Two decades of numerical modelling to understand long term fluvial archives: Advances and future perspectives

Abstract

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Applying Pattern Oriented Sampling in current fieldwork practice to enable more effective model evaluation in fluvial landscape evolution research

“…Equifinality is well known to play an important role in fluvial records and their modelling by dedicated LEMs (Beven 1996;Nicholas and Quine 2010;Veldkamp et al 2017). The model output for the present is the simplest to both evaluate (comparing modelled and field data) and analyse (tracing development through time) for explanatory understanding of landscape evolution and the geological/geomorphological record preserved from it.…”

“…Table I) with system response (e.g. Nonetheless, as noted by Blum et al (2013), criteria for distinguishing between allogenic and autogenic control in catchments still remain to be tightly defined and it is recognized by Veldkamp et al (2017) that there is an urgent need for research strategies that allow the separation of intrinsic and extrinsic record signals using combined fieldwork and modelling. This comparison shows whether the sediment flux signal coming out of the source region is buffered, or even 'shredded' with relation to the original signal (Métivier 1999;Castelltort and van den Driessche 2003;Wittmann et al 2009;Jerolmack and Paola 2010;Armitage et al 2013).…”

“…Since the early 1990s (see review by Veldkamp et al 2017) these have developed into tools used to undertake theoretical experiments about the complexity of earth surface processes, although under controlled and strongly simplified conditions. Since the early 1990s (see review by Veldkamp et al 2017) these have developed into tools used to undertake theoretical experiments about the complexity of earth surface processes, although under controlled and strongly simplified conditions.…”

“…LEMs are distinctive because they combine elements of the other four, frequently enabling all domains to change during a model run rather than modelling one and specifying others as input parameters. This is not only because process observations, even 'long-term' ones, rarely scale to the geological timescales under study (parameters of the LEM can account partially for this, see Veldkamp et al 2017), but even more so because the initial conditions required for the LEM cannot be specified simply from modern datasets, even though LEMs are notoriously sensitive to the specification of initial conditions. Temme et al 2017).…”

“…Alongside this, the use of numerical LEMs has accelerated. Since the early 1990s (see review by Veldkamp et al 2017) these have developed into tools used to undertake theoretical experiments about the complexity of earth surface processes, although under controlled and strongly simplified conditions. Because they were invented to explore theoretical questions about past forcings within landscapes, these LEMs are significantly different from other types of models that simulate and forecast processes operating at present.…”