The development and application of numerical models to investigate fluvial sedimentary archives has increased during the last decades resulting in a sustained growth in the number of scientific publications with keywords, ‘fluvial models’, ‘fluvial process models’ and ‘fluvial numerical models’. In this context we compile and review the current contributions of numerical modelling to the understanding of fluvial archives. In particular, recent advances, current limitations, previous unexpected results and future perspectives are all discussed. Numerical modelling efforts have demonstrated that fluvial systems can display non-linear behaviour with often unexpected dynamics causing significant delay, amplification, attenuation or blurring of externally controlled signals in their simulated record. Numerical simulations have also demonstrated that fluvial records can be generated by intrinsic dynamics without any change in external controls. Many other model applications demonstrate that fluvial archives, specifically of large fluvial systems, can be convincingly simulated as a function of the interplay of (palaeo) landscape properties and extrinsic climate, base level and crustal controls. All discussed models can, after some calibration, produce believable matches with real world systems suggesting that equifinality - where a given end state can be reached through many different pathways starting from different initial conditions and physical assumptions - plays an important role in fluvial records and their modelling. The overall future challenge lies in the development of new methodologies for a more independent validation of system dynamics and research strategies that allow the separation of intrinsic and extrinsic record signals using combined fieldwork and modelling.
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- Fluvial stratigraphy
- Numerical model
- Signal shredding
- Intrinsic and extrinsic control
Veldkamp, A., Baartman, J. E. M., Coulthard, T. J., Maddy, D., Schoorl, J. M., Storms, J. E. A., ... Whittaker, A. C. (2017). Two decades of numerical modelling to understand long term fluvial archives: Advances and future perspectives. Quaternary Science Reviews, 166, 177-187. https://doi.org/10.1016/j.quascirev.2016.10.002