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assimilation. Hydrol Sci J 61(13):2348–2366. https://doi.org/10.1080/02626667.2015.1127376
87. Evensen G (2003) The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dyn 53:343–367
88. Heemink AW, Verlaan M, Segers AJ (2001) Variance reduced ensemble Kalman filtering. Mon
Weather Rev 129(7):1718–1728
89. Reichle R, McLaughlin DB, Entekhabi D (2002) Hydrologic data assimilation with the ensemble Kalman filter. Am Meteorol Soc 130(1):103–114. https://doi.org/10.1175/1520-0493(2002)
130<0103:HDAWTE>2.0.CO;2
90. Weerts AH, El Serafy GYH (2006) Particle filtering and ensemble Kalman filtering for state
updating with hydrological conceptual rainfall-runoff models. Water Resour Res 42(9):1–17.
https://doi.org/10.1029/2005WR004093
91. Anderson JL (2001) An ensemble adjustment kalman filter for data assimilation. Mon Weather
Rev 129:2884–2903
92. Murphy JM (1988) The impact of ensemble forecasts on predictability. Q J Roy Meteorol Soc
114(480):463–493. https://doi.org/10.1002/qj.49711448010
93. Pauwels VRN, De Lannoy GJM (2009) Ensemble-based assimilation of discharge into rainfallrunoff models: a comparison of approaches to mapping observational information to state space.
Water Resour Res 45(8):W08428. https://doi.org/10.1029/2008WR007590
94. De Lannoy GJM, Reichle RH, Houser PR, Pauwels VRN, Verhoest NEC (2007) Correcting for
forecast bias in soil moisture assimilation with the ensemble Kalman filter. Water Resour Res 43
(9):W09410. https://doi.org/10.1029/2006WR005449
95. Brouwer T, Eilander D, Van Loenen A, Booij MJ, Wijnberg KM, Verkade JS, Wagemaker J
(2017) Probabilistic flood extent estimates from social media flood observations. Nat Hazards
Earth Syst Sci 17(5):735
96. Cipra T, Romera R (1997) Kalman filter with outliers and missing observations. TEST 6
(2):379–395. https://doi.org/10.1007/BF02564705
234
M. Mazzoleni et al.