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Two PhD scholarships in 'Hydrological Forecasting and Data Assimilation'



The Committee for Sustainable Energy and Environment under the Danish Strategic Research Council has recently funded the project HydroCast - Hydrological forecasting and data assimilation. The project is a multi-disciplinary and multi-institutional project and involves the following partners: DHI, Geological Survey of Denmark and Greenland (GEUS), University of Copenhagen, Aalborg University, Danish Meteorological Institute, European Center for Medium-Range Weather, Delft University, Danish Road Directorate, Knowledge Center for Agriculture, and Danish Nature Agency. The project leader is Dr. Henrik Madsen from DHI.

Applications are invited for two PhD scholarship openings within the following subject areas:

(1) Hydrological data assimilation

Development of a multi-variate hydrological data assimilation system for assimilation of in situ and remote sensing data in the MIKE SHE hydrological modeling system. Application of the Open Source OpenDA data assimilation toolbox, which an interface standard for implementation of data assimilation in numerical models, may be considered. The link to MIKE SHE may be established through the open modelling interface (OpenMI) standard leading to a flexible framework for implementation and testing of different data assimilation algorithms and assimilation of different types of hydrological data in MIKE SHE. Variables of interest for assimilation are in-situ measurements of river runoff, groundwater levels, and soil moisture profiles and remote sensing measurements of soil moisture and land surface temperature. Another research topic of the PhD project is uncertainty in models and measurements and how this is propagated to uncertainty in the hydrological predictions. The hydrological data assimilation system will be applied and tested at a local highway construction site near Silkeborg and in the Skjern catchment.

(2) Probabilistic hydrological forecasting

Development of a methodology for producing probabilistic hydrological forecasts, considering short-range, medium-range and seasonal forecasting. The following ensemble Quantitative precipitation forecasts (QPF) products are considered:

  • Short-range forecasting: The operational limited area ensemble prediction system at DMI.
  • Medium-range forecasting: The European Centre for Medium-Range Weather Forecasts (ECMWF) medium-range ensemble prediction system
  • Seasonal forecasting: The ECMWF seasonal ensemble prediction system and the IRI (International Research Institute for Climate and Society) seasonal ensemble

These products will form the basis for quantifying the uncertainty of QPF and its propagation in the MIKE SHE hydrological modeling system. The project will advance a framework for quantification and propagation of the different uncertainty sources in the hydrological forecast system for estimation of the resulting forecast uncertainty, including uncertainties in the QPF and hydrological model uncertainty (initial state, model parameters and model structure. Focus will be on developing an uncertainty framework that is feasible for real-time hydrological forecasting and is consistent with the uncertainty descriptions in the data assimilation system. The probabilistic hydrological forecast system will be applied and tested at the same sites as above.

For both scholarships the successful candidates will be employed at the Department of Geography and Geology, University of Copenhagen, and enrolled the PhD school of Science, University of Copenhagen. Both candidates will be supervised by a supervision panel consisting of Professor Karsten H. Jensen, University of Copenhagen (khj@geo.ku.dk), Dr. Henrik Madsen, DHI (hem@dhigroup.com), and Professor Jens Christian Refsgaard, GEUS (jcr@geus.dk). However, the students will also collaborate closely with other scientists on the HydroCast project and in particular two postdocs employed at DHI and GEUS. Also collaboration with the international partners European Center for Medium-Range Weather and Delft University will be an important element. The students are expected to visit these organizations for shorter and longer time.

Applicants are expected to possess a strong background in applied mathematics, statistics, and numerical methods. An additional background in hydrology and/or meteorology will be an advantage.

Applicants are requested to fill Part 1 of the application form 'Application for scholarship and admission' that can be downloaded from http://www.science.ku.dk/phd/applying/forms/ and attach the requested documentation.

Terms of employment

The successful PhD candidate will be offered a full-time PhD position for a period of three years, contingent on a satisfactory performance, with the specific intent that it results in a PhD degree and scientific publications. It is a prerequisite for the appointment as a PhD-fellow, that the person concerned can be registered as a PhD-fellow according to the Ministry of Science, Technology and Innovation Executive Order no 18 of 14. January 2008. Information about the PhD programs at the Faculty of Science can be found at http://www.science.ku.dk/phd/.

The salary depends on seniority, as agreed between the Ministry of Finance and the Danish Confederation of Professional Associations within the range of 23,000-30,000 DKK/month (approximately 3,100-4,000 Euro/month).

The scholarships are open to both Danish and international applicants.

The applications will be evaluated by an evaluation committee appointed by the department. Selected applicants will be invited for interviews. The two scholarships will be awarded according to the applicants' background and qualifications.

Further information may be obtained from the supervisors.

Applications must be submitted by using the link below. Applications with insufficient documentation or applications that do not comply with the above requirements will not be considered.

The deadline for receipt of applications is April 23, 2012 at noon.


posted: 20 March 2012     Please mention EARTHWORKS when responding to this advertisement.