Journal
ENVIRONMENTAL MODELLING & SOFTWARE
Volume 93, Issue -, Pages 418-435Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2017.03.011
Keywords
Cloud computing; Integrated hydrological modelling; Data assimilation; Water resources management; HydroGeoSphere; Wireless sensor networks
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Funding
- German Research Foundation (DFG) [SFB-TR32]
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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. (C) 2017 Elsevier Ltd. All rights reserved.
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