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Volumn 19, Issue 8, 2015, Pages 3695-3714

Improving real-time inflow forecasting into hydropower reservoirs through a complementary modelling framework

Author keywords

[No Author keywords available]

Indexed keywords

CATCHMENTS; COMMERCE; DECISION MAKING; HYDROELECTRIC POWER; RESERVOIRS (WATER); UNCERTAINTY ANALYSIS; WATER RESOURCES;

EID: 84940861028     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-19-3695-2015     Document Type: Article
Times cited : (21)

References (46)
  • 1
    • 0142027619 scopus 로고    scopus 로고
    • Managing uncertainty in hydrological models using complementary models
    • Abebe, A. J. and Price, R. K.: Managing uncertainty in hydrological models using complementary models, Hydrolog. Sci. J., 48, 679-692, 2003.
    • (2003) Hydrolog. Sci. J. , vol.48 , pp. 679-692
    • Abebe, A.J.1    Price, R.K.2
  • 2
    • 33745773952 scopus 로고    scopus 로고
    • Influence of rating curve uncertainty on daily rainfall-runoff model predictions
    • Aronica, G. T., Candela, A., Viola, F., and Cannarozz, M.: Influence of rating curve uncertainty on daily rainfall-runoff model predictions, Predict. Ungau. Basins, 303, 116-124, 2006.
    • (2006) Predict. Ungau. Basins , vol.303 , pp. 116-124
    • Aronica, G.T.1    Candela, A.2    Viola, F.3    Cannarozz, M.4
  • 3
    • 0000119989 scopus 로고
    • The HBV model
    • edited by: Singh, V. P., Water Resources Publications, Highlands Ranch, CO.
    • Bergström, S.: The HBV model, in: Computer Models of Watershed Hydrology, edited by: Singh, V. P., Water Resources Publications, Highlands Ranch, CO., 443-476, 1995.
    • (1995) Computer Models of Watershed Hydrology , pp. 443-476
    • Bergström, S.1
  • 5
    • 84888749158 scopus 로고    scopus 로고
    • Wiley-Blackwell, Chichester
    • nd Edn., Wiley-Blackwell, Chichester, 2012.
    • (2012) nd Edn.
    • Beven, K.1
  • 6
    • 43449131518 scopus 로고    scopus 로고
    • So just why would a modeller choose to be incoherent?
    • Beven, K. J., Smith, P. J., and Freer, J.: So just why would a modeller choose to be incoherent?, J. Hydrol., 354, 15-32, 2008.
    • (2008) J. Hydrol. , vol.354 , pp. 15-32
    • Beven, K.J.1    Smith, P.J.2    Freer, J.3
  • 7
    • 0000133998 scopus 로고
    • An analysis of transformations
    • Box, G. E. P. and Cox, D. R.: An analysis of transformations, J. Roy. Stat. Soc. B, 62, 211-252, 1964.
    • (1964) J. Roy. Stat. Soc. B , vol.62 , pp. 211-252
    • Box, G.E.P.1    Cox, D.R.2
  • 9
    • 0027558431 scopus 로고
    • Shuffled complex evolution approach for effective and efficient global minimization
    • Duan, Q. Y., Gupta, V. K., and Sorooshian, S.: Shuffled complex evolution approach for effective and efficient global minimization, J. Optimiz. Theory Appl., 76, 501-521, 1993.
    • (1993) J. Optimiz. Theory Appl. , vol.76 , pp. 501-521
    • Duan, Q.Y.1    Gupta, V.K.2    Sorooshian, S.3
  • 10
    • 13244265879 scopus 로고    scopus 로고
    • Assessing uncertainties in a conceptual water balance model using Bayesian methodology
    • Engeland, K., Xu, C.-Y., and Gottschalk, L.: Assessing uncertainties in a conceptual water balance model using Bayesian methodology, Hydrolog. Sci. J., 50, 45-63, 2005.
    • (2005) Hydrolog. Sci. J. , vol.50 , pp. 45-63
    • Engeland, K.1    Xu, C.-Y.2    Gottschalk, L.3
  • 11
    • 27644470780 scopus 로고    scopus 로고
    • Assessing the performance of eight real-time updating models and procedures for the Brosna River
    • Goswami, M., O'Connor, K. M., Bhattarai, K. P., and Shamseldin, A. Y.: Assessing the performance of eight real-time updating models and procedures for the Brosna River, Hydrol. Earth Syst. Sci., 9, 394-411, doi:10.5194/hess-9-394-2005, 2005.
    • (2005) Hydrol. Earth Syst. Sci. , vol.9 , pp. 394-411
    • Goswami, M.1    O'Connor, K.M.2    Bhattarai, K.P.3    Shamseldin, A.Y.4
  • 12
    • 84931275179 scopus 로고    scopus 로고
    • Recursively updating the error-forecasting scheme of a complementary modelling framework for enhancing accuracy of reservoir inflow forecasts
    • Gragne, A. S., Alfredsen, K., Sharma, A., and Mehrotra, R.: Recursively updating the error-forecasting scheme of a complementary modelling framework for enhancing accuracy of reservoir inflow forecasts, J. Hydrol., 527, 967-977, 2015.
    • (2015) J. Hydrol. , vol.527 , pp. 967-977
    • Gragne, A.S.1    Alfredsen, K.2    Sharma, A.3    Mehrotra, R.4
  • 13
    • 84879917815 scopus 로고    scopus 로고
    • Specifying a hierarchical mixture of experts for hydrologic modeling: Gating function variable selection
    • Jeremiah, E., Marshall, L., Sisson, S. A., and Sharma, A.: Specifying a hierarchical mixture of experts for hydrologic modeling: Gating function variable selection, Water Resour. Res., 49, 2926-2939, 2013.
    • (2013) Water Resour. Res. , vol.49 , pp. 2926-2939
    • Jeremiah, E.1    Marshall, L.2    Sisson, S.A.3    Sharma, A.4
  • 14
    • 0026613408 scopus 로고
    • River flow forecasting: Part 1 A discussion of the principles
    • Kachroo, R. K.: River flow forecasting: Part 1 A discussion of the principles, J. Hydrol., 133, 1-15, 1992.
    • (1992) J. Hydrol. , vol.133 , pp. 1-15
    • Kachroo, R.K.1
  • 15
    • 0032853041 scopus 로고    scopus 로고
    • Bayesian theory of probabilistic forecasting via deterministic hydrologic model
    • Krzysztofowicz, R.: Bayesian theory of probabilistic forecasting via deterministic hydrologic model, Water Resour. Res., 35, 2739-2750, 1999.
    • (1999) Water Resour. Res. , vol.35 , pp. 2739-2750
    • Krzysztofowicz, R.1
  • 16
    • 0035426007 scopus 로고    scopus 로고
    • The case for probabilistic forecasting in hydrology
    • Krzysztofowicz, R.: The case for probabilistic forecasting in hydrology, J. Hydrol., 249, 2-9, 2001.
    • (2001) J. Hydrol. , vol.249 , pp. 2-9
    • Krzysztofowicz, R.1
  • 17
    • 34248166114 scopus 로고    scopus 로고
    • Verification tools for probabilistic forecasts of continuous hydrological variables
    • Laio, F. and Tamea, S.: Verification tools for probabilistic forecasts of continuous hydrological variables, Hydrol. Earth Syst. Sci., 11, 1267-1277, doi:10.5194/hess-11-1267-2007, 2007.
    • (2007) Hydrol. Earth Syst. Sci. , vol.11 , pp. 1267-1277
    • Laio, F.1    Tamea, S.2
  • 18
    • 84875494514 scopus 로고    scopus 로고
    • Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling
    • Li, L., Xu, C. Y., and Engeland, K.: Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling, J. Hydrol., 486, 384-394, 2013.
    • (2013) J. Hydrol. , vol.486 , pp. 384-394
    • Li, L.1    Xu, C.Y.2    Engeland, K.3
  • 20
    • 20144376350 scopus 로고    scopus 로고
    • Adaptive state updating in real-time river flow forecasting - A combined filtering and error forecasting procedure
    • Madsen, H. and Skotner, C.: Adaptive state updating in real-time river flow forecasting - a combined filtering and error forecasting procedure, J. Hydrol., 308, 302-312, 2005.
    • (2005) J. Hydrol. , vol.308 , pp. 302-312
    • Madsen, H.1    Skotner, C.2
  • 21
    • 33846370929 scopus 로고    scopus 로고
    • Modelling the Catchment via Mixtures: Issues of Model Specification and Validation
    • Marshall, L., Sharma, A., and Nott, D. J.: Modelling the Catchment via Mixtures: Issues of Model Specification and Validation, Water Resour. Res., 42, W11409, doi:10.1029/2005WR004613, 2006.
    • (2006) Water Resour. Res. , vol.42
    • Marshall, L.1    Sharma, A.2    Nott, D.J.3
  • 23
    • 2542555104 scopus 로고    scopus 로고
    • A stochastic approach for assessing the uncertainty of rainfall-runoff simulations
    • Montanari, A. and Brath, A.: A stochastic approach for assessing the uncertainty of rainfall-runoff simulations, Water Resour. Res., 42, W01106, doi:10.1029/2003WR002540, 2004.
    • (2004) Water Resour. Res. , vol.42
    • Montanari, A.1    Brath, A.2
  • 24
    • 0014776873 scopus 로고
    • River flow forecasting through conceptual models part I - A discussion of principles
    • Nash, J. and Sutcliffe, J.: River flow forecasting through conceptual models part I - A discussion of principles, J. Hydrol., 10, 282-290, 1970.
    • (1970) J. Hydrol. , vol.10 , pp. 282-290
    • Nash, J.1    Sutcliffe, J.2
  • 25
    • 33745470431 scopus 로고    scopus 로고
    • Influence of uncertain boundary conditions and model structure on flood inundation predictions
    • Pappenberger, F., Matgen, P., Beven, K. J., Henry, J. B., Pfister, L., and De Fraipont, P.: Influence of uncertain boundary conditions and model structure on flood inundation predictions, Adv. Water Resour., 29, 1430-1449, 2006.
    • (2006) Adv. Water Resour. , vol.29 , pp. 1430-1449
    • Pappenberger, F.1    Matgen, P.2    Beven, K.J.3    Henry, J.B.4    Pfister, L.5    De Fraipont, P.6
  • 26
    • 67649804749 scopus 로고    scopus 로고
    • Bayesian Rating Curve Inference as a Streamflow Data Quality Assessment Tool
    • Petersen-Overleir, A., Soot, A., and Reitan, T.: Bayesian Rating Curve Inference as a Streamflow Data Quality Assessment Tool, Water Resour. Manage., 23, 1835-1842, 2009.
    • (2009) Water Resour. Manage. , vol.23 , pp. 1835-1842
    • Petersen-Overleir, A.1    Soot, A.2    Reitan, T.3
  • 27
    • 84884884828 scopus 로고    scopus 로고
    • A Bayesian joint probability post-processor for reducing errors and quantifying uncertainty in monthly streamflow predictions
    • Pokhrel, P., Robertson, D. E., and Wang, Q. J.: A Bayesian joint probability post-processor for reducing errors and quantifying uncertainty in monthly streamflow predictions, Hydrol. Earth Syst. Sci., 17, 795-804, doi:10.5194/hess-17-795-2013, 2013.
    • (2013) Hydrol. Earth Syst. Sci. , vol.17 , pp. 795-804
    • Pokhrel, P.1    Robertson, D.E.2    Wang, Q.J.3
  • 28
    • 77950177246 scopus 로고    scopus 로고
    • Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors
    • Renard, B., Kavetski, D., Kuczera, G., Thyer, M., and Franks, S.W.: Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors, Water Resour. Res., 46, W05521, doi:10.1029/2009WR008328, 2010.
    • (2010) Water Resour. Res. , vol.46
    • Renard, B.1    Kavetski, D.2    Kuczera, G.3    Thyer, M.4    Franks, S.W.5
  • 29
    • 33746624237 scopus 로고    scopus 로고
    • Data assimilation and adaptive forecasting of water levels in the river Severn catchment, United Kingdom
    • Romanowicz, R. J., Young, P. C., and Beven, K. J.: Data assimilation and adaptive forecasting of water levels in the river Severn catchment, United Kingdom, Water Resour. Res., 42, W06407, doi:10.1029/2005WR004373, 2006.
    • (2006) Water Resour. Res. , vol.42
    • Romanowicz, R.J.1    Young, P.C.2    Beven, K.J.3
  • 30
    • 77954727893 scopus 로고    scopus 로고
    • A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors
    • Schoups, G. and Vrugt, J. A.: A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non-Gaussian errors, Water Resour. Res., 46, W10531, doi:10.1029/2009WR008933, 2010.
    • (2010) Water Resour. Res. , vol.46
    • Schoups, G.1    Vrugt, J.A.2
  • 32
    • 0035701248 scopus 로고    scopus 로고
    • A non-linear neural network technique for updating of river flow forecasts
    • Shamseldin, A. Y. and O'Connor, K. M.: A non-linear neural network technique for updating of river flow forecasts, Hydrol. Earth Syst. Sci., 5, 577-598, doi:10.5194/hess-5-577-2001, 2001.
    • (2001) Hydrol. Earth Syst. Sci. , vol.5 , pp. 577-598
    • Shamseldin, A.Y.1    O'Connor, K.M.2
  • 33
    • 0034694808 scopus 로고    scopus 로고
    • Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 2 - Predictor identification of quarterly rainfall using ocean-atmosphere information
    • Sharma, A., Luk, K. C., Cordery, I., and Lall, U.: Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 2 - Predictor identification of quarterly rainfall using ocean-atmosphere information, J. Hydrol., 239, 240-248, 2000.
    • (2000) J. Hydrol. , vol.239 , pp. 240-248
    • Sharma, A.1    Luk, K.C.2    Cordery, I.3    Lall, U.4
  • 34
    • 33645987256 scopus 로고    scopus 로고
    • Machine learning approaches for estimation of prediction interval for the model output
    • Shrestha, D. L. and Solomatine, D. P.: Machine learning approaches for estimation of prediction interval for the model output, Neural Networks, 19, 225-235, 2006.
    • (2006) Neural Networks , vol.19 , pp. 225-235
    • Shrestha, D.L.1    Solomatine, D.P.2
  • 35
    • 84887631554 scopus 로고    scopus 로고
    • Considering rating curve uncertainty in water level predictions
    • Sikorska, A. E., Scheidegger, A., Banasik, K., and Rieckermann, J.: Considering rating curve uncertainty in water level predictions, Hydrol. Earth Syst. Sci., 17, 4415-4427, doi:10.5194/hess-17-4415-2013, 2013.
    • (2013) Hydrol. Earth Syst. Sci. , vol.17 , pp. 4415-4427
    • Sikorska, A.E.1    Scheidegger, A.2    Banasik, K.3    Rieckermann, J.4
  • 36
    • 84869402553 scopus 로고    scopus 로고
    • Adaptive correction of deterministic models to produce probabilistic forecasts
    • Smith, P. J., Beven, K. J., Weerts, A. H., and Leedal, D.: Adaptive correction of deterministic models to produce probabilistic forecasts, Hydrol. Earth Syst. Sci., 16, 2783-2799, doi:10.5194/hess-16-2783-2012, 2012.
    • (2012) Hydrol. Earth Syst. Sci. , vol.16 , pp. 2783-2799
    • Smith, P.J.1    Beven, K.J.2    Weerts, A.H.3    Leedal, D.4
  • 37
    • 84935016150 scopus 로고    scopus 로고
    • Modeling residual hydrologic errors with Bayesian inference
    • Smith, T., Marshall, L., and Sharma, A.: Modeling residual hydrologic errors with Bayesian inference, J. Hydrol., 528, 29-37, doi:10.1016/j.jhydrol.2015.05.051, 2015.
    • (2015) J. Hydrol. , vol.528 , pp. 29-37
    • Smith, T.1    Marshall, L.2    Sharma, A.3
  • 38
    • 72149087074 scopus 로고    scopus 로고
    • A novel method to estimate model uncertainty using machine Learning techniques
    • Solomatine, D. P. and Shrestha, D. L.: A novel method to estimate model uncertainty using machine Learning techniques, Water Resour. Res., 45, W00B11, doi:10.1029/2008WR006839, 2009.
    • (2009) Water Resour. Res. , vol.45
    • Solomatine, D.P.1    Shrestha, D.L.2
  • 39
    • 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., Renard, B., Kavetski, D., Kuczera, G., Franks, S. W., and Srikanthan, S.: 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.
    • (2009) Water Resour. Res. , vol.45
    • Thyer, M.1    Renard, B.2    Kavetski, D.3    Kuczera, G.4    Franks, S.W.5    Srikanthan, S.6
  • 40
    • 33846392553 scopus 로고    scopus 로고
    • Hydrological catchment modelling: Past, present and future
    • Todini, E.: Hydrological catchment modelling: past, present and future, Hydrol. Earth Syst. Sci., 11, 468-482, doi:10.5194/hess-11-468-2007, 2007.
    • (2007) Hydrol. Earth Syst. Sci. , vol.11 , pp. 468-482
    • Todini, E.1
  • 41
    • 0033385186 scopus 로고    scopus 로고
    • Real-time flood forecasting via combined use of conceptual and stochastic models
    • Toth, E., Brath, A., and Montanari, A.: Real-time flood forecasting via combined use of conceptual and stochastic models, Phys. Chem. Earth B, 24, 793-798, 1999.
    • (1999) Phys. Chem. Earth B , vol.24 , pp. 793-798
    • Toth, E.1    Brath, A.2    Montanari, A.3
  • 42
    • 67650292897 scopus 로고    scopus 로고
    • A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites
    • Wang, Q. J., Robertson, D. E., and Chiew, F. H. S.: A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites, Water Resour. Res., 45, W05407, doi:10.1029/2008WR007355, 2009.
    • (2009) Water Resour. Res. , vol.45
    • Wang, Q.J.1    Robertson, D.E.2    Chiew, F.H.S.3
  • 44
    • 18844480083 scopus 로고    scopus 로고
    • Comparison of four updating models for real-time river flow forecasting
    • Xiong, L. H. and O'Connor, K. M.: Comparison of four updating models for real-time river flow forecasting, Hydrolog. Sci. J., 47, 621-639, 2002.
    • (2002) Hydrolog. Sci. J. , vol.47 , pp. 621-639
    • Xiong, L.H.1    O'Connor, K.M.2
  • 45
    • 70349545766 scopus 로고    scopus 로고
    • Indices for assessing the prediction bounds of hydrological models and application by generalised likelihood uncertainty estimation
    • Xiong, L. H., Wan, M., Wei, X. J., and O'Connor, K. M.: Indices for assessing the prediction bounds of hydrological models and application by generalised likelihood uncertainty estimation, Hydrolog. Sci. J., 54, 852-871, 2009.
    • (2009) Hydrolog. Sci. J. , vol.54 , pp. 852-871
    • Xiong, L.H.1    Wan, M.2    Wei, X.J.3    O'Connor, K.M.4
  • 46
    • 0035314733 scopus 로고    scopus 로고
    • Statistical analysis of parameters and residuals of a conceptual water balance model - Methodology and case study
    • Xu, C.-Y.: Statistical analysis of parameters and residuals of a conceptual water balance model - methodology and case study, Water Resour. Manage., 15, 75-92, 2001.
    • (2001) Water Resour. Manage. , vol.15 , pp. 75-92
    • Xu, C.-Y.1


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