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.

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 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 Entropy and optimality in river deltas

2017 ◽  
Vol 114 (44) ◽  
pp. 11651-11656 ◽  
Author(s):  
Alejandro Tejedor ◽  
Anthony Longjas ◽  
Douglas A. Edmonds ◽  
Ilya Zaliapin ◽  
Tryphon T. Georgiou ◽  
...  
Keyword(s):  
Anthropogenic Activities ◽  
Sediment Flux ◽  
Channel Network ◽  
Channel Networks ◽  
Form And Function ◽  
River Deltas ◽  
Self Organized ◽  
Water And Sediment ◽  
Network Topologies ◽  
And Function

The form and function of river deltas is intricately linked to the evolving structure of their channel networks, which controls how effectively deltas are nourished with sediments and nutrients. Understanding the coevolution of deltaic channels and their flux organization is crucial for guiding maintenance strategies of these highly stressed systems from a range of anthropogenic activities. To date, however, a unified theory explaining how deltas self-organize to distribute water and sediment up to the shoreline remains elusive. Here, we provide evidence for an optimality principle underlying the self-organized partition of fluxes in delta channel networks. By introducing a suitable nonlocal entropy rate (nER) and by analyzing field and simulated deltas, we suggest that delta networks achieve configurations that maximize the diversity of water and sediment flux delivery to the shoreline. We thus suggest that prograding deltas attain dynamically accessible optima of flux distributions on their channel network topologies, thus effectively decoupling evolutionary time scales of geomorphology and hydrology. When interpreted in terms of delta resilience, high nER configurations reflect an increased ability to withstand perturbations. However, the distributive mechanism responsible for both diversifying flux delivery to the shoreline and dampening possible perturbations might lead to catastrophic events when those perturbations exceed certain intensity thresholds.

scholarly journals Geometry and Topology of Estuary and Braided River Channel Networks Automatically Extracted From Topographic Data

2020 ◽  
Vol 125 (1) ◽  
Author(s):  
Matthew Hiatt ◽  
Willem Sonke ◽  
Elisabeth A. Addink ◽  
Wout M. Dijk ◽  
Marc Kreveld ◽  
...  
Keyword(s):  
River Channel ◽  
Braided River ◽  
Channel Networks ◽  
Topographic Data ◽  
And Topology

scholarly journals Age and sedimentological features of fluvial series in the Toruń Basin and the Drwęca Valley (Poland)

2011 ◽  
Vol 38 (4) ◽  
pp. 397-412 ◽  
Author(s):  
Piotr Weckwerth ◽  
Krzysztof Przegiętka ◽  
Alicja Chruścińska ◽  
Barbara Woronko ◽  
Hubert Oczkowski
Keyword(s):  
River Channel ◽  
Second Phase ◽  
Braided River ◽  
Fluvial System ◽  
Quaternary Deposits ◽  
Braided Rivers ◽  
Energy Flows ◽  
Late Weichselian ◽  
Two Phases ◽  
Quartz Grains

Abstract The deposits of the Toruń Basin are dominated by a few-metre thick sand series which fill up buried valley-like depressions. In many cases they underlie the Weichselian till which builds up the ice marginal streamway (pradolina) terraces or they are exposed at the basin slopes. As the results of the geological and sedimentological studies, as well as of the dating of the deposits at the sites in the Toruń Basin indicate, the deposits include two fluvial series accumulated before the advancement of the Leszno Phase ice sheet, i.e. in Middle Weichselian and at the beginning of Late Weichselian. The oldest fluvial series connected with the Saalian Glaciation was found at the mouth section of the Drwęca Valley. The fluvial system of the Toruń Basin during Middle Weichselian and at the beginning of Late Weichselian developed in two phases of the sand-bed braided river. During the first one the river channel were dominated by large mid-riverbed sandbars, while during the second phase the water flow was smaller and, as a result, low transverse sandbars and two-dimensional dunes developed. Other active river channel also showed low-energy flows, more intensive meandering than in the case of the braided rivers, as well as sandy side-bars. Analysis of the rounding and frosting of the quartz grains indicate that the studied series of the Weichselian sandy deposits represent alluvia of a river which were fed from two diverse sources. The first one might have represented the alluvia of a warm river which transformed its load, while the other one might have mainly carried the underlying Quaternary deposits.

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.

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.

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