64. Mazzoleni M, Amaranto A, Solomatine DP (2019) Integrating qualitative flow observations in a
lumped hydrologic routing model. Water Resour Res 55. https://doi.org/10.1029/
2018WR023768
65. WeSenseIt (2016) WeSenseIt: citizen water observatories. http://wesenseit.eu/. Accessed
19 Feb 2016
66. Sugeno M, Yasukawa T (1993) A fuzzy-logic-based approach to qualitative modelling. IEEE
Trans Fuzzy Syst 1:7–31
67. Moore RJ, Jones DA, Cox DR, Isham VS (2000) Design of the HYREX raingauge network.
Hydrol Earth Syst Sci 4(4):521–530. https://doi.org/10.5194/hess-4-521-2000
68. Wood SJ, Jones DA, Moore RJ (2000) Accuracy of rainfall measurement for scales of
hydrological interest. Hydrol Earth Syst Sci Discuss 4(4):531–543
69. Szilagyi J, Szollosi-Nagy A (2010) Recursive streamflow forecasting: a state space approach.
CRC Press, Leiden
70. Cunge JA (1969) On the subject of a flood propagation computation method (Muskingum
method). J Hydraul Res 7(2):205–230
71. Ferri M, Monego M, Norbiato D, Baruffi F, Toffolon C, Casarin R (2012) La piattaforma
previsionale per i bacini idrografici del Nord Est Adriatico (I). Proceedings XXXIII conference
of hydraulics and hydraulic engineering, Brescia, p 10
72. Huwald H, Barrenetxea G, de Jong S, Ferri M, Carvalho R, Lanfranchi V, McCarthy S,
Glorioso G, Prior S, Solà E, Gil-Roldàn E, Alfonso L, Wehn de Montalvo U, Onencan A,
Solomatine D, Lobbrecht A (2013) D1.11 sensor technology requirement analysis. Confidential
deliverable, the WeSenseIt project (FP7/2007-2013 grant agreement no 308429)
73. Duan Q, Ajami NK, Gao X, Sorooshian S (2007) Multi-model ensemble hydrologic prediction
using Bayesian model averaging. Adv Water Resour 30(5):1371–1386. https://doi.org/10.1016/
j.advwatres.2006.11.014
74. Georgakakos AP, Georgakakos KP, Baltas EA (1990) A state-space model for hydrologic river
routing. Water Resour Res 26:827–838
75. Refsgaard JC (1997) Validation and intercomparison of different updating procedures for realtime forecasting. Nord Hydrol 28(2):65–84. https://doi.org/10.2166/nh.1997.005
76. WMO (1992) Simulated real-time intercomparison of hydrological models. World Meteorological Organization, Geneva
77. Moradkhani H, Hsu KL, Gupta H, Sorooshian S (2005) Uncertainty assessment of hydrologic
model states and parameters: sequential data assimilation using the particle filter. Water Resour
Res 41(5):W05012. https://doi.org/10.1029/2004WR003604
78. Moradkhani H, Sorooshian S, Gupta HV, Houser PR (2005) Dual state–parameter estimation of
hydrological models using ensemble Kalman filter. Adv Water Resour 28(2):135–147
79. Salamon P, Feyen L (2009) Assessing parameter, precipitation, and predictive uncertainty in a
distributed hydrological model using sequential data assimilation with the particle filter.
J Hydrol 376(3-4):428–442
80. Lü H, Yu Z, Zhu Y, Drake S, Hao Z, Sudicky EA (2011) Dual state-parameter estimation of root
zone soil moisture by optimal parameter estimation and extended Kalman filter data assimilation. Adv Water Resour 34(3):395–406
81. Kalman RE (1960) A new approach to linear filtering and prediction problems. J Basic Eng 82
(1):35–45. https://doi.org/10.1115/1.3662552
82. Heemink AW, Segers AJ (2002) Modeling and prediction of environmental data in space and
time using Kalman filtering. Stoch Environ Res Risk Assess 16(3):225–240. https://doi.org/10.
1007/s00477-002-0097-1
83. Reichle RH, Crow WT, Keppenne CL (2008) An adaptive ensemble Kalman filter for soil
moisture data assimilation. Water Resour Res 44(3):W03423. https://doi.org/10.1029/
2007WR006357
84. Robinson AR, Lermusiaux PFJ, Sloan III NQ (1998) Data assimilation. Sea 10:541–594
85. Walker JP, Houser PR (2005) Hydrologic data assimilation. Adv Water Sci Methodol 41:233.
https://doi.org/10.5772/1112
Exploring Assimilation of Crowdsourcing Observations into Flood Models
233
lumped hydrologic routing model. Water Resour Res 55. https://doi.org/10.1029/
2018WR023768
65. WeSenseIt (2016) WeSenseIt: citizen water observatories. http://wesenseit.eu/. Accessed
19 Feb 2016
66. Sugeno M, Yasukawa T (1993) A fuzzy-logic-based approach to qualitative modelling. IEEE
Trans Fuzzy Syst 1:7–31
67. Moore RJ, Jones DA, Cox DR, Isham VS (2000) Design of the HYREX raingauge network.
Hydrol Earth Syst Sci 4(4):521–530. https://doi.org/10.5194/hess-4-521-2000
68. Wood SJ, Jones DA, Moore RJ (2000) Accuracy of rainfall measurement for scales of
hydrological interest. Hydrol Earth Syst Sci Discuss 4(4):531–543
69. Szilagyi J, Szollosi-Nagy A (2010) Recursive streamflow forecasting: a state space approach.
CRC Press, Leiden
70. Cunge JA (1969) On the subject of a flood propagation computation method (Muskingum
method). J Hydraul Res 7(2):205–230
71. Ferri M, Monego M, Norbiato D, Baruffi F, Toffolon C, Casarin R (2012) La piattaforma
previsionale per i bacini idrografici del Nord Est Adriatico (I). Proceedings XXXIII conference
of hydraulics and hydraulic engineering, Brescia, p 10
72. Huwald H, Barrenetxea G, de Jong S, Ferri M, Carvalho R, Lanfranchi V, McCarthy S,
Glorioso G, Prior S, Solà E, Gil-Roldàn E, Alfonso L, Wehn de Montalvo U, Onencan A,
Solomatine D, Lobbrecht A (2013) D1.11 sensor technology requirement analysis. Confidential
deliverable, the WeSenseIt project (FP7/2007-2013 grant agreement no 308429)
73. Duan Q, Ajami NK, Gao X, Sorooshian S (2007) Multi-model ensemble hydrologic prediction
using Bayesian model averaging. Adv Water Resour 30(5):1371–1386. https://doi.org/10.1016/
j.advwatres.2006.11.014
74. Georgakakos AP, Georgakakos KP, Baltas EA (1990) A state-space model for hydrologic river
routing. Water Resour Res 26:827–838
75. Refsgaard JC (1997) Validation and intercomparison of different updating procedures for realtime forecasting. Nord Hydrol 28(2):65–84. https://doi.org/10.2166/nh.1997.005
76. WMO (1992) Simulated real-time intercomparison of hydrological models. World Meteorological Organization, Geneva
77. Moradkhani H, Hsu KL, Gupta H, Sorooshian S (2005) Uncertainty assessment of hydrologic
model states and parameters: sequential data assimilation using the particle filter. Water Resour
Res 41(5):W05012. https://doi.org/10.1029/2004WR003604
78. Moradkhani H, Sorooshian S, Gupta HV, Houser PR (2005) Dual state–parameter estimation of
hydrological models using ensemble Kalman filter. Adv Water Resour 28(2):135–147
79. Salamon P, Feyen L (2009) Assessing parameter, precipitation, and predictive uncertainty in a
distributed hydrological model using sequential data assimilation with the particle filter.
J Hydrol 376(3-4):428–442
80. Lü H, Yu Z, Zhu Y, Drake S, Hao Z, Sudicky EA (2011) Dual state-parameter estimation of root
zone soil moisture by optimal parameter estimation and extended Kalman filter data assimilation. Adv Water Resour 34(3):395–406
81. Kalman RE (1960) A new approach to linear filtering and prediction problems. J Basic Eng 82
(1):35–45. https://doi.org/10.1115/1.3662552
82. Heemink AW, Segers AJ (2002) Modeling and prediction of environmental data in space and
time using Kalman filtering. Stoch Environ Res Risk Assess 16(3):225–240. https://doi.org/10.
1007/s00477-002-0097-1
83. Reichle RH, Crow WT, Keppenne CL (2008) An adaptive ensemble Kalman filter for soil
moisture data assimilation. Water Resour Res 44(3):W03423. https://doi.org/10.1029/
2007WR006357
84. Robinson AR, Lermusiaux PFJ, Sloan III NQ (1998) Data assimilation. Sea 10:541–594
85. Walker JP, Houser PR (2005) Hydrologic data assimilation. Adv Water Sci Methodol 41:233.
https://doi.org/10.5772/1112
Exploring Assimilation of Crowdsourcing Observations into Flood Models
233