A new process sensitivity index to identify important system processes under process model and parametric uncertainty
Abstract
A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the newmore »
- Authors:
-
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Florida State Univ., Tallahassee FL (United States). Dept. of Scientific Computing
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Environmental Sciences Division and Climate Change Science Inst.
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1376306
- Grant/Contract Number:
- AC05-00OR22725; SC0008272; 1552329; AC05-76RL01830
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Water Resources Research
- Additional Journal Information:
- Journal Volume: 53; Journal Issue: 4; Journal ID: ISSN 0043-1397
- Publisher:
- American Geophysical Union (AGU)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; process sensitivity index; variance decomposition; model averaging; model uncertainty; parametric uncertainty; groundwater reactive transport modeling
Citation Formats
Dai, Heng, Ye, Ming, Walker, Anthony P., and Chen, Xingyuan. A new process sensitivity index to identify important system processes under process model and parametric uncertainty. United States: N. p., 2017.
Web. doi:10.1002/2016WR019715.
Dai, Heng, Ye, Ming, Walker, Anthony P., & Chen, Xingyuan. A new process sensitivity index to identify important system processes under process model and parametric uncertainty. United States. https://doi.org/10.1002/2016WR019715
Dai, Heng, Ye, Ming, Walker, Anthony P., and Chen, Xingyuan. Tue .
"A new process sensitivity index to identify important system processes under process model and parametric uncertainty". United States. https://doi.org/10.1002/2016WR019715. https://www.osti.gov/servlets/purl/1376306.
@article{osti_1376306,
title = {A new process sensitivity index to identify important system processes under process model and parametric uncertainty},
author = {Dai, Heng and Ye, Ming and Walker, Anthony P. and Chen, Xingyuan},
abstractNote = {A hydrological model consists of multiple process level submodels, and each submodel represents a process key to the operation of the simulated system. Global sensitivity analysis methods have been widely used to identify important processes for system model development and improvement. The existing methods of global sensitivity analysis only consider parametric uncertainty, and are not capable of handling model uncertainty caused by multiple process models that arise from competing hypotheses about one or more processes. To address this problem, this study develops a new method to probe model output sensitivity to competing process models by integrating model averaging methods with variance-based global sensitivity analysis. A process sensitivity index is derived as a single summary measure of relative process importance, and the index includes variance in model outputs caused by uncertainty in both process models and their parameters. Here, for demonstration, the new index is used to assign importance to the processes of recharge and geology in a synthetic study of groundwater reactive transport modeling. The recharge process is simulated by two models that convert precipitation to recharge, and the geology process is simulated by two models of hydraulic conductivity. Each process model has its own random parameters. Finally, the new process sensitivity index is mathematically general, and can be applied to a wide range of problems in hydrology and beyond.},
doi = {10.1002/2016WR019715},
journal = {Water Resources Research},
number = 4,
volume = 53,
place = {United States},
year = {Tue Mar 28 00:00:00 EDT 2017},
month = {Tue Mar 28 00:00:00 EDT 2017}
}
Web of Science
Works referenced in this record:
A unified approach for process‐based hydrologic modeling: 1. Modeling concept
journal, April 2015
- Clark, Martyn P.; Nijssen, Bart; Lundquist, Jessica D.
- Water Resources Research, Vol. 51, Issue 4
Analytical solutions for multiple species reactive transport in multiple dimensions
journal, January 1999
- Sun, Y.; Petersen, J. N.; Clement, T. P.
- Journal of Contaminant Hydrology, Vol. 35, Issue 4
Model selection on solid ground: Rigorous comparison of nine ways to evaluate Bayesian model evidence
journal, December 2014
- Schöniger, Anneli; Wöhling, Thomas; Samaniego, Luis
- Water Resources Research, Vol. 50, Issue 12
Dominant processes concept, model simplification and classification framework in catchment hydrology
journal, August 2007
- Sivakumar, Bellie
- Stochastic Environmental Research and Risk Assessment, Vol. 22, Issue 6
From Models to Performance Assessment: The Conceptualization Problem
journal, September 2003
- Bredehoeft, John D.
- Ground Water, Vol. 41, Issue 5
The quantity and quality of information in hydrologic models
journal, January 2015
- Nearing, Grey S.; Gupta, Hoshin V.
- Water Resources Research, Vol. 51, Issue 1
Facets of uncertainty: epistemic uncertainty, non-stationarity, likelihood, hypothesis testing, and communication
journal, May 2016
- Beven, Keith
- Hydrological Sciences Journal, Vol. 61, Issue 9
What do we mean by sensitivity analysis? The need for comprehensive characterization of “global” sensitivity in Earth and Environmental systems models: A Critical Look at Sensitivity Analysis
journal, May 2015
- Razavi, Saman; Gupta, Hoshin V.
- Water Resources Research, Vol. 51, Issue 5
Predicting long-term carbon sequestration in response to CO 2 enrichment: How and why do current ecosystem models differ?
journal, April 2015
- Walker, Anthony P.; Zaehle, Sönke; Medlyn, Belinda E.
- Global Biogeochemical Cycles, Vol. 29, Issue 4
Bayesian evidence and model selection
journal, December 2015
- Knuth, Kevin H.; Habeck, Michael; Malakar, Nabin K.
- Digital Signal Processing, Vol. 47
Evaluating model structure adequacy: The case of the Maggia Valley groundwater system, southern Switzerland: Evaluating Model Structure Adequacy
journal, January 2013
- Foglia, L.; Mehl, S. W.; Hill, M. C.
- Water Resources Research, Vol. 49, Issue 1
Maximum likelihood Bayesian averaging of uncertain model predictions
journal, November 2003
- Neuman, S. P.
- Stochastic Environmental Research and Risk Assessment (SERRA), Vol. 17, Issue 5
On model selection criteria in multimodel analysis: ON MODEL SELECTION CRITERIA IN MULTIMODEL ANALYSIS
journal, March 2008
- Ye, Ming; Meyer, Philip D.; Neuman, Shlomo P.
- Water Resources Research, Vol. 44, Issue 3
Improving the theoretical underpinnings of process-based hydrologic models: NARROWING THE GAP BETWEEN HYDROLOGIC THEORY AND MODELS
journal, March 2016
- Clark, Martyn P.; Schaefli, Bettina; Schymanski, Stanislaus J.
- Water Resources Research, Vol. 52, Issue 3
Integrating structural geological data into the inverse modelling framework of iTOUGH2
journal, April 2014
- Wellmann, J. Florian; Finsterle, Stefan; Croucher, Adrian
- Computers & Geosciences, Vol. 65
Practical Use of Computationally Frugal Model Analysis Methods: M.C. Hill et al. Ground Water xx, no. x: xx-xx
journal, March 2015
- Hill, Mary C.; Kavetski, Dmitri; Clark, Martyn
- Groundwater, Vol. 54, Issue 2
A unified approach for process‐based hydrologic modeling: 2. Model implementation and case studies
journal, April 2015
- Clark, Martyn P.; Nijssen, Bart; Lundquist, Jessica D.
- Water Resources Research, Vol. 51, Issue 4
Scaling in hydrology: INVITED COMMENTARY
journal, March 2001
- Blöschl, Günter
- Hydrological Processes, Vol. 15, Issue 4
An efficient, high-order probabilistic collocation method on sparse grids for three-dimensional flow and solute transport in randomly heterogeneous porous media
journal, May 2009
- Lin, G.; Tartakovsky, A. M.
- Advances in Water Resources, Vol. 32, Issue 5
Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications
journal, April 2015
- Song, Xiaomeng; Zhang, Jianyun; Zhan, Chesheng
- Journal of Hydrology, Vol. 523
Making sense of global sensitivity analyses
journal, April 2014
- Wainwright, Haruko M.; Finsterle, Stefan; Jung, Yoojin
- Computers & Geosciences, Vol. 65
Dominant processes concept in hydrology: moving forward
journal, August 2004
- Sivakumar, Bellie
- Hydrological Processes, Vol. 18, Issue 12
Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index
journal, February 2010
- Saltelli, Andrea; Annoni, Paola; Azzini, Ivano
- Computer Physics Communications, Vol. 181, Issue 2
Assessment of parametric uncertainty for groundwater reactive transport modeling
journal, May 2014
- Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.
- Water Resources Research, Vol. 50, Issue 5
Assessing five evolving microbial enzyme models against field measurements from a semiarid savannah-What are the mechanisms of soil respiration pulses?
journal, September 2014
- Zhang, Xia; Niu, Guo-Yue; Elshall, Ahmed S.
- Geophysical Research Letters, Vol. 41, Issue 18
Bayesian analysis of data-worth considering model and parameter uncertainties
journal, February 2012
- Neuman, Shlomo P.; Xue, Liang; Ye, Ming
- Advances in Water Resources, Vol. 36
Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models: DIFFERENCES BETWEEN HYDROLOGICAL MODELS
journal, August 2008
- Clark, Martyn P.; Slater, Andrew G.; Rupp, David E.
- Water Resources Research, Vol. 44, Issue 12
Multimodel Bayesian analysis of groundwater data worth
journal, November 2014
- Xue, Liang; Zhang, Dongxiao; Guadagnini, Alberto
- Water Resources Research, Vol. 50, Issue 11
A Model-Averaging Method for Assessing Groundwater Conceptual Model Uncertainty
journal, August 2010
- Ye, Ming; Pohlmann, Karl F.; Chapman, Jenny B.
- Ground Water, Vol. 48, Issue 5
Identification of sorption processes and parameters for radionuclide transport in fractured rock
journal, January 2012
- Dai, Zhenxue; Wolfsberg, Andrew; Reimus, Paul
- Journal of Hydrology, Vol. 414-415
Evaluating marginal likelihood with thermodynamic integration method and comparison with several other numerical methods: THERMODYNAMIC INTEGRATION FOR EVALUATING MARGINAL LIKELIHOOD
journal, February 2016
- Liu, Peigui; Elshall, Ahmed S.; Ye, Ming
- Water Resources Research, Vol. 52, Issue 2
Evaluating Groundwater Interbasin Flow Using Multiple Models and Multiple Types of Data: Groundwater XX, no. XX: XX-XX
journal, April 2016
- Ye, Ming; Wang, Liying; Pohlmann, Karl. F.
- Groundwater, Vol. 54, Issue 6
Multimodel Bayesian analysis of data-worth applied to unsaturated fractured tuffs
journal, January 2012
- Lu, Dan; Ye, Ming; Neuman, Shlomo P.
- Advances in Water Resources, Vol. 35
Towards simplification of hydrologic modeling: identification of dominant processes
journal, January 2016
- Markstrom, Steven L.; Hay, Lauren E.; Clark, Martyn P.
- Hydrology and Earth System Sciences, Vol. 20, Issue 11
Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models
journal, October 2015
- Lu, Dan; Ye, Ming; Curtis, Gary P.
- Journal of Hydrology, Vol. 529
Debates-the future of hydrological sciences: A (common) path forward? Using models and data to learn: A systems theoretic perspective on the future of hydrological science
journal, June 2014
- Gupta, Hoshin V.; Nearing, Grey S.
- Water Resources Research, Vol. 50, Issue 6
Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models: Distributed evaluation of local sensitivity analysis
journal, January 2014
- Rakovec, O.; Hill, M. C.; Clark, M. P.
- Water Resources Research, Vol. 50, Issue 1
An adaptive sparse-grid high-order stochastic collocation method for Bayesian inference in groundwater reactive transport modeling: Sparse-Grid Method for Bayesian Inference
journal, October 2013
- Zhang, Guannan; Lu, Dan; Ye, Ming
- Water Resources Research, Vol. 49, Issue 10
Sensitivity Analysis for Chemical Models
journal, July 2005
- Saltelli, Andrea; Ratto, Marco; Tarantola, Stefano
- Chemical Reviews, Vol. 105, Issue 7
Managing complexity in simulations of land surface and near-surface processes
journal, April 2016
- Coon, Ethan T.; David Moulton, J.; Painter, Scott L.
- Environmental Modelling & Software, Vol. 78
Bayesian process-identification in bacteria transport in porous media
journal, October 2013
- Massoudieh, Arash; Lu, Nanxi; Liang, Xiaomeng
- Journal of Contaminant Hydrology, Vol. 153
Expert elicitation of recharge model probabilities for the Death Valley regional flow system
journal, June 2008
- Ye, Ming; Pohlmann, Karl F.; Chapman, Jenny B.
- Journal of Hydrology, Vol. 354, Issue 1-4
The conceptualization model problem?surprise
journal, February 2005
- Bredehoeft, John
- Hydrogeology Journal, Vol. 13, Issue 1
Time-varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior: TIME-VARYING SENSITIVITY OF WATERSHED MODELS
journal, March 2013
- Herman, J. D.; Reed, P. M.; Wagener, T.
- Water Resources Research, Vol. 49, Issue 3
A philosophical basis for hydrological uncertainty
journal, May 2016
- Nearing, Grey S.; Tian, Yudong; Gupta, Hoshin V.
- Hydrological Sciences Journal, Vol. 61, Issue 9
Works referencing / citing this record:
On the Sensitivity of the Precipitation Partitioning Into Evapotranspiration and Runoff in Land Surface Parameterizations
journal, January 2019
- Zheng, Hui; Yang, Zong‐Liang; Lin, Peirong
- Water Resources Research, Vol. 55, Issue 1
Parametric and Structural Sensitivities of Turbine‐Height Wind Speeds in the Boundary Layer Parameterizations in the Weather Research and Forecasting Model
journal, June 2019
- Yang, Ben; Berg, Larry K.; Qian, Yun
- Journal of Geophysical Research: Atmospheres, Vol. 124, Issue 12
A Comprehensive Distributed Hydrological Modeling Intercomparison to Support Process Representation and Data Collection Strategies
journal, February 2019
- Baroni, Gabriele; Schalge, Bernd; Rakovec, Oldrich
- Water Resources Research, Vol. 55, Issue 2
The multi-assumption architecture and testbed (MAAT v1.0): R code for generating ensembles with dynamic model structure and analysis of epistemic uncertainty from multiple sources
journal, January 2018
- Walker, Anthony P.; Ye, Ming; Lu, Dan
- Geoscientific Model Development, Vol. 11, Issue 8
A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions
journal, January 2019
- Schürz, Christoph; Hollosi, Brigitta; Matulla, Christoph
- Hydrology and Earth System Sciences, Vol. 23, Issue 3
A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions
journal, August 2018
- Schurz, Christoph; Hollosi, Brigitta; Matulla, Christoph
- Hydrology and Earth System Sciences Discussions