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Flood risk in a changing climate (CEDIM)

Aims: Floods in small and medium-sized river catchments have often been a focus of attention in the past. In contrast to large rivers like the Rhine, the Elbe or the Danube, discharge can increase very rapidly in such catchments; we are thus confronted with a high damage potential combined with almost no time for advance warning. Since the heavy precipitation events causing such floods are often spatially very limited, they are difficult to forecast; long-term provision is therefore an important task, which makes it necessary to identify vulnerable regions and to develop prevention measures. For that purpose, one needs to know how the frequency and the intensity of floods will develop in the future, especially in the near future, i.e. the next few decades. Besides providing such prognoses, an important goal of this project was also to quantify their uncertainty. Method: These questions were studied by a team of meteorologists and hydrologists from KIT and GFZ. They simulated the natural chain 'large-scale weather - regional precipitation - catchment discharge' by a model chain 'global climate model (GCM) - regional climate model (RCM) - hydrological model (HM)'. As a novel feature, we performed so-called ensemble simulations in order to estimate the range of possible results, i.e. the uncertainty: we used two GCMs with different realizations, two RCMs and three HMs. The ensemble method, which is quite standard in physics, engineering and recently also in weather forecasting has hitherto rarely been used in regional climate modeling due to the very high computational demands. In our study, the demand was even higher due to the high spatial resolution (7 km by 7 km) we used; presently, regional studies use considerably larger grid boxes of about 100 km2. However, our study shows that a high resolution is necessary for a realistic simulation of the small-scale rainfall patterns and intensities. This combination of high resolution and an ensemble using results from global, regional and hydrological models is unique. Results: By way of example, we considered the low-mountain range rivers Mulde and Ruhr and the more alpine Ammer river in this study, all of which had severe flood events in the past. Our study confirms that heavy precipitation events will occur more frequently in the future. Does this also entail an increased flood risk? Our results indicate that in any case, the risk will not decrease. However, each catchment reacts differently, and different models may produce different precipitation and runoff regimes, emphasizing the need of ensemble studies. A statistically significant increase of floods is expected for the river Ruhr in winter and in summer. For the river Mulde, we observe a slight increase of floods during summer and autumn, and for the river Ammer a slight decrease in summer and a slight increase in winter.

Langjährige Niederschlagsverteilung 1961-1990 (Umweltatlas)

Langjährige Niederschlagsverteilung (1961-1990) in Berlin und dem näheren Umland (Gesamtjahr, Sommer, Winter), Bearbeitungsstand Juli 1994.

PARAFAC components and fluorescent dissolved organic matter (FDOM) indices on organic matter transformation processes in the sea-surface microlayer and the underlying water during a mesocosm phytoplankton bloom in 2023

The effects of a phytoplankton bloom and photobleaching on colored dissolved organic matter (CDOM) in the sea-surface microlayer (SML) and the underlying water (ULW) were studied in a month-long mesocosm study, in May and June of 2023, at the Institute for Chemistry and Biology of the Marine Environment (ICBM) in Wilhelmshaven, Germany. The mesocosm study was conducted by the DFG research group BASS (Biogeochemical processes and Air–sea exchange in the Sea-Surface microlayer, Bibi et al., 2025) in the Sea Surface Facility (SURF) of the ICBM. The facility contains an 8 m × 1.5 m × 0.8 m large outdoor basin with a retractable roof, which was closed at night and during rain events. The basin was filled with North Sea water from the adjacent Jade Bay. Homogeneity of the ULW in the basin was achieved by constant mixing of the water column. The daily SML and ULW samples were collected alternating in the morning, about 1 h after sunrise, and in the afternoon, about 10 h after sunrise. The alternation of sampling times intended to capture a potential effect of sun-exposure duration on DOM transformations and elucidated the day and night variability of the layers. The SML was collected via glass plate sampling (Cunliffe and Wurl, 2014). The ULW was sampled via a submerged tube and a connected syringe suction system in 0.4 m depth. The removed sample volume was refilled with Jade Bay water every day. SML and ULW samples were filtered through pre-flushed 0.7 µm Whatman GF/F and 0.2 nucleopore filters into clear 40 ml SUPELCO bottles. These bottles were acid-washed twice and combusted at 500 °C for 5 h. The samples were stored dark and at 4 °C and measured within a few days of the study. FDOM was measured using a Aqualog fluorescence spectrometer (Horiba Scientific, Japan) with 10 seconds integration time and high gain of the CCD (charge-coupled device) sensor within an excitation range from 240 to 500 nm, and an emission range from 209.15 to 618.53 nm. The Aqualog measures fluorescence as well as absorption. The resulting data includes an excitation-emission-matrix (EEM) of the blank (MilliQ Starna cuvette), an EEM of the sample, and the absorption values of the sample. The raw exported Aqualog data was corrected for errors and lamp shifts. The corrected EEM data is then decomposed by PARAFAC (Murphy et al., 2013) for its underlying fluorophore components. Before running the PARAFAC routine, the corrected data needed to undergo a correction process by subtracting the blank from the sample EEM and canceling the influences of the inner-filter effect (IFE, Parker & Rees, 1962; Kothawala et al., 2013). The fluorescence intensity of the IFE-corrected EEM is calibrated by using the Raman scatter peak of water (Lawaetz & Stedmon, 2009). For PARAFAC the corrected data was processed using the drEEM and NWAY toolbox (version 0.6.5; Murphy et al., 2013) in MATLAB (R2020b). A 4-component model was validated with the validation style S4C6T3 for the split half analysis with nonnegativity constraints and 1-8e as the convergence criteria with 50 random starts and a maximum number of 2500 iterations. The resulting final model had a core consistency of 88.11 and the explained percentage was 99.55%. Furthermore, four fluorescence indices were calculated from the corrected EEM data (HIX – Humification index, Zsolnay et al., 1999; BIX – Biological index, Huguet et al., 2009; REPIX – Recently produced index, Parlanti et al., 2000, Drozdowska et al., 2015; ARIX, Murphy, 2025).

Global Precipitation Analysis Products of the GPCC

The Global Precipitation Climatology Centre (GPCC) has been established in 1989 on request of the World Meteorological Organization (WMO). It is operated by Deutscher Wetterdienst (DWD, National Meteorological Service of Germany) as a German contribution to the World Climate Research Programme (WCRP). Mandate of the GPCC is the global analysis of precipitation on earth’s land surface based on in situ rain gauge data. These gridded analyses provide long-term means, monthly and daily totals, quantiles and a drought index.

Ecosystem functions of rare arable plants - field experiment: Carabidae data

Partly taken from the materials and methods of https://doi.org/10.1016/j.baae.2022.12.003: To compare the activity densities of ground-dwelling predators between treatments with and without RAPs, carabids were sampled using pitfall traps, which were set up after each round of aphid counting (one per plot, twice per year; Brown & Matthews, 2016). The traps (with a volume of 400 ml and a width of 90 mm) were filled with a mixture of water and ethylene glycol (1:1; 120 ml) and dug at ground level into the middle of each plot. The traps were covered with a plastic roof and a metal grid (15 × 15 mm grid size) to avoid overflowing during rain and accidental rodent catches (Császár et al., 2018). The traps were activated for 7 days. Subsequently, all arthropods were transferred into 70% ethanol. Carabids were identified to species according to Hůrka (1996). Carabid feeding behavior was classified according to Homburg et al. (2014). To simplify the dataset, carabid feeding behavior was classified as predominantly granivorous (species mainly feed on seeds and fruits) or as carnivorous/omnivorous, because carnivorous and omnivorous species are potentially feeding on aphids and other non-plant material.

Ecosystem functions of rare arable plants - field study: Carabidae data

Partly taken from the materials and methods of https://doi.org/10.1016/j.baae.2022.12.003: To compare the activity densities of ground-dwelling predators between treatments with and without RAPs, carabids were sampled using pitfall traps, which were set up after each round of aphid counting (one per plot, twice per year; Brown & Matthews, 2016). The traps (with a volume of 400 ml and a width of 90 mm) were filled with a mixture of water and ethylene glycol (1:1; 120 ml) and dug at ground level into the middle of each plot. The traps were covered with a plastic roof and a metal grid (15 × 15 mm grid size) to avoid overflowing during rain and accidental rodent catches (Császár et al., 2018). The traps were activated for 7 days. Subsequently, all arthropods were transferred into 70% ethanol. Carabids were identified to species according to Hůrka (1996). Carabid feeding behavior was classified according to Homburg et al. (2014). To simplify the dataset, carabid feeding behavior was classified as predominantly granivorous (species mainly feed on seeds and fruits) or as carnivorous/omnivorous, because carnivorous and omnivorous species are potentially feeding on aphids and other non-plant material.

Stickstoffempfindliche Lebensraumtypen NRW (LINFOS)

Stickstoffempfindliche Lebensraumtypen sind Lebensraumtypen / Biotoptypen, welche sensibel auf atmosphärische Stickstoffeinträge reagieren. Die Daten stammen aus der Landschaftsinformationssammlung (LINFOS) des Landesamtes für Natur, Umwelt und Klima Nordrhein-Westfalen (LANUK) und werden direkt über den LINFOS-WFS bezogen: https://www.wfs.nrw.de/umwelt/linfos Die WFS-Layer „stickstoffempfindliche_lrt_point“, „stickstoffempfindliche_lrt_polyline“ und „stickstoffempfindliche_lrt_polygon“ werden dabei zu einem Polygonlayer zusammengeführt; Punkt- und Linienobjekte werden dabei mit einem 5-m-Puffer in Flächen umgewandelt. Ab einem Maßstab von 1:25000 werden die Daten geometrisch leicht vereinfacht dargestellt.

Starkregenrisikomanagement (SRRM) - Wasserhöhe extrem Kreis Viersen

Angabe der Wasserhöhe in m, extremes Szenario, >>> 100-jährig, N20000 = 90,0 mm/h

Speicherdimensionierung von Regenwassersammelanlagen

Auf der Basis eines Simulationsmodells zur Untersuchung der optimalen Speichergröße für Nichttrinkwassernutzung wurden zahlreiche Bauvorhaben mit einem hohen Bedarf an Trinkwasser für untergeordnete Zwecke in den letzten Jahren mit Regenwassersammelanlagen ausgestattet. Im Rahmen des Projektes wurden Gebäude mit Nichttrinkwasseranlagen untersucht und die Ansätze der Simulationsrechnung mit den tatsächlichen Nutzungsbedingungen und Bedarfsdeckungsraten verglichen. Als Ergebnis des Projektes werden für zukünftige Planungen Empfehlungen bzw. Berechnungsmethoden vorgeschlagen.

Aerosol-Wolken-Niederschlags-Wechselwirkungen für regionale Emissionen

Aerosol-Wolken-Wechselwirkungen stellen einen der wesentlichen Unsicherheitsfaktoren bei Verständnis und Quantifizierung der geographischen Verteilung von Wolken- und Niederschlagseigenschaften, aber auch des Strahlungsantriebs des globalen Klimawandels dar. Die grundlegende Idee des Projekts ist es, regional unterschiedliche Trends in anthropogenenen Emissionen von Aerosolen zu nutzen, um deren Einfluss auf Trends in Wolken-, Niederschlags- und Strahlungsgrößen zu bestimmen. Hierzu sollen verschiedene Szenarien in Multi-Klimamodell-Ensembles ('historische' Simulationen mit allen Strahlungsantrieben und 'Aerosol'-Simulationen mit allen Antrieben außer anthropogenem Aerosol) analysiert werden und mit Beobachtungsdaten verglichen werden. Konkret werden vier Fragen untersucht:(i) Welche Beziehung besteht zwischen regionalen Trends in Aerosolemissionen und Wolken-Strahlungs-Effekten? - Diese Studien analysieren Simulationen aus dem Multi-Modell-Ensemble.(ii) Wie erfolgreich reproduzieren die Modelle beobachtete Trends? Hier werden die Klimamodelle mit Beobachtungsdaten verglichen.(iii) Welchen Einfluss haben Emissionstrends für Aerosole und resultierende Strahlungsantriebe auf die atmosphärische Zirkulation? Simulationen mit dem Aerosol-Klima-Modell ECHAM6-HAM2 sollen für drei Zeitscheiben durchgeführt und analysiert werden.(iv) Welche Rolle spielen Emissionstrends für Änderungen in Extremniederschlägen in Südost-Asien? - Mit speziellen Simulationen sollen die verschiedenen Hypothesen getestet werden.

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