A robust, two-parameter method for the extraction of drainage networks from high-resolution digital elevation models (DEMs): Evaluation using synthetic and real-world DEMs

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Abstract

In this article, a method for drainage network extraction from high-resolution digital elevation models (DEMs; e.g., those derived from airborne laser swath mapping) is presented, which requires just two user-defined parameters and is capable of handling discontinuous valley networks. The accuracy and robustness of the method are illustrated using synthetic valley networks that mimic the complexities of real landscapes and for which the true drainage network is known exactly by construction. The method involves six principal steps: optimal Wiener filtering to remove microtopographic noise, mapping of the contour curvature, identification of valley heads using a user-defined contour-curvature threshold criterion, routing of a unit discharge of water from each valley head using a multiple-flow-direction routing algorithm, removal of discontinuous reaches from the drainage network using a user-defined discharge-per-upstream-valley-head threshold criterion, and thinning of the valley network to a single pixel width. The method yields accurate results using the same user-defined parameters for the two field sites considered in this study, suggesting that for DEMs with resolution of approximately 1 m, the method has the ability to produce accurate results for a variety of landscapes by using the same parameter values used in this study.

Original languageEnglish (US)
Pages (from-to)75-89
Number of pages15
JournalWater Resources Research
Volume49
Issue number1
DOIs
StatePublished - 2013

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drainage network
digital elevation model
valley
routing
curvature
thinning
parameter
evaluation
method
pixel
laser

ASJC Scopus subject areas

  • Water Science and Technology

Cite this

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title = "A robust, two-parameter method for the extraction of drainage networks from high-resolution digital elevation models (DEMs): Evaluation using synthetic and real-world DEMs",
abstract = "In this article, a method for drainage network extraction from high-resolution digital elevation models (DEMs; e.g., those derived from airborne laser swath mapping) is presented, which requires just two user-defined parameters and is capable of handling discontinuous valley networks. The accuracy and robustness of the method are illustrated using synthetic valley networks that mimic the complexities of real landscapes and for which the true drainage network is known exactly by construction. The method involves six principal steps: optimal Wiener filtering to remove microtopographic noise, mapping of the contour curvature, identification of valley heads using a user-defined contour-curvature threshold criterion, routing of a unit discharge of water from each valley head using a multiple-flow-direction routing algorithm, removal of discontinuous reaches from the drainage network using a user-defined discharge-per-upstream-valley-head threshold criterion, and thinning of the valley network to a single pixel width. The method yields accurate results using the same user-defined parameters for the two field sites considered in this study, suggesting that for DEMs with resolution of approximately 1 m, the method has the ability to produce accurate results for a variety of landscapes by using the same parameter values used in this study.",
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N2 - In this article, a method for drainage network extraction from high-resolution digital elevation models (DEMs; e.g., those derived from airborne laser swath mapping) is presented, which requires just two user-defined parameters and is capable of handling discontinuous valley networks. The accuracy and robustness of the method are illustrated using synthetic valley networks that mimic the complexities of real landscapes and for which the true drainage network is known exactly by construction. The method involves six principal steps: optimal Wiener filtering to remove microtopographic noise, mapping of the contour curvature, identification of valley heads using a user-defined contour-curvature threshold criterion, routing of a unit discharge of water from each valley head using a multiple-flow-direction routing algorithm, removal of discontinuous reaches from the drainage network using a user-defined discharge-per-upstream-valley-head threshold criterion, and thinning of the valley network to a single pixel width. The method yields accurate results using the same user-defined parameters for the two field sites considered in this study, suggesting that for DEMs with resolution of approximately 1 m, the method has the ability to produce accurate results for a variety of landscapes by using the same parameter values used in this study.

AB - In this article, a method for drainage network extraction from high-resolution digital elevation models (DEMs; e.g., those derived from airborne laser swath mapping) is presented, which requires just two user-defined parameters and is capable of handling discontinuous valley networks. The accuracy and robustness of the method are illustrated using synthetic valley networks that mimic the complexities of real landscapes and for which the true drainage network is known exactly by construction. The method involves six principal steps: optimal Wiener filtering to remove microtopographic noise, mapping of the contour curvature, identification of valley heads using a user-defined contour-curvature threshold criterion, routing of a unit discharge of water from each valley head using a multiple-flow-direction routing algorithm, removal of discontinuous reaches from the drainage network using a user-defined discharge-per-upstream-valley-head threshold criterion, and thinning of the valley network to a single pixel width. The method yields accurate results using the same user-defined parameters for the two field sites considered in this study, suggesting that for DEMs with resolution of approximately 1 m, the method has the ability to produce accurate results for a variety of landscapes by using the same parameter values used in this study.

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