H11A:
Advances in Sensitivity and Uncertainty Analysis of Earth and Environmental Systems Models II Posters

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Session ID#: 13465

Session Description:
Proper characterization of uncertainty remains a major challenge, and is inherent to many aspects of modelling such as parameter estimation and model prediction. To address this challenge, methods for “uncertainty analysis” (UA) that try to quantify uncertainty and how it propagates through models, and the closely-related methods for “sensitivity analysis” (SA) that facilitate understanding the role and significance of uncertain factors in the functioning of models, have proved to be very helpful.

This session invites contributions on both theory or application of SA/UA methods, including those related to parameter estimation, input data, and initial and boundary conditions. Particular topics of interest include:

  1. Methods for effective characterization of “uncertainty” and “sensitivity”
  2. Single- versus Multi-criteria SA/UA
  3. Metric specification for model evaluations
  4. The role of data error in model SA/UA
  5. Methods for improving computational efficiency of SA/UA (e.g. surrogate modelling)
  6. Spatial and/or temporal variation of SA/UA
Primary Convener:  Amin Haghnegahdar, University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada
Conveners:  Saman Razavi, University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada, Hoshin Vijai Gupta, University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States and Mary C Hill
Chairs:  Hoshin Vijai Gupta1, Amin Haghnegahdar2, Saman Razavi2 and Mary C Hill, (1)University of Arizona, Department of Hydrology and Atmospheric Sciences, Tucson, AZ, United States(2)University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada
OSPA Liaison:  Amin Haghnegahdar, University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada

Cross-Listed:
  • PA - Public Affairs
Index Terms:

1805 Computational hydrology [HYDROLOGY]
1846 Model calibration [HYDROLOGY]
1847 Modeling [HYDROLOGY]
1873 Uncertainty assessment [HYDROLOGY]

Abstracts Submitted to this Session:

Transport Behavior in Fractured Rock under Conceptual and Parametric Uncertainty (129402)
Hai V Pham1, Rishi Parashar2, Nicole Lyn Sund3 and Karl Pohlmann1, (1)Desert Research Institute, Las Vegas, NV, United States, (2)Desert Research Institute, Division of Hydrologic Sciences, Reno, United States, (3)Desert Research Institute, Reno, United States
NWT of MODFLOW: HOW WELL DOES IT REPRESENT REALITY? (135707)
Sevgi Cavdar1,2, Abdusselam Altunkaynak2 and Hasan Elmazoghi3, (1)Cumhuriyet University, Sivas, Turkey, (2)Istanbul Technical University, Maslak, Turkey, (3)University of Benghazi, Libya, Libya
Conditioning geostatistical simulations of a heterogeneous paleo-fluvial bedrock aquifer using lithologs and pumping tests (139063)
Amir Niazi1, Laurence R Bentley1 and Masaki Hayashi2, (1)University of Calgary, Calgary, AB, Canada, (2)University of Calgary, Department of Geoscience, Calgary, AB, Canada
Adaptive Kernel-density Independence Sampling based Monte Carlo Sampling (A-KISMCS) for inverse hydrological modelling (141720)
Saket Pande, Delft University of Technology, Delft, Netherlands and Mojtaba Shafiei, Technical University of Delft, Delft, Netherlands
Uncertainty Analysis for a Bayesian Multi-objective Ecohydrological Study (131205)
Yating Tang1, Lucy Amanda Marshall1, Ashish Sharma2 and Hoori Ajami3, (1)University of New South Wales, School of Civil and Environmental Engineering, Sydney, NSW, Australia, (2)University of New South Wales, Sydney, NSW, Australia, (3)University of California Riverside, Riverside, CA, United States
How Long And How Frequent Should We Measure Groundwater Heads? (140660)
Mark Bakker, Delft University of Technology, Water Management, Delft, Netherlands and Joanne Van Der Spek, Delft University of Technology, Delft, Netherlands
A two-step sensitivity analysis for hydrological signatures in Jinhua River Basin, East China (137549)
Suli Pan1, Guangtao Fu2, Yen-Ming Chiang1 and Yue-ping Xu3, (1)Zhejiang University, Hangzhou, China, (2)University of Exeter, Exeter, United Kingdom, (3)Zhejiang University, Institute of Water Science and Engineering, Hangzhou, China
Study of sensitivity of hydraulic properties of unconfined aquifer with oscillatory pumping test (148030)
Angélique Poulain, University of Mons, Geology and Applied Geology, Mons, Belgium and Pascal Goderniaux, Organization Not Listed, Washington, DC, United States
Parameter Optimisation and Uncertainty Analysis in Visual MODFLOW based Flow Model for predicting the groundwater head in an Eastern Indian Aquifer (157195)
Suraj Jena, Ph.D. Scholar, School of Infrastructure, Bhubaneswar, India, Rabindra Kumar Panda, Professor, School of Infrastructure, Bhubaneswar, India and Binayak Mohanty, Texas A&M University, Department of Biological and Agricultural Engineering, College Station, United States
Updating model parameter sensitivity on contaminant concentration with newly acquired dynamic observations (157426)
Jihoon Park1, Celine Scheidt2, Guang Yang1 and Jef Caers3, (1)Stanford University, Stanford, CA, United States, (2)Stanford University, Department of Energy Resources Engineering, Stanford, CA, United States, (3)Stanford Earth Sciences, Stanford, CA, United States
Quality of Mass Flux Measurements under Heterogeneous Aquifer Conditions (160723)
Ki Young Cha, Environmental Protection Agency Ada, Ada, OK, United States, Michael Carson Brooks, U.S. Environmental Protection Agency, Ada, OK, United States and Alvin L Wood, US EPA, Ada, OK, United States
Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions (154488)
Jeffrey Y Jung, Colorado State University, Fort Collins, CO, United States, Jeffrey D Niemann, Colorado State University, Department of Civil and Environmental Engineering, Fort Collins, United States and Blair P Greimann, Bureau of Reclamation Denver, Denver, CO, United States
Interpretation of Nonlinear Well Loss Coefficients for Rorabaugh (1953) Method. (177726)
Bedri Kurtulus, Tolga Necati Yaylım and Özgür Avşar, Muğla Sıtkı Koçman University, Department of Geological Engineering, Mugla, Turkey
Exploring Mass Flux Response to Local Source Zone Properties Using a Coupled-Process Adjoint Sensitivity Method (182669)
Tian Tang1, Eric L Miller1 and Linda M Abriola2, (1)Tufts University, Medford, MA, United States, (2)Tufts University, Civil and Environmental Engineering, Medford, MA, United States
A Bayesian Network Based Global Sensitivity Analysis Method for Identifying Dominant Processes in a Multi-physics Model (183643)
Heng Dai1, Xingyuan Chen2, Ming Ye3, Xuehang Song1 and John M Zachara1, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Pacific Northwest National Laboratory, Richland, United States, (3)Florida State University, Earth, Ocean, and Atmospheric Science, Tallahassee, United States
Dominant hydrological process identification for ungauged basins: Bayesian approach (160806)
Cristina Prieto1,2, Nataliya Le Vine3, Claudia Vitolo3,4, Nans Addor5 and Raul Medina2, (1)Imperial College London, Department of Civil and Environmental Engineering, London, SW7, United Kingdom, (2)Environmental Hydraulics Institute "IH Cantabria", University of Cantabria, Santander, Spain, (3)Imperial College London, Department of Civil and Environmental Engineering, London, United Kingdom, (4)European Centre for Medium-range Weather Forecasts (ECMWF), Forecast Department, Shinfield Park, Reading, United Kingdom, (5)National Center for Atmospheric Research, Hydrometeorological Applications Program, Research Applications Laboratory, Boulder, CO, United States
The sensitivity of training image and integration of airborne 3D electromagnetic data in multiple-point geostatistical simulation and the impact on groundwater modeling (188337)
Karsten H H. Jensen, University of Copenhagen, Department of Geosciences and Natural Resource Management, København K, Denmark, Xiulan He, Copenhagen University, Copenhagen, Denmark, Torben Obel Sonnenborg, Geological Survey of Denmark and Greenland, København K, Denmark and Flemming Jørgensen, Geological Survey of Denmark and Greenland, Groundwater and Quaternary Geology Mapping, Aarhus, Denmark
Calibration of Land Subsidence Model Using Well Head and InSAR Data: Parameter Estimation and Uncertainty Assessment (192039)
Liangping Li, South Dakota School of Mines and Technology, Rapid City, SD, United States and Meijing Zhang, University of Florida, Ft Walton Beach, FL, United States
Multi-Objective Calibration of a Hydrologic Model using Multi-Objective Screening  (183516)
Juliane Mai1, Matthias Cuntz2, Luis Samaniego3 and Bryan Tolson1, (1)University of Waterloo, Department of Civil and Environmental Engineering, Waterloo, ON, Canada, (2)Helmholtz Centre for Environmental Research UFZ Leipzig, Leipzig, Germany, (3)Helmholtz Centre for Environmental Research UFZ Leipzig, Computation Hydrosystems, Leipzig, Germany
Time-varying Uncertainty Bands for Streamflow Time Series Using Probabilistic Dynamic Rating Curves (182732)
Luis Camilo Galindo and Steven Weijs, University of British Columbia, Civil Engineering, Vancouver, BC, Canada
VARS-TOOL: A Comprehensive, Efficient, and Robust Sensitivity Analysis Toolbox (176938)
Saman Razavi1, Razi Sheikholeslami2, Amin Haghnegahdar1 and Bahareh Esfahbod1, (1)University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada, (2)Sharif University of Technology, Department of Civil Engineering, Tehran, Iran
Progressive Sampling Technique for Efficient and Robust Uncertainty and Sensitivity Analysis of Environmental Systems Models: Stability and Convergence (186632)
Nasim Hosseini, University of Saskatchewan, Saskatoon, SK, Canada, Razi Sheikholeslami, Sharif University of Technology, Department of Civil Engineering, Tehran, Iran and Saman Razavi, University of Saskatchewan, Global Institute for Water Security, Saskatoon, SK, Canada
Addressing Curse of Dimensionality in Sensitivity Analysis: How Can We Handle High-Dimensional Problems? (189991)
Sahar Safaei, Amin Haghnegahdar and Saman Razavi, Global Institute for Water Security, University of Saskatchewan, Saskatoon, SK, Canada
Sensitivity of different satellites gridded data over Brahmaputra Basin byusing Soil and Water Assessment Tool (SWAT) (196935)
Supria Paul1, Soni M Pradhanang1 and Akm Saiful Islam2, (1)University of Rhode Island, Narragansett, RI, United States, (2)Bangladesh Institute of Water and Flood Management, Dhaka, Bangladesh
Uncertainty Diagnostics for Probabilistic Flash Flood Forecasting over the Conterminous United States (198938)
Humberto J Vergara1, Pierre Kirstetter2, Jonathan J Gourley3 and Zac Flamig1, (1)University of Oklahoma Norman Campus, Norman, OK, United States, (2)University of Oklahoma Norman, School of Meteorology and School of Civil Engineering and Environmental Science, Norman, United States, (3)National Severe Storms Lab, Oklahoma City, United States

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