Can We Link Cause and Effect in Landscape Evolution?

Coulthard, Tom; Wiel, Marco J. Van De

doi:10.1002/9781119952497.ch36

Cited by 4 publications

(5 citation statements)

References 37 publications

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“…Although the use of numerical models is progressively gaining an important role in fluvial geomorphology and in its application to river management, the prediction of morphological evolution is still difficult, given the inherent significant complexity of the processes involved and of the cause-effect relations, which are highly non-linear, and much debate still exists concerning the problems, uncertainties and limitations of the models (e.g., Darby and Van De Wiel, 2003;Wilcock and Iverson, 2003;Coulthard and Van De Wiel, 2012). Consequently, prediction of future changes within the IDRAIM framework is openended, and various types of modeling approaches could be used, including conceptual, empirical/statistical, analytical and numerical models (Darby and Van de Wiel, 2003).…”

Section: Prediction Of Future Trendsmentioning

confidence: 99%

A methodological framework for hydromorphological assessment, analysis and monitoring (IDRAIM) aimed at promoting integrated river management

et al. 2015

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Section: Prediction Of Future Trendsmentioning

confidence: 99%

A methodological framework for hydromorphological assessment, analysis and monitoring (IDRAIM) aimed at promoting integrated river management

et al. 2015

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“…1-7). Thus, mountain basins seem to be SOC: Self Organized Critically (Bak et al, 1988;Thomas J Coulthard & Van De Wiel, 2012); indeed, drainage areas also distribute as power law (Molnar, 2013). Criticality is linked to an optimal principle, which is erasing gradients as fast as possible, as shown via physics by A.…”

Section: Sediment Transport Morphodynamics and Stabilitymentioning

confidence: 99%

Self-organized criticality in river basins: Challenging sedimentary records of environmental change

Wiel

Coulthard

2010

Geology

116

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Mountain basins are open dynamic systems which organize at multiple scales to transform hillslope sediment supply to fluvial sediment transport. In a given river reach, its form and sediment regime depend on basin processes and are contingent to geomorphic history. Lack of such information makes modelling the way to estimate this spatiotemporal context. However, there is a gap of combining spatiotemporal variability of hydrology and landslides sediment supply with its effect: the feedback between channel form and sediment transport. Hillslope and fluvial modules of a new model called Fluvial Hydro-Geomorphology Model (FHGM) are produced which, in hollows and river reaches that are deformable, encapsulates complexity via parameterization or random forcing. FHGM solves responses to every major rain event, and accumulate them in decadal timescale, to include occurrence of channel forming floods as well as landslides with varied sizes and source zones. FHGM landslides module reproduces power law spatial distribution of landslide volumes, as well as magnitud and frecuency of sediment supply. FHGM fluvial module, calibrated with a new gravel flume experiment, reproduces a broad range of morphologic conditions, from incised to clogged, and produces mean bankfull capacity consistent to mean maximum annual flood and with empirical dimensionless hydraulic geometry patterns for channel depth and width. This work shows how mountain basins organize to minimize the duration of formative events, by editing channels capacity and deforming sediment storages to recover stability and structure; a resilience akin to living beings.

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“…From the entrainment of individual pebbles, to the development of meander belts across a floodplain, up to the formation of large-scale sedimentary basins, river systems exhibit unpredictable, nonlinear and chaotic behaviour [96]. The extent of this is such that recent studies question whether or not it is possible to establish a response to external forcings within river systems [95]. Jerolmack & Paola [97] suggested that a river catchment may act as a giant filter, shredding input signals (e.g.…”

Section: Reliability Value and Meaning Of Modelsmentioning

confidence: 98%

“…years to decades, notably for specific floods or specific short periods of high fluvial change [82,94]. They are less useful for long-term simulationscenturies to millennia-partly because of the computational problem noted earlier (although this may be overcome with future technologies) and partly because the accumulation of uncertainties over many iterations of the model simulation would make the predictions unreliable [95].…”

Section: (E) Reach-based Cellular Modelsmentioning

confidence: 99%

Modelling river history and evolution

Coulthard

Wiel

2012

Phil. Trans. R. Soc. A.

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Over the last few decades, a suite of numerical models has been developed for studying river history and evolution that is almost as diverse as the subject of river history itself. A distinction can be made between landscape evolution models (LEMs), alluvial architecture models, meander models, cellular models and computational fluid dynamics models. Although these models share some similarities, there also are notable differences between them, which make them more or less suitable for simulating particular aspects of river history and evolution. LEMs embrace entire drainage basins at the price of detail; alluvial architecture models simulate sedimentary facies but oversimplify flow characteristics; and computational fluid dynamics models have to assume a fixed channel form. While all these models have helped us to predict erosion and depositional processes as well as fluvial landscape evolution, some areas of prediction are likely to remain limited and short-term owing to the often nonlinear response of fluvial systems. Nevertheless, progress in model algorithms, computing and field data capture will lead to greater integration between these approaches and thus the ability to interpret river history more comprehensively.

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Can We Link Cause and Effect in Landscape Evolution?

Cited by 4 publications

References 37 publications

A methodological framework for hydromorphological assessment, analysis and monitoring (IDRAIM) aimed at promoting integrated river management

A methodological framework for hydromorphological assessment, analysis and monitoring (IDRAIM) aimed at promoting integrated river management

Self-organized criticality in river basins: Challenging sedimentary records of environmental change

Modelling river history and evolution

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