Exploration of sequential streamflow assimilation in snow dominated watersheds

Advances in Water Resources

Volumn 80, Issue , 2015, Pages 79-89

  Abaza, Mabrouk ^a   Anctil, François ^a   Fortin, Vincent ^b   Turcotte, Richard ^c  

^a UNIVERSITÉ LAVAL   (Canada)

^b ENVIRONMENT CANADA   (Canada)

^c Centre d expertise hydrique du Québec   (Canada)

Author keywords

Ensemble forecast; Ensemble Kalman filter; Performance; Reliability; Semi distributed hydrological model; Snow accumulation and melt

Indexed keywords

CLIMATE MODELS; HYDROLOGY; KALMAN FILTERS; MOISTURE; RELIABILITY; RESERVOIRS (WATER); SOIL MOISTURE; STREAM FLOW; WATERSHEDS;

ENSEMBLE FORECASTS; ENSEMBLE KALMAN FILTER; PERFORMANCE; SEMI DISTRIBUTED HYDROLOGICAL MODELS; SNOW ACCUMULATION;

SNOW;

DATA ACQUISITION; ENSEMBLE FORECASTING; HYDROLOGICAL MODELING; KALMAN FILTER; PERFORMANCE ASSESSMENT; RELIABILITY ANALYSIS; SNOW ACCUMULATION; SNOWMELT; SOIL MOISTURE; STREAMFLOW; WATERSHED;

EID: 84928137520     PISSN: 03091708     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.advwatres.2015.03.011     Document Type: Article

References (41)

1. Abaza M., Anctil F., Fortin V., Turcotte R. A comparison of the Canadian global and regional meteorological ensemble prediction systems for short-term hydrological forecasting. Mon Weather Rev 2013, 141:3462-3476. 10.1175/MWR-D-12-00206.1.
2. Abaza M., Anctil F., Fortin V., Turcotte R. Sequential streamflow assimilation for short-term hydrological ensemble forecasting. J Hydrol 2014, 519:2692-2706. 10.1016/j.jhydrol.2014.08.038.
3. Anderson J.L. An ensemble adjustment Kalman filter for data assimilation. Mon Weather Rev 2001, 129:2884-2903. 10.1175/1520-0493(2001)129<2884:AEAKFF>2.0.CO;2.
4. Andreadis K.M., Lettenmaier D.P. Assimilating remotely sensed snow observations into a macroscale hydrology model. Adv Water Resour 2006, 29:872-886. 10.1016/j.advwatres.2005.08.004.
5. Brocca L., Melone F., Moramarco T., Wagner W., Naeimi V., Bartalis Z., Hasenauer S. Improving runoff prediction through the assimilation of the ASCAT soil moisture product. Hydrol Earth Syst Sci 2010, 14:1881-1893. 10.5194/hess-14-1881-2010.
6. Brochero D., Anctil F., Gagné C. Simplifying a hydrological ensemble prediction system with a backward greedy selection of members - Part 1: optimization criteria. Hydrol Earth Syst Sci 2011, 8:2739-2782. 10.5194/hess-15-3307-2011.
7. 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.
8. Candille G., Talagrand O. Evaluation of probabilistic prediction systems for a scalar variable. Q J R Meteorolog Soc 2005, 131:2131-2150. 10.1256/qj.04.71.
9. Charron M., Pellerin G., Spacek L., Houtekamer P.L., Gagnon N., Mitchell H.L., Michelin L. Toward random sampling of model error in the Canadian ensemble prediction system. Mon Weather Rev 2010, 138:1877-1901. 10.1175/2009MWR3187.1.
10. Clark M.P., Slater A.G., Barrett A.P., Hay L.E., Mc-Cabe G.J., Rajagopalan B., Leavesley G.H. Assimilation of snow covered area information into hydrologic and land-surface models. Adv Water Resour 2006, 29:1209-1221. 10.1016/j.advwatres.2005.10.001.
11. Clark M.P., Rupp D.E., Woods R.A., Zheng X., Ibbitt R.P., Slater A.G., Schmidt J., Uddstrom M.J. 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.
12. DeChant C., Moradkhani H. Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation. Hydrol Earth Syst Sci 2011, 15:3399-3410. 10.5194/hess-15-3399-2011.
13. Dechant C.M., Moradkhani H. Examining the effectiveness and robustness of sequential data assimilation methods for quantification of uncertainty in hydrologic forecasting. Water Resour Res 2012, 48(4):W04518. 10.1029/2011WR011011.
14. Evensen G. Sequential data assimilation with a nonlinear quasigeostrophic model using monte-carlo methods to forecast error statistics. J Geophys Res Oceans 1994, 99:10143-10162. 10.1029/94JC00572.
15. Evensen G. Advanced data assimilation for strongly nonlinear dynamics. Mon Weather Rev 1997, 125:1342-1354. 10.1175/1520-0493(1997)125,1342:ADAFSN.2.0.CO;2.
16. Evensen G. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dyn 2003, 53:343-367. 10.1007/s10236-003-0036-9.
17. Flores A.N., Bras R.L., Entekhabi D. Hydrologic data assimilation with a hillslope-scale-resolving model and L band radar observations: synthetic experiments with the ensemble Kalman filter. Water Resour Res 2012, 48:W08509. 10.1029/2011WR011500.
18. Fortin J.P., Moussa R., Bocquillon C., Villeneuve J.P. Hydrotel, un modèle hydrologique distribué pouvant bénéficier des données fournies par la télédétection et les systèmes d'information géographique. Water Sci Rev 1995, 8:97-124. 10.7202/705215ar.
19. Fortin J.P., Turcotte R., Massicotte S., Moussa R., Fitzback J. A distributed watershed model compatible with remote sensing and GIS data, part i: description of the model. J Hydrol Eng - Am Soc Civ Eng 2001, 6(2):91-99. 10.1061/(ASCE)1084-0699(2001)6:2(91).
20. Fortin V., Abaza M., Anctil F., Turcotte R. Why should ensemble spread match the RMSE of the ensemble mean?. J Hydrometeorol 2014, 15:1708-1713. 10.1175/JHM-D-14-0008.1.
21. Gagnon N, Coauthors. Improvements to the Global Ensemble Prediction System (GEPS) from version 2.0.3 to version 3.0.0. Tech. Note, Environment Canada 2013: p. 88. <>. http://collaboration.cmc.ec.gc.ca/cmc/cmoi/product_guide/docs/lib/op_systems/doc_opchanges/technote_geps300_20130213_e.pdf.
22. Gelb A. Applied optimal estimation 1974, The M.I.T Press.
23. Gneiting T., Raftery A.E. Strictly proper scoring rules, prediction, and estimation. J Am Stat Assoc 2007, 102:359-378. 10.1198/016214506000001437.
24. Hersbach H. Decomposition of the continuous ranked probability score for ensemble prediction systems. Weather Forecasting 2000, 15(5):559-570. 10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2.
25. Kalman R.E. A new approach to linear filtering and prediction problem. J Basic Eng 1960, 82D:35-45. 10.1115/1.3662552.
26. Liu Y., Gupta H.V. Uncertainty in hydrologic modeling: toward an integrated data assimilation framework. Water Resour Res 2007, 43:1-18. 10.1029/2006WR005756.
27. Liu Y., Weerts A.H., Clark M., Hendricks Franssen H.J., Kumar S., Moradkhani H., Seo D.J., Schwanenberg D., Smith P., van Dijk A.I.J.M., van Velzen N., He M., Lee H., Noh S.J., Rakovec O., Restrepo P. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities. Hydrol Earth Syst Sci 2012, 16:3863-3887. 10.5194/hess-16-3863-2012.
28. Mandel J. Efficient implementation of the ensemble Kalman filter (CCM Report 231, University of Colorado at Denver and Health Sciences Center); 2006.
29. Matgen P., Montanari M., Hostache R., Pfister L., Hoffmann L., Plaza D., Pauwels V.R.N., De Lannoy G.J.M., De Keyser R., Savenije H.H.G. Towards the sequential assimilation of SAR-derived water stages into hydraulic models using the particle filter: proof of concept. Hydrol Earth Syst Sci 2010, 14:1773-1785. 10.5194/hess-14-1773-2010.
30. Moradkhani H., Sorooshian S., Gupta H.V., Houser P. Dual state parameter estimation of hydrologic models using ensemble Kalman filter. Adv Water Resour 2005, 28:135-147. 10.1016/j.advwatres.2004.09.002.
31. Nash J.E., Sutcliffe J.V. River flow forecasting through conceptual models: part I-a discussion of principles. J Hydrol 1970, 10:282-290. 10.1016/0022-1694(70)90255-6.
32. Rakovec O., Weerts A.H., Hazenberg P., Torfs P.J.J.F., Uijlenhoet R. State updating of a distributed hydrological model with ensemble Kalman filtering: effects of updating frequency and observation network density on forecast accuracy. Hydrol Earth Syst Sci 2012, 16(9):3435-3449. 10.5194/hess-16-3435-2012.
33. Reichle R.H. Data assimilation methods in the Earth sciences. Adv Water Resour 2008, 31:1411-1418. 10.1016/j.advwatres.2008.01.001.
34. Seo D.J., Koren V., Cajina N. Real-time variational assimilation of hydrologic and hydrometeorological data into operational hydrologic forecasting. J Hydrometeorol 2003, 4(3):627-641. 10.1175/1525-7541(2003)004<0627:RVAOHA>2.0.CO;2.
35. Seo D.J., Cajina L., Corby R., Howieson T. Automatic state updating for operational streamflow forecasting via variational data assimilation. J Hydrol 2009, 367(3-4):255-275. 10.1016/j.jhydrol.2009.01.019.
36. Stanski HR, Wilson LJ, Burrows WR. Survey of common verification methods in meteorology. WMO World Weather Watch Tech Rep 8 1989; WMO TD 358: 114 pp.
37. Turcotte R., Lacombe P., Dimnik C., Villeneuve J.P. Prévision hydrologique distribuée pour la gestion des barrages publics du Québec. Revue canadienne de génie civil 2004, 31(2):308-320. 10.1139/l04-011.
38. Valstar J.R., McLaughlin D.B., Stroet C.M.B.T, Van Geer F.C. A representer-based inverse method for groundwater flow and transport applications. Water Resour Res 2004, 40:W05116. 10.1029/2003WR002922.
39. 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.
40. 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, 42:W09403. 10.1029/2005WR004093.
41. Zaitchik B.F., Rodell M. Forward-looking assimilation of MODIS-derived snow-covered area into a land surface model. J Hydrometeorol 2009, 10:130-148. 10.1175/2008jhm1042.1.