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Volumn 48, Issue 5, 2010, Pages 701-715

Model averaging techniques for quantifying conceptual model uncertainty

Author keywords

[No Author keywords available]

Indexed keywords

AKAIKE INFORMATION CRITERION; ANDERSONS; BAYESIAN; BAYESIAN MODEL AVERAGING; COMPARATIVE ASSESSMENT; CONCEPTUAL MODEL; GENERALIZED LIKELIHOOD UNCERTAINTY ESTIMATION; GROUNDWATER MODELING; GROUNDWATER MODELS; INFORMATION CRITERION; MODEL AVERAGING; MODEL UNCERTAINTIES; MODELING PARADIGMS; MONTE CARLO; PROS AND CONS; STATISTICAL MODELS;

EID: 77954973403     PISSN: 0017467X     EISSN: 17456584     Source Type: Journal    
DOI: 10.1111/j.1745-6584.2009.00642.x     Document Type: Article
Times cited : (79)

References (44)
  • 1
    • 0000501656 scopus 로고
    • Information theory as an extension of the maximum likelihood principle
    • Petrov BN. ed., Budapest, Hungary, Akademiai Kiado
    • Akaike H. Information theory as an extension of the maximum likelihood principle. Second International Symposium on Information Theory 1973, 267-281. Petrov BN. ed., Budapest, Hungary, Akademiai Kiado
    • (1973) Second International Symposium on Information Theory , pp. 267-281
    • Akaike, H.1
  • 3
    • 34247638849 scopus 로고    scopus 로고
    • Death Valley regional ground-water flow system, Nevada and California-Hydrogeologic framework and transient ground-water flow model
    • Belcher WR. ed., U.S. Geological Survey Scientific Investigations Report 2004-5205, Reston, Virginia, USGS
    • Death Valley regional ground-water flow system, Nevada and California-Hydrogeologic framework and transient ground-water flow model. 2004, Belcher WR. ed., U.S. Geological Survey Scientific Investigations Report 2004-5205, 408 p., Reston, Virginia, USGS
    • (2004) , pp. 408
  • 5
    • 33748792555 scopus 로고    scopus 로고
    • On undermining the science?
    • Beven KJ. On undermining the science? Hydrological Processes 2006, 20:3141-3146.
    • (2006) Hydrological Processes , vol.20 , pp. 3141-3146
    • Beven, K.J.1
  • 6
    • 0033762270 scopus 로고    scopus 로고
    • Uniqueness of place and process representations in hydrological modelling
    • Beven KJ. Uniqueness of place and process representations in hydrological modelling. Hydrology and Earth System Sciences 2000, 4:203-213.
    • (2000) Hydrology and Earth System Sciences , vol.4 , pp. 203-213
    • Beven, K.J.1
  • 7
    • 0027788553 scopus 로고
    • Prophecy, reality and uncertainty in distributed hydrological modeling
    • Beven KJ. Prophecy, reality and uncertainty in distributed hydrological modeling. Advances in Water Resources 1993, 16:41-51.
    • (1993) Advances in Water Resources , vol.16 , pp. 41-51
    • Beven, K.J.1
  • 8
    • 0035426008 scopus 로고    scopus 로고
    • Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology
    • Beven K, Freer J. Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology. Journal of Hydrology 2001, 249:11-29.
    • (2001) Journal of Hydrology , vol.249 , pp. 11-29
    • Beven, K.1    Freer, J.2
  • 9
    • 0027009437 scopus 로고
    • The future of distributed models: Model calibration and uncertainty prediction
    • Beven KJ, Binley A. The future of distributed models: Model calibration and uncertainty prediction. Hydrological Processes 1992, 6:279-298.
    • (1992) Hydrological Processes , vol.6 , pp. 279-298
    • Beven, K.J.1    Binley, A.2
  • 10
    • 0022923351 scopus 로고
    • Estimation of aquifer parameters under transient and steady state conditions. 1, Maximum likelihood method incorporating prior information
    • no.
    • Carrera J, Neuman SP. Estimation of aquifer parameters under transient and steady state conditions. 1, Maximum likelihood method incorporating prior information. Water Resources Research 1986, 22(2):199-210. no.
    • (1986) Water Resources Research , vol.22 , Issue.2 , pp. 199-210
    • Carrera, J.1    Neuman, S.P.2
  • 11
    • 0018654860 scopus 로고
    • Spatial variability and uncertainty in ground water flow parameters: A geostatistical approach
    • no.
    • Delhomme JP. Spatial variability and uncertainty in ground water flow parameters: A geostatistical approach. Water Resources Research 1979, 15(2):269-280. no.
    • (1979) Water Resources Research , vol.15 , Issue.2 , pp. 269-280
    • Delhomme, J.P.1
  • 12
    • 77955941843 scopus 로고    scopus 로고
    • PEST: Model-independent parameter estimation, user manual, version 5. Brisbane, Australia: Watermark Numerical Computing
    • Doherty J. 2004, PEST: Model-independent parameter estimation, user manual, version 5. Brisbane, Australia: Watermark Numerical Computing
    • (2004)
    • Doherty, J.1
  • 13
    • 0013396180 scopus 로고    scopus 로고
    • Bayesian averaging of classifiers and the overfitting problem
    • ICML'00.
    • Domingos P. Bayesian averaging of classifiers and the overfitting problem. 2000, http://www.cs.washington.edu/homese/pedrod/mlc00b.ps.gz, ICML'00.
    • (2000)
    • Domingos, P.1
  • 16
    • 0024686367 scopus 로고
    • Predictions of transmissivities, heads, and seepage velocities using mathematical models and geostatistics
    • no.
    • Hoeksema RJ, Kitanidis PK. Predictions of transmissivities, heads, and seepage velocities using mathematical models and geostatistics. Advances in Water Resources 1989, 12(2):90-102. no.
    • (1989) Advances in Water Resources , vol.12 , Issue.2 , pp. 90-102
    • Hoeksema, R.J.1    Kitanidis, P.K.2
  • 18
    • 70349119250 scopus 로고
    • Regression and time series model selection in small sample
    • no.
    • Hurvich CM, Tsai C-L. Regression and time series model selection in small sample. Biometrika 1989, 76(2):99-104. no.
    • (1989) Biometrika , vol.76 , Issue.2 , pp. 99-104
    • Hurvich, C.M.1    Tsai, C.-L.2
  • 21
    • 84950945692 scopus 로고
    • Model selection and accounting for model uncertainty in graphical models using Occam's window
    • no.
    • Madigan D, Raftery AE. Model selection and accounting for model uncertainty in graphical models using Occam's window. Journal of the American Statistical Association 1994, 89(428):1535-1546. no.
    • (1994) Journal of the American Statistical Association , vol.89 , Issue.428 , pp. 1535-1546
    • Madigan, D.1    Raftery, A.E.2
  • 22
    • 33748808177 scopus 로고    scopus 로고
    • Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology
    • Mantovan P, Todini E. Hydrological forecasting uncertainty assessment: Incoherence of the GLUE methodology. Journal of Hydrology 2006, 330:368-381.
    • (2006) Journal of Hydrology , vol.330 , pp. 368-381
    • Mantovan, P.1    Todini, E.2
  • 23
    • 79551477338 scopus 로고    scopus 로고
    • Bayesian model averaging is not model combination, MIT Media Lab note (7/6/00)
    • Available at
    • Minka TP. Bayesian model averaging is not model combination, MIT Media Lab note (7/6/00). 2000, http://research.microsoft.com/~minka/papers/minka-bma-isnt-mc.pdf, Available at
    • (2000)
    • Minka, T.P.1
  • 24
    • 31644442912 scopus 로고    scopus 로고
    • The cost of uniqueness in groundwater model calibration
    • Moore C, Doherty J. The cost of uniqueness in groundwater model calibration. Advances in Water Resources 2006, 29:605-623.
    • (2006) Advances in Water Resources , vol.29 , pp. 605-623
    • Moore, C.1    Doherty, J.2
  • 25
    • 33845267497 scopus 로고    scopus 로고
    • Assessing the impacts of parameter uncertainty for computationally expensive ground water models
    • doi:10.1029/2005WR004640
    • Mugunthan P, Shoemaker CA. Assessing the impacts of parameter uncertainty for computationally expensive ground water models. Water Resources Research 2006, 42:W10428. doi:10.1029/2005WR004640
    • (2006) Water Resources Research , vol.42
    • Mugunthan, P.1    Shoemaker, C.A.2
  • 26
    • 0014776873 scopus 로고
    • River flow forecasting through conceptual models, 1. A 849 discussion of principles.
    • Nash J, Sutcliffe J. River flow forecasting through conceptual models, 1. A 849 discussion of principles. Journal of Hydrology 1970, 10:282-290.
    • (1970) Journal of Hydrology , vol.10 , pp. 282-290
    • Nash, J.1    Sutcliffe, J.2
  • 28
    • 0348225037 scopus 로고    scopus 로고
    • Maximum likelihood Bayesian averaging of uncertain model predictions
    • no.
    • Neuman SP. Maximum likelihood Bayesian averaging of uncertain model predictions. Stochastic Environmental Research and Risk Assessment 2003, 17(5):291-305. no.
    • (2003) Stochastic Environmental Research and Risk Assessment , vol.17 , Issue.5 , pp. 291-305
    • Neuman, S.P.1
  • 29
    • 84879575554 scopus 로고
    • Statistical characterization of aquifer heterogeneities: An overview
    • Geological Society of America Special Paper 189., Boulder, Colorado: Geological Society of America
    • Neuman SP. Statistical characterization of aquifer heterogeneities: An overview. Recent Trends in Hydrogeology 1982, 81-102. Geological Society of America Special Paper 189., Boulder, Colorado: Geological Society of America
    • (1982) Recent Trends in Hydrogeology , pp. 81-102
    • Neuman, S.P.1
  • 31
    • 77955968697 scopus 로고    scopus 로고
    • MMA, A computer code for Multi-Model Analysis: U.S. Geological Survey Techniques and Methods
    • Reston, Virginia: USGS
    • Poeter EP, Hill MC. MMA, A computer code for Multi-Model Analysis: U.S. Geological Survey Techniques and Methods. 2007, 6-E3. Reston, Virginia: USGS
    • (2007)
    • Poeter, E.P.1    Hill, M.C.2
  • 32
    • 22244490375 scopus 로고    scopus 로고
    • Multimodel ranking and inference in ground water modeling
    • no.
    • Poeter E, Anderson D. Multimodel ranking and inference in ground water modeling. Ground Water 2005, 43(4):597-605. no.
    • (2005) Ground Water , vol.43 , Issue.4 , pp. 597-605
    • Poeter, E.1    Anderson, D.2
  • 33
    • 0001201909 scopus 로고
    • Bayesian model selection in social research
    • Raftery AE. Bayesian model selection in social research. Sociological Methodology 1995, 25:111-163.
    • (1995) Sociological Methodology , vol.25 , pp. 111-163
    • Raftery, A.E.1
  • 34
    • 0024483119 scopus 로고
    • Estimation of spatial covariance structures by adjoint state maximum likelihood cross validation: 1, Theory
    • Samper FJ, Neuman SP. Estimation of spatial covariance structures by adjoint state maximum likelihood cross validation: 1, Theory. Water Resources Research 1989, 25:351-362.
    • (1989) Water Resources Research , vol.25 , pp. 351-362
    • Samper, F.J.1    Neuman, S.P.2
  • 35
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • no.
    • Schwarz G. Estimating the dimension of a model. Annals of Statistics 1978, 6(2):461-464. no.
    • (1978) Annals of Statistics , vol.6 , Issue.2 , pp. 461-464
    • Schwarz, G.1
  • 37
    • 55249111575 scopus 로고    scopus 로고
    • Ground water inverse modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window
    • no., doi:10.1029/2007WR006576
    • Tsai FT-C, Li X. Ground water inverse modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window. Water Resources Research 2008, 44(9):W09434. no., doi:10.1029/2007WR006576
    • (2008) Water Resources Research , vol.44 , Issue.9
    • Tsai, F.T.-C.1    Li, X.2
  • 38
    • 69949188688 scopus 로고    scopus 로고
    • Appraisal of the Generalized Likelihood Uncertainty Estimation (GLUE) method
    • doi:10.1029/2008WR006822, 2008
    • Vogel RM, Batchelder R, Stedinger JR. Appraisal of the Generalized Likelihood Uncertainty Estimation (GLUE) method. Water Resources Research 2007, 44:WOOB06. doi:10.1029/2008WR006822, 2008
    • (2007) Water Resources Research , vol.44
    • Vogel, R.M.1    Batchelder, R.2    Stedinger, J.R.3
  • 39
    • 0024800594 scopus 로고
    • Reliable aquifer remediation in the presence of spatially variable hydraulic conductivity; from data to design
    • no.
    • Wagner BJ, Gorelick SM. Reliable aquifer remediation in the presence of spatially variable hydraulic conductivity; from data to design. Water Resources Research 1989, 25(10):2211-2225. no.
    • (1989) Water Resources Research , vol.25 , Issue.10 , pp. 2211-2225
    • Wagner, B.J.1    Gorelick, S.M.2
  • 40
    • 43249109413 scopus 로고    scopus 로고
    • On model selection criteria in multimodel analysis
    • doi:10.1029/2008WR006803
    • Ye M, Meyer PD, Neuman SP. On model selection criteria in multimodel analysis. Water Resources Research 2008b, 44:W03428. doi:10.1029/2008WR006803
    • (2008) Water Resources Research , vol.44
    • Ye, M.1    Meyer, P.D.2    Neuman, S.P.3
  • 41
    • 77955962457 scopus 로고    scopus 로고
    • On evaluation of conceptual models: a priori and a posteriori. International High-Level Radioactive Waste Management Conference, April 30 - May 4, Las Vegas, NV. Available at
    • Ye M, Pohlmann K, Chapman J, Shafer D. 2005, http://www.osti.gov/bridge/product.biblio.jsp?osti_id=875590, On evaluation of conceptual models: a priori and a posteriori. International High-Level Radioactive Waste Management Conference, April 30 - May 4, Las Vegas, NV. Available at
    • (2005)
    • Ye, M.1    Pohlmann, K.2    Chapman, J.3    Shafer, D.4
  • 42
    • 31444456874 scopus 로고    scopus 로고
    • Sensitivity analysis and assessment of prior model probabilities in MLBMA with application to unsaturated fractured tuff
    • doi:10.1029/2005WR004260
    • Ye M, Neuman SP, Meyer PD, Pohlmann KF. Sensitivity analysis and assessment of prior model probabilities in MLBMA with application to unsaturated fractured tuff. Water Resources Research 2005, 41:W12429. doi:10.1029/2005WR004260
    • (2005) Water Resources Research , vol.41
    • Ye, M.1    Neuman, S.P.2    Meyer, P.D.3    Pohlmann, K.F.4
  • 43
    • 2942700220 scopus 로고    scopus 로고
    • Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff
    • Ye M, Neuman SP, Meyer PD. Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff. Water Resources Research 2004, 40:W05113.
    • (2004) Water Resources Research , vol.40
    • Ye, M.1    Neuman, S.P.2    Meyer, P.D.3
  • 44
    • 43449120662 scopus 로고    scopus 로고
    • Expert elicitation of recharge model probabilities for the Death Valley regional flow system
    • doi:10.1016/j.jhydrol.2008.03.001
    • Ye M, Pohlmann KF, Chapman JB. Expert elicitation of recharge model probabilities for the Death Valley regional flow system. Journal of Hydrology 2008a, 354:102-115. doi:10.1016/j.jhydrol.2008.03.001
    • (2008) Journal of Hydrology , vol.354 , pp. 102-115
    • Ye, M.1    Pohlmann, K.F.2    Chapman, J.B.3


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