Assessing the Hydrological and Geomorphic Behaviour of a Landscape Evolution Model within a Limits-of-Acceptability Uncertainty Analysis Framework

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Abstract

Landscape evolution models (LEMs) have the capability to characterize key aspects of geomorphological and hydrological processes. However, their usefulness is hindered by model equifinality and paucity of available calibration data. Estimating uncertainty in the parameter space and resultant model predictions is rarely achieved as this is computationally intensive and the uncertainties inherent in the observed data are large. Therefore, a limits-of-acceptability (LoA) uncertainty analysis approach was adopted in this study to assess the value of uncertain hydrological and geomorphic data. These were used to constrain simulations of catchment responses and to explore the parameter uncertainty in model predictions. We applied this approach to the River Derwent and Cocker catchments in the UK using a LEM CAESAR-Lisflood. Results show that the model was generally able to produce behavioural simulations within the uncertainty limits of the streamflow. Reliability metrics ranged from 24.4% to 41.2%, and captured the high magnitude low-frequency sediment events. Since different sets of behavioural simulations were found across different parts of the catchment, evaluating LEM performance, in quantifying and assessing both at-a-point behaviour and spatial catchment response, remains a challenge. Our results show evaluating LEMs within uncertainty analyses framework that takes into account the varying quality of different observations constrains behavioural simulations and parameter distributions and is a step towards a full ensemble uncertainty evaluation of such models. We believe this approach will have benefits to reflecting uncertainties in flooding events where channel morphological changes are occurring and various diverse (and yet often sparse) data has been collected over such events.
Original languageEnglish
Pages (from-to)1981-2003
Number of pages23
JournalEarth Surface Processes and Landforms
Volume46
Issue number10
Early online date27 Apr 2021
DOIs
Publication statusPublished - Aug 2021

Bibliographical note

Funding Information:
Jefferson Wong was funded by a University of Bristol Postgraduate Scholarship. The authors thank the UK Environment Agency for providing the rain gauge and flow gauging station data. Thanks are also due to Dr. Jorge Ramirez for his efforts in collecting the grain size data and providing access to the data used in this study. The authors furthermore thank the two anonymous reviewers and Stuart Lane, the editor, for their invaluable comments, which greatly helped to improve the quality of the paper. Paul Bates was supported by a Royal Society Wolfson Research Merit Award. Jim Freer was partly funded for his time by the Global Water Futures program, University of Saskatchewan. Paul Bates and Jim Freer time was partly funded by NERC grant NE/K00882X/1.

Funding Information:
Jefferson Wong was funded by a University of Bristol Postgraduate Scholarship. The authors thank the UK Environment Agency for providing the rain gauge and flow gauging station data. Thanks are also due to Dr. Jorge Ramirez for his efforts in collecting the grain size data and providing access to the data used in this study. The authors furthermore thank the two anonymous reviewers and Stuart Lane, the editor, for their invaluable comments, which greatly helped to improve the quality of the paper. Paul Bates was supported by a Royal Society Wolfson Research Merit Award. Jim Freer was partly funded for his time by the Global Water Futures program, University of Saskatchewan. Paul Bates and Jim Freer time was partly funded by NERC grant NE/K00882X/1.

Publisher Copyright:
© 2021 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.

Keywords

  • uncertainty analysis
  • limits-of-acceptability
  • GLUE
  • observational uncertainty
  • parameter uncertainty
  • CAESAR-Lisflood
  • landscape evolution models

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