IAHR, founded in 1935, is a worldwide independent member-based organisation of engineers and water specialists working in fields related to the hydro-environmental sciences and their practical application. Activities range from river and maritime hydraulics to water resources development and eco-hydraulics, through to ice engineering, hydroinformatics, and hydraulic machinery.
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You are here : eLibrary : IAHR World Congress Proceedings : 36th Congress - The Hague (2015) ALL CONTENT : Flood risk management and adaptation : Towards the assimilation of anarchist flow observations in hydrological models
Towards the assimilation of anarchist flow observations in hydrological models
Early warning systems have been used in the last decades to provide accurate flood forecast and reduce flood risk in
urbanized areas. In order to reduce the intrinsic model uncertainty and improve the flood forecasting accuracy, different
data assimilation techniques have been proposed to update model states and output as response of real-time
observations from physical sensors. Traditionally, hydrological observations from such sensors have a well defined
structure in terms of frequency, accuracy and implementation in data assimilation approaches. Nowadays, observations
from low-cost sensors having variable space and temporal coverage and unpredictable accuracy in time and space are
becoming more available. Such observations can be considered as anarchist since they have no rules in the information
retrieving, in contrast to the common observations coming from physical sensors. However, the assimilation of anarchist
observations has not been properly considered in hydrological application. The objective of this study is to propose an
adaptive modelling framework for the assimilation of anarchist observations in hydrological models to improve flood
forecasting accuracy. Synthetic experiments are carried out assuming different distributions of observations accuracy and
location within the domain of the Brue basin. Models using data assimilation with and without anarchist observations are
compared to evaluate the performance of the method. Preliminary results show how anarchist observations can be
integrated in hydrological model in addition to standard streamflow observations to improve flood forecasting.
File Size : 380,425 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 36th Congress - The Hague (2015) ALL CONTENT
Article : Flood risk management and adaptation
Date Published : 18/08/2015
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