Hydro-Scientific Software Development

Team

Focus

Our main focus is on providing high quality software in cooperation with working groups related to Hydro-Science at the UFZ. This means, we act as Model-Keepers for code already in existence and production and further enable and implement projects in close collaboration with researchers.

You focus on research, we focus on code.

Projects

mHM - the Mesoscale Hydrological Model

Website: https://www.ufz.de/mhm

Repository: https://git.ufz.de/mhm/mhm

Model-Keeper: Stephan Thober, Sebastian Müller

GeoStat Framework
Create your geo-statistical model with Python!

Website: https://geostat-framework.org

Repository: https://github.com/GeoStat-Framework

Model-Keeper: Sebastian Müller

Fortran EDK
External Drift Kriging in Fortran supporting NetCDF in- and output.

Repository: https://git.ufz.de/chs/progs/edk_nc

Model-Keeper: Sebastian Müller, Stephan Thober

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Contact

Head
Prof. Dr. Sabine Attinger
Department of Computational Hydrosystems
tbl-modmon@ufz.de

Deputy Head
Dr. Luis Samaniego
Department of Computational Hydrosystems
luis.samaniego@ufz.de

Assistance
Nora Pabst
Phone +49 341 235-1281

Sindy Bleiholder
Phone +49 341 235-1250

Anne Dornfeld
Phone +49 341 235-482427

sekces@ufz.de

Permoserstraße 15 | 04318 Leipzig

News / Press

Aug 20, 2021

Open house days of the Swabian MOSES Campaign received large public interest. A research consortium of several Helmholtz centers, universities and the German Weather Service, investigates the cause and effects of hydro-meteorological extremes such as heavy thunderstorms, high precipitation and floods as well as heatwaves and droughts. The MOSES initiative is coordinated by the UFZ.

Aug 17, 2021

Start of the third phase of Collaborative Research Centre AquaDiva, investigating the links between surface and subsurface signals in the earth critical zone. Two projects are lead by researchers of CHS. They will investigate with modeling and observations how temporal and spatial variation of surface input and processes during subsurface transit drive the water flow and element transport to groundwater and rivers.

Jul 22, 2021

We are happy to announce the next release of mHM: v5.11.2 .

May 19, 2021

In October 2020 a new Helmholtz Young Investigator group ( link ) led by Jakob Zscheischler started in CHS. The group will work on compound weather and climate events with a particular focus on using novel ideas from explainable machine learning to identify compounding weather drivers of extreme impacts such as vegetation mortality, crop failure and floods. Recently the group was awarded a Helmholtz AI project called CausalFlood, in which compounding drivers of floods will be identified based on causal inference in collaboration with the group of Jakob Runge from DLR.

Older news are stored in the news archive.

New publications

Najafi H, Robertson AW, Massah Bavani AR, Irannejad P, Wanders N, Wood EF. Improved multi-model ensemble forecasts of Iran's precipitation and temperature using a hybrid dynamical-statistical approach during fall and winter seasons. Int
J Climatol. 2021;1–28. DOI: 10.1002/joc.7148

Hari, V., Rakovec, O., Markonis, Y. et al. Increased future occurrences of the exceptional 2018–2019 Central European drought under global warming. Sci Rep 10, 12207 (2020). DOI: 10.1038/s41598-020-68872-9

Schmidt, L., Heße, F., Attinger, S., Kumar, R., (2020): "Challenges in applying machine learning models for hydrological inference: A case study for flooding events across Germany", Water Resources Research DOI: 10.1029/2019WR025924

Jing, M., Kumar, R., Heße, F., Thober, S., Rakovec, O., Samaniego, L., Attinger, S., (2020): "Assessing the response of groundwater quantity and travel time distribution to 1.5, 2, and 3 °C global warming in a mesoscale central German basin", Hydrology and Earth System Sciences DOI: 10.5194/hess-24-1511-2020