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Young scientist network on hydrological and meteorological data assimilation (HyMeDAs network)

Subject Area Hydrogeology, Hydrology, Limnology, Urban Water Management, Water Chemistry, Integrated Water Resources Management
Term from 2009 to 2011
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 129455175
 
Final Report Year 2013

Final Report Abstract

The main objective of this young scientist network was the organization and conduction of a graduate student course on data assimilation in the disciplines of hydrology and meteorology. The young researcher network met several times for preparation of this event. During the meetings, we detailed out and focused the agenda. We also got in touch with experts to propagate the schedule and understand which parts of this topic should be presented in the lectures and exercises. Partly with the help of the experts, we developed or documented tools and exercises for practical training. We prepared a webspace for exchange of information, data, publications. The course announcement was met with great interest in the graduate student community, and we received far more applications for participations than we had open spots. As a result of our work, the course was conducted for one week in Bad Schandau in April 2010 in form of a spring school. The feedback of the participants was overwhelmingly positive, and was also due to the excellent teaching of our invited lecturers. The course was not only a teaching event, but had also the desired effect of networking between leading experts in the field with young scientists. Thus, further reaching results include two more follow up graduate courses with one of the experts in 2011 and 2012 in Leipzig and Freiburg. Besides organizing the school, the members of the network contributed to the course actively by teaching modules or tutoring the exercises. We, the organizers did not only broaden our own expertise in the field, but also our teaching portfolio and experience. We believe that this course came at a right time and has promoted the topic of intelligently merging data with models in the graduate student community in Germany.

 
 

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