H41B:
Diagnostics, Sensitivity, and Uncertainty Analysis of Earth and Environmental Models I


Submit an Abstract to this Session


Session ID#: 62258

Session Description:
Environmental models are key monitoring and prediction tools used in science and engineering. These complex models not only have uncertain inputs and structure, which propagate into uncertain model outputs, but also continually increase in computational demand. Sensitivity and Uncertainty Analyses (SA/UA) are used to understand model structure, identify informative model parameters, characterize uncertainties, and reduce the computational load of demanding applications such as model optimizations. This session invites contributions on both theory and application of model diagnostics as well as sensitivity and uncertainty analysis. We further welcome contributions focusing on aspects of the model-data interface, which plays an important role in uncertainty quantification.

Particular topics of interest include (but are not limited to):

  • Methods for better understanding and characterization of "uncertainty" and "sensitivity";
  • Strategies for more comprehensive SA/UA (e.g., multi-criteria SA);
  • Input data uncertainty quantification;
  • Methods for improving computational efficiency of SA/UA;
  • Combining models and data to make better predictions.
Primary Convener:  Juliane Mai, University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada
Conveners:  Mary C Hill, University of Kansas, Geology, Lawrence, KS, United States, Saman Razavi, University of Saskatchewan, Saskatoon, SK, Canada and Matthias Cuntz, INRA Institut National de la Recherche Agronomique, Paris Cedex 07, France
Primary Liaison:  Juliane Mai, University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada
Chairs:  Juliane Mai, University of Waterloo, Waterloo, ON, Canada and Saman Razavi, University of Saskatchewan, Saskatoon, SK, Canada
OSPA Liaison:  Juliane Mai, University of Waterloo, Waterloo, ON, Canada

Cross-Listed:
  • B - Biogeosciences
  • EP - Earth and Planetary Surface Processes
  • GC - Global Environmental Change
  • 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:

Calibrating a Terrestrial Hydrology Model for Process-Realism (Invited) (344030)
Dr. Grey Stephen Nearing, PHD, University of Alabama, Geological Sciences, Tuscaloosa, United States and Benjamin L Ruddell, Northern Arizona University, School of Informatics, Computing, and Cyber Systems, Flagstaff, United States
Benefits of parsimonious representations of hydrological processes in Earth System Models (441251)
Rafael Rosolem1, Thorsten Wagener2, Mostaquimur Rahman1, Stamatis Christos Batelis3, Stefan J Kollet4, Fanny Sarrazin5, Andreas J Hartmann6 and Francesca Pianosi1, (1)University of Bristol, Civil Engineering, Bristol, United Kingdom, (2)University of Potsdam, Potsdam, Germany, (3)University of Bristol, Civil Engineering, Bristol, BS8, United Kingdom, (4)Research Center Juelich, Jülich, Germany, (5)University of Bristol, Bristol, UK, Civil Engineering, Bristol, United Kingdom, (6)University of Bristol, Bristol, United Kingdom
Demonstrating the Added Values of Suction Losses for Channel Infiltration in WRF-Hydro Hydrologic Model and its Applications in Semiarid Region (354690)
Yuan-Heng Wang1, Pieter Hazenberg2, Hoshin Gupta3, Christopher L Castro3, Timothy M Lahmers4, Carl C Unkrich5 and David C Goodrich6, (1)University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (2)Unversity of Arizona, Tucson, AZ, United States, (3)University of Arizona, Hydrology and Atmospheric Sciences, Tucson, AZ, United States, (4)NASA Goddard Space Flight Center, Greenbelt, United States, (5)Agricultural Research Service Tucson, Tucson, United States, (6)USDA-ARS Southwest Watershed Research Center, Tucson, United States
A Generic Framework For Sensitivity Analysis With Correlated and/or Uncorrelated Inputs: Mathematical Underpinning, Computational Implementation and Case Studies (463773)
Jasper A Vrugt, University of California Irvine, Irvine, United States and Abdullah Sahin, University of California Irvine, Civil and Environmental Engineering, Irvine, CA, United States
Variogram-based global sensitivity analysis of environmental models with dependent variables (441453)
Nhu Cuong Do and Saman Razavi, University of Saskatchewan, Saskatoon, SK, Canada
Towards Automatic Model Structure Identification for Conceptual Hydrologic Models (429242)
Diana Spieler1, Juliane Mai2, James R Craig2, Bryan Tolson2 and Niels Schütze3, (1)University of Calgary, Department of Civil Engineering, Calgary, AB, Canada, (2)University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada, (3)Dresden University of Technology, Department of Hydrosciences, Dresden, Germany
Repetitive Optimization Diagnosis for High-Dimensional Water Quality Model Calibration and Application to Extensive Lake Data (469243)
Christine A Shoemaker1, Wei Xia1, Taimoor Akhtar1 and Manh Tuan Nguyen2, (1)National University of Singapore, Singapore, Singapore, (2)Public Utilities Board, Singapore, Singapore
Improving NWP wind speed forecast using a surrogate based uncertainty quantification method (372062)
Qingyun Duan, Hohai University, Nanjing, China, Zhenhua Di, Beijing Normal University, Beijing, China and Wei Gong, Beijing Normal University, Institute of Land Surface System and Sustainable Development, Faculty of Geographical Sciences, Beijing, China

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