A differential equation for specific catchment area

Gallant, John; Hutchinson, Michael F.

doi:10.1029/2009wr008540

Cited by 59 publications

(100 citation statements)

References 45 publications

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“…where α s = specific contributing area, and tan β = local slope (Frankenberger et al, 1999;Sorenson et al, 2005). Here, specific contributing area is defined as the total upslope area contributing flow to a given location, divided by the specific contour length (Chirico et al, 2005;Galant and Hutchinson, 2011). The DEM cell edge length has been applied as the value for specific contour length in several terrain analyses (Zhang and Montgomery, 1994;Wolock and McCabe, 1995).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of digital channel network derivation methods in a glaciated subalpine catchment

Hastings

Kampf

2014

Earth Surf Processes Landf

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The digital elevation model (DEM) has become an essential tool for an increasing array of mountain runoff analyses, particularly the derivation and mapping of stream channel networks. This study examines how well commonly applied DEM‐based channel derivation methods at different spatial resolutions can represent the channel network for a glaciated Rocky Mountain headwater catchment. The specific objectives are to (1) examine how differences in gridded DEM resolution affect spatially distributed values of local slope, specific contributing area, and topographic wetness index derived from both eight and infinite directional flow algorithms, (2) map the actual stream channel network to examine the influence of surface variables on channel initiation, and (3) assess accuracy of DEM‐derived networks compared with the field surveyed network. Results show that for the same contributing area threshold, increasing grid cell size leads to increased channelization of modeled networks. A plot of local slope versus contributing area reveals a negative relationship similar to that of prior studies in un‐glaciated areas but with breaks in slope at contributing areas that are too small to represent thresholds for channelization. Field survey results and evaluation of DEM‐derived channel networks suggest that channel network formation is not clearly related to surface topographic variables at Loch Vale. Digitally derived channel networks do not accurately predict low order channel locations, but approximations of the channel network with drainage density and headward extent of channelization similar to the observed network can be derived with both a 1 m and 10 m DEM using a contributing area threshold of approximately 4x104 m2. Copyright © 2014 John Wiley & Sons, Ltd.

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Section: Introductionmentioning

confidence: 99%

Evaluation of digital channel network derivation methods in a glaciated subalpine catchment

Hastings

Kampf

2014

Earth Surf Processes Landf

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“…However, if the flow is also affected by surface forces implying for instance significant pressure or stress gradients, then flow lines are not necessarily the same as slope lines and flow dispersion becomes a relevant process. The distinction between slope and flow lines is outlined by Tarboton [1997] and Orlandini et al [2003], and is explicitly made by Gallant and Hutchinson [2011]. In light of this distinction, the term “flow direction method” used in terrain analysis, hydrology, and fluvial geomorphology may not be entirely appropriate.…”

Section: Introductionmentioning

confidence: 99%

“…The attention is focused in this paper on dominant classes of terrain analysis methods designed to process grid digital elevation models. Reviews of these methods can be found by Tarboton [1997], Orlandini and Moretti [2009], and Gallant and Hutchinson [2011]. Methods designed to process contour digital elevation models [e.g., Moretti and Orlandini , 2008] or based on the aspect driven method of Lea [1992] [e.g., Costa‐Cabral and Burges , 1994] are not evaluated in this paper.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of flow direction methods against field observations of overland flow dispersion

Orlandini

Moretti

Corticelli

et al. 2012

Water Resources Research

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The D8, D8-LTD, D∞-LTD, D∞, MD∞, and MD8 flow direction methods are evaluated against field observations of overland flow dispersion obtained from novel experimental methods. Thin flows of cold water were released at selected points on a warmer slope and individual overland flow patterns originating from each of these points were observed using a terrestrial laser scanner and a thermal imaging camera. Land microtopography was determined by using laser returns from the dry land surface, whereas overland flow patterns were determined by using either laser returns or infrared emissions from the wetted portions of the land surface. Planar overland flow dispersion is found to play an important role in the region laying immediately downslope of the point source, but attenuates rapidly as flow propagates downslope. In contrast, existing dispersive flow direction methods are found to provide a continued dispersion with distance downslope. Predicted propagation patterns, for all methods considered here, depend critically on the size h of grid cells involved. All methods are found to be poorly sensitive in extremely fine grids (h ≤ 2 cm), and to be poorly specific in coarse grids (h = 2 m). Satisfactory results are, however, obtained in grids having resolutions h that approach the average flow width (50 cm), with the best performances displayed by the MD8 method in the finest grids (5 ≤ h ≤ 20 cm), and by the MD∞, D∞, and D∞-LTD methods in the coarsest grids (20 cm < h ≤ 1 m)

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“…extraction because they are able to simulate stream flow over the terrain (Freeman, 1991;Gallant & Hutchinson, 2011;Holmgren, 1994;Ibbitt, Willgoose, & Duncan, 1999;O'Callaghan & Mark, 1984;Orlandini, Moretti, Franchini, Aldighieri, & Testa, 2003;Pilesjö & Hasan, 2014;Quinn, Beven, Chevallier, & Planchon, 1991;Tarboton, 1997;Turcotte, Fortin, Rousseau, Massicotte, & Villeneuve, 2001;Xiong, Tang, Yan, Zhu, & Sun, 2014;Zhou, Pilesjö, & Chen, 2011).…”

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confidence: 99%

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

Yan

Tang

Pilesjö

2018

Hydrological Processes

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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.

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A differential equation for specific catchment area

Cited by 59 publications

References 45 publications

Evaluation of digital channel network derivation methods in a glaciated subalpine catchment

Evaluation of digital channel network derivation methods in a glaciated subalpine catchment

Evaluation of flow direction methods against field observations of overland flow dispersion

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

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