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Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources

Auteur(s)
Kropf, Peter 
Institut d'informatique 
Kurtz, Wolfgang
Lapin, Andrei 
Institut d'informatique 
Schilling, Oliver 
Centre d'hydrogéologie et de géothermie 
Schiller, Eryk 
Institut d'informatique 
Braun, Torsten
Hunkeler, Daniel 
Centre d'hydrogéologie et de géothermie 
Vereecken, Harry
Sudicky, Edward
Franssen, Harrie-Jan Hendricks
Brunner, Philip 
Centre d'hydrogéologie et de géothermie 
Date de parution
2017-7-1
In
Environmental Modelling and Software
No
93
De la page
418
A la page
435
Revu par les pairs
1
Mots-clés
  • Cloud computingIntegr...

Résumé
Online data acquisition, data assimilation and integrated hydrological modelling have become more and more important in hydrological science. In this study, we explore cloud computing for integrating field data acquisition and stochastic, physically-based hydrological modelling in a data assimilation and optimisation framework as a service to water resources management. For this purpose, we developed an ensemble Kalman filter-based data assimilation system for the fully-coupled, physically-based hydrological model HydroGeoSphere, which is able to run in a cloud computing environment. A synthetic data assimilation experiment based on the widely used tilted V-catchment problem showed that the computational overhead for the application of the data assimilation platform in a cloud computing environment is minimal, which makes it well-suited for practical water management problems. Advantages of the cloud-based implementation comprise the independence from computational infrastructure and the straightforward integration of cloud-based observation databases with the modelling and data assimilation platform.
URI
https://libra.unine.ch/handle/123456789/27351
DOI
10.1016/j.envsoft.2017.03.011
Autre version
https://doi.org/10.1016/j.envsoft.2017.03.011
Type de publication
Resource Types::text::journal::journal article
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