Technical Papers
Jan 21, 2015

Evaluation of Parameter and Model Uncertainty in Simple Applications of a 1D Sediment Transport Model

Publication: Journal of Hydraulic Engineering
Volume 141, Issue 5

Abstract

This paper separately evaluates two methods from Bayesian Statistics to estimate parameter and model uncertainty in simulations from a one-dimensional (1D) sediment transport model. The first method, multivariate shuffled complex evolution metropolis-uncertainty analysis (MSU), is an algorithm that identifies the most likely parameter values and estimates parameter uncertainty for models with multiple outputs. The second method, Bayesian model averaging (BMA), determines a combined prediction based on three sediment transport equations that are calibrated with MSU and evaluates the uncertainty associated with the selection of the transport equation. These tools are applied to simulations of three flume experiments. For these cases, MSU does not converge substantially faster than a previously used and simpler parameter uncertainty method, but its ability to consider correlation between parameters improves its estimate of the uncertainty. Also, the BMA results suggest that a combination of transport equations usually provides a better forecast than using an individual equation, and the selection of a single transport equation substantially increases the overall uncertainty in the model forecasts.

Get full access to this article

View all available purchase options and get full access to this article.

Acknowledgments

The authors thank Mazdak Arabi and Jennifer A. Hoeting for their assistance in the selection and application of the MSU and BMA methods. Financial support from the U.S. Bureau of Reclamation Science and Technology Program for this research is also gratefully acknowledged. We also thank two anonymous reviewers, the associate editor, and the editor in chief for their help in improving this manuscript.

References

Abramowitz, G., et al. (2006). “Neural error regression diagnosis (NERD): A tool for model bias identification and prognostic data assimilation.” J. Hydrometeorol., 7(1), 160–177.
Apel, H., Aronica, G. T., Kreibich, H., and Thieken, A. H. (2009). “Flood risk analysis—How detailed do we need to be?” Natural Hazards, 49(1), 79–98.
Ashida, K., and Michiue, M. (1971). “An investigation of river bed degradation downstream of a dam.” Proc., 14th Int. Assoc. for Hydraulic Research Congress, International Association for Hydraulic Research, Madrid, Spain, 247–256.
Beven, K., and Binley, A. (1992). “The future of distributed models: Model calibration and uncertainty prediction.” Hydrol. Process., 6(3), 279–298.
Blasone, R.-S., Vrugt, J. A., Madsen, H., Rosbjerg, D., Robinson, B. A., and Zyvoloski, G. A. (2008). “Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling.” Adv. Water Resour., 31(4), 630–648.
Carrera, J., and Neuman, S. P. (1986). “Estimation of aquifer parameters under transient and steady state conditions: 3. Application to synthetic and field data.” Water Resour. Res., 22(2), 228–242.
Chang, C. H., Yang, J. C., and Tung, Y. K. (1993). “Sensitivity and uncertainty analysis of a sediment transport model—A global approach.” Stochastic Hydrol. Hydraul., 7(4), 299–314.
Cowles, M. K., and Carlin, B. P. (1996). “Markov chain Monte Carlo convergence diagnostics: A comparative review.” J. Am. Stat. Assoc., 91(434), 883–904.
Dempster, A. P., Laird, N., and Rubin, D. B. (1977). “Maximum likelihood from incomplete data via the EM algorithm.” J. R. Stat. Soc. B Methodological, 39(1), 1–38.
Gaeuman, D., Andrews, E. D., Krause, A., and Smith, W. (2009). “Predicting fractional bed load transport rates: Application of the Wilcock-Crowe equations to a regulated gravel bed river.” Water Resour. Res., 45(6), W06409.
Gelman, A., and Rubin, D. B. (1992). “Inference from iterative simulation using multiple sequences.” Stat. Sci., 7(4), 457–472.
Givens, G. H., and Hoeting, J. A. (2005). Computational statistics, John Wiley & Sons, Hoboken, NJ.
Greimann, B., Lai, Y., and Huang, J. (2008). ”Two-dimensional total sediment load model equations.” J. Hydraul. Eng., 1142–1146.
Hoeting, J. A., Madigan, D., Raftery, A. E., and Volinsky, C. T. (1999). “Bayesian model averaging: A tutorial.” Stat. Sci., 14(4), 382–417.
Huang, J. V., and Greimann, B. P. (2010). User’s manual for SRH-1D 2.6, Denver Bureau of Reclamation, U.S. Dept. of the Interior, Denver.
Laloy, E., and Vrugt, J. A. (2012). “High-dimensional posterior exploration of hydrologic models using multiple-try DREAM(ZS) and high-performance computing.” Water Resour. Res., 48(1), W01526.
MacDonald, L. H., Smart, A. W., and Wissmar, R. C. (1991). Monitoring guidelines to evaluate effects of forestry activities on streams in the Pacific Northwest and Alaska, U.S. Environmental Protection Agency, Seattle.
Mo, X., and Beven, K. (2004). “Multi-objective parameter conditioning of a three-source wheat canopy model.” Agric. Forest Meteorol., 122(1–2), 39–63.
Pappenberger, F., Matgen, P., Beven, K. J., Henry, J.-B., Pfister, L., Fraipoint de, P. (2006). “Influence of uncertain boundary conditions and model structure on flood inundation predictions.” Adv. Water Resour., 29(10), 1430–1449.
Parker, G. (1990). “Surface-based bedload transport relation for gravel rivers.” J. Hydraul. Res., 28(4), 417–436.
Pender, G., Hoey, T. B., Fuller, C., and McEwan, I. K. (2001). “Selective bedload transport during the degradation of a well sorted graded sediment bed.” J. Hydraul. Res., 39(3), 269–277.
Raftery, A. E., Gneiting, T., Balabdaoui, F., and Polakowski, M. (2005). “Using Bayesian model averaging to calibrate forecast ensembles.” Monthly Weather Rev., 133(5), 1155–1174.
Ruark, M. D., Niemann, J. D., Greimann, B. P., and Arabi, M. (2011). “Method for assessing impacts of parameter uncertainty in sediment transport modeling applications.” J. Hydraul. Eng., 623–636.
Seal, R., Paola, C., Parker, G., Southard, J. B., and Wilcock, P. R. (1997). “Experiments on downstream fining of gravel: I. Narrow-channel runs.” J. Hydraul. Eng., 874–884.
Shen, Z. Y., Chen, L., and Chen, T. (2012). “Analysis of parameter uncertainty in hydrologic and sediment transport modeling using GLUE method: A case study of SWAT model applied to Three Gorges Reservoir region, China.” Hydrol. Earth Syst. Sci., 16(1), 121–132.
van Griensven, A., and Meixner, T. (2007). “A global and efficient multi-objective auto-calibration and uncertainty estimation method for water quality catchment models.” J. Hydroinform., 9(4), 277–291.
Vrugt, J. A., Diks, C. G. H., and Clark, M. P. (2008). “Ensemble Bayesian model averaging using Markov Chain Monte Carlo sampling.” Environ. Fluid Mech., 8(5–6), 579–595.
Vrugt, J. A., Gupta, H. V., Bouten, W., and Sorooshian, S. (2003). “A shuffled complex evolution metropolis algorithm for optimization and uncertainty assessment of hydrologic model parameters.” Water Resour. Res., 39, 1201–1216.
Werner, M. G. F., Hunter, N. M., and Bates, P. D. (2005). “Indentifiability of distributed floodplain roughness values in flood extent estimation.” J. Hydrol., 314(1–4), 139-157.
Wilcock, P. R., and Crowe, J. C. (2003). “Surface-based transport model for mixed-size sediment.” J. Hydraul. Eng., 120–128.
Wöhling, T., and Vrugt, J. A. (2008). “Combining multiobjective optimization and Bayesian model averaging to calibrate ensembles of soil hydraulic models.” Water Resour. Res., 44(12), W12432.
Wong, J. S., Freer, J. E., Bates, P. D., Sear, D. A., and Stephens, E. M. (2014). “Sensitivity of a hydraulic model to channel erosion uncertainty during extreme flooding.” Hydrol. Process., 29(2), 261–279.
Wong, M. G., and Parker, G. (2006). “Reanalysis and correction of bed-load relation of Meyer-Peter and Müller using their own database.” J. Hydraul. Eng., 1159–1168.
Wu, F.-C., and Chen, C. C. (2009). “Bayesian updating of parameters for a sediment entrainment model via Markov chain Monte Carlo.” J. Hydraul. Eng., 22–37.
Yapo, P. O., Gupta, H. V., and Sorooshian, S. (1998). “Multi-objective global optimization for hydrologic models.” J. Hydrol., 204(1–4), 83– 97.
Yeh, K., Lin, E., and Chen, S. (2004). “Effect of uncertainty of mobile-bed model parameters on bed evolution.” Advances in hydro-science and engineering, M. S. Altinakar, S. S. Y. Wang, K. P. Holz, and M. Kawahara, eds., Vol. VI, Univ. of Mississippi, Oxford, MS.

Information & Authors

Information

Published In

Go to Journal of Hydraulic Engineering
Journal of Hydraulic Engineering
Volume 141Issue 5May 2015

History

Received: Oct 26, 2014
Accepted: Dec 3, 2014
Published online: Jan 21, 2015
Published in print: May 1, 2015
Discussion open until: Jun 21, 2015

Permissions

Request permissions for this article.

Authors

Affiliations

Shaina M. Sabatine
Junior River Engineer and Modeling Specialist, Watershed Science and Engineering, 110 Prefontaine Pl. S., Suite 508, Seattle, WA 98104.
Jeffrey D. Niemann, M.ASCE [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Colorado State Univ., Campus Delivery 1372, Fort Collins, CO 80523 (corresponding author). E-mail: [email protected]
Blair P. Greimann, M.ASCE
Hydraulic Engineer, Sedimentation and River Hydraulics Group, Technical Service Center, Bureau of Reclamation, Denver Federal Center, Building 67, Denver, CO 80225.

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share