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Interoperability challenges in river discharge modelling: A cross domain application scenario.

Authors :
Santoro, Mattia
Andres, Volker
Jirka, Simon
Koike, Toshio
Looser, Ulrich
Nativi, Stefano
Pappenberger, Florian
Schlummer, Manuela
Strauch, Adrian
Utech, Michael
Zsoter, Ervin
Source :
Computers & Geosciences. Jun2018, Vol. 115, p66-74. 9p.
Publication Year :
2018

Abstract

River discharge is a critical water cycle variable, as it integrates all the processes (e.g. runoff and evapotranspiration) occurring within a river basin and provides a hydrological output variable that can be readily measured. Its prediction is of invaluable help for many water-related tasks including water resources assessment and management, flood protection, and disaster mitigation. Observations of river discharge are important to calibrate and validate hydrological or coupled land, atmosphere and ocean models. This requires using datasets from different scientific domains (Water, Weather, etc.). Typically, such datasets are provided using different technological solutions. This complicates the integration of new hydrological data sources into application systems. Therefore, a considerable effort is often spent on data access issues instead of the actual scientific question. This paper describes the work performed to address multidisciplinary interoperability challenges related to river discharge modeling and validation. This includes definition and standardization of domain specific interoperability standards for hydrological data sharing and their support in global frameworks such as the Global Earth Observation System of Systems (GEOSS). The research was developed in the context of the EU FP7-funded project GEOWOW (GEOSS Interoperability for Weather, Ocean and Water), which implemented a “River Discharge” application scenario. This scenario demonstrates the combination of river discharge observations data from the Global Runoff Data Centre (GRDC) database and model outputs produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) predicting river discharge based on weather forecast information in the context of the GEOSS. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00983004
Volume :
115
Database :
Academic Search Index
Journal :
Computers & Geosciences
Publication Type :
Academic Journal
Accession number :
129252784
Full Text :
https://doi.org/10.1016/j.cageo.2018.03.008