bruce H. Carlisle,et al.  Modelling the Spatial Distribution of DEM Error , 2005, Trans. GIS.

[92]  Jie Shan,et al.  Evaluation of Recently Released Open Global Digital Elevation Models of Hubei, China , 2017, Remote. Sens..

[93]  P. Fisher First experiments in viewshed uncertainty : the accuracy of the viewshed area , 1991 .

[94]  Jeffrey L. Anderson A Method for Producing and Evaluating Probabilistic Forecasts from Ensemble Model Integrations , 1996 .

[95]  Gerhard Krieger,et al.  Generation and performance assessment of the global TanDEM-X digital elevation model , 2017 .

[96]  J. Neal,et al.  Modelling of flood hazard extent in data sparse areas: a case study of the Oti River basin, West Africa , 2017 .

[97]  C. Hirt,et al.  Comparison of free high resolution digital elevation data sets (ASTER GDEM2, SRTM v2.1/v4.1) and validation against accurate heights from the Australian National Gravity Database , 2014 .