H13N:
Efficient Diagnostics, Sensitivity, and Uncertainty Analysis of Complex Environmental Models II


Session ID#: 10632

Session Description:
Environmental models are key monitoring and prediction tools used in applied sciences. Modern environmental models incorporate multiple physical processes, have high-dimensional input/output spaces and tend to increase continually in computation time. Many-query applications such as sensitivity analysis, uncertainty quantification as well as model calibration usually require a large number of model evaluations leading to a high computational demand. This makes rigorous analyses often impractical.

In this session we invite contributions that deal with the efficient handling of parameter identifiability, sensitivity analysis, uncertainty quantification, model calibration, or optimisation. We encourage reports of all kind of efficiency improvements that may include but are not limited to algorithmic improvements, dimensionality reductions, approximation techniques, surrogate models, or surrogate assisted methods. We further invite original works that exploit efficient methods on different types of data.

Primary Convener:  Matthias Cuntz, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
Conveners:  Juliane Mai, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany, Dmitri Kavetski, School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, South Australia, Australia and Rafael Rosolem, University of Bristol, Civil Engineering, Bristol, United Kingdom
Chairs:  Matthias Cuntz, Helmholtz Centre for Environmental Research UFZ Leipzig, Leipzig, Germany and Dmitri Kavetski, School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, South Australia, Australia
OSPA Liaison:  Dmitri Kavetski, School of Civil, Environmental and Mining Engineering, University of Adelaide, Adelaide, South Australia, Australia

Cross-Listed:
  • B - Biogeosciences
  • NG - Nonlinear Geophysics
Index Terms:

0430 Computational methods and data processing [BIOGEOSCIENCES]
1805 Computational hydrology [HYDROLOGY]
1846 Model calibration [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]

Abstracts Submitted to this Session:

Beauty and the beast: Some perspectives on efficient model analysis, surrogate models, and the future of modeling (Invited) (60604)
Mary C Hill, John Jakeman, Sandia National Laboratories, Albuquerque, NM, United States, Saman Razavi, University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada and Bryan Tolson, University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada
Petascale Diagnostic Assessment of the Global Portfolio Rainfall Space Missions’ Ability to Support Flood Forecasting (Invited) (59647)
Patrick M Reed, Cornell University, School of Civil and Environmental Engineering, Ithaca, NY, United States, Nathaniel W. Chaney, Duke University, Durham, NC, United States, Jonathan D Herman, University of California Davis, Civil & Environmental Engineering, Davis, CA, United States, Eric F Wood, Princeton University, Civil and Environmental Engineering, Princeton, NJ, United States and Matthew P Ferringer, The Aerospace Corporation, Chantilly, VA, United States
Parallel and Preemptable Dynamically Dimensioned Search Algorithms for Single and Multi-objective Optimization in Water Resources (Invited) (60539)
Bryan Tolson1, L. Shawn Matott2, Thouheed A Gaffoor3, Masoud Asadzadeh4, Mahyar Shafii5, Pawel Pomorski6, Xiaoyong Xu3, Mohammadamin Jahanpour3, Saman Razavi7, Amin Haghnegahdar7 and James R Craig1, (1)University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada, (2)University of Buffalo, Center for Computational Research, Buffalo, NY, United States, (3)University of Waterloo, Waterloo, ON, Canada, (4)University of Manitoba, Department of Civil Engineering, Winnipeg, MB, Canada, (5)University of Waterloo, Ecohydrology Research Group, Waterloo, ON, Canada, (6)University of Waterloo, SHARCNET Waterloo, Waterloo, ON, Canada, (7)University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada
A Multi-Objective Data Assimilation Filtering Method for Distributed High-Resolution Hydrologic Modeling (69992)
Felipe Hernandez, University of Pittsburgh Pittsburgh Campus, Pittsburgh, PA, United States and Xu Liang, University of Pittsburgh, Department of Civil and Environmental Engineering, Pittsburgh, PA, United States
Efficient Calibration of Computationally Intensive Hydrological Models (80342)
Pierre-Luc Huot1, Annie Poulin1, Charles Audet2 and Stéphane Alarie3, (1)École de Technologie Supérieure, Montreal, QC, Canada, (2)Ecole Polytechnique de Montreal, Montreal, QC, Canada, (3)Hydro-Québec, Montreal, QC, Canada
Maximising the value of computer experiments using multi-method global sensitivity analysis (Invited) (60011)
Francesca Pianosi1, Joost Iwema2, Rafael Rosolem1 and Thorsten Wagener1, (1)University of Bristol, Civil Engineering, Bristol, United Kingdom, (2)University of Bristol, Bristol, United Kingdom
Revisiting PLUMBER: Why Do Simple Data-driven Models Outperform Modern Land Surface Models? (60534)
Bart Nijssen, University of Washington Seattle Campus, Seattle, WA, United States, Martyn P Clark, National Center for Atmospheric Research, Boulder, United States, Ned Haughton, University of New South Wales, Climate Change Research Centre (CCRC), Sydney, Australia and Gab Abramowitz, Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia

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