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What we see now: Event-persistence and the predictability of hydro-eco-geomorphological systems

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  • Beven, Keith

Abstract

What we see now in the landscape is the result of a long history of events with varying degrees of persistence. We have only limited access to much of that history and we know that many current events have only a minimal impact on what we see. Even rather extreme events may have impacts that are not very long-lasting but can have the effect of changing the antecedent states for future events. That means that sampling of sequences of events might be important in understanding the evolution of the catchments. In some cases, however, extreme events can have an impact on the system that persists over hundreds or thousands of years. Any evolution of the landscape is then constrained by those past events, however much it might be also constrained by self-organisational principles. It might be difficult to verify those principles given the epistemic uncertainties about past histories and system properties that are generic to the studies that are possible within a research project or career. These arguments are investigated in a simple slab model of landslip failures in a hillslope hollow subject to stochastic forcing over long periods of time. The complementarity of an event-persistence approach to hydro-eco-geomorphological systems is captured in suggestions for future research questions.

Suggested Citation

  • Beven, Keith, 2015. "What we see now: Event-persistence and the predictability of hydro-eco-geomorphological systems," Ecological Modelling, Elsevier, vol. 298(C), pages 4-15.
  • Handle: RePEc:eee:ecomod:v:298:y:2015:i:c:p:4-15
    DOI: 10.1016/j.ecolmodel.2014.07.019
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    References listed on IDEAS

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    1. Phillips, Jonathan D., 2011. "Predicting modes of spatial change from state-and-transition models," Ecological Modelling, Elsevier, vol. 222(3), pages 475-484.
    2. Cartwright,Nancy, 1999. "The Dappled World," Cambridge Books, Cambridge University Press, number 9780521643368, October.
    3. Cartwright,Nancy, 1999. "The Dappled World," Cambridge Books, Cambridge University Press, number 9780521644112, October.
    4. Suckling, Emma B. & Smith, Leonard A., 2013. "An evaluation of decadal probability forecasts from state-of-the-art climate models," LSE Research Online Documents on Economics 55142, London School of Economics and Political Science, LSE Library.
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    Cited by:

    1. Deliang Sun & Danlu Chen & Jialan Zhang & Changlin Mi & Qingyu Gu & Haijia Wen, 2023. "Landslide Susceptibility Mapping Based on Interpretable Machine Learning from the Perspective of Geomorphological Differentiation," Land, MDPI, vol. 12(5), pages 1-37, May.

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