Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrologic and Hydraulic Models

Improving Flood Prediction Assimilating Uncertain Crowdsourced Data into Hydrologic and Hydraulic Models

Mazzoleni, M. (TU Delft Water Resources)

Solomatine, D.P. (promotor)
Alfonso, L (copromotor)

Delft University of Technology

2016-11-28

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.

http://resolver.tudelft.nl/uuid:e4ae4035-72dc-41cc-bad0-eab044e0613a

CRC Press / Balkema - Taylor & Francis Group

978-1-138-03590-4

Dissertation submitted in fulfilment of the requirements of the Board for Doctorates of Delft University of Technology and of the Academic Board of the UNESCO-IHE Institute for Water Education.

Institutional Repository

doctoral thesis

© 2016 M. Mazzoleni