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Assessing and Reducing the Uncertainty of Predictions from Hydraulic and Hydrologic Models

Project ID: 9320
Principal Investigator: Blair Greimann
Research Topic: Sediment Management and River Restoration
Priority Area Assignments: 2011 (Climate Adaptation), 2012 (Climate Adaptation)
Funded Fiscal Years: 2011, 2012 and 2013
Keywords: None

Project Abstract

The U.S. Bureau of Reclamation (USBR) uses many kinds of computational hydrologic, hydraulic, and sediment-transport models to protect and manage water resources. Such models inherently contain simplifications in their representations of the physical systems, uncertainty in the appropriate values for parameters, and errors in model forcing. These sources of uncertainty ultimate produce uncertainty in the forecasts obtained from the models. It is important to understand the nature of this uncertainty in order to guide data collection and model calibration strategies. The long-term objective of this project is to develop a method to assess and reduce uncertainty in forecasts from hydrologic, hydraulic, and sediment-transport models. In particular, this project aims to develop guidance on parameter selection for reducing uncertainty and a general methodology for assessing uncertainty. The new approach for uncertainty will require few enough simulations to be applied to complex model applications, and retain enough formality to reliably evaluate data collection and model calibration strategies. To constrain the scope, this research will evaluate the proposed methodology through coupling with a sediment-transport model called Sedimentation and River Hydraulics – One Dimension (SRH-1D). Five major tasks must be completed to achieve the project objective: (1) analyze the application of a previously developed methodology (MSU/BMA) to SRH-1D simulations of flume experiments to assess model weaknesses and data collection strategies; (2) apply MSU/BMA to an SRH-1D model of a real river system and evaluate the method's performance; (3) develop and evaluate a simplified methodology that requires fewer simulations to evaluate uncertainty; (4) implement the method in streamlined software and train USBR staff in its use; and (5) publish project results in refereed journals.

Contributing Partners

None

Research Products

Independent Peer Review

The following documents were reviewed by qualified Bureau of Reclamation employees. The findings were determined to be achieved using valid means.

Method for Assessing Impacts of Parameter Uncertainty in sediment transport models (interim, PDF, 1.4MB)
By Jeff Niemann and Blair Greimann
Publication completed on June 01, 2011

The writers aim to develop a method that quantifies
the degree to which parameter values are constrained by calibration data and the impacts of the remaining parameter uncertainty on model
forecasts. The method uses a new multiobjective version of generalized likelihood uncertainty estimation. The likelihoods of parameter values
are assessed using a function that weights different output variables on the basis of their first-order global sensitivities.
Keywords: sediment transport, uncertainty

EVALUATION OF PARAMETER AND MODEL UNCERTAINTY IN SIMPLE APPLICATIONS OF A 1D SEDIMENT TRANSPORT MODEL (final, PDF, 1.5MB)
By Ms. Shaina Sabatine
Report completed on January 17, 2012

Mater Thesis describing research work
Keywords: model uncertainty, sediment transport

Evaluation of Parameter and Model Uncertainty in Simple Applications of a 1D Sediment Transport Model (final, PDF, 1.8MB)
By Ms. Shaina Sabatine, Jeff Niemann and Blair Greimann
Publication completed on November 28, 2014

This paper separately evaluates two methods from Bayesian Statistics to estimate parameter and model uncertainty in simulations from a 1D sediment transport model.
Keywords: sediment transport, uncertainty analysis

Not Reviewed

The following documents were not reviewed. Statements made in these documents are those of the authors. The findings have not been verified.

Assessing and Reducing the Uncertainty of Predictions from Hydraulic and Hydrologic Models - Progress Report (final, PDF, 130KB)
By Jeff Niemann
Report completed on July 01, 2013

The overall objective of this project is to develop a method to assess and potentially reduce uncertainty in the forecasts from hydrologic, hydraulic, and sediment-transport models. The project results to date are briefly summarized and future tasks are outlined.
Keywords: uncertainty analysis, sediment transport

This information was last updated on December 20, 2014
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