Anna-Lena Müller,
Guillermo Pardo,
Sebastian Friedrich,
Ralf Kiese,
Clemens Scheer
Berechtigungen: Open Access
Berechtigungen: Peer Reviewed
An LCA-based approach to integrate drained peatland emissions into the carbon footprint of dairy production: a case study from the pre-alpine region of Southern Germany (2026) The International Journal of Life Cycle Assessment 31 , S. 41.
DOI: 10.1007/s11367-026-02599-z
Sebastian Friedrich,
Gerner Alexander,
Michael Tarantik,
Gabriele Chiogna,
Markus Disse
Study regionRaised bog “Königsdorfer-Weidfilz”, Bavaria, GermanyStudy focusThis study investigates effects of different rewetting scenarios on water levels in raised bog peat under varying climatic conditions. We apply physically-based models with high temporal and spatial resolutions to compare seasonal and annual water levels. The results were evaluated to determine the significance of these water level changes. Based on these water levels, a qualitative assessment was conducted to determine the percentage of areas that are more or less likely contributing to climate change through greenhouse gas emissions.New hydrological insightsOur study demonstrates the potential for investigating the rewetting of small peatland areas using high-resolution three-dimensional hydrological models. By utilizing a partially rewetted raised bog as a case study, we successfully modeled areas with different drainage states. Our results indicate that the areas rewetted in the respective scenarios behave similarly to the areas that have already been rewetted on site. Our study highlights that additional rewetting measures have a positive impact on reducing climate-active areas with low water levels in raised bogs. When combined with natural vegetation succession and changes in soil properties resulting from the formation of a new functional acrotelm layer after rewetting, these changes further enhance the effectiveness of the rewetting process. Although the influence of relevant dry periods after rewetting remains significant, our results suggest that the resilience of the peatland increases.
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Baoli Zhu,
Sebastian Friedrich,
Zhe Wang,
András Táncsics,
Tillmann Lueders
Microorganisms are essential in the degradation of environmental pollutants. Aromatic hydrocarbons, e.g., benzene, toluene, ethylbenzene, and xylene (BTEX), are common aquifer contaminants, whose degradation in situ is often limited by the availability of electron acceptors. It is clear that different electron acceptors such as nitrate, iron, or sulfate support the activity of distinct degraders. However, this has not been demonstrated for the availability of nitrate vs. nitrite, both of which can be respired in reductive nitrogen cycling. Here via DNA-stable isotope probing, we report that nitrate and nitrite provided as electron acceptors in different concentrations and ratios not only modulated the microbial communities responsible for toluene degradation but also influenced how nitrate reduction proceeded. Zoogloeaceae members, mainly Azoarcus spp., were the key toluene degraders with nitrate-only, or both nitrate and nitrite as electron acceptors. In addition, a shift within Azoarcus degrader populations was observed on the amplicon sequence variant (ASV) level depending on electron acceptor ratios. In contrast, members of the Sphingomonadales were likely the most active toluene degraders when only nitrite was provided. Nitrate reduction did not proceed beyond nitrite in the nitrate-only treatment, while it continued when nitrite was initially also present in the microcosms. Likely, this was attributed to the fact that different microbial communities were stimulated and active in different microcosms. Together, these findings demonstrate that the availability of nitrate and nitrite can define degrader community selection and N-reduction outcomes. It also implies that nitrate usage efficiency in bioremediation could possibly be enhanced by an initial co-supply of nitrite, via modulating the active degrader communities.
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Konferenzbeiträge
Sebastian Friedrich
Kartierung der Bayerischen Moorgebiete: Hochauflösende Flurabstandsmodellierung mittels KI (2025) Posterpräsentation, Tag der Hydrologie in Augsburg, 19. - 21. März 2025 .
Organische Böden bilden seit Jahrtausenden einen fossilen Kohlenstoffspeicher.Atmosphäre, Biosphäre und Hydrosphäre interagieren im Ökosystem Moor undermöglichen die Speicherung von Kohlenstoff als Torf. Zur Gewinnung vonNutzflächen wurden insbesondere in Europa Moore drainiert. Durch dieseWasserstandsabsenkung gelangt Sauerstoff in den Torf, der mikrobielleAbbauprozesse verstärkt, die zu Treibhausgasemission führen. Als Teil des KliMoBay-Projektes (https://www.klimobay.de/) untersuchen wir den Wasserhaushalt im Moorund modellieren diesen mit dem Modell MIKESHE. Die Genauigkeit modellierterWasserstände steht dabei im Fokus, da flächige Treibhausgasemissionen mit Hilfevon Wasserstands-Treibhausgas-Modellen berechnet werden. Hierfür wurden dreiTestgebiete mit Messstationen für Moorwasserstand, Abfluss und Meteorologieausgestattet, welche in hoher zeitlicher Auflösung Daten sammeln. Die Messungenzeigen, dass Wasserstände im anthropogen überprägten Torf starken Schwankungenunterliegen. Dabei ergeben sich in Phasen mit eher ausgeglichener klimatischerWasserbilanz geringe Fluktuationen. Starkregenereignisse mit größerem zeitlichenAbstand führen hingegen zu starken kurzfristigen Wasserstandsschwankungen. ErsteResultate der Modellierung zeigen, dass es möglich ist, Dynamiken und Amplitudender Wasserstände im Moor gut wiederzugeben. Basierend auf den kalibriertenModellen soll im weiteren Verlauf die Auswirkung des Klimawandels auf denMoorwasserhalt untersucht werden.
Moore sind wichtige Kohlenstoffspeicher, doch Entwässerung führt zu CO2-Emissionen, die stark vom Flurabstand abhängen. Diese Arbeit entwickelt einen übertragbaren Ansatz zur hochaufgelösten Regionalisierung von Moorwasserständen in bayerischen Mooren durch Monitoring, physikalisch basierter Modellierung und maschinellen Lernens. Ziel ist eine flächendeckende, aktualisierbare Datengrundlage der Moorwasserstände.
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Sonstige Veröffentlichungen
Sebastian Friedrich,
Sarah Gutermuth,
Matthias Drösler
Gabriele Chiogna,
Markus Disse,
Margret Frischhut,
Thomas Machl,
Nadine Conze,
Martin Herr,
Jutta Kotzi,
Anna Kühnel,
Lena Reifschneider,
Julian Welte,
Gisbert Kuhn,
Annette Freibauer,
Verena Huber García,
Thomas Ramsauer,
Yueli Chen,
Verena Kuch,
Philip Marzahn,
Ralf Ludwig,
Matthias Drösler,
Janina Klatt,
Heta Meyer,
Clarisse Brehier,
Sebastian Friedrich,
Alexander Gerner,
Michael Tarantik
Kristian Förster,
Lena Endrich,
Sebastian Friedrich,
Marcel Goerke,
Tobias Koch,
Maria Herminia Pesci,
Richard Poncet,
Antonia Richter,
Vera Tigges,
Daniel Westerholt,
Jean-Luc Bertrand-Krajewski
Sebastian Friedrich,
Werner Wiedemann,
Sarah Gutermuth,
Florian Siegert,
Matthias Drösler
Berechtigungen: Open Access
Kartierung der Bayerischen Moorgebiete: Hochauflösende Flurabstandsmodellierung mittels KI (2025) Vortrag und Workshop auf dem 2. Workshop „Copernicus Netzwerkbüro Boden“, 19.02.2025, Hannover .
Kartierung der Bayerischen Moorgebiete: Hochauflösende Flurabstandsmodellierung mittels KI – Erweiterungspotential durch Satellitendaten und vielfältige Anwendungsperspektiven für Behörden, Ingenieurbüros und Forschung [Workshop Vortrag]. 2. Workshop „Copernicus Netzwerkbüro Boden“, Hannover.
Sebastian Friedrich,
Gerner Alexander,
Gabriele Chiogna,
Markus Disse
KliMoBay Project: A hydrological perspective (2024) Vortrag am PhD Seminar Summer 2023; Chair of Hydrology and River Basin Managment, München .
Sebastian Friedrich,
Gerner Alexander,
Gabriele Chiogna,
Markus Disse
Water table modeling in peatlands is often done on the large scale and, consequently, based on coarsely resolved models. The models commonly used in literature are often either not capable of modelling the full water cycle or they are not purely physically based. In particular in Bavaria there is a high number of small isolated peatlands with a dense drainage network, therefore a coarse model is not feasible. For rewetting success and climate impact analysis the fully integrated and largely physically based Mike She modelling software by DHI was used in the KliMoBay Project.The main goal was to achieve a temporally and spatially highly resolved model enabling water table investigations for different rewetting stages as well as associated vegetation and soil changes.For this purpose, the partially rewetted raised bog Königsdorfer Weidfilz in Bavaria was monitored and replicated in Mike She. Active and partially rewetted drainage ditches were implemented in the hydrodynamic model Mike Hydro and coupled with the Mike She model. After calibration and validation on twelve automatic water level gauges, scenario analyses were conducted. Compared with the climatic reference period (1961 – 1990), the dry year 2018 and the average year 2020 were modeled for three different scenarios: 1. current state, 2. drainage ditches deactivated, 3. vegetation and soil property succession after rewetting. The influence on the water table was analyzed based on a reference depth of - 0.15 m which is considered as an average threshold for climate impact. For this purpose, seasonal and annual mean water table maps were created, as well as standard deviation maps to portray high water table dynamics within the respective mean season. As the model results show, it is possible to investigate even small peatland areas for their rewetting potential. Furthermore, we could show the positive impact of rewetting measurements on reducing climate active areas with water levels below - 0.15 m in raised bogs. Vegetation and thus soil property changes in the model – which are assumed to occur after sufficient rewetting along with active acrotelm growth – increase the effect even more. Although, the impact of dry seasons is still significant, the resilience of the peatland increases.Using the example of the partially rewetted raised bog we were able to proof, that areas with different drainage states could be modeled. The areas rewetted in the respective model scenario react similar to the areas already rewetted in nature. Thus, we assume that the method is capable for planning stages. Consequently, it can offer a descriptive decision support tool. However, the process of model setup, calibration and validation is rather time consuming. Regarding fen peatland management, further models can be set up considering the capability of Mike Hydro to model controllable weirs. How to cite: Friedrich, S., Gerner, A., Gabriele, C., and Disse, M.: Scenario-based groundwater modeling of a raised bog with Mike She, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15608, https://doi.org/10.5194/egusphere-egu23-15608, 2023.
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Gerner Alexander,
Sebastian Friedrich,
Gabriele Chiogna,
Markus Disse
Maschinelles Lernen zur Entwicklung einer dynamischen Wasserstandskarte für alle bayerischen Moorstandorte (2023) Vortrag auf dem 46. Dresdner Wasserbaukolloquium 2023 „Wasserbau und Wasserwirtschaft im`Stresstest`“, 10.03.2023, Dresden .
Markus Disse,
Sebastian Friedrich,
Gerner Alexander,
Gabriele Chiogna
Monitoring und Modellierung von dynamischen Wasserständen in bayerischen Mooren (2022) Vortrag auf dem Symposium Moorschutz: Forschung und Praxis verbinden, 19.09.2022, Rosenheim .
Gerner Alexander,
Sebastian Friedrich,
Gabriele Chiogna,
Markus Disse
Prozessierung von Geofaktoren und Machine Learning für eine bayernweiten Karte der Moorwasserstände (2021) Vortrag auf der Münchner GI-Runde, 21.03.2021, München .
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