TR32-Database: Database of Transregio 32

[1632] - Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources

All available metadata of the dataset are listed below. Some features are available, e.g. download of dataset or additional description file.

Features
Citation
Kurtz, W., Lapin, A., Schilling, O. S., Tang, Q., Schiller, E., Braun, T., Hunkeler, D., Vereecken, H., Sudicky, E., Kropf, P., Hendricks-Franssen, H., Brunner, P., 2017. Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources. Environmental Modelling & Software, 93, 418 - 435. DOI: 10.1016/j.envsoft.2017.03.011.
Identification
Title(s):Main Title: Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources
Description(s):Abstract: 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.
Identifier(s):DOI: 10.1016/j.envsoft.2017.03.011
Citation Advice:Kurtz, W., Lapin, A., Schilling, O.S., Tang, Q., Schiller, E., Braun, T., Hunkeler, D., Vereecken, H., Sudicky, E., Kropf, P., Hendricks Franssen, H.-J., Brunner, P., 2017. Integrating hydrological modelling, data assimilation and cloud computing for real-time management of water resources. Environ. Modell. Software 93, 418-435, DOI: 10.1016/j.envsoft.2017.03.011.
Responsible Party
Creator(s):Author: Wolfgang Kurtz
Author: Andrei Lapin
Author: Oliver S. Schilling
Author: Qi Tang
Author: Eryk Schiller
Author: Torsten Braun
Author: Daniel Hunkeler
Author: Harry Vereecken
Author: Edward Sudicky
Author: Peter Kropf
Author: Harrie-Jan Hendricks-Franssen
Author: Philip Brunner
Publisher:Elsevier
Topic
TR32 Topic:Other
Related Sub-project(s):C6
Subject(s):CRC/TR32 Keywords: Data Assimilation, Groundwater Hydrology, Modelling
File Details
File Name:Kurtz_etal_2017_EnvSoft.pdf
Data Type:Text
File Size:6196 kB (6.051 MB)
Date(s):Date Accepted: 2017-03-11
Mime Type:application/pdf
Data Format:PDF
Language:English
Status:Completed
Constraints
Download Permission:OnlyTR32
General Access and Use Conditions:According to the TR32DB data policy agreement.
Access Limitations:According to the TR32DB data policy agreement.
Licence:TR32DB Data policy agreement
Geographic
North:-no map data
East:-
South:-
West:-
Measurement Region:Other
Measurement Location:--Other--
Specific Informations - Publication
Status:Accepted
Review:PeerReview
Year:2017
Type:Article
Article Type:Journal
Source:Environmental Modelling & Software
Volume:93
Page Range:418 - 435
Metadata Details
Metadata Creator:Wolfgang Kurtz
Metadata Created:2017-10-06
Metadata Last Updated:2017-10-06
Subproject:C6
Funding Phase:3
Metadata Language:English
Metadata Version:V42
Dataset Metrics
Page Visits:41
Metadata Downloads:0
Dataset Downloads:1
Dataset Activity
Features