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Volumn 50, Issue 12, 2014, Pages 9586-9603

Improved Bayesian multimodeling: Integration of copulas and Bayesian model averaging

Author keywords

Bayesian model averaging; copula; forecast post processing; uncertainty in hydrologic forecasts

Indexed keywords

BAYESIAN NETWORKS; FLEXIBLE STRUCTURES; FORECASTING; METADATA; PROBABILITY DISTRIBUTIONS;

EID: 85027932033     PISSN: 00431397     EISSN: 19447973     Source Type: Journal    
DOI: 10.1002/2014WR015965     Document Type: Article
Times cited : (129)

References (90)
  • 1
    • 33847624519 scopus 로고    scopus 로고
    • An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction
    • Ajami, N. K.; Q. Duan, and, S. Sorooshian, (2007), An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction, Water Resour. Res.; 43, W01403, doi: 10.1029/2005WR004745.
    • (2007) Water Resour. Res. , vol.43 , pp. W01403
    • Ajami, N.K.1    Duan, Q.2    Sorooshian, S.3
  • 2
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • Akaike, H.; (1974), A new look at the statistical model identification, IEEE Trans. Autom. Control, 19 (6), 716-723.
    • (1974) IEEE Trans. Autom. Control , vol.19 , Issue.6 , pp. 716-723
    • Akaike, H.1
  • 3
    • 0014629731 scopus 로고
    • The combination of forecasts
    • (4)
    • Bates, J. M.; and, C. W. J. Granger, (1969), The combination of forecasts, Oper. Res.; 20 (4), 451-468.
    • (1969) Oper. Res. , vol.20 , pp. 451-468
    • Bates, J.M.1    Granger, C.W.J.2
  • 4
    • 33846341173 scopus 로고    scopus 로고
    • Copula-based geostatistical models for groundwater quality parameters
    • Bárdossy, A.; (2006), Copula-based geostatistical models for groundwater quality parameters, Water Resour. Res.; 42, W11416, doi: 10.1029/2005WR004754.
    • (2006) Water Resour. Res. , vol.42 , pp. W11416
    • Bárdossy, A.1
  • 5
    • 0027009437 scopus 로고
    • The future of distributed hydrological models: Model calibration and uncertainty prediction
    • Beven, K. J.; and, A. M. Binley, (1992), The future of distributed hydrological models: Model calibration and uncertainty prediction, Hydrol. Processes, 6, 279-298, doi: 10.1002/hyp.3360060305.
    • (1992) Hydrol. Processes , vol.6 , pp. 279-298
    • Beven, K.J.1    Binley, A.M.2
  • 6
    • 0000133998 scopus 로고
    • An analysis of transformations
    • (2)
    • Box, G. E. P.; and, D. R. Cox, (1964), An analysis of transformations, J. R. Stat. Soc. Ser. B, 26 (2), 211-252.
    • (1964) J. R. Stat. Soc. Ser. B , vol.26 , pp. 211-252
    • Box, G.E.P.1    Cox, D.R.2
  • 7
    • 84871438655 scopus 로고    scopus 로고
    • Evaluation of a nonparametric post-processor for bias correction and uncertainty estimation of hydrologic predictions
    • Brown, J. D.; and, D. J. Seo, (2012), Evaluation of a nonparametric post-processor for bias correction and uncertainty estimation of hydrologic predictions, Hydrol. Processes, doi: 10.1002/hyp.9263.
    • (2012) Hydrol. Processes
    • Brown, J.D.1    Seo, D.J.2
  • 8
    • 0030613470 scopus 로고    scopus 로고
    • Model selection: An integral part of inference
    • Buckland, S. T.; K. P. Burnham, and, N. H. Augustin, (1997), Model selection: An integral part of inference, Biometrics, 53, 603-618.
    • (1997) Biometrics , vol.53 , pp. 603-618
    • Buckland, S.T.1    Burnham, K.P.2    Augustin, N.H.3
  • 12
    • 0030465032 scopus 로고    scopus 로고
    • Modeling of land-surface evaporation by four schemes and comparison with FIFE observations
    • Chen, F.; K. Mitchell, J. Schaake, Y. Xue, H. Pan, V. Koren, Y. Duan, M. Ek, and, A. Betts, (1996), Modeling of land-surface evaporation by four schemes and comparison with FIFE observations, J. Geophys. Res.; 101 (D3), 7251-7268.
    • (1996) J. Geophys. Res. , vol.101 , Issue.D3 , pp. 7251-7268
    • Chen, F.1    Mitchell, K.2    Schaake, J.3    Xue, Y.4    Pan, H.5    Koren, V.6    Duan, Y.7    Ek, M.8    Betts, A.9
  • 13
    • 84945601297 scopus 로고
    • On the composition of elementary errors
    • Cramer, H.; (1928), On the composition of elementary errors, Scand. Actuarial J.; 11, 141-180.
    • (1928) Scand. Actuarial J. , vol.11 , pp. 141-180
    • Cramer, H.1
  • 14
    • 84893946462 scopus 로고    scopus 로고
    • A methodology to implement Box-Cox transformation when no covariate is available
    • Dag, O.; O. Asar, and, O. Ilk, (2013), A methodology to implement Box-Cox transformation when no covariate is available, Commun. Stat. Simul. Comput.; 43 (7), 1740-1759.
    • (2013) Commun. Stat. Simul. Comput. , vol.43 , Issue.7 , pp. 1740-1759
    • Dag, O.1    Asar, O.2    Ilk, O.3
  • 15
    • 0028552275 scopus 로고
    • A statistical-topographic model for mapping climatological precipitation over mountainous terrain
    • Daly, C.; R. P. Neilson, and, D. L. Phillips, (1994), A statistical-topographic model for mapping climatological precipitation over mountainous terrain, J. Appl. Meteorol.; 33, 140-158.
    • (1994) J. Appl. Meteorol. , vol.33 , pp. 140-158
    • Daly, C.1    Neilson, R.P.2    Phillips, D.L.3
  • 16
    • 0022266169 scopus 로고
    • Extended streamflow forecasting using NWSRFS
    • Day, G. N.; (1985), Extended streamflow forecasting using NWSRFS, J. Water Resour. Plan. Manage.; 111 (2), 157-170.
    • (1985) J. Water Resour. Plan. Manage. , vol.111 , Issue.2 , pp. 157-170
    • Day, G.N.1
  • 17
    • 81355139449 scopus 로고    scopus 로고
    • Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation
    • DeChant, C.; and, H. Moradkhani, (2011), Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation, Hydrol. Earth Syst. Sci.; 15, 3399-3410, doi: 10.5194/hess-15-3399.
    • (2011) Hydrol. Earth Syst. Sci. , vol.15 , pp. 3399-3410
    • Dechant, C.1    Moradkhani, H.2
  • 18
    • 84918841653 scopus 로고    scopus 로고
    • Toward a reliable prediction of seasonal forecast uncertainty: Addressing model and initial condition uncertainty with ensemble data assimilation and sequential Bayesian combination
    • (in press), special issue on Ensemble Forecasting and Data Assimilation, doi: 10.1016/j.jhydrol.2014.05.045
    • DeChant, C. M.; and, H. Moradkhani, (in press), Toward a reliable prediction of seasonal forecast uncertainty: Addressing model and initial condition uncertainty with ensemble data assimilation and sequential Bayesian combination, J. Hydrol.; special issue on Ensemble Forecasting and Data Assimilation, doi: 10.1016/j.jhydrol.2014.05.045.
    • J. Hydrol.
    • Dechant, C.M.1    Moradkhani, H.2
  • 19
    • 77954425477 scopus 로고    scopus 로고
    • Comparison of point forecast accuracy of model averaging methods in hydrologic applications
    • Diks, C. G. H.; and, J. A. Vrugt, (2010), Comparison of point forecast accuracy of model averaging methods in hydrologic applications, Stoch. Environ. Res. Risk Assess.; 24, 809-820, doi: 10.1007/s00477-010-0378-z.
    • (2010) Stoch. Environ. Res. Risk Assess. , vol.24 , pp. 809-820
    • Diks, C.G.H.1    Vrugt, J.A.2
  • 20
    • 1442328890 scopus 로고    scopus 로고
    • Scale problems in hydrology
    • edited by N. Buras, AGU, Washington, D. C
    • Dooge, J. C.; (1997), Scale problems in hydrology, in Reflections on Hydrology: Science and Practice, edited by, N. Buras, pp. 84-143, AGU, Washington, D. C.
    • (1997) Reflections on Hydrology: Science and Practice , pp. 84-143
    • Dooge, J.C.1
  • 21
    • 33644551546 scopus 로고    scopus 로고
    • Model parameter estimation experiment: Overview of science strategy and major results of the second and third workshops
    • Duan, Q.; et al. (2006), Model parameter estimation experiment: Overview of science strategy and major results of the second and third workshops, J. Hydrol.; 320, 3-17.
    • (2006) J. Hydrol. , vol.320 , pp. 3-17
    • Duan, Q.1
  • 22
    • 33847274843 scopus 로고    scopus 로고
    • Multi-model ensemble hydrologic prediction using Bayesian model averaging
    • Duan, Q.; N. K. Ajami, X. Gao, and, S. Sorooshian, (2007), Multi-model ensemble hydrologic prediction using Bayesian model averaging, Adv. Water Resour.; 30 (5), 1371-1386.
    • (2007) Adv. Water Resour. , vol.30 , Issue.5 , pp. 1371-1386
    • Duan, Q.1    Ajami, N.K.2    Gao, X.3    Sorooshian, S.4
  • 26
    • 84984442855 scopus 로고
    • Improved methods of combining forecasts
    • Granger, C. W. J.; and, R. Ramanathan, (1984), Improved methods of combining forecasts, J Forecast, 3, 197-204.
    • (1984) J Forecast , vol.3 , pp. 197-204
    • Granger, C.W.J.1    Ramanathan, R.2
  • 27
    • 0031741599 scopus 로고    scopus 로고
    • The land surface parameterization scheme SWAP: Description and partial validation
    • Gusev, Ye M.; and, O. N. Nasonova, (1998), The land surface parameterization scheme SWAP: Description and partial validation, Global Planet. Change, 19, 63-86.
    • (1998) Global Planet. Change , vol.19 , pp. 63-86
    • Gusev, Y.M.1    Nasonova, O.N.2
  • 28
    • 53649099464 scopus 로고    scopus 로고
    • Least-squares forecast averaging
    • Hansen, B. E.; (2008), Least-squares forecast averaging, J. Econ.; 146, 342-350.
    • (2008) J. Econ. , vol.146 , pp. 342-350
    • Hansen, B.E.1
  • 30
    • 41149132113 scopus 로고    scopus 로고
    • Calibration of hydrological model GR2M using Bayesian uncertainty analysis
    • Huard, D.; and, A. Mailhot, (2008), Calibration of hydrological model GR2M using Bayesian uncertainty analysis, Water Resour. Res.; 44, W02424, doi: 10.1029/2007WR005949.
    • (2008) Water Resour. Res. , vol.44 , pp. W02424
    • Huard, D.1    Mailhot, A.2
  • 31
    • 68349099316 scopus 로고    scopus 로고
    • A sequential Bayesian approach for hydrologic model selection and prediction
    • Hsu, K.; H. Moradkhani, and, S. Sorooshian, (2009), A sequential Bayesian approach for hydrologic model selection and prediction, Water Resour. Res.; 45, W00B12, doi: 10.1029/2008WR006824.
    • (2009) Water Resour. Res. , vol.45 , pp. W00B12
    • Hsu, K.1    Moradkhani, H.2    Sorooshian, S.3
  • 32
    • 0002437730 scopus 로고
    • A test for normality of observations and regression residuals
    • Jarque, C. M.; and, A. K. Bera, (1987), A test for normality of observations and regression residuals, Int. Stat. Rev.; 55 (2), 163-172.
    • (1987) Int. Stat. Rev. , vol.55 , Issue.2 , pp. 163-172
    • Jarque, C.M.1    Bera, A.K.2
  • 34
    • 71849084400 scopus 로고    scopus 로고
    • A copula-based joint deficit index for droughts
    • Kao, S.; and, R. S. Govindaraju, (2010), A copula-based joint deficit index for droughts, J. Hydrol.; 380, 121-134.
    • (2010) J. Hydrol. , vol.380 , pp. 121-134
    • Kao, S.1    Govindaraju, R.S.2
  • 35
    • 14944381637 scopus 로고    scopus 로고
    • Confronting input uncertainty in environmental modeling
    • edited by Q. Y. Duan, et al.; AGU, Washington, D. C
    • Kavetski, D.; S. Franks, and, G. Kuczera, (2002), Confronting input uncertainty in environmental modeling, in Calibration of Watershed Models, Water Sci. Appl. Ser.; vol. 6, edited by, Q. Y. Duan, et al.; pp. 49-68, AGU, Washington, D. C.
    • (2002) Calibration of Watershed Models, Water Sci. Appl. Ser. , vol.6 , pp. 49-68
    • Kavetski, D.1    Franks, S.2    Kuczera, G.3
  • 36
    • 0002098934 scopus 로고    scopus 로고
    • A bivariate meta-Gaussian density for use in hydrology
    • Kelly, K. S.; and, R. Krzysztofowicz, (1997), A bivariate meta-Gaussian density for use in hydrology, Stochastic Hydrol. Hydraul.; 11, 17-31.
    • (1997) Stochastic Hydrol. Hydraul. , vol.11 , pp. 17-31
    • Kelly, K.S.1    Krzysztofowicz, R.2
  • 37
    • 84856800964 scopus 로고    scopus 로고
    • Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios
    • Kling, H.; M. Fuchs, and, M. Paulin, (2012), Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios, J. Hydrol.; 424, 264-277.
    • (2012) J. Hydrol. , vol.424 , pp. 264-277
    • Kling, H.1    Fuchs, M.2    Paulin, M.3
  • 38
    • 33750474092 scopus 로고    scopus 로고
    • Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters
    • Kuczera, G.; D. Kavetski, S. Franks, and, M. Thyer, (2006), Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters, J. Hydrol.; 331 (1-2), 161-177, doi: 10.1016/j.jhydrol.2006.05.010.
    • (2006) J. Hydrol. , vol.331 , Issue.12 , pp. 161-177
    • Kuczera, G.1    Kavetski, D.2    Franks, S.3    Thyer, M.4
  • 39
    • 34248166114 scopus 로고    scopus 로고
    • Verification tools for probabilistic forecasts of continuous hydrological variables
    • Laio, F.; and, S. Tamea, (2007), Verification tools for probabilistic forecasts of continuous hydrological variables, Hydrol. Earth Syst. Sci.; 11, 1267-1277.
    • (2007) Hydrol. Earth Syst. Sci. , vol.11 , pp. 1267-1277
    • Laio, F.1    Tamea, S.2
  • 40
    • 0028602239 scopus 로고
    • A simple hydrologically based model of land surface water and energy fluxes for GSMs
    • Liang, X.; D. P. Lettenmaier, E. F. Wood, and, S. J. Burges, (1994), A simple hydrologically based model of land surface water and energy fluxes for GSMs, J. Geophys. Res.; 99 (D7), 14,415-14,428.
    • (1994) J. Geophys. Res. , vol.99 , Issue.D7 , pp. 14
    • Liang, X.1    Lettenmaier, D.P.2    Wood, E.F.3    Burges, S.J.4
  • 41
    • 34247990255 scopus 로고
    • On the Kolmogorov-Smirnov test for normality with mean and variance unknown
    • Lilliefors, H. W.; (1967), On the Kolmogorov-Smirnov test for normality with mean and variance unknown, J. Am. Stat. Assoc.; 62, 399-402.
    • (1967) J. Am. Stat. Assoc. , vol.62 , pp. 399-402
    • Lilliefors, H.W.1
  • 43
    • 84881350413 scopus 로고    scopus 로고
    • Drought analysis under climate change using copula
    • Madadgar, S.; and, H. Moradkhani, (2013a), Drought analysis under climate change using copula, J. Hydrol. Eng.; 18 (7), 746-759.
    • (2013) J. Hydrol. Eng. , vol.18 , Issue.7 , pp. 746-759
    • Madadgar, S.1    Moradkhani, H.2
  • 44
    • 84888878263 scopus 로고    scopus 로고
    • A Bayesian framework for probabilistic seasonal drought forecasting
    • special issue of Advances in Drought Monitoring, doi: 10.1175/JHM-D-13-010.1
    • Madadgar, S.; and, H. Moradkhani, (2013b), A Bayesian framework for probabilistic seasonal drought forecasting, J. Hydrometeorol.; special issue of Advances in Drought Monitoring, 14, 1685-1705, doi: 10.1175/JHM-D-13-010.1.
    • (2013) J. Hydrometeorol. , vol.14 , pp. 1685-1705
    • Madadgar, S.1    Moradkhani, H.2
  • 45
    • 84896131892 scopus 로고    scopus 로고
    • Spatio-temporal drought forecasting within Bayesian networks
    • Madadgar, S.; and, H. Moradkhani, (2014), Spatio-temporal drought forecasting within Bayesian networks, J. Hydrol.; 512, 134-146.
    • (2014) J. Hydrol. , vol.512 , pp. 134-146
    • Madadgar, S.1    Moradkhani, H.2
  • 46
    • 84890312326 scopus 로고    scopus 로고
    • Towards improved post-processing of hydrologic forecast ensembles
    • Madadgar, S.; H. Moradkhani, and, D. Garen, (2014), Towards improved post-processing of hydrologic forecast ensembles, Hydrol. Processes, 28, 104-122, doi: 10.1002/hyp.9562.
    • (2014) Hydrol. Processes , vol.28 , pp. 104-122
    • Madadgar, S.1    Moradkhani, H.2    Garen, D.3
  • 47
    • 17644401378 scopus 로고    scopus 로고
    • NOAA's advanced hydrologic prediction service, Building pathways for better science in water forecasting
    • McEnery, J.; J. Ingram, Q. Y. Duan, T. Adams, and, L. Anderson, (2005), NOAA's advanced hydrologic prediction service, Building pathways for better science in water forecasting, Bull. Am. Meteorol. Soc.; 86, 375-385.
    • (2005) Bull. Am. Meteorol. Soc. , vol.86 , pp. 375-385
    • McEnery, J.1    Ingram, J.2    Duan, Q.Y.3    Adams, T.4    Anderson, L.5
  • 48
    • 0036822427 scopus 로고    scopus 로고
    • Macroscale water fluxes: 2. Water and energy supply control of their interannual variability
    • Milly, P. C. D.; and, K. A. Dunne, (2002), Macroscale water fluxes: 2. Water and energy supply control of their interannual variability, Water Resour. Res.; 38, 1206, doi: 10.1029/2001WR000760.
    • (2002) Water Resour. Res. , vol.38 , pp. 1206
    • Milly, P.C.D.1    Dunne, K.A.2
  • 49
    • 84879201434 scopus 로고    scopus 로고
    • Multivariate probabilistic forecasting using ensemble Bayesian model averaging and copulas
    • Möller, A.; A. Lenkoski, and, T. L. Thorarinsdottir, (2013), Multivariate probabilistic forecasting using ensemble Bayesian model averaging and copulas, Q. J. R. Meteorol. Soc.; 139, 982-991, doi: 10.1002/qj.2009.
    • (2013) Q. J. R. Meteorol. Soc. , vol.139 , pp. 982-991
    • Möller, A.1    Lenkoski, A.2    Thorarinsdottir, T.L.3
  • 51
    • 11944268965 scopus 로고    scopus 로고
    • Dual state-parameter estimation of hydrological models using ensemble Kalman filter
    • Moradkhani, H.; S. Sorooshian, H. V. Gupta, and, P. R. Houser, (2005a), Dual state-parameter estimation of hydrological models using ensemble Kalman filter, Adv. Water Resour.; 28, 135-147.
    • (2005) Adv. Water Resour. , vol.28 , pp. 135-147
    • Moradkhani, H.1    Sorooshian, S.2    Gupta, H.V.3    Houser, P.R.4
  • 52
    • 20844449766 scopus 로고    scopus 로고
    • Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using particle filter
    • Moradkhani, H.; K. Hsu, H. V. Gupta, and, S. Sorooshian, (2005b), Uncertainty assessment of hydrologic model states and parameters: Sequential data assimilation using particle filter, Water Resour. Res.; 41, W05012, doi: 10.1029/2004WR003604.
    • (2005) Water Resour. Res. , vol.41 , pp. W05012
    • Moradkhani, H.1    Hsu, K.2    Gupta, H.V.3    Sorooshian, S.4
  • 53
    • 84871364784 scopus 로고    scopus 로고
    • Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov Chain Monte Carlo method
    • Moradkhani, H.; C. M. DeChant, and, S. Sorooshian, (2012), Evolution of ensemble data assimilation for uncertainty quantification using the particle filter-Markov Chain Monte Carlo method, Water Resour. Res.; 48, W12520, doi: 10.1029/2012WR012144.
    • (2012) Water Resour. Res. , vol.48 , pp. W12520
    • Moradkhani, H.1    Dechant, C.M.2    Sorooshian, S.3
  • 54
    • 80051577111 scopus 로고    scopus 로고
    • Assessing the uncertainties of hydrologic model selection in climate change impact studies
    • Najafi, M.; H. Moradkhani, and, I. Jung, (2011), Assessing the uncertainties of hydrologic model selection in climate change impact studies, Hydrol. Processes, 25 (18), 2814-2826.
    • (2011) Hydrol. Processes , vol.25 , Issue.18 , pp. 2814-2826
    • Najafi, M.1    Moradkhani, H.2    Jung, I.3
  • 55
    • 84885533219 scopus 로고    scopus 로고
    • Analysis of runoff extremes using spatial hierarchical Bayesian modeling
    • Najafi, M. R.; and, H. Moradkhani, (2013), Analysis of runoff extremes using spatial hierarchical Bayesian modeling, Water Resour. Res.; 49, 1-15, doi: 10.1002/wrcr.20381.
    • (2013) Water Resour. Res. , vol.49 , pp. 1-15
    • Najafi, M.R.1    Moradkhani, H.2
  • 56
    • 84861210595 scopus 로고    scopus 로고
    • Ensemble streamflow prediction: Climate signal weighting vs. Climate forecast system reanalysis
    • 442443
    • Najafi, M. R.; H. Moradkhani, and, T. Piechota, (2012), Ensemble streamflow prediction: Climate signal weighting vs. climate forecast system reanalysis, J. Hydrol.; 442-443, 105-116, doi: 10.1016/j.jhydrol.2012.04.003.
    • (2012) J. Hydrol. , pp. 105-116
    • Najafi, M.R.1    Moradkhani, H.2    Piechota, T.3
  • 57
    • 77952632411 scopus 로고    scopus 로고
    • Investigating the ability of a land surface model to simulate streamflow with the accuracy of hydrological models: A case study using MOPEX materials
    • Nasonova, O. N.; M. G. Yeugeniy, and, Y. E. Kovalev, (2009), Investigating the ability of a land surface model to simulate streamflow with the accuracy of hydrological models: A case study using MOPEX materials, J. Hydrometeorol.; 10, 1128-1150.
    • (2009) J. Hydrometeorol. , vol.10 , pp. 1128-1150
    • Nasonova, O.N.1    Yeugeniy, M.G.2    Kovalev, Y.E.3
  • 60
    • 0024837527 scopus 로고
    • A simple parameterization of land surface processes for meteorological models
    • Noilhan, J.; and, S. Planton, (1989), A simple parameterization of land surface processes for meteorological models, Mon. Weather Rev.; 117, 536-549.
    • (1989) Mon. Weather Rev. , vol.117 , pp. 536-549
    • Noilhan, J.1    Planton, S.2
  • 61
    • 38649112281 scopus 로고    scopus 로고
    • Evaluation and calibration of operational hydrological ensemble forecasts in Sweden
    • Olsson, J.; and, G. Lindström, (2008), Evaluation and calibration of operational hydrological ensemble forecasts in Sweden, J. Hydrol.; 350, 14-24.
    • (2008) J. Hydrol. , vol.350 , pp. 14-24
    • Olsson, J.1    Lindström, G.2
  • 63
    • 84858823339 scopus 로고    scopus 로고
    • Towards reduction of model uncertainty: Integration of Bayesian model averaging and data assimilation
    • Parrish, M.; H. Moradkhani, and, C. M. DeChant, (2012), Towards reduction of model uncertainty: Integration of Bayesian model averaging and data assimilation, Water Resour. Res.; 48, W03519, doi: 10.1029/2011WR011116.
    • (2012) Water Resour. Res. , vol.48 , pp. W03519
    • Parrish, M.1    Moradkhani, H.2    Dechant, C.M.3
  • 64
    • 0001454867 scopus 로고
    • On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling
    • Pearson, K.; (1900), On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling, Philos. Mag. Ser.; 550 (302), 157-175.
    • (1900) Philos. Mag. Ser. , vol.550 , Issue.302 , pp. 157-175
    • Pearson, K.1
  • 65
    • 0141682120 scopus 로고    scopus 로고
    • Improvement of a parsimonious model for streamflow simulation
    • Perrin, C.; C. Michel, and, V. Andréassian, (2003), Improvement of a parsimonious model for streamflow simulation, J. Hydrol.; 279 (1-4), 275-289.
    • (2003) J. Hydrol. , vol.279 , Issue.14 , pp. 275-289
    • Perrin, C.1    Michel, C.2    Andréassian, V.3
  • 66
    • 20444497873 scopus 로고    scopus 로고
    • Using Bayesian model averaging to calibrate forecast ensembles
    • Raftery, A. E.; T. Gneiting, F. Balabdaoui, and, M. Polakowski, (2005), Using Bayesian model averaging to calibrate forecast ensembles, Mon. Weather Rev.; 113, 1155-1174.
    • (2005) Mon. Weather Rev. , vol.113 , pp. 1155-1174
    • Raftery, A.E.1    Gneiting, T.2    Balabdaoui, F.3    Polakowski, M.4
  • 68
    • 79961092436 scopus 로고    scopus 로고
    • Statistical trends in watershed scale response to climate change in selected basins across the United States
    • Risley, J.; H. Moradkhani, L. Hay, and, S. Markstrom, (2011), Statistical trends in watershed scale response to climate change in selected basins across the United States, AMS Earth Interact.; 15 (14), 1-26.
    • (2011) AMS Earth Interact. , vol.15 , Issue.14 , pp. 1-26
    • Risley, J.1    Moradkhani, H.2    Hay, L.3    Markstrom, S.4
  • 69
    • 76749154579 scopus 로고    scopus 로고
    • Assessment of conceptual model uncertainty for the regional aquifer Pampa del Tamarugal-North Chile
    • Rojas, R.; O. Batelaan, L. Feyen, and, A. Dassargues, (2010), Assessment of conceptual model uncertainty for the regional aquifer Pampa del Tamarugal-North Chile, Hydrol. Earth Syst. Sci.; 14 (2), 171-192.
    • (2010) Hydrol. Earth Syst. Sci. , vol.14 , Issue.2 , pp. 171-192
    • Rojas, R.1    Batelaan, O.2    Feyen, L.3    Dassargues, A.4
  • 70
    • 77957736207 scopus 로고    scopus 로고
    • Multivariate multiparameter extreme value models and return periods: A copula approach
    • Salvadori, G.; and, C. De Michele, (2010), Multivariate multiparameter extreme value models and return periods: A copula approach, Water Resour. Res.; 46, W10501, doi: 10.1029/2009WR009040.
    • (2010) Water Resour. Res. , vol.46 , pp. W10501
    • Salvadori, G.1    De Michele, C.2
  • 71
    • 0030466349 scopus 로고    scopus 로고
    • Simple water balance model for estimating runoff at different spatial and temporal scales
    • Schaake, J. C.; V. I. Koren, Q.-Y. Duan, K. Mitchell, and, F. Chen, (1996), Simple water balance model for estimating runoff at different spatial and temporal scales, J. Geophys. Res.; 101 (D3), 7461-7475, doi: 10.1029/95JD02892.
    • (1996) J. Geophys. Res. , vol.101 , Issue.D3 , pp. 7461-7475
    • Schaake, J.C.1    Koren, V.I.2    Duan, Q.-Y.3    Mitchell, K.4    Chen, F.5
  • 73
    • 84856608113 scopus 로고    scopus 로고
    • A statistical post-processor for accounting of hydrologic uncertainty in short-range ensemble streamflow prediction
    • Seo, D. J.; H. D. Herr, and, J. C. Schaake, (2006), A statistical post-processor for accounting of hydrologic uncertainty in short-range ensemble streamflow prediction, Hydrol. Earth Syst. Sci. Discuss.; 3 (4), 1987-2035.
    • (2006) Hydrol. Earth Syst. Sci. Discuss. , vol.3 , Issue.4 , pp. 1987-2035
    • Seo, D.J.1    Herr, H.D.2    Schaake, J.C.3
  • 74
    • 0000898845 scopus 로고
    • An analysis of variance test for normality (complete samples)
    • Shapiro, S. S.; and, M. B. Wilk, (1965), An analysis of variance test for normality (complete samples), Biometrika, 52 (3/4), 591-611.
    • (1965) Biometrika , vol.52 , Issue.34 , pp. 591-611
    • Shapiro, S.S.1    Wilk, M.B.2
  • 75
    • 33747607479 scopus 로고    scopus 로고
    • Fitting drought duration and severity with two-dimensional copulas
    • Shiau, J. T.; (2006), Fitting drought duration and severity with two-dimensional copulas, Water Resour. Manage.; 20 (5), 795-815.
    • (2006) Water Resour. Manage. , vol.20 , Issue.5 , pp. 795-815
    • Shiau, J.T.1
  • 78
    • 77952562085 scopus 로고    scopus 로고
    • Probabilistic wind speed forecasting using ensembles and Bayesian model averaging
    • Sloughter, J. M.; T. Gneiting, and, A. E. Raftery, (2010), Probabilistic wind speed forecasting using ensembles and Bayesian model averaging, J. Am. Stat. Assoc.; 105, 25-35, doi: 10.1198/jasa.2009.ap08615.
    • (2010) J. Am. Stat. Assoc. , vol.105 , pp. 25-35
    • Sloughter, J.M.1    Gneiting, T.2    Raftery, A.E.3
  • 79
    • 0034794967 scopus 로고    scopus 로고
    • Bayesian recursive parameter estimation for hydrologic models
    • Thiemann, M.; H. Trosset, H. Gupta, and, S. Sorooshian, (2001), Bayesian recursive parameter estimation for hydrologic models, Water Resour. Res.; 37 (10), 2521-2535, doi: 10.1029/2000WR900405.
    • (2001) Water Resour. Res. , vol.37 , Issue.10 , pp. 2521-2535
    • Thiemann, M.1    Trosset, H.2    Gupta, H.3    Sorooshian, S.4
  • 80
    • 69849096009 scopus 로고    scopus 로고
    • Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis
    • Thyer, M.; B. Renard, D. Kavetski, G. Kuczera, S. W. Franks, and, S. Srikanthan, (2009), Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis, Water Resour. Res.; 45, W00B14, doi: 10.1029/2008WR006825.
    • (2009) Water Resour. Res. , vol.45 , pp. W00B14
    • Thyer, M.1    Renard, B.2    Kavetski, D.3    Kuczera, G.4    Franks, S.W.5    Srikanthan, S.6
  • 81
    • 55249111575 scopus 로고    scopus 로고
    • Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window
    • Tsai, F. T.-C.; and, X. Li, (2008), Inverse groundwater modeling for hydraulic conductivity estimation using Bayesian model averaging and variance window, Water Resour. Res.; 44, W09434, doi: 10.1029/2007WR006576.
    • (2008) Water Resour. Res. , vol.44 , pp. W09434
    • Tsai, F.T.-C.1    Li, X.2
  • 82
    • 66049147497 scopus 로고    scopus 로고
    • A model conditional processor to assess predictive uncertainty in flood forecasting
    • Todini, E.; (2008), A model conditional processor to assess predictive uncertainty in flood forecasting, Int. J. River Basin Manage.; 6 (2), 123-137.
    • (2008) Int. J. River Basin Manage. , vol.6 , Issue.2 , pp. 123-137
    • Todini, E.1
  • 83
    • 33847633276 scopus 로고    scopus 로고
    • Multi-objective calibration of forecast ensembles using Bayesian model averaging
    • Vrugt, J. A.; M. P. Clark, C. G. H. Diks, Q. Duan, and, B. A. Robinson, (2006), Multi-objective calibration of forecast ensembles using Bayesian model averaging, Geophys. Res. Lett.; 33, L19817, doi: 10.1029/2006GL027126.
    • (2006) Geophys. Res. Lett. , vol.33 , pp. L19817
    • Vrugt, J.A.1    Clark, M.P.2    Diks, C.G.H.3    Duan, Q.4    Robinson, B.A.5
  • 84
    • 33847624077 scopus 로고    scopus 로고
    • Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging
    • Vrugt, J. A.; and, B. A. Robinson, (2007), Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging, Water Resour. Res.; 43, W01411, doi: 10.1029/2005WR004838.
    • (2007) Water Resour. Res. , vol.43 , pp. W01411
    • Vrugt, J.A.1    Robinson, B.A.2
  • 85
    • 57049103413 scopus 로고    scopus 로고
    • Ensemble Bayesian model averaging using Markov chain Monte Carlo sampling
    • Vrugt, J. A.; C. G. Diks, and, M. P. Clark, (2008), Ensemble Bayesian model averaging using Markov chain Monte Carlo sampling, Environ. Fluid Mech.; 8 (5-6), 579-595.
    • (2008) Environ. Fluid Mech. , vol.8 , Issue.56 , pp. 579-595
    • Vrugt, J.A.1    Diks, C.G.2    Clark, M.P.3
  • 86
    • 41949124639 scopus 로고    scopus 로고
    • Can multi-model combination really enhance the prediction skill of probabilistic ensemble forecasts?
    • Weigel, A. P.; M. A. Liniger, and, C. Appenzeller, (2008), Can multi-model combination really enhance the prediction skill of probabilistic ensemble forecasts?, Q. J. R. Meteorol. Soc.; 134, 241-260, doi: 10.1002/qj.210.
    • (2008) Q. J. R. Meteorol. Soc. , vol.134 , pp. 241-260
    • Weigel, A.P.1    Liniger, M.A.2    Appenzeller, C.3
  • 87
    • 84888116303 scopus 로고    scopus 로고
    • Hydrologic post-processing of MOPEX streamflow simulations
    • (5)
    • Ye, A.; Q. Duan, X. Yuan, E. F. Wood, and, J. Schaake, (2014), Hydrologic post-processing of MOPEX streamflow simulations, J. Hydrol.; 40 (5), doi: 10.1016/j.jhydrol.2013.10.055.
    • (2014) J. Hydrol. , vol.40
    • Ye, A.1    Duan, Q.2    Yuan, X.3    Wood, E.F.4    Schaake, J.5
  • 88
    • 2942700220 scopus 로고    scopus 로고
    • Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff
    • Ye, M.; S. P. Neuman, and, P. D. Meyer, (2004), Maximum likelihood Bayesian averaging of spatial variability models in unsaturated fractured tuff, Water Resour. Res.; 40, W05113, doi: 10.1029/2003WR002557.
    • (2004) Water Resour. Res. , vol.40 , pp. W05113
    • Ye, M.1    Neuman, S.P.2    Meyer, P.D.3
  • 89
    • 77954990181 scopus 로고    scopus 로고
    • A model-averaging method for assessing groundwater conceptual model uncertainty
    • (5)
    • Ye, M.; K. F. Pohlmann, J. B. Chapman, G. M. Pohll, and, D. M. Reeves, (2010), A model-averaging method for assessing groundwater conceptual model uncertainty, Ground Water, 48 (5), 716-728, doi: 10.1111/j.1745-6584.2009.00633.x.
    • (2010) Ground Water , vol.48 , pp. 716-728
    • Ye, M.1    Pohlmann, K.F.2    Chapman, J.B.3    Pohll, G.M.4    Reeves, D.M.5
  • 90
    • 79952163188 scopus 로고    scopus 로고
    • A hydrologic post-processor for ensemble streamflow predictions
    • Zhao, L.; Q. Duan, J. Schaake, A. Ye, and, J. Xia, (2011), A hydrologic post-processor for ensemble streamflow predictions, Adv. Geosci.; 29, 51-59.
    • (2011) Adv. Geosci. , vol.29 , pp. 51-59
    • Zhao, L.1    Duan, Q.2    Schaake, J.3    Ye, A.4    Xia, J.5


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