Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrologic and Hydraulic Models
M. Mazzoleni (TU Delft - Water Resources)
Dimitri Solomatine – Promotor (TU Delft - Water Resources)
L Alfonso – Copromotor (IHE Delft Institute for Water Education)
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Abstract
Monitoring stations have been used for decades to measure hydrological variables,
and mathematical water models used to predict floods can be enhanced by the
incorporation of these observations, i.e. by data assimilation. The assimilation of
remotely sensed water level observations in hydrological and hydraulic modelling
has become more attractive due to their availability and spatially distributed nature.
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