scholarly journals Technical Note: Automatic river network generation for a physically-based river catchment model

2010 ◽  
Vol 14 (9) ◽  
pp. 1767-1771 ◽  
Author(s):  
S. J. Birkinshaw
Keyword(s):  
Automatic Generation ◽  
Technical Note ◽  
River Channel ◽  
River Channels ◽  
Channel Network ◽  
Channel Networks ◽  
Distributed Modelling ◽  
Digital Elevation ◽  
Physically Based ◽  
Elevation Data

Abstract. SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.

scholarly journals Technical Note: Automatic river network generation for a physically-based river catchment model

2010 ◽  
Vol 7 (3) ◽  
pp. 3237-3248
Author(s):  
S. J. Birkinshaw
Keyword(s):  
Automatic Generation ◽  
Technical Note ◽  
River Channel ◽  
River Channels ◽  
Channel Network ◽  
Channel Networks ◽  
Distributed Modelling ◽  
Digital Elevation ◽  
Physically Based ◽  
Elevation Data

Abstract. SHETRAN is a physically-based distributed modelling system that gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. Standard algorithms for the automatic generation of river channel networks from digital elevation data are impossible to apply in SHETRAN and other similar models because the river channels are assumed to run along the edges of grid cells. In this work a new algorithm for the automatic generation of a river channel network in SHETRAN is described and its use in an example catchment demonstrated.

scholarly journals An Improved Method Constructing 3D River Channel for Flood Modeling

Water ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 403 ◽  
Author(s):  
Pengbo Hu ◽  
Jingming Hou ◽  
Zaixing Zhi ◽  
Bingyao Li ◽  
Kaihua Guo
Keyword(s):  
High Resolution ◽  
River Channel ◽  
Hydrodynamic Process ◽  
River Channels ◽  
Section Data ◽  
Terrain Model ◽  
Digital Elevation ◽  
Hydrodynamic Processes ◽  
Hermite Spline ◽  
Elevation Model

The high-resolution topography is very crucial to investigate the hydrological and hydrodynamic process. To resolve the deficiency problem of high resolution terrain data in rivers, the Quartic Hermite Spline with Parameter (QHSP) method constructing the river channel terrain based on the limited cross-section data is presented. The proposed method is able to not only improve the reliability of the constructed river terrain, but also avoid the numerical oscillations caused by the existing constructing approach, e.g., the Cubic Hermite Spline (CHS) method. The performance of the proposed QHSP method is validated against two benchmark tests. Comparing the constructed river terrains, the QHSP method can improve the accuracy by at least 15%. For the simulated flood process, the QHSP method could reproduce more acceptable modeling results as well, e.g., in Wangmaogou catchment, the numerical model applying the Digital Elevation Model (DEM) produced by the QHSP method could increase the reliability by 18.5% higher than that of CHS method. It is indicated that the QHSP method is more reliable for river terrain model construction than the CHS and is a more reasonable tool investigating the hydrodynamic processes in river channels lacking of high resolution topography data.

On the extraction of channel networks from digital elevation data

1991 ◽  
Vol 5 (1) ◽  
pp. 81-100 ◽  
Author(s):  
David G. Tarboton ◽  
Rafael L. Bras ◽  
Ignacio Rodriguez-Iturbe
Keyword(s):  
Channel Networks ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data

scholarly journals Determining flow directions in river channel networks using planform morphology and topology

2020 ◽  
Vol 8 (1) ◽  
pp. 87-102 ◽  
Author(s):  
Jon Schwenk ◽  
Anastasia Piliouras ◽  
Joel C. Rowland
Keyword(s):  
Flow Direction ◽  
Remotely Sensed ◽  
River Channel ◽  
Braided River ◽  
Channel Network ◽  
Channel Networks ◽  
Braided Rivers ◽  
Morphologic Characteristic ◽  
Network Topologies ◽  
Flow Directions

Abstract. The abundance of global, remotely sensed surface water observations has accelerated efforts toward characterizing and modeling how water moves across the Earth's surface through complex channel networks. In particular, deltas and braided river channel networks may contain thousands of links that route water, sediment, and nutrients across landscapes. In order to model flows through channel networks and characterize network structure, the direction of flow for each link within the network must be known. In this work, we propose a rapid, automatic, and objective method to identify flow directions for all links of a channel network using only remotely sensed imagery and knowledge of the network's inlet and outlet locations. We designed a suite of direction-predicting algorithms (DPAs), each of which exploits a particular morphologic characteristic of the channel network to provide a prediction of a link's flow direction. DPAs were chained together to create “recipes”, or algorithms that set all the flow directions of a channel network. Separate recipes were built for deltas and braided rivers and applied to seven delta and two braided river channel networks. Across all nine channel networks, the recipe-predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreements were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions. Our results highlight the (non)universality of process–form relationships across deltas and braided rivers.

scholarly journals Determining flow directions in river channel networks using planform morphology and topology

2019 ◽  
Author(s):  
Jon Schwenk ◽  
Anastasia Piliouras ◽  
Joel C. Rowland
Keyword(s):  
Flow Direction ◽  
Remotely Sensed ◽  
River Channel ◽  
Braided River ◽  
Channel Network ◽  
Channel Networks ◽  
Braided Rivers ◽  
Morphologic Characteristic ◽  
Network Topologies ◽  
Flow Directions

Abstract. The abundance of global, remotely-sensed surface water observations has paved the way toward characterizing and modeling how water moves across the Earth's surface through complex channel networks. In particular, deltas and braided river channel networks may contain thousands of links that route water, sediment, and nutrients across landscapes. In order to model flows through channel networks and characterize network structure, the direction of flow for each link within the network must be known. In this work, we propose a rapid, automatic, and objective method to identify flow directions for all links of a channel network using only remotely-sensed imagery and knowledge of the network's inlet and outlet locations. We designed a suite of direction-predicting algorithms (DPAs), each of which exploits a particular morphologic characteristic of the channel network to provide a prediction of a link's flow direction. DPAs were chained together to create “recipes”, or algorithms that set all the flow directions of a channel network. Separate recipes were built for deltas and braided rivers and applied to seven delta and two braided river channel networks. Across all nine channel networks, the recipes' predicted flow directions agreed with expert judgement for 97 % of all tested links, and most disagreements were attributed to unusual channel network topologies that can easily be accounted for by pre-seeding critical links with known flow directions.

On the expected width function for topologically random channel networks

1984 ◽  
Vol 21 (4) ◽  
pp. 836-849 ◽  
Author(s):  
Brent M. Troutman ◽  
Michael R. Karlinger
Keyword(s):  
River Channel ◽  
Plane Tree ◽  
Channel Network ◽  
Channel Networks ◽  
Width Function ◽  
Expected Width

An idealized river-channel network is represented by a trivalent planted plane tree, the root of which corresponds to the outlet of the network. A link of the network is any segment between a source and a junction, two successive junctions, or the outlet and a junction. For any x≧0, the width of the network is the number of links with the property that the distance of the downstream junction from the outlet is ≦x, and the distance of the upstream junction to the outlet is > x. Expressions are obtained for the expected width conditioned on N, (N, M), and (N, D), where N is the magnitude, M the order, and D the diameter of the network, under the assumption that the network is drawn from an infinite topologically random population and the link lengths are random.

On the expected width function for topologically random channel networks

1984 ◽  
Vol 21 (04) ◽  
pp. 836-849 ◽  
Author(s):  
Brent M. Troutman ◽  
Michael R. Karlinger
Keyword(s):  
River Channel ◽  
Plane Tree ◽  
Channel Network ◽  
Channel Networks ◽  
Width Function ◽  
Expected Width

An idealized river-channel network is represented by a trivalent planted plane tree, the root of which corresponds to the outlet of the network. A link of the network is any segment between a source and a junction, two successive junctions, or the outlet and a junction. For any x≧0, the width of the network is the number of links with the property that the distance of the downstream junction from the outlet is ≦x, and the distance of the upstream junction to the outlet is > x. Expressions are obtained for the expected width conditioned on N, (N, M), and (N, D), where N is the magnitude, M the order, and D the diameter of the network, under the assumption that the network is drawn from an infinite topologically random population and the link lengths are random.

Urban Flood Mapping

2017 ◽  
Author(s):  
Indra Riyanto ◽  
Lestari Margatama
Keyword(s):  
Natural Disasters ◽  
Satisfying Condition ◽  
Three Dimensions ◽  
Urban Flood ◽  
Digital Elevation ◽  
Elevation Data ◽  
Recent Occurrence ◽  
Elevation Model ◽  
Digital Elevation Model Data ◽  
Potential Area

The recent degradation of environment quality becomes the prime cause of the recent occurrence of natural disasters. It also contributes in the increase of the area that is prone to natural disasters. Flood history data in Jakarta shows that flood occurred mainly during rainy season around January – February each year, but the flood area varies each year. This research is intended to map the flood potential area in DKI Jakarta by segmenting the Digital Elevation Model data. The data used in this research is contour data obtained from DPP–DKI with the resolution of 1 m. The data processing involved in this research is extracting the surface elevation data from the DEM, overlaying the river map of Jakarta with the elevation data. Subsequently, the data is then segmented using watershed segmentation method. The concept of watersheds is based on visualizing an image in three dimensions: two spatial coordinates versus gray levels, in which there are two specific points; that are points belonging to a regional minimum and points at which a drop of water, if placed at the location of any of those points, would fall with certainty to a single minimum. For a particular regional minimum, the set of points satisfying the latter condition is called the catchments basin or watershed of that minimum, while the points satisfying condition form more than one minima are termed divide lines or watershed lines. The objective of this segmentation is to find the watershed lines of the DEM image. The expected result of the research is the flood potential area information, especially along the Ciliwung river in DKI Jakarta.

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