Sliding of Ice Past an Obstacle at Engabreen, Norway

At Engabreen, Norway, an instrumented panel containing a decimetric obstacle was mounted flush With the bed surface beneath 210 m of ice. Simultaneous measurements of normal and shear stresses, ice velocity and temperature were obtained as dirty basal ice flowed past the obstacle. Our measurements were broadly consistent with ice thickness, flow conditions and bedrock topography near the site of the experiment. Ice speed 0.45 m above the bed was about 130 mm d(-1), much less than the surface velocity of 800 mm d(-1) Average normal stress on the panel was 1.0-1.6 MPa, smaller than the expected ice overburden pressure. Normal stress was larger and temperature was lower on the stoss side than on the lee side, in accord with flow dynamics and equilibrium thermodynamics. Annual differences in normal stresses were correlated with changes in sliding speed and ice-flow direction. These temporal variations may have been caused by changes in ice rheology associated with changes in sediment concentration, water content or both. Temperature and normal stress were generally correlated, except when clasts presumably collided with the panel. Temperature gradients in the obstacle indicated that regelation was negligible, consistent with the obstacle size. Melt rate was about 10% of the sliding speed. Despite high sliding speed, no significant ice/bed separation was observed in the lee of the obstacle. Frictional forces between sediment particles in the ice and the panel, estimated from Hallet's (1981) model, indicated that friction accounted for about 5% of the measured bed-parallel force. This value is uncertain, as friction theories are largely untested. Some of these findings agree with sliding theories, others do not.

Retrospective analysis of a nonforecasted rain-on-snow flood in the Alps – a matter of model limitations or unpredictable nature?

A rain-on-snow flood occurred in the Bernese Alps, Switzerland, on 10 October 2011, and caused significant damage. As the flood peak was unpredicted by the flood forecast system, questions were raised concerning the causes and the predictability of the event. Here, we aimed to reconstruct the anatomy of this rain-on-snow flood in the Lötschen Valley (160 km2) by analyzing meteorological data from the synoptic to the local scale and by reproducing the flood peak with the hydrological model WaSiM-ETH (Water Flow and Balance Simulation Model). This in order to gain process understanding and to evaluate the predictability. The atmospheric drivers of this rain-on-snow flood were (i) sustained snowfall followed by (ii) the passage of an atmospheric river bringing warm and moist air towards the Alps. As a result, intensive rainfall (average of 100 mm day-1) was accompanied by a temperature increase that shifted the 0° line from 1500 to 3200 m a.s.l. (meters above sea level) in 24 h with a maximum increase of 9 K in 9 h. The south-facing slope of the valley received significantly more precipitation than the north-facing slope, leading to flooding only in tributaries along the south-facing slope. We hypothesized that the reason for this very local rainfall distribution was a cavity circulation combined with a seeder-feeder-cloud system enhancing local rainfall and snowmelt along the south-facing slope. By applying and considerably recalibrating the standard hydrological model setup, we proved that both latent and sensible heat fluxes were needed to reconstruct the snow cover dynamic, and that locally high-precipitation sums (160 mm in 12 h) were required to produce the estimated flood peak. However, to reproduce the rapid runoff responses during the event, we conceptually represent likely lateral flow dynamics within the snow cover causing the model to react "oversensitively" to meltwater. Driving the optimized model with COSMO (Consortium for Small-scale Modeling)-2 forecast data, we still failed to simulate the flood because COSMO-2 forecast data underestimated both the local precipitation peak and the temperature increase. Thus we conclude that this rain-on-snow flood was, in general, predictable, but requires a special hydrological model setup and extensive and locally precise meteorological input data. Although, this data quality may not be achieved with forecast data, an additional model with a specific rain-on-snow configuration can provide useful information when rain-on-snow events are likely to occur.

Anisotropy of magnetic susceptibility in natural olivine single crystals

Mantle flow dynamics can cause preferential alignment of olivine crystals that results in anisotropy of physical properties. To interpret anisotropy in mantle rocks, it is necessary to understand the anisotropy of olivine single crystals. We determined anisotropy of magnetic susceptibility (AMS) for natural olivine crystals. High-field AMS allows for the isolation of the anisotropy due to olivine alone. The orientations of the principal susceptibility axes are related to the olivine’s crystallographic structure as soon as it contains >3 wt % FeO. The maximum susceptibility is parallel to the c axis both at room temperature (RT) and at 77 K. The orientation of the minimum axis at RT depends on iron content; it is generally parallel to the a axis in crystals with 3–5 wt % FeO, and along b in samples with 6–10 wt % FeO. The AMS ellipsoid is prolate and the standard deviatoric susceptibility, k0, is on the order of 8*10210 m3/kg for the samples with <1wt % FeO, and ranges from 3.1*1029 m3/kg to 5.7*1029 m3/kg for samples with 3–10 wt % FeO. At 77 K, the minimum susceptibility is along b, independent of iron content. The shape of the AMS ellipsoid is prolate for samples with <5 wt % FeO, but can be prolate or oblate for higher iron content. The degree of anisotropy increases at 77 K with p0 7757.160.5. The results from this study will allow AMS fabrics to be used as a proxy for olivine texture in ultramafic rocks with high olivine content.

Regulación de la hidratación y la turgencia foliares por mecanismos evitadores del estrés, y resistencia a déficit hídrico en vid

El transporte del agua en las plantas es impulsado por diferencias de energía libre entre el suelo y la atmósfera, y está regulado por mecanismos biológicos evitadores, como el cierre estomático. La hidratación y la turgencia foliares resultan del equilibrio entre ΨL del apoplasto, el potencial osmótico del simplasto y la elasticidad de los tejidos. Sobre esta base se conjeturó que las interacciones de los mecanismos evitadores del estrés hídrico de la planta tienen un rol clave en la definición de su resistencia a déficit hídrico. Para probar esta hipótesis se construyó un modelo mecanístico basado en las leyes del flujo de savia de Van de Honert, de difusión de Fick, de elasticidad de Hooke, la ecuación de Gardner para el flujo del agua en la rizósfera y el modelo de conductancia estomática (gs) de Buckley. Mediante el modelo se demostró teóricamente que la hidratación y la turgencia foliares dependen de la oferta de agua edáfica (representada por el potencial hídrico del suelo) y de la demanda evaporativa de la atmósfera (representada por la radiación absorbida, la temperatura del aire, la velocidad del viento y el déficit de presión de vapor de la atmósfera). También que los mecanismos evitadores del estrés hídrico -i.e., conductancia hidráulica de la planta, conductancia estomática, elasticidad del tejido y potencial osmótico a turgencia máxima- son todos necesarios para determinar la hidratación y la turgencia foliares. El modelo también demostró que la conductancia hidráulica suelo-hoja (kL) depende de la fracción de agua edáfica transpirable (FTSW) con un patrón de decaimiento sigmoide, a medida que el suelo se seca. Esto implica que las variables que dependen en parte de kL (i.e., gs, transpiración, fotosíntesis y superficie foliar) también dependen de FTSW con el mismo patrón. El modelo se probó experimentalmente a distintos niveles de humedad edáfica (desde déficit hídrico nulo, hasta severo) en cinco variedades de vid y mostró un poder predictivo superior al 90%. En todas las variedades las gs se asociaron linealmente con las kL observadas, al considerar todas las situaciones de déficit hídrico en conjunto, si bien la pendiente de estas relaciones fueron distintas en cada variedad. La contrastación experimental mostró que, en una escala de tiempo de varios meses, las variedades más evitadoras -i.e., Grenache y Cereza- mantuvieron mayor kL, ajuste osmótico y rigidez de los tejidos y una menor pendiente de la relación de gs vs. kL, que las variedades menos evitadoras -i.e., Malbec y Syrah-. La menor pendiente de la relación entre gs y kL, en las variedades más evitadoras, estuvo asociada a una mayor cantidad de estomas, en relación con la cantidad de células epidérmicas. Los variedades más evitadoras bajo déficit hídrico moderado -i.e., con una fracción de agua edáfica transpirable entre 0,6 y 0,4- tuvieron mayor superficie foliar y produjeron más biomasa, favoreciendo raíces profundas y densas, y ahorrando agua. Chardonnay mantuvo una alta hidratación y turgencia a expensas de un alto gasto de agua debido a que privilegiaba una alta kL por sobre el ajuste estomático, por lo que no podría considerarse en forma estricta como muy evitadora.

Measured ice surface velocities on the King George Island ice cap with DGPS

King George Island is located at the northern tip of the Antarctic Peninsula, which is influenced by maritime climate conditions. The observed mean annual air temperature at sea level is -2.4°C. Thus, the ice cap is regarded as sensitive to changing climatic conditions. Ground-penetrating radar surveys indicate a partly temperate ice cap with an extended water layer at the firn/ice transition of the up to 700 m high ice cap. Measured firn temperatures are close to 0°C at the higher elevations, and they differ considerably from the measured mean annual air temperature. The aim of this paper is to present ice-flow dynamics by means of observations and simulations of the flow velocities. During several field campaigns from 1997/98 to 2008/09, ice surface velocities were derived with repeated differential GPS measurements. Ice velocities vary from 0.7 m/a at the dome to 112.1 m/a along steep slopes. For the western part of the ice cap a three-dimensional diagnostic full-Stokes model was applied to calculate ice flow. Parameters of the numerical model were identified with respect to measured ice surface velocities. The simulations indicate cold ice at higher elevations, while temperate ice at lower elevations is consistent with the observations.

Composition of particulate matter in the neutrally buoyant plumes of the TAG and Broken Spur Hydrothermal Fields

This publication considers data on aquatic anomalies (hydrothermal plumes) in the areas of 26° and 29°N of the Mid-Atlantic Ridge (MAR). Mass of hydrothermal iron supply and intensity of iron sedimentation onto the bottom were estimated by means of sediment traps. It was found that the plume of the TAG hydrothermal vent 6 km**3 in volume contained about 67 tons of particulate Fe; the plume of the Broken Spur field (up to 8.24 km**3 in volume) contained 23.5 tons of particulate Fe or less because of its lower concentration. Data on sediment matter fluxes showed that 0.3-0.5% of hydrothermal iron was precipitated immediately from the neutrally buoyant plume onto the bottom; the bulk of iron was dissipated into environment. From dimensions of the plumes, flow dynamics, iron concentrations in the plumes, and amounts of iron supplied by hydrothermal vents, it was found that resident time of the plumes considered was from 5 to 10 days.

Northeast Greenland - Digital Bathymetric Compilation, with links to DBM in ArcGIS format

A new digital bathymetric model (DBM) for the Northeast Greenland (NEG) continental shelf (74°N - 81°N) is presented. The DBM has a grid cell size of 250 m × 250 m and incorporates bathymetric data from 30 multibeam cruises, more than 20 single-beam cruises and first reflector depths from industrial seismic lines. The new DBM substantially improves the bathymetry compared to older models. The DBM not only allows a better delineation of previously known seafloor morphology but, in addition, reveals the presence of previously unmapped morphological features including glacially derived troughs, fjords, grounding-zone wedges, and lateral moraines. These submarine landforms are used to infer the past extent and ice-flow dynamics of the Greenland Ice Sheet during the last full-glacial period of the Quaternary and subsequent ice retreat across the continental shelf. The DBM reveals cross-shelf bathymetric troughs that may enable the inflow of warm Atlantic water masses across the shelf, driving enhanced basal melting of the marine-terminating outlet glaciers draining the ice sheet to the coast in Northeast Greenland. Knolls, sinks, and hummocky seafloor on the middle shelf are also suggested to be related to salt diapirism. North-south-orientated elongate depressions are identified that probably relate to ice-marginal processes in combination with erosion caused by the East Greenland Current. A single guyot-like peak has been discovered and is interpreted to have been produced during a volcanic event approximately 55 Ma ago.

Predicting bed form roughness: the influence of lee side angle

Flow transverse bedforms (ripples and dunes) are ubiquitous in rivers and coastal seas. Local hydrodynamics and transport conditions depend on the size and geometry of these bedforms, as they constitute roughness elements at the bed. Bedform influence on flow energy must be considered for the understanding of flow dynamics, and in the development and application of numerical models. Common estimations or predictors of form roughness (friction factors) are based mostly on data of steep bedforms (with angle-of-repose lee slopes), and described by highly simplified bedform dimensions (heights and lengths). However, natural bedforms often are not steep, and differ in form and hydraulic effect relative to idealised bedforms. Based on systematic numerical model experiments, this study shows how the hydraulic effect of bedforms depends on the flow structure behind bedforms, which is determined by the bedform lee side angle, aspect ratio and relative height. Simulations reveal that flow separation behind bedform crests and, thus, a hydraulic effect is induced at lee side angles steeper than 11 to 18° depending on relative height, and that a fully developed flow separation zone exists only over bedforms with a lee side angle steeper than 24°. Furthermore, the hydraulic effect of bedforms with varying lee side angle is evaluated and a reduction function to common friction factors is proposed. A function is also developed for the Nikuradse roughness (k s), and a new equation is proposed which directly relates k s to bedform relative height, aspect ratio and lee side angle.

Análisis y modelización de la dinámica emergente durante el proceso de difusión de información en las redes sociales de internet

Durante la actividad diaria, la sociedad actual interactúa constantemente por medio de dispositivos electrónicos y servicios de telecomunicaciones, tales como el teléfono, correo electrónico, transacciones bancarias o redes sociales de Internet. Sin saberlo, masivamente dejamos rastros de nuestra actividad en las bases de datos de empresas proveedoras de servicios. Estas nuevas fuentes de datos tienen las dimensiones necesarias para que se puedan observar patrones de comportamiento humano a grandes escalas. Como resultado, ha surgido una reciente explosión sin precedentes de estudios de sistemas sociales, dirigidos por el análisis de datos y procesos computacionales. En esta tesis desarrollamos métodos computacionales y matemáticos para analizar sistemas sociales por medio del estudio combinado de datos derivados de la actividad humana y la teoría de redes complejas. Nuestro objetivo es caracterizar y entender los sistemas emergentes de interacciones sociales en los nuevos espacios tecnológicos, tales como la red social Twitter y la telefonía móvil. Analizamos los sistemas por medio de la construcción de redes complejas y series temporales, estudiando su estructura, funcionamiento y evolución en el tiempo. También, investigamos la naturaleza de los patrones observados por medio de los mecanismos que rigen las interacciones entre individuos, así como medimos el impacto de eventos críticos en el comportamiento del sistema. Para ello, hemos propuesto modelos que explican las estructuras globales y la dinámica emergente con que fluye la información en el sistema. Para los estudios de la red social Twitter, hemos basado nuestros análisis en conversaciones puntuales, tales como protestas políticas, grandes acontecimientos o procesos electorales. A partir de los mensajes de las conversaciones, identificamos a los usuarios que participan y construimos redes de interacciones entre los mismos. Específicamente, construimos una red para representar quién recibe los mensajes de quién y otra red para representar quién propaga los mensajes de quién. En general, hemos encontrado que estas estructuras tienen propiedades complejas, tales como crecimiento explosivo y distribuciones de grado libres de escala. En base a la topología de estas redes, hemos indentificado tres tipos de usuarios que determinan el flujo de información según su actividad e influencia. Para medir la influencia de los usuarios en las conversaciones, hemos introducido una nueva medida llamada eficiencia de usuario. La eficiencia se define como el número de retransmisiones obtenidas por mensaje enviado, y mide los efectos que tienen los esfuerzos individuales sobre la reacción colectiva. Hemos observado que la distribución de esta propiedad es ubicua en varias conversaciones de Twitter, sin importar sus dimensiones ni contextos. Con lo cual, sugerimos que existe universalidad en la relación entre esfuerzos individuales y reacciones colectivas en Twitter. Para explicar los factores que determinan la emergencia de la distribución de eficiencia, hemos desarrollado un modelo computacional que simula la propagación de mensajes en la red social de Twitter, basado en el mecanismo de cascadas independientes. Este modelo nos permite medir el efecto que tienen sobre la distribución de eficiencia, tanto la topología de la red social subyacente, como la forma en que los usuarios envían mensajes. Los resultados indican que la emergencia de un grupo selecto de usuarios altamente eficientes depende de la heterogeneidad de la red subyacente y no del comportamiento individual. Por otro lado, hemos desarrollado técnicas para inferir el grado de polarización política en redes sociales. Proponemos una metodología para estimar opiniones en redes sociales y medir el grado de polarización en las opiniones obtenidas. Hemos diseñado un modelo donde estudiamos el efecto que tiene la opinión de un pequeño grupo de usuarios influyentes, llamado élite, sobre las opiniones de la mayoría de usuarios. El modelo da como resultado una distribución de opiniones sobre la cual medimos el grado de polarización. Aplicamos nuestra metodología para medir la polarización en redes de difusión de mensajes, durante una conversación en Twitter de una sociedad políticamente polarizada. Los resultados obtenidos presentan una alta correspondencia con los datos offline. Con este estudio, hemos demostrado que la metodología propuesta es capaz de determinar diferentes grados de polarización dependiendo de la estructura de la red. Finalmente, hemos estudiado el comportamiento humano a partir de datos de telefonía móvil. Por una parte, hemos caracterizado el impacto que tienen desastres naturales, como innundaciones, sobre el comportamiento colectivo. Encontramos que los patrones de comunicación se alteran de forma abrupta en las áreas afectadas por la catástofre. Con lo cual, demostramos que se podría medir el impacto en la región casi en tiempo real y sin necesidad de desplegar esfuerzos en el terreno. Por otra parte, hemos estudiado los patrones de actividad y movilidad humana para caracterizar las interacciones entre regiones de un país en desarrollo. Encontramos que las redes de llamadas y trayectorias humanas tienen estructuras de comunidades asociadas a regiones y centros urbanos. En resumen, hemos mostrado que es posible entender procesos sociales complejos por medio del análisis de datos de actividad humana y la teoría de redes complejas. A lo largo de la tesis, hemos comprobado que fenómenos sociales como la influencia, polarización política o reacción a eventos críticos quedan reflejados en los patrones estructurales y dinámicos que presentan la redes construidas a partir de datos de conversaciones en redes sociales de Internet o telefonía móvil. ABSTRACT During daily routines, we are constantly interacting with electronic devices and telecommunication services. Unconsciously, we are massively leaving traces of our activity in the service providers’ databases. These new data sources have the dimensions required to enable the observation of human behavioral patterns at large scales. As a result, there has been an unprecedented explosion of data-driven social research. In this thesis, we develop computational and mathematical methods to analyze social systems by means of the combined study of human activity data and the theory of complex networks. Our goal is to characterize and understand the emergent systems from human interactions on the new technological spaces, such as the online social network Twitter and mobile phones. We analyze systems by means of the construction of complex networks and temporal series, studying their structure, functioning and temporal evolution. We also investigate on the nature of the observed patterns, by means of the mechanisms that rule the interactions among individuals, as well as on the impact of critical events on the system’s behavior. For this purpose, we have proposed models that explain the global structures and the emergent dynamics of information flow in the system. In the studies of the online social network Twitter, we have based our analysis on specific conversations, such as political protests, important announcements and electoral processes. From the messages related to the conversations, we identify the participant users and build networks of interactions with them. We specifically build one network to represent whoreceives- whose-messages and another to represent who-propagates-whose-messages. In general, we have found that these structures have complex properties, such as explosive growth and scale-free degree distributions. Based on the topological properties of these networks, we have identified three types of user behavior that determine the information flow dynamics due to their influence. In order to measure the users’ influence on the conversations, we have introduced a new measure called user efficiency. It is defined as the number of retransmissions obtained by message posted, and it measures the effects of the individual activity on the collective reacixtions. We have observed that the probability distribution of this property is ubiquitous across several Twitter conversation, regardlessly of their dimension or social context. Therefore, we suggest that there is a universal behavior in the relationship between individual efforts and collective reactions on Twitter. In order to explain the different factors that determine the user efficiency distribution, we have developed a computational model to simulate the diffusion of messages on Twitter, based on the mechanism of independent cascades. This model, allows us to measure the impact on the emergent efficiency distribution of the underlying network topology, as well as the way that users post messages. The results indicate that the emergence of an exclusive group of highly efficient users depends upon the heterogeneity of the underlying network instead of the individual behavior. Moreover, we have also developed techniques to infer the degree of polarization in social networks. We propose a methodology to estimate opinions in social networks and to measure the degree of polarization in the obtained opinions. We have designed a model to study the effects of the opinions of a small group of influential users, called elite, on the opinions of the majority of users. The model results in an opinions distribution to which we measure the degree of polarization. We apply our methodology to measure the polarization on graphs from the messages diffusion process, during a conversation on Twitter from a polarized society. The results are in very good agreement with offline and contextual data. With this study, we have shown that our methodology is capable of detecting several degrees of polarization depending on the structure of the networks. Finally, we have also inferred the human behavior from mobile phones’ data. On the one hand, we have characterized the impact of natural disasters, like flooding, on the collective behavior. We found that the communication patterns are abruptly altered in the areas affected by the catastrophe. Therefore, we demonstrate that we could measure the impact of the disaster on the region, almost in real-time and without needing to deploy further efforts. On the other hand, we have studied human activity and mobility patterns in order to characterize regional interactions on a developing country. We found that the calls and trajectories networks present community structure associated to regional and urban areas. In summary, we have shown that it is possible to understand complex social processes by means of analyzing human activity data and the theory of complex networks. Along the thesis, we have demonstrated that social phenomena, like influence, polarization and reaction to critical events, are reflected in the structural and dynamical patterns of the networks constructed from data regarding conversations on online social networks and mobile phones.

Stem CO2 efflux and its contribution to ecosystem CO2 efflux decrease with drought in a Mediterranean forest stand

tThe rate of metabolic processes demanding energy in tree stems changes in relation with prevailing cli-matic conditions. Tree water availability can affect stem respiration through impacts on growth, phloemtransport or maintenance of diverse cellular processes, but little is known on this topic. Here we moni-tored seasonal changes in stem CO2efflux (Fs), radial growth, sap flow and non-structural carbohydrates intrees of Quercus ilex in a Mediterranean forest stand subjected since 2003 to either partial (33%) through-fall exclusion (E) or unchanged throughfall (C). Fsincreased exponentially during the day by an effectof temperature, although sap flow attenuated the increase in Fsduring the day time. Over the year, Fsalso increased exponentially with increasing temperatures, but Fscomputed at a standard temperatureof 15?C (F15s) varied by almost 4-fold among dates. F15swas the highest after periods of stem growth anddecreased as tree water availability decreased, similarly in C and E treatments. The decline in F15swas notlinked to a depletion of soluble sugars, which increased when water stress was higher. The proportionof ecosystem respiration attributed to the stems was highest following stem growth (23.3%) and lowestduring the peak of drought (6.5%). High within-year variability in F15smakes unadvisable to pool annualdata of Fsvs. temperature to model Fsat short time scales (hours to months) in Mediterranean-type for-est ecosystems. We demonstrate that water availability is an important factor governing stem CO2effluxand suggest that trees in Mediterranean environments acclimate to seasonal drought by reducing stemrespiration. Stem respiratory rates do not seem to change after a long-term increase in drought intensity,however.

Confidentiala "Mode 3" Systems Approach for Knowledge Creation, Diffusion and Use: Towards a 21st Century Fractal Innovation Ecosystem. ACES Working Paper (Report) No. 4, 2007

"Mode 3" allows and emphasizes the co-existence and co-evolution of different knowledge and innovation paradigms: the competitiveness and superiority of a knowledge system is highly determined by its adaptive capacity to combine and integrate different knowledge and innovation modes via co-evolution, co-specialization and coopetition [sic] of knowledge stock and flow dynamics. What results is an emerging fractal knowledge and innovation ecosystem, well-configured for the knowledge economy and society. The intrinsic litmus test of the capacity of such an ecosystem to survive and prosper in the context of continually glocalizing [sic] and intensifying competition represents the ultimate competitiveness benchmark with regards to the robustness and quality of the ecosystem's knowledge and innovation architecture and topology.

German Bight bedform reconstructions

Bodenformen an der Sohle von Flüssen, Küstenzonen und flachen Schelfen sind wichtige skalenübergreifende Elemente der Küstendynamik in ihren Eigenschaften als Transportkörper von Sedimenten und ihrer Wirkung auf die Strömungsdynamik als Rauheitselemente. Neben vielen neueren Studien über die Entstehung, Gestalt und Dynamik von Bodenformen in vergleichsweise kleinen Untersuchungsgebieten ist die Arbeit von ULRICH (1973) über die Verteilung von Bodenformen in der Deutschen Bucht bis heute die einzige verfügbare zusammenhängende Darstellung für die deutsche Nordseeküste. Die analogen Karten und die Darstellung der Klassifizierung in Buchstabenkürzeln macht sie für heutige quantitative Analysen schwer zugänglich. Hier wurden diese Karten digitalisiert und Eigenschaften der Bodenformen rekonstruiert und interpretiert. Das Ergebnis ist eine Zusammenstellung digitaler Karten eines vollständigen - und eines auf steile, hydrodynamisch wirksame Bodenformen reduzierten Datensatzes der Minimal, Maximalund Mittelwerte von Höhen, Längen und Steilheiten von Bodenformen in der Deutschen Bucht. Die Datensätze stehen der Allgemeinheit in der Datenbank Pangaea zur Verfügung. Bedforms in rivers, coastal zones and shallow shelf seas are important cross-scale elements of coastal dynamics in their function as sediment transport agent and in their effect on the flow dynamics as roughness elements. In addition to many recent studies on the origin, shape and dynamics of bedforms in relatively small study areas the work of ULRICH (1973) on the classification of bedform types in the German Bight is until today the only available coherent representation of the spatial distribution of bedforms for the whole German coastal sea. The analogue maps and the coded classification makes them difficult to access for quantitative analyses. Here these maps were digitized and properties of the bedforms were reconstructed and interpreted. Resulting digital maps of the whole and a reduced dataset on steep bedforms contain minimum, maximum and average values of heights, lengths and steepness of bedform types in the German Bight. The data sets are available to the public in the database Pangaea.