Share

Feedback

Research Outputs

Get an overview about the publications and related data

Towards efficient uncertainty quantification with high-resolution morphodynamic models

View publication

Published on 30/06/2019 by Berends, K.D., Scheel, F., Warmink, J.J., de Boer, W.P., Ranasinghe, R., Hulscher, S.J.M.H.

Contact details

Koen Berends

Deltares

Output contains: Model or tool access Publication

Schematic overview of the idealised system. The greenfield port is located just inside the estuary.

Innovative compoments

Computer models used to predict sedimentation are computationally very demanding and sensitive to uncertainty in model parameters. In this publication, we explore an alternative multifidelity approach to estimate model output uncertainty for computationally expensive but accurate morphodynamic models using computationally fast but innacurate models. The approach is tested on a siltation study of an estuarine navigation approach channel.

Probability density function of the low-fidelity model (red) and ten random realisations of the high-fidelity model (gray). Source: Berends et al. 2019.

Finding and implications to practice

We found that multifidelity approach is promising to approximate the uncertainty of detailed morphodynamic models. Compared to a full Monte Carlo analysis, the computational effort can be reduced by over 80%, while the precision of the approximation is explicitly computed. For practice, this opens up the possibility to approximate the uncertainty of computer model output on standard computer resources (i.e., without the need for high-performance computing).

Related Content

Publication

Berends, K.D., Scheel, F., Warmink, J.J., de Boer, W.P., Ranasinghe, R., Hulscher, S.J.M.H., 2019. Towards efficient uncertainty quantification with high-resolution morphodynamic models: A multifidelity approach applied to channel sedimentation. Coastal Engineering 152, 103520. https://doi.org/10.1016/j.coastaleng.2019.103520

Model or tool access

Models and datasets are available on request. An implementation of the method described in the publication is available from https://github.com/kdberends/coral

Related outputs

Uncertainty quantification of flood mitigation predictions and implications for decision making

For six typical interventions along the river Waal, we show that the choice between interventions can be different when relative uncertainty is taken into account.

14/11/2018 by Koen Berends et al.

View output View publication

Contains: Dataset access

Efficient uncertainty quantification for impact analysis of human interventions in rivers

A novel method is presented to estimate model uncertainty with a reduced number of model evaluations.

14/06/2018 by Koen Berends et al.

View output View publication

Contains: Dataset access Model or tool upon request

Last modified: 17/07/2019