Monitoring a river channel network at Salar de Uyuni using Landsat ETM+ images

2012 ◽  
Author(s):  
S.E. Hosseini Aria ◽  
M.E. Donselaar ◽  
R. Lindenbergh ◽  
R. Koenders ◽  
J. Li ◽  
...  
Keyword(s):  
River Channel ◽  
Channel Network

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 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.

scholarly journals RUN-OFF MODEL OF WASH LOAD USING RIVER CHANNEL NETWORK

2001 ◽  
Vol 45 ◽  
pp. 793-798
Author(s):  
Shinji TOKUDA ◽  
Mikio KUROKI ◽  
Tadaoki ITAKURA
Keyword(s):  
River Channel ◽  
Channel Network ◽  
Run Off ◽  
Wash Load

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.

Sorting out river channel patterns

2010 ◽  
Vol 34 (3) ◽  
pp. 287-326 ◽  
Author(s):  
Maarten G. Kleinhans
Keyword(s):  
Laboratory Experiments ◽  
Bank Erosion ◽  
River Channel ◽  
Bed Sediment ◽  
Channel Network ◽  
Spatial Sorting ◽  
Channel Avulsion ◽  
Sorting Process ◽  
Channel Patterns ◽  
Load Sediment

Rivers self-organize their pattern/planform through feedbacks between bars, channels, floodplain and vegetation, which emerge as a result of the basic spatial sorting process of wash load sediment and bed sediment. The balance between floodplain formation and destruction determines the width and pattern of channels. Floodplain structure affects the style and rate of channel avulsion once aggradation takes place. Downstream fining of bed sediment and the sediment balance of fines in the pores of the bed sediment provide the ‘template’ or sediment boundary conditions, from which sorting at smaller scales leads to the formation of distinct channel patterns. Bar patterns provide the template of bank erosion and formation as well as the dynamics of the channel network through bifurcation destabilization. However, so far we have been unable to obtain dynamic meandering in laboratory experiments and in physics-based models that can also produce braiding, which reflects our lack of understanding of what causes the different river patterns.

Natural Flood Risk Management

2019 ◽  
Author(s):  
Anna Murgatroyd ◽  
Simon Dadson
Keyword(s):  
At Risk ◽  
Overland Flow ◽  
Flood Management ◽  
River Channel ◽  
Flood Hazards ◽  
Management Options ◽  
Channel Network ◽  
Adaptation Measures ◽  
Diverse Range ◽  
Quantitative Evidence

Flooding is a natural hazard with the potential to cause damage at the local, national, and global scale. Flooding is a natural product of heavy precipitation and increased runoff. It may also arise from elevated groundwater tables, coastal inundation, or failed drainage systems. Flooded areas can be identified as land beyond the channel network covered by water. Although flooding can cause significant damage to urban developments and infrastructure, it may be beneficial to the natural environment. Preemptive actions may be taken to protect communities at risk of inundation that are not able to relocate to an area not at risk of flooding. Adaptation measures include flood defenses, river channel modification, relocation, and active warning systems. Natural flood management (NFM) interventions are designed to restore, emulate, or enhance catchment processes. Such interventions are common in upper reaches of the river and in areas previously transformed by agriculture and urban development. Natural techniques can be categorized into three groups: water retention through management of infiltration and overland flow, managing channel connectivity and conveyance, and floodplain conveyance and storage. NFM may alter land use, improve land management, repair river channel morphology, enhance the riparian habitat, enrich floodplain vegetation, or alter land drainage. The range of natural flood management options allows a diverse range of flood hazards to be considered. As a consequence, there is an abundance of NFM case studies from contrasting environments around the globe, each addressing a particular set of flood risks. Much of the research supporting the use of NFM highlights both the benefits and costs of working with natural processes to reduce flood hazards in the landscape. However, there is a lack of quantitative evidence of the effectiveness of measures, both individually and in combination, especially at the largest scales and for extreme floods. Most evidence is based on modeling studies and observations often relate to a specific set of upstream measures that are challenging to apply elsewhere.

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