A phenomenon‐based approach to upslope contributing area and depressions in DEMs

Description of the terrain surface through digital elevation models (DEMs) strongly depends on data collection methods and DEM data structures. For efficiency and availability reasons regular point distributions are most common, which yield artefacts such as depressions and preferential flow directions. These facts need to be considered when natural phenomena are modelled, as is shown for handling depressions and for estimation of flow paths and upslope contributing areas. Analysis of the main reasons for the occurrence of depressions shows that they usually better reflect the terrain than their surroundings. Thus, the most common remedial method of raising depressions is rejected. Algorithms that 'cut' a flow path from the depression through its bounding barrier are favoured instead. Several flow routing algorithms are evaluated for their behaviour in regular grids. It is shown that the multiple flow direction (mfd) algorithm that distributes water from a grid cell to the lower of its eight neighbours proportionally to their elevation differences (slope) exhibits correct flow directions and the best rotation invariance. It is suggested that the estimation of upslope contributing areas (TCAs) is undertaken in two steps: first, a high quality flow direction data set is derived by a well-behaved mfd algorithm or by subgrid modelling of flow paths; secondly, the upslope contributing areas are obtained by counting the upslope elements.

[1]  R. Freeze,et al.  Blueprint for a physically-based, digitally-simulated hydrologic response model , 1969 .

[2]  Malcolm G. Anderson,et al.  The role of topography in controlling throughflow generation , 1978 .

[3]  L. F. Huggins,et al.  ANSWERS: A Model for Watershed Planning , 1980 .

[4]  D. Zasłavsky,et al.  Surface Hydrology: I—Explanation of Phenomena , 1981 .

[5]  Vincent M. Caruso,et al.  Digital elevation models , 1983 .

[6]  John F. O'Callaghan,et al.  The extraction of drainage networks from digital elevation data , 1984, Comput. Vis. Graph. Image Process..

[7]  J. Dozier,et al.  Automated basin delineation from digital elevation data , 1984 .

[8]  B. Makarovic,et al.  Structures for geo-information and their application in selective sampling for digital terrain models , 1984 .

[9]  E. O'Loughlin.  Prediction of Surface Saturation Zones in Natural Catchments by Topographic Analysis , 1986 .

[10]  O. Palacios-Velez,et al.  Automated river-course, ridge and basin delineation from digital elevation data , 1986 .

[11]  L. Band.  Topographic Partition of Watersheds with Digital Elevation Models , 1986 .

[12]  S. K. Jenson,et al.  Extracting topographic structure from digital elevation data for geographic information-system analysis , 1988 .

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

[14]  James B. Campbell,et al.  DNESYS-an expert system for automatic extraction of drainage networks from digital elevation data , 1990 .

[15]  F. C. Hadipriono,et al.  The development of a knowledge-based expert system for analysis of drainage patterns , 1990 .

[16]  A. Skidmore.  Terrain position as mapped from a gridded digital elevation model , 1990 .

[17]  K. Beven,et al.  THE PREDICTION OF HILLSLOPE FLOW PATHS FOR DISTRIBUTED HYDROLOGICAL MODELLING USING DIGITAL TERRAIN MODELS , 1991 .

[18]  J. Fairfield,et al.  Drainage networks from grid digital elevation models , 1991 .

[19]  I. Moore,et al.  Terrain‐based catchment partitioning and runoff prediction using vector elevation data , 1991 .

[20]  Heinrich Ebner,et al.  Automatic derivation of skeleton lines from digitized contours , 1991 .

[21]  David G. Tarboton,et al.  On the extraction of channel networks from digital elevation data , 1991 .

[22]  I. Moore,et al.  Digital terrain modelling: A review of hydrological, geomorphological, and biological applications , 1991 .

[23]  Charles Ichoku,et al.  A combined algorithm for automated drainage network extraction , 1992 .

[24]  K. Tempfli,et al.  A digital image processing approach to creating DTMs from digitized contours , 1992 .

[25]  Nicholas J. Lea,et al.  An Aspect-Driven Kinematic Routing Algorithm , 1992 .

[26]  Andrea Tribe,et al.  Automated recognition of valley lines and drainage networks from grid digital elevation models: a review and a new method , 1992 .

[27]  Mark Gahegan,et al.  Feature-Based Derivation of Drainage Networks , 1993, Int. J. Geogr. Inf. Sci..

[28]  M. Bonell.  Progress in the understanding of runoff generation dynamics in forests , 1993 .

[29]  Ian D. Moore,et al.  Terrain attributes: estimation methods and scale effects , 1993 .

[30]  K. Beven,et al.  Terrain analysis and distributed modelling in hydrology , 1993 .

[31]  M. Costa-Cabral,et al.  Digital Elevation Model Networks (DEMON): A model of flow over hillslopes for computation of contributing and dispersal areas , 1994 .

[32]  D. Montgomery,et al.  Digital elevation model grid size, landscape representation, and hydrologic simulations , 1994 .

[33]  Mike Kirkby,et al.  Process models and theoretical geomorphology , 1994 .

[34]  Randomness in geomorphological process response models , 1994 .

[35]  A. Meijerink.  Introduction to the use of geographic information systems for practical hydrology , 1994 .

[36]  Gregory J. McCabe,et al.  Comparison of Single and Multiple Flow Direction Algorithms for Computing Topographic Parameters in TOPMODEL , 1995 .

[37]  M. B. Beck,et al.  Modelling Change in Environmental Systems , 1995 .

[38]  Dieter Fritsch,et al.  The TopoSys Laser Scanner-System , 1995 .

[39]  K. Beven,et al.  The in(a/tan/β) index:how to calculate it and how to use it within the topmodel framework , 1995 .

[40]  N. Haala,et al.  Capture Andevaluation of Airborne Laser Scanner Data , 1996 .

[41]  P. J. J. Desmet,et al.  Comparison of Routing Algorithms for Digital Elevation Models and Their Implications for Predicting Ephemeral Gullies , 1996, Int. J. Geogr. Inf. Sci..

[42]  Reply [to Comment on Digital Elevation Model Grid Size, Landscape Representation, and Hydrologic S , 1996 .

[43]  E. Næsset.  Determination of mean tree height of forest stands using airborne laser scanner data , 1997 .

[44]  Carl Gerstenecker,et al.  Digital Elevation Models for Mount Merapi , 2000 .