Using stochastic state-space modelling to specify and reduce hydrograph error

Hydrological Processes

Volumn 22, Issue 8, 2008, Pages 1173-1179

  Collier, C G ^a   Robbins, G L ^a,b  

^a UNIVERSITY OF SALFORD   (United Kingdom)

^b ENVIRONMENT AGENCY   (United Kingdom)

Author keywords

Bayesian post processor; Hydrograph errors; Stochastic model

Indexed keywords

BAYESIAN NETWORKS; RAIN GAGES; STATE SPACE METHODS; STOCHASTIC MODELS;

BAYESIAN POST PROCESSOR; HYDROGRAPH ERRORS;

FLOW MEASUREMENT;

BAYESIAN NETWORKS; FLOW MEASUREMENT; RAIN GAGES; STATE SPACE METHODS; STOCHASTIC MODELS;

BAYESIAN ANALYSIS; CATCHMENT; ERROR ANALYSIS; FORECASTING METHOD; HYDROGRAPH; HYDROLOGICAL MODELING; PEAK FLOW; RIVER FLOW; STOCHASTICITY;

BOLTON; CROAL RIVER; ENGLAND; EURASIA; EUROPE; UNITED KINGDOM; WESTERN EUROPE;

EID: 42149087211     PISSN: 08856087     EISSN: 10991085     Source Type: Journal    
DOI: 10.1002/hyp.6685     Document Type: Article

References (23)

1. Abbott MB, Bathhurst JC, Cunge JA, O'Connell PE, Rasmussen J. 1986. An introduction to the European Hydrological System - System Hydrologique European, 'SHE' 1: History and philosophy of a physically-based distributed modelling system, 2: Structure of a physically-based distributed modelling system. Journal of Hydrology 87: 45-77.
2. Beven KJ. 1997. TOPMODEL: a critique. Hydrological Processes 11: 1069-1086.
3. Beven KJ, Binley AM. 1992. The future of distributed models-model calibration and uncertainty prediction. Hydrological Processes 6: 279-298.
4. Beven KJ, Warren R, Zaoui J. 1980. SHE: towards a methodology for physically-based distributed forecasting in hydrology, IAHS Publication No. 129. IAHS: Wallingford; 133-137.
5. Beven KJ, Lamb R, Quinn P, Romanowicz R, Freer J. 1995. Topmodel. In Computer Models of Watershed, Singh VP (ed.). Hydrological Water Resource Publications: Highlands Ranch, CO; 627-668.
6. Collier CG. 1999. The impact of wind drift on the utility of very high spatial resolution radar data over urban areas. Physics & Chemistry of the Earth (B) 24: 889-893.
7. Collier CG, Knowles JM. 1986. Accuracy of rainfall estimates by radar, Part III: Application for short-term flood forecasting. Journal of Hydrology 83: 237-249.
8. Comford D. 2004. A Bayesian state space modelling approach to probabilistic quantitative precipitation forecasting. Journal of Hydrology 288: 92-104.
9. DeRoo APJ, Bartholmes J, Bongioannini-Cerlim P, Todini E, Bates PD, Horritt M, Hunter N, Beven K, Pappenberger F, Heise E, Rivin G, Hils M, Hollingworth A, Holst B, Kwadijk J, Reggioni P, Van Dijk M, Sattler K, Sprokkereef E. 2003. Development of a European flood forecasting system. International Journal of River Basin Management 1: 49-59.
10. Grum M, Harremoes P, Linde JJ. 2002. Assimilating a multitude of rainfall and runoff data using a stochastic state space modelling approach. In Proceedings ofthe 9th International Conference on Urban Drainage, Portland, OR, 8-11 September 2002. American Society of Civil Engineering: Reston, VA.
11. Krzysztofowicz R. 1999a. Bayesian theory of probabilistic forecasting via deterministic hydrologic model. Water Resources Research 35: 2739-2750.
12. Krzysztofowicz R. 1999b. Bayesian forecasting via deterministic model. Risk-Analysis 19: 739-749.
13. Krzysztofowicz R, Kelly KS. 2000. Hydrologic uncertainty processor for probabilistic river stage forecasting. Water Resources Research 36: 3265-3277.
14. Lambert AO. 1972. Catchments models based on ISO functions. Journal of the Institute of Water Engineers 26: 413-422.
15. McEnery J, Ingram J, Duan Q, Adams T, Anderson L. 2005. NOAA's advanced hydrologic prediction service. Bulletin for the American Meteorological Society 86: 375-385.
16. Moore RJ. 1985. The probability-distributed principle and runoff production at point and basin scales. Hydrological Science Journal 30: 273-297.
17. Refsgaard JC. 1996. Terminology, modelling protocol and classification of hydrological model codes. In Distributed Hydrological Modelling, Abbott MB, Refsgaard JC (eds). Kluwer Academic Publishers: Dordrecht; 17-39.
18. Robbins GL, Collier CG. 2005. Assessing error in hydrological and hydraulic model output flows. Atmospheric Science Letters 6: 47-53.
19. Robbins GL, Grum M, Collier CG. 2004. Combining and comparing rainfall observing systems in hydrological modelling of a rural catchment. In Proceedings ERAD(2004). Copernicus GmbH: Katlenburg-Lindau; 115-119.
20. Sempere Torres D, Rodriquez J-Y, Obled C. 1992. Using the DPFr approach to improve flash flood forecasting models. Natural Hazards 5: 17-41.
21. Shutts G. 2005. A kinetic energy backscatter algorithm for use in ensemble prediction systems. Quarterly Journal for the Royal Meteorological Society 131: 3079-3102.
22. Todini E. 1995. New trends in modelling soil processes from hillslope to GCM scales. In The Role of Water and the Hydrological Cycle in Global Change, Oliver HR, Oliver SA (eds), NATO ASI Series. Springer Verlag: Berlin; vol. 131, 317-347.
23. Young PC, Beven KJ. 1994. Data-based mechanistic modelling and the rainfall - flows nonlinearity. Environmetrics 5: 335-363.