Sebastian Müller - Helmholtz-Centre for Environmental Research

Dipl. Math. Sebastian Müller

Contact

Dipl. Math. Sebastian Müller

Model keeper

Hydro-Scientific Software Development (HSD)
Department Computational Hydrosystems (CHS)
Helmholtz Centre for Environmental Research – UFZ
Permoserstr. 15, 04318 Leipzig - Germany

sebastian.mueller@ufz.de

The GeoStat-Framework

The GeoStat-Framework - Create your geostatistical model in Python!

Research Interests

I am developing software tools for hydro-scientific applications. I founded the GeoStat-Framework and act as a model-keeper for mHM.

Former projects

Determining statistical parameters of aquifer heterogeneity from pumping test data

Scientific Career

since 10/2019

Model keeper at the Department CHS at the UFZ

09/2018

Research stay at the KTH university in Stockholm. In co-operation with Vladimir Cvetkovic.

since 10/2016

PhD-Student at the Department CHS at the UFZ and scholarship holder of the German Federal Environmental Foundation link

10/2015 - 09/2016

Research Assistant in the Department CHS at the Helmholtz Centre for Environmental Research - UFZ

04/2014 - 09/2015

Student Assistant in the Department CHS at the Helmholtz Centre for Environmental Research - UFZ

10/2011 - 03/2016

Tutor at the Faculty of Mathematics at the University of Leipzig

10/2009 - 09/2015

Studies of Mathematics and Informatics at the University of Leipzig

Co-operations

KTH Stockholm
Institute: Resources, Energy and Infrastructure
Address: Teknikringen 10B, 11428 Stockholm
Partner: Vladimir Cvetkovic, Liangchao Zou

Project: Effective description and analysis of stochastic discrete fracture networks (DFN) and pumping tests in fractal media.

Publications

Müller, S., Schüler, L., Zech, A., Heße, F. (2022)
GSTools v1.3: a toolbox for geostatistical modelling in Python.
Geoscientific Model Development, 15, 3161–3182
https://doi.org/10.5194/gmd-15-3161-2022

Schweppe, R., Thober, S., Müller, S., Kelbling, M., Kumar, R., Attinger, S., Samaniego, L. (2022)
MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models
Geoscientific Model Development, 15, 859–882
https://doi.org/10.5194/gmd-15-859-2022

Marx, A., Boeing, F., Rakovec, O., Müller, S., Can, Ö., Malla, C., Peichl, M., Samaniego, L. (2021)
Auswirkungen des Klimawandels auf Wasserbedarf und -dargebot
Wasserwirtschaft 111(11):14-19
https://doi.org/10.1007/s35147-021-0905-5

Müller, S., Heße, F., Attinger, S., Zech, A. (2021)
The extended generalized radial flow model and effective conductivity for truncated power law variograms.
Advances in Water Resources 156:104027
https://doi.org/10.1016/j.advwatres.2021.104027

Müller, S., Leven, C., Dietrich, P., Attinger, S., Zech, A. (2021)
How to Find Aquifer Statistics Utilizing Pumping Tests? Two Field Studies Using welltestpy.
Groundwater, 60: 137-144
https://doi.org/10.1111/gwat.13121

Müller, S., Zech, A., Heße, F. (2020)
ogs5py: A Python-API for the OpenGeoSys 5 Scientific Modeling Package.
Groundwater, 59: 117-122
https://doi.org/10.1111/gwat.13017

Müller, S. (2019)
pentapy: A Python toolbox for pentadiagonal linear systems.
Journal of Open Source Software, 4(42), 1759
https://doi.org/10.21105/joss.01759

Zech, A., Müller, S., Mai, J., Heße, F., & Attinger, S. (2016)
Extending theis’ solution: Using transient pumping tests to estimate parameters of aquifer heterogeneity.
Water Resources Research 52, 6156–617
https://doi.org/10.1002/2015WR018509

Müller, S. (2015)
Eine erweiterte Theis-Lösung: Berechnung und Implementierung einer Lösung der transienten Grundwassergleichung unter Berücksichtigung von Heterogenität im Coarse-Graining Modell.
Diplomarbeit, Universität Leipzig.
https://doi.org/10.13140/RG.2.2.34074.24002

Software Publications

Müller, S., Schüler, L.: GeoStat-Framework/GSTools
Zenodo, 2018-now. https://doi.org/10.5281/zenodo.1313628

Müller, S.: GeoStat-Framework/ogs5py
Zenodo, 2018-now. https://doi.org/10.5281/zenodo.2546767

Müller, S.: GeoStat-Framework/AnaFlow
Zenodo, 2018-now. https://doi.org/10.5281/zenodo.1135723

Müller, S., Herrmann, J.: GeoStat-Framework/welltestpy
Zenodo, 2018-now. https://doi.org/10.5281/zenodo.1229051

Müller, S.: GeoStat-Framework/pentapy
Zenodo, 2019-now. https://doi.org/10.5281/zenodo.2587158

Murphy, B., Müller, S., Yurchak, R.: GeoStat-Framework/PyKrige
Zenodo, 2019-now. https://doi.org/10.5281/zenodo.3738604

mHM Developers: mhm-ufz/basinex
Zenodo, 2022-now. https://doi.org/10.5281/zenodo.6025795

mHM Developers: The Soil Moisture Index program - SMI
Zenodo, 2022-now. https://doi.org/10.5281/zenodo.6023024

mHM Developers: mesoscale Hydrologic Model - mHM
Zenodo, 2019-now. https://doi.org/10.5281/zenodo.1069202

Mälicke, M., Hugennet, R., Schneider, H. D., Müller, S., Möller, E., Van de Wauw, J.: mmaelicke/scikit-gstat: A scipy flavoured geostatistical variogram analysis toolbox
Zenodo, 2021-now. https://doi.org/10.5281/zenodo.1345584

Murray S., Müller S., Poulin F. J., Zaslavsky D., Bazán, J., Niemeyer, K.: steven-murray/hankel
Zenodo, 2018-now. http://dx.doi.org/10.5281/zenodo.1336791

Müller, S.: MuellerSeb/mlabtex: Mighty Mug
Zenodo, 2019-now. https://doi.org/10.5281/zenodo.3380567

Conference Contributions

Müller, S., Schüler, L., Zech, A., and Heße, F.: The GeoStat-Framework: Create your geostatistical model in Python!, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8167, https://doi.org/10.5194/egusphere-egu22-8167, 2022.

Boeing, F., Rakovec, O., Kumar, R., Samaniego, L., Schrön, M., Hildebrandt, A., Rebmann, C., Thober, S., Müller, S., Zacharias, S., Bogena, H., Schneider, K., Kiese, R., and Marx, A.: High resolution soil drought simulations evaluated at an unprecedented broad-range of soil moisture networks in Germany, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11356, https://doi.org/10.5194/egusphere-egu22-11356, 2022.

Thober, S., Samaniego, L., Müller, S., Shrestha, P., Kelbling, M., Rakovec, O., Boeing, F., Marx, A., Kumar, R., and Attinger, S.: Hyperresolution Global Operational Hydrological Modelling and Forecasting: enhancing reproducability, skill and workflows setup , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-3529, https://doi.org/10.5194/egusphere-egu22-3529, 2022.

Rakovec, O., Kaluza, M., Kumar, R., Schweppe, R., Shrestha, P., Thober, S., Müller, S., Attinger, S., and Samaniego, L.: Advancements in the mesoscale Hydrologic Model at the global scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15869, https://doi.org/10.5194/egusphere-egu21-15869, 2021.

Müller, S., Zech, A., Leven, C., Dietrich, P., and Attinger, S.: Where to find aquifer statistics utilizing pumping tests? Two field studies using welltestpy., AGU Fall Meeting 2020, Online, 1–17 December 2020, H195-0021, https://agu.confex.com/agu/fm20/meetingapp.cgi/Paper/692507, 2020.

Müller, S., Schüler, L., Zech, A., Attinger, S., and Heße, F.: GSTools: The Python toolbox for your geo-statistical project!, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10104, https://doi.org/10.5194/egusphere-egu2020-10104, 2020.

Najafi, H., Thober, S., Boeing, F., Rakovec, O., Kelbling, M., Müller, S., Marx, A., and Samaniego, L.: A Real-time Ensemble Hydrological Forecasting System over Germany at Sub-seasonal to Seasonal Time Range, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-9773, https://doi.org/10.5194/egusphere-egu2020-9773, 2020.

Heße, F., Isachsen, L., Müller, S., and Sabine, A.: Bayesian Analysis of the Data Worth of Pumping Tests Using Informative Prior Distributions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-8510, https://doi.org/10.5194/egusphere-egu2020-8510, 2020.

Müller, S., Schüler, L., Zech, A., Attinger, S., and Heße, F.: GeoStat Framework: Create your geo-statistical model with Python!, EGU General Assembly 2019, Vienna, 7–12 April 2019, EGU2019-10159, 2019.

Müller, S., Schüler, L., Heße, F., Zech, A., and Attinger, S.: Python Framework for geostatistical simulation: Subsurface Applications, CMWR 2018, Saint-Malo, 3–7 June 2018, CMWR2018-262, 2018.

Müller, S., Zech, A., Heße, F., and Attinger, S.: Extending Theis’ solution to incorporate heterogeneity into pumping test analysis, EGU General Assembly 2017, Vienna, 23–28 April 2017, EGU2019-10159, 2017.

Contact

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

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

Assistance
Nora Pabst
Phone +49 341 6025-2367

Sindy Bleiholder
Phone +49 341 6025-1250

Susanne Gangloff
Phone +49 341 6025-2533

sekces@ufz.de

Permoserstraße 15 | 04318 Leipzig

News / Press

May 2024

New research published in Nature Communications by Hussian et al., (2024) emphasizes the game-changing potential of near-real-time and impact-based flood prediction. Their study demonstrates a 10-meter floodplain inundation hindcast of the 2021 European Summer Flood, showcasing a 17-hour lead time for better disaster preparedness. Impact-based early warnings can empower local authorities with crucial data on citizens at-risk for targeted emergency responses.

July 30, 2023

Hitze und Dürre - Interview with climate researcher Jakob Zscheischler
in Deutschlandfunk (only in German, 10:50 min) Link to interview

May 16, 2023

Start of ESA funded project 4DHydro

The overarching objective of 4DHydro is to foster collaborations between the Earth Observation (EO) water cycle community developing novel high-resolution EO data products, and the land surface and hydrological modelling community (LSM/HM) engaged in advancing hyperresolution modelling of the hydrological cycle at regional and continental scales. By involving several European institutions 4DHydro will assess and improve data sets of EO as well as synchronize EO products and LSM/HM models in order to improve predictions of the hydrological system. Overall, it will assist end-users and decisions-makers as well as the EU Destination Earth initiative. The project’s kick-off meeting will take place in Leipzig on 21st of June 2023.

Jan 30, 2023

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The following paper received the ASCE-EWRI 2023 Award for Best Case Study in the Journal of Hydrologic Engineering.

Mai, J. , B. A. Tolson, H. Shen, É. Gaborit, V. Fortin, N. Gasset, H. Awoye, T. A. Stadnyk, L. M. Fry, E. A. Bradley, F. Seglenieks, A. G. Temgoua, D. G. Princz, S. Gharari, A. Haghnegahdar, M. E. Elshamy, S. Razavi, M. Gauch, J. Lin, X. Ni, Y. Yuan, M. McLeod, N. B. Basu, R. Kumar, O. Rakovec, L. Samaniego, S. Attinger, N. K. Shrestha, P. Daggupati, T. Roy, S. Wi, T. Hunter, J. R. Craig, and A. Pietroniro (2021):
The Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E)
Journal of Hydrologic Engineering, 26(9), 05021020. Accepted Feb 16, 2021.

https://ascelibrary.org/doi/10.1061/%28ASCE%29HE.1943-5584.0002097

Dec 1, 2022

Award Poster Masooma Batool

Masooma Batool won the "Best student poster award" at the XXI International Nitrogen Workshop.
This conference, hosted by ETSIAAB, Universidad Politécnica de Madrid, brought together nearly 300 papers from authors from 40 countries in Madrid, Spain, October 24-28, 2022.
At the conference, Masooma and her colleagues presented long-term trends in soil nitrogen (N) surplus across Europe (1850-2019). Excess N provides information on the trends and spatial distribution of N surplus in soil systems across Europe, highlighting agricultural areas in Central Europe as nitrogen hotspots. These areas have undergone dramatic changes over the past 150 years. Importantly, we show that estimates of N surplus are subject to large uncertainties, requiring explicit consideration of these uncertainties when analyzing past trends in N surplus.

Nov 15, 2022

Earthrise - Mission Klima
How our research contributes to climate mitigation and adaptation is demonstrated in this WELT report.

Video at www.welt.de (only in German)

05:50': Hohes Holz research station
10:40': FORMIND in the Vislab
15:45': Fragmentation of forests
43:00': FORMIND and climate scenarios

Oct 12, 2022

Dr. Husain Najafi won the UFZ Young Scientist Award for Applied Research 2022. The award goes to him for his excellence and dedication in development of the operational drought forecasting system in Germany and investigation of 2021 summer flood predictability. Hydrological forecasting systems are the fundamental component of early warning systems - disaster risk reduction.

Older news are stored in the news archive.

New publications

Najafi, H., Shrestha, P.K., Rakovec, O. et al. High-resolution impact-based early warning system for riverine flooding. Nat Commun 15, 3726 (2024). https://doi.org/10.1038/s41467-024-48065-y
Henniger, H., Huth, A., Frank, K., & Bohn, F. J. (2023). Creating virtual forests around the globe and analysing their state space. Ecological Modelling, 483, 110404. https://doi.org/10.1016/j.ecolmodel.2023.110404

In this paper we present the "Forest Factory 2.0″ algorithm, which generates various virtual forest stands for different biomes on Earth. To demonstrate the potential of this approach, we analyse different forest-structure->ecosystem-function relationships across biomes.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx. High-resolution drought simulations and comparison to soil moisture observations in Germany. Hydrol. Earth Syst. Sci., 26, 5137–5161, 2022. https://doi.org/10.5194/hess-26-5137-2022

In this paper, we deliver an evaluation of the second generation operational German drought monitor ( https://www.ufz.de/duerremonitor ) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Mahnken, M., Cailleret, M., Collalti, A., Trotta, C., Biondo, C., D’Andrea, E., ... & Reyer, C. P. O. (2022). Accuracy, realism and general applicability of European forest models. Global Change Biology. DOI: 10.1111/gcb.16384
Pacheco-Labrador, J., Weber, U., Ma, X., Mahecha, M. D., Carvalhais, N., Wirth, C., Huth, A., Bohn, F. J., Kraemer, G., Heiden, U., FunDivEUROPE members, and Migliavacca, M.: EVALUATING THE POTENTIAL OF DESIS TO INFER PLANT TAXONOMICAL AND FUNCTIONAL DIVERSITIES IN EUROPEAN FORESTS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVI-1/W1-2021, 49–55, 2022. DOI: 10.5194/isprs-archives-XLVI-1-W1-2021-49-2022
Bevacqua, E., De Michele, C., Manning, C., Couasnon, A., Ribeiro, A.F.S., Ramos, A.M., Vignotto, E., Bastos, A., Blesić, S., Durante, F., Hillier, J., Oliveira, S.C., Pinto, J.G., Ragno, E., Rivoire, P., Saunders, K., van der Wiel, K., Wu, W., Zhang, T., Zscheischler, J. (2021): Guidelines for Studying Diverse Types of Compound Weather and Climate Events. Earth Future. 10.1029/2021EF002340
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

Sep 2, 2022

The collaborative project "Standardisiertes Monitoring von Wachstumsreaktionen wichtiger Waldbaumarten auf klimatische Extremereignisse" (MW³) with participation of the UFZ will develop a standardized monitoring system and protocol to record growth responses of important Central European forest tree species with a focus on climatic extremes. Future extreme events and their impact on forest carbon fluxes in Germany will be analyzed using smart models.