DOI: 10.1016/j.coastaleng.2020.103673
论文题名: Ranking uncertainty: Wave climate variability versus model uncertainty in probabilistic assessment of coastline change
作者: Kroon A. ; de Schipper M.A. ; van Gelder P.H.A.J.M. ; Aarninkhof S.G.J.
刊名: Coastal Engineering
ISSN: 3783839
出版年: 2020
卷: 158 语种: 英语
英文关键词: Coastline modeling
; Generalized Likelihood Uncertainty Estimation (GLUE)
; Large-scale nourishment
; Model uncertainty
; Sensitivity analysis
; Wave climate variability
Scopus关键词: Climate change
; Climate models
; Engines
; Glues
; Gluing
; Landforms
; Sediment transport
; Sensitivity analysis
; Shore protection
; Epistemic uncertainties
; Generalized likelihood uncertainty estimation
; Global sensitivity analysis
; Large-scale nourishment
; Model uncertainties
; Probabilistic assessments
; Probabilistic framework
; Wave climates
; Uncertainty analysis
; beach nourishment
; coastal evolution
; coastal protection
; probability
; sediment transport
; sensitivity analysis
; uncertainty analysis
; wave climate
; wave modeling
; Netherlands
英文摘要: Sand nourishments are increasingly applied as adaptive coastal protection measures. Predictions of the evolution of these nourishments and their impact on the surrounding coastline contain many uncertainties. The sources that add to this uncertainty can be delineated between intrinsic and epistemic uncertainty, i.e. inevitably in the system or related to knowledge limitations. Effects of intrinsic uncertainty (e.g. due to wave climate variability) on coastal evolution can be significant. In studying these effects, it has often been assumed that intrinsic uncertainty is dominant over epistemic uncertainty (e.g. introduced by the model), yet the magnitude of both contributions have not been explicitly quantified to assess the validity of this assumption. This paper examines the relative importance of intrinsic and epistemic uncertainty in coastline modeling of a large-scale nourishment. It uses a probabilistic framework in which sediment transport is considered to be a function of random wave forcing (intrinsic) and model (epistemic) uncertainty, calculating transport using a one-line model. The test case for this analysis is the mega-nourishment, the Sand Engine, located in the Netherlands. The applied wave climate variability is obtained from long term wave observations, whereas model uncertainty is quantified using the Generalized Likelihood Uncertainty Estimation (GLUE) method relying on monthly observations. We find that the confidence intervals on predicted volume losses increase substantially when including both intrinsic and epistemic sources of uncertainty. A global sensitivity analysis shows that ignoring model uncertainty would underestimate the variance by at least 50% after a 2.5-year simulation period for the Sand Engine, hence producing significant overconfidence in the results. These findings imply that for coastal modeling purposes a dual approach should be considered, evaluating both epistemic and intrinsic uncertainties. © 2020 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/158115
Appears in Collections: 气候变化与战略
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作者单位: Delft University of Technology, Faculty of Civil Engineering, Department of Hydraulic Engineering, Section of Coastal Engineering, Stevinweg 1, 2628CN Delft, Netherlands; Svašek Hydraulics, Kratonkade 23, 3024ES Rotterdam, Netherlands; Delft University of Technology, Faculty of Technology, Policy and Management, Department of Values, Technology and Innovation, Section of Safety and Security Science, Jaffalaan 5, 2929XJ Delft, Netherlands
Recommended Citation:
Kroon A.,de Schipper M.A.,van Gelder P.H.A.J.M.,et al. Ranking uncertainty: Wave climate variability versus model uncertainty in probabilistic assessment of coastline change[J]. Coastal Engineering,2020-01-01,158