Hydrological data assimilation with the Ensemble Square-Root-Filter: Use of streamflow observations to update model states for real-time flash flood forecasting

Advances in Water Resources

Volumn 59, Issue , 2013, Pages 209-220

  Chen, He ^a   Yang, Dawen ^a   Hong, Yang ^b,c   Gourley, Jonathan J ^d   Zhang, Yu ^b,c  

^a TSINGHUA UNIVERSITY   (China)

^b UNIVERSITY OF OKLAHOMA   (United States)

^c Atmospheric Radar Research Center   (United States)

^d NATIONAL SEVERE STORMS LABORATORY   (United States)

Author keywords

Data assimilation; Ensemble Kalman filter; Ensemble Square Root Filter; Flash flood forecast; Rainfall runoff model

Indexed keywords

DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; ENSEMBLE SQUARE-ROOT-FILTER; FLASH FLOOD; RAINFALL-RUNOFF MODELS;

FLOOD CONTROL; KALMAN FILTERS; RUNOFF; STREAM FLOW;

FLOODS;

DATA ASSIMILATION; ENSEMBLE FORECASTING; FLASH FLOOD; FLOOD FORECASTING; HYDROLOGICAL MODELING; KALMAN FILTER; RAINFALL-RUNOFF MODELING; STREAMFLOW; WATERSHED;

CHINA; UNITED STATES;

EID: 84880969393     PISSN: 03091708     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.advwatres.2013.06.010     Document Type: Article

References (42)

1. Sivapalan M., Takeuchi K., Franks S.W., Gupta V.K., Karambiri H., Lakshmi V., et al. IAHS decade on predictions in ungauged basins (PUB), 2003-2012: shaping an exciting future for the hydrological sciences. Hydrol Sci J 2003, 48:857-880. 10.1623/hysj.48.6.857.51421.
2. Thirel G., Martin E., Mahfouf J.F., Massart S., Ricci S., Habets F. A past discharges assimilation system for ensemble streamflow forecasts over France. Part 1: Description and validation for the assimilation system. Hydrol Earth Syst Sci 2010, 14:1623-1637. 10.5194/hess-14-1623-2010.
3. Götzinger J., Bàrdossy A. Generic error model for calibration and uncertainty estimation of hydrological models. Water Resour Res 2008, 44:W00B07. 10.1029/2007WR006691.
4. Moradkhani M., Sorooshian S. General review of rainfall-runoff modeling: model calibration, data assimilation, and uncertainty analysis. Hydrological modeling and the water cycle 2009, 1-24. Springer. 10.1007/978-3-540-77843-1_1. S. Sorooshian, K.L. Hsu, E. Coppola, B. Tomassetti, M. Verdecchia, G. Visconti (Eds.).
5. Salamon P., Feyen L. Assessing parameter, precipitation, and predictive uncertainty in a distributed hydrological model using sequential data assimilation with the particle filter. J Hydrol 2009, 376:428-442. 10.1016/j.jhydrol.2009.07.051.
6. Kalman R.E. A new approach to linear filtering and prediction problems. Trans ASME J Basic Eng 1960, 82:35-45. 10.1115/1.3662552.
7. Kitinadis P.K., Bras R.L. Real time forecasting with a conceptual hydrologic model. 1. Analysis of uncertainty. Water Resour Res 1980, 16:1025-1033. 10.1029/WR016i006p01025.
8. Georgakakos K.P. A generalized stochastic hydrometeorological model for flood and flash-flood forecasting. 1. Formulation. Water Resour Res 1986, 22:2083-2095. 10.1029/WR022i013p02083.
9. Georgakakos K.P. A generalized stochastic hydrometeorological model for flood and flash-flood forecasting. 2. Case studies. Water Resour Res 1986, 22:2096-2106. 10.1029/WR022i013p02096.
10. Gelb A. Applied optimal estimation 1974, The MIT Press, ISBN:0-262-20027-9.
11. Evensen G. Using the extended Kalman filter with a nonlinear quasi-geostrophic ocean model. J Geophys Res 1992, 97:17905-17924. 10.1029/92JC01972.
12. Evensen G. Sequential data assimilation with a nonlinear quasigeostrophic model using Monte Carlo methods to forecast error statistics. J Geophys Res 1994, 99:10143-10162. 10.1029/94JC00572.
13. Reichle R.H., Walker J.P., Koster R.D., Houser P.R. Extended versus ensemble Kalman filtering for land data assimilation. J Hydrometeorol 2002, 3:728-740. 10.1175/1525-7541.
14. Lorenc A.C. The potential of the ensemble Kalman filter for NWP - a comparison with 4D-Var. Q J R Meteor Soc 2003, 129(595):3183-3203. 10.1256/qj.02.132.
15. Weerts A.H., El Serafy G.Y.H. Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall-runoff models. Water Resour Res 2006, 4:W09403. 10.1029/2005WR004093.
16. Whitaker J.S., Hamill T.M. Ensemble data assimilation without perturbed observations. Mon Weather Rev 2002, 130(7):1913-1924. 10.1175/1520-0493.
17. Vrugt J.A., Diks C.G.H., Gupta H.V., Bouten W., Verstraten J.M. Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation. Water Resour Res 2005, 41:W01017. 10.1029/2004WR003059.
18. Aubert D., Loumagne C., Oudin L. Sequential assimilation of soil moisture and streamflow datain a conceptual rainfall-runoff model. J Hydrol 2003, 280:141-161. 10.1016/S0022-1694.
19. Komma J., Blöschl G., Reszler C. Soil moisture updating by ensemble Kalman filtering in real-time flood forecasting. J Hydrol 2008, 357:228-242. 10.1016/j.jhydrol.2008.05.020.
20. Thirel G., Martin E., Mahfouf J.F., Massart S., Ricci S., Habets F. A past discharges assimilation system for ensemble streamflow forecasts over France. Part 2: Impact on the ensemble streamflow forecast. Hydrol Earth Syst Sci 2010, 14:1639-1653. 10.5194/hess-14-1639-2010.
21. Boyle DP. Multicriteria calibration of hydrological models. Ph.D. dissertation, Dep of Hydrol and Water Resour, Univ of Arizona, Tucson; 2000. UMI number: 3023521.
22. Moradkhani M., Sorooshian S., Gupta H.V., Houser P.R. Dual state-parameter estimation of hydrological models using ensemble Kalman filter. Adv Water Resour 2005, 28:135-147. 10.1016/j.advwatres.2004.09.002.
23. van Delft G., El Serafy G.Y., Heemink A.W. The ensemble particle filter (EnPF) in rainfall-runoff models. Stoch Environ Res Risk A 2009, 23:1203-1211. 10.1007/s00477-008-0301-z.
24. Gourley J.J., Hong Y., Flamig Z.L., Wang J., Vergara H., Anagnostou E.N. Hydrologic evaluation of rainfall estimates from radar, satellite, gauge, and combinations on Ft. Cobb basin, Oklahoma. J. Hydrometeor 2011, 12:973-988. 10.1175/2011JHM1287.1.
25. Li M., Yang D., Chen J., Hubbard S.H. Calibration of a distributed flood forecasting model with input uncertainty using a Bayesian framework. Water Resour Res 2012, 48:W08510. 10.1029/2010WR010062.
26. Tripp D.R., Niemann J.D. Evaluating the parameter identifiability and structural validity of a probability-distributed model for soil moisture. J Hydrol 2008, 353:93-108. 10.1016/j.jhydrol.2008.01.028.
27. Homer C., Dewitz J., Fry J., Coan M., Hossain N., Larson C., et al. Completion of the 2001 national land cover database for the conterminous United States. Photogramm Eng Remote Sens 2007, 73:337-341.
28. Soil survey staff State soil geographic database (STATSGO) data users guide 1994, vol. 1492. USDA Natural Resources Conservation Service Miscellaneous Publication, [p. 88-1036].
29. Li M. Uncertainty estimation of hydrological models under a Bayesian framework. Ph.D dissertation. Tsinghua University. 2012; p. 141.
30. Wagener T., Boyle D.P., Lees M.J., Wheater H.S., Gupta H.V., Sorooshian S. A framework for development and application of hydrological models. Hydrol Earth Syst Sci 2001, 5(1):13-16. 10.5194/hess-5-13-2001.
31. Blasone R.S., Vrugt J.A., Madsen H., Rosbjerg D., Robinson B.A., Zyvoloski G.A. Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling. Adv Water Resour 2008, 31:630-648. 10.1016/j.advwatres.2007.12.003.
32. Kalman R., Bucy R. New results in linear prediction and filtering theory. Trans AMSE J Basic Eng 1961, 83D:95-108. 10.1115/1.3658902.
33. Burgers G., van Leeuwen P.J., Evensen G. Analysis scheme in the ensemble Kalman filter. Mon Weather Rev 1998, 126:1719-1724. /10.1175/1520-0493(1998)126<1719:ASITEK>2.0.CO;2.
34. Clark M.P., Rupp D.E., Woods R.A., Zheng X., Ibbitt R.P., Slater A.G., et al. Hydrological data assimilation with the ensemble Kalman filter: use of streamflow observations to update states in a distributed hydrological model. Adv Water Res 2008, 31:1309-1324. 10.1016/j.advwatres.2008.06.005.
35. Vrugt J.A., Gupta H.V., Nualláin B.Ó., Bouten W. Real-time data assimilation for operational ensemble streamflow forecasting. J Hydrometeorol 2006, 7:548-565. 10.1175/JHM504.1.
36. Crow W.T., Loon E.V. Impact of incorrect model error assumptions on the sequential assimilation of remotely sensed surface soil moisture. J Hydrometeorol 2006, 7(3):421-432. 10.1175/JHM499.1.
37. Vrugt J.A., ter Braak C.J.F., Diks C.G.H., Higdon D., Robinson B.A., Hyman J.M. Accelerating Markov chain Monte Carlo simulation by differential evolution with self-adaptive randomized subspace sampling. Int J Nonlinear Sci Numer Simul 2009, 10(3):273-290. 10.1515/IJNSNS.2009.10.3.273.
38. Sauer VB, Meyer RW, Determination of error in individual discharge measurements. US geological survay. Norcross, Georgia; 1992.
39. Harmel R.D., Cooper R.J., Slade R.M., Haney R.L., Arnold J.G. Cumulative uncertainty in measured streamflow and water quality data for small watersheds. Am Soc Agric Biol Eng 2006, 49(3):689-701.
40. Zhou Y., McLaughlin D., Entekhabi D., Chatdarong V. Assessing the performance of the ensemble Kalman filter for land. Mon Weather Rev 2006, 134(8):2128-2142. 10.1175/MWR3153.1.
41. Pan M., Wood E.F., Wójcik R., McCabe M.F. Estimation of regional terrestrial water cycle using multi-sensor remote sensing observations and data assimilation. Remote Sens Environ 2008, 112:1282-1294. 10.1016/j.rse.2007.02.039.
42. Chen F., Crow W.T., Starks P.J., Moriasi D.N. Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture. Adv Water Res 2011, 34:526-536. 10.1016/j.advwatres.2011.01.011.