TY - JOUR A1 - Speckhann, Gustavo Andrei A1 - Kreibich, Heidi A1 - Merz, Bruno T1 - Inventory of dams in Germany JF - Earth system science data : the data publishing journal N2 - Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists, and policymakers for various purposes, such as seasonal forecasting of water availability or flood mitigation. However, detailed information on dams on the national level for Germany is so far not freely available. We present the most comprehensive open-access dam inventory for Germany (DIG) to date. We have collected and combined information on dams using books, state agency reports, engineering reports, and internet pages. We have applied a priority rule that ensures the highest level of reliability for the dam information. Our dam inventory comprises 530 dams in Germany with information on name, location, river, start year of construction and operation, crest length, dam height, lake area, lake volume, purpose, dam structure, and building characteristics. We have used a global, satellite-based water surface raster to evaluate the location of the dams. A significant proportion (63 %) of dams were built between 1950-2013. Our inventory shows that dams in Germany are mostly single-purpose (52 %), 53% can be used for flood control, and 25% are involved in energy production. The inventory is freely available through GFZ (GeoForschungsZentrum) Data Services (https://doi.org/10.5880/GFZ.4.4.2020.005) Y1 - 2021 U6 - https://doi.org/10.5194/essd-13-731-2021 SN - 1866-3508 SN - 1866-3516 VL - 13 IS - 2 SP - 731 EP - 740 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Bürger, Gerd A1 - Heistermann, Maik T1 - Shallow and deep learning of extreme rainfall events from convective atmospheres JF - Natural hazards and earth system sciences : NHESS N2 - Our subject is a new catalogue of radar-based heavy rainfall events (CatRaRE) over Germany and how it relates to the concurrent atmospheric circulation. We classify daily ERA5 fields of convective indices according to CatRaRE, using an array of 13 statistical methods, consisting of 4 conventional (“shallow”) and 9 more recent deep machine learning (DL) algorithms; the classifiers are then applied to corresponding fields of simulated present and future atmospheres from the Coordinated Regional Climate Downscaling Experiment (CORDEX) project. The inherent uncertainty of the DL results from the stochastic nature of their optimization is addressed by employing an ensemble approach using 20 runs for each network. The shallow random forest method performs best with an equitable threat score (ETS) around 0.52, followed by the DL networks ALL-CNN and ResNet with an ETS near 0.48. Their success can be understood as a result of conceptual simplicity and parametric parsimony, which obviously best fits the relatively simple classification task. It is found that, on summer days, CatRaRE convective atmospheres over Germany occur with a probability of about 0.5. This probability is projected to increase, regardless of method, both in ERA5-reanalyzed and CORDEX-simulated atmospheres: for the historical period we find a centennial increase of about 0.2 and for the future period one of slightly below 0.1. Y1 - 2023 U6 - https://doi.org/10.5194/nhess-23-3065-2023 SN - 1561-8633 SN - 1684-9981 VL - 23 IS - 9 SP - 3065 EP - 3077 PB - European Geophysical Society CY - Katlenburg-Lindau ER - TY - JOUR A1 - Metin, Ayse Duha A1 - Nguyen Viet Dung, A1 - Schröter, Kai A1 - Guse, Björn A1 - Apel, Heiko A1 - Kreibich, Heidi A1 - Vorogushyn, Sergiy A1 - Merz, Bruno T1 - How do changes along the risk chain affect flood risk? JF - Natural hazards and earth system sciences N2 - Flood risk is impacted by a range of physical and socio-economic processes. Hence, the quantification of flood risk ideally considers the complete flood risk chain, from atmospheric processes through catchment and river system processes to damage mechanisms in the affected areas. Although it is generally accepted that a multitude of changes along the risk chain can occur and impact flood risk, there is a lack of knowledge of how and to what extent changes in influencing factors propagate through the chain and finally affect flood risk. To fill this gap, we present a comprehensive sensitivity analysis which considers changes in all risk components, i.e. changes in climate, catchment, river system, land use, assets, and vulnerability. The application of this framework to the mesoscale Mulde catchment in Germany shows that flood risk can vary dramatically as a consequence of plausible change scenarios. It further reveals that components that have not received much attention, such as changes in dike systems or in vulnerability, may outweigh changes in often investigated components, such as climate. Although the specific results are conditional on the case study area and the selected assumptions, they emphasize the need for a broader consideration of potential drivers of change in a comprehensive way. Hence, our approach contributes to a better understanding of how the different risk components influence the overall flood risk. Y1 - 2018 U6 - https://doi.org/10.5194/nhess-18-3089-2018 SN - 1561-8633 SN - 1684-9981 VL - 18 IS - 11 SP - 3089 EP - 3108 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Metin, Ayse Duha A1 - Dung, Nguyen Viet A1 - Schröter, Kai A1 - Vorogushyn, Sergiy A1 - Guse, Björn A1 - Kreibich, Heidi A1 - Merz, Bruno T1 - The role of spatial dependence for large-scale flood risk estimation JF - Natural hazards and earth system sciences N2 - Flood risk assessments are typically based on scenarios which assume homogeneous return periods of flood peaks throughout the catchment. This assumption is unrealistic for real flood events and may bias risk estimates for specific return periods. We investigate how three assumptions about the spatial dependence affect risk estimates: (i) spatially homogeneous scenarios (complete dependence), (ii) spatially heterogeneous scenarios (modelled dependence) and (iii) spatially heterogeneous but uncorrelated scenarios (complete independence). To this end, the model chain RFM (regional flood model) is applied to the Elbe catchment in Germany, accounting for the spatio-temporal dynamics of all flood generation processes, from the rainfall through catchment and river system processes to damage mechanisms. Different assumptions about the spatial dependence do not influence the expected annual damage (EAD); however, they bias the risk curve, i.e. the cumulative distribution function of damage. The widespread assumption of complete dependence strongly overestimates flood damage of the order of 100% for return periods larger than approximately 200 years. On the other hand, for small and medium floods with return periods smaller than approximately 50 years, damage is underestimated. The overestimation aggravates when risk is estimated for larger areas. This study demonstrates the importance of representing the spatial dependence of flood peaks and damage for risk assessments. Y1 - 2020 U6 - https://doi.org/10.5194/nhess-20-967-2020 SN - 1561-8633 SN - 1684-9981 VL - 20 IS - 4 SP - 967 EP - 979 PB - European Geosciences Union (EGU) ; Copernicus CY - Göttingen ER - TY - JOUR A1 - Heistermann, Maik A1 - Francke, Till A1 - Scheiffele, Lena A1 - Petrova, Katya Dimitrova A1 - Budach, Christian A1 - Schrön, Martin A1 - Trost, Benjamin A1 - Rasche, Daniel A1 - Güntner, Andreas A1 - Doepper, Veronika A1 - Förster, Michael A1 - Köhli, Markus A1 - Angermann, Lisa A1 - Antonoglou, Nikolaos A1 - Zude, Manuela A1 - Oswald, Sascha T1 - Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany JF - Earth system science data : ESSD N2 - Cosmic-ray neutron sensing (CRNS) allows for the estimation of root-zone soil water content (SWC) at the scale of several hectares. In this paper, we present the data recorded by a dense CRNS network operated from 2019 to 2022 at an agricultural research site in Marquardt, Germany - the first multi-year CRNS cluster. Consisting, at its core, of eight permanently installed CRNS sensors, the cluster was supplemented by a wealth of complementary measurements: data from seven additional temporary CRNS sensors, partly co-located with the permanent ones; 27 SWC profiles (mostly permanent); two groundwater observation wells; meteorological records; and Global Navigation Satellite System reflectometry (GNSS-R). Complementary to these continuous measurements, numerous campaign-based activities provided data by mobile CRNS roving, hyperspectral im-agery via UASs, intensive manual sampling of soil properties (SWC, bulk density, organic matter, texture, soil hydraulic properties), and observations of biomass and snow (cover, depth, and density). The unique temporal coverage of 3 years entails a broad spectrum of hydro-meteorological conditions, including exceptional drought periods and extreme rainfall but also episodes of snow coverage, as well as a dedicated irrigation experiment. Apart from serving to advance CRNS-related retrieval methods, this data set is expected to be useful for vari-ous disciplines, for example, soil and groundwater hydrology, agriculture, or remote sensing. Hence, we show exemplary features of the data set in order to highlight the potential for such subsequent studies. The data are available at doi.org/10.23728/b2share.551095325d74431881185fba1eb09c95 (Heistermann et al., 2022b). Y1 - 2023 U6 - https://doi.org/10.5194/essd-15-3243-2023 SN - 1866-3508 SN - 1866-3516 VL - 15 IS - 7 SP - 3243 EP - 3262 PB - Copernics Publications CY - Katlenburg-Lindau ER - TY - JOUR A1 - Billing, Maik A1 - Thonicke, Kirsten A1 - Sakschewski, Boris A1 - von Bloh, Werner A1 - Walz, Ariane T1 - Future tree survival in European forests depends on understorey tree diversity JF - Scientific reports N2 - Climate change heavily threatens forest ecosystems worldwide and there is urgent need to understand what controls tree survival and forests stability. There is evidence that biodiversity can enhance ecosystem stability (Loreau and de Mazancourt in Ecol Lett 16:106-115, 2013; McCann in Nature 405:228-233, 2000), however it remains largely unclear whether this also holds for climate change and what aspects of biodiversity might be most important. Here we apply machine learning to outputs of a flexible-trait Dynamic Global Vegetation Model to unravel the effects of enhanced functional tree trait diversity and its sub-components on climate-change resistance of temperate forests (http://www.pik-potsdam.de/similar to billing/video/Forest_Resistance_LPJmLFIT.mp4). We find that functional tree trait diversity enhances forest resistance. We explain this with 1. stronger complementarity effects (similar to 25% importance) especially improving the survival of trees in the understorey of up to +16.8% (+/- 1.6%) and 2. environmental and competitive filtering of trees better adapted to future climate (40-87% importance). We conclude that forests containing functionally diverse trees better resist and adapt to future conditions. In this context, we especially highlight the role of functionally diverse understorey trees as they provide the fundament for better survival of young trees and filtering of resistant tree individuals in the future. Y1 - 2022 U6 - https://doi.org/10.1038/s41598-022-25319-7 SN - 2045-2322 VL - 12 IS - 1 PB - Springer Nature CY - Berlin ER - TY - JOUR A1 - Apel, Heiko A1 - Vorogushyn, Sergiy A1 - Merz, Bruno T1 - Brief communication: impact forecasting could substantially improve the emergency management of deadly floods: case study July 2021 floods in Germany JF - Natural hazards and earth system sciences N2 - Floods affect more people than any other natural hazard; thus flood warning and disaster management are of utmost importance. However, the operational hydrological forecasts do not provide information about affected areas and impact but only discharge and water levels at gauges. We show that a simple hydrodynamic model operating with readily available data is able to provide highly localized information on the expected flood extent and impacts, with simulation times enabling operational flood warning. We demonstrate that such an impact forecast would have indicated the deadly potential of the 2021 flood in western Germany with sufficient lead time. Y1 - 2022 U6 - https://doi.org/10.5194/nhess-22-3005-2022 SN - 1561-8633 SN - 1684-9981 VL - 22 IS - 9 SP - 3005 EP - 3014 PB - European Geophysical Society CY - Katlenburg-Lindau ER - TY - JOUR A1 - Codeço, Marta S. A1 - Weis, Philipp A1 - Andersen, Christine T1 - Numerical modeling of structurally controlled ore formation in magmatic-hydrothermal systems JF - Geochemistry, geophysics, geosystems : G 3 ; an electronic journal of the earth sciences N2 - Faults and fractures can be permeable pathways for focused fluid flow in structurally controlled ore-forming hydrothermal systems. However, quantifying their role in fluid flow on the scale of several kilometers with numerical models typically requires high-resolution meshes. This study introduces a modified numerical representation of m-scale fault zones using lower-dimensional elements (here, one-dimensional [1D] elements in a 2D domain) to resolve structurally controlled fluid flow with coarser mesh resolutions and apply the method to magmatic-hydrothermal ore-forming systems. We modeled horizontal and vertical structure-controlled magmatic-hydrothermal deposits to understand the role of permeability and structure connectivity on ore deposition. The simulation results of vertically extended porphyry copper systems show that ore deposition can occur along permeable vertical structures where ascending, overpressured magmatic fluids are cooled by downflowing ambient fluids. Structure permeability and fault location control the distribution of ore grades. In highly permeable structures, the mineralization can span up to 3 km vertically, resulting in heat-pipe mechanisms that promote the ascent of a magmatic vapor phase to an overlying structurally controlled epithermal system. Simulations for the formation of subhorizontal vein-type deposits suggest that the major control on fluid flow and metal deposition along horizontal structures is the absence of vertical structures above the injection location but their presence at greater distances. Using a dynamic permeability model mimicking crack-seal mechanisms within the structures leads to a pulsating behavior of fracture-controlled hydrothermal systems and prevents the inflow of ambient fluids under overpressured conditions. KW - magmatic-hydrothermal systems KW - ore deposits KW - fluid flow KW - numerical simulations KW - faults and fractures Y1 - 2022 U6 - https://doi.org/10.1029/2021GC010302 SN - 1525-2027 VL - 23 IS - 8 PB - American Geophysical Union CY - Washington, DC ER -