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

    Briant, Rebecca and Cohen, K. and Cordier, S. and Demoulin, A. and Macklin, M. and Mather, A. and Rixhon, G. and Veldkamp, A. and Wainwright, J. and Whittaker, A. and Wittmann-Oelze, H. (2018) Applying Pattern Oriented Sampling in current fieldwork practice to enable more effective model evaluation in fluvial landscape evolution research. Earth Surface Processes and Landforms 43 (4), pp. 2964-6980. ISSN 0197-9337.

    Briant et al 2018 FACSIMILE preprint.pdf - Author's Accepted Manuscript

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    Field geologists and geomorphologists are increasingly looking to numerical modelling to understand landscape change over time, particularly in river catchments. The application of Landscape Evolution Models (LEMs) started with abstract research questions in synthetic landscapes. Now, however, studies using LEMs on real-world catchments are becoming increasingly common. This development has philosophical implications for model specification and evaluation using geological and geomorphological data, besides practical implications for fieldwork targets and strategy. The type of data produced to drive and constrain LEM simulations has very little in common with that used to calibrate and validate models operating over shorter timescales, making a new approach necessary. Here we argue that catchment fieldwork and LEM studies are best synchronised by complementing the Pattern Oriented Modelling (POM) approach of most fluvial LEMs with Pattern Oriented Sampling (POS) fieldwork approaches. POS can embrace a wide range of field data types, without overly increasing the burden of data collection. In our approach, both POM output and POS field data for a specific catchment are used to quantify key characteristics of a catchment. These are then compared to provide an evaluation of the performance of the model. Early identification of these key characteristics should be undertaken to drive focused POS data collection and POM model specification. Once models are evaluated using this POM / POS approach, conclusions drawn from LEM studies can be used with greater confidence to improve understanding of landscape change.


    Item Type: Article
    Additional Information: This is the peer reviewed version of the article, which has been published in final form at the link above. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
    School: Birkbeck Faculties and Schools > Faculty of Humanities and Social Sciences > School of Social Sciences
    Research Centres and Institutes: Research in Environment and Sustainability, Centre for
    Depositing User: Becky Briant
    Date Deposited: 25 Jun 2018 09:55
    Last Modified: 09 May 2024 15:55


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