550 Geowissenschaften
Filtern
Erscheinungsjahr
Dokumenttyp
- Wissenschaftlicher Artikel (1216) (entfernen)
Schlagworte
- climate change (26)
- Germany (12)
- Climate change (10)
- Himalaya (10)
- Europe (9)
- permafrost (9)
- Holocene (8)
- Time-series analysis (8)
- adaptation (8)
- earthquake (8)
Institut
- Institut für Geowissenschaften (818)
- Institut für Umweltwissenschaften und Geographie (274)
- Extern (78)
- Institut für Biochemie und Biologie (31)
- Institut für Physik und Astronomie (18)
- Institut für Mathematik (15)
- Fachgruppe Volkswirtschaftslehre (7)
- Mathematisch-Naturwissenschaftliche Fakultät (6)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (2)
- Institut für Chemie (2)
The Altiplano-Puna plateau, in Central Andes, is the second-largest continental plateau on Earth, extending between 22 degrees and 27 degrees S at an average altitude of 4400 m. The Puna plateau has been formed in consequence of the subduction of the oceanic Nazca Plate beneath the continental South American plate, which has an average crustal thickness of 50 km at this location. A large seismicity cluster, the Jujuy cluster, is observed at depth of 150-250 km beneath the central region of the Puna plateau. The cluster is seismically very active, with hundreds of earthquakes reported and a peak magnitude MW 6.6 on 25th August 2006. The cluster is situated in one of three band of intermediate-depth focus seismicity, which extend parallel to the trench roughly North to South. It has been hypothesized that the Jujuy cluster could be a seismic nest, a compact seismogenic region characterized by a high stationary activity relative to its surroundings. In this study, we collected more than 40 years of data from different catalogs and proof that the cluster meets the three conditions of a seismic nest. Compared to other known intermediate depth nests at Hindu Kush (Afganisthan) or Bucaramanga (Colombia), the Jujuy nest presents an outstanding seismicity rate, with more than 100 M4+ earthquakes per year. We additionally performed a detailed analysis of the rupture process of some of the largest earthquakes in the nest, by means of moment tensor inversion and directivity analysis. We focused on the time period 2017-2018, where the seismic monitoring was the most extended. Our results show that earthquakes in the nest take place within the eastward subducting oceanic plate, but rupture along sub-horizontal planes dipping westward. We suggest that seismicity at Jujuy nest is controlled by dehydration processes, which are also responsible for the generation of fluids ascending to the crust beneath the Puna volcanic region. We use the rupture plane and nest geometry to provide a constraint to maximal expected magnitude, which we estimate as MW -6.7.
Purpose:
Soil erosion by water yields sediment to surface reservoirs, reducing their storage capacities, changing their geometry, and degrading water quality. Sediment reuse, i.e., fertilization of agricultural soils with the nutrient-enriched sediment from reservoirs, has been proposed as a recovery strategy. However, the sediment needs to meet certain criteria. In this study, we characterize sediments from the densely dammed semiarid Northeast Brazil by VNIR-SWIR spectroscopy and assess the effect of spectral resolution and spatial scale on the accuracy of N, P, K, C, electrical conductivity, and clay prediction models.
Methods
Sediment was collected in 10 empty reservoirs, and physical and chemical laboratory analyses as well as spectral measurements were performed. The spectra, initially measured at 1 nm spectral resolution, were resampled to 5 and 10 nm, and samples were analysed for both high and low spectral resolution at three spatial scales, namely (1) reservoir, (2) catchment, and (3) regional scale.
Results
Partial least square regressions performed from good to very good in the prediction of clay and electrical conductivity from reservoir (<40 km(2)) to regional (82,500 km(2)) scales. Models for C and N performed satisfactorily at the reservoir scale, but degraded to unsatisfactory at the other scales. Models for P and K were more unstable and performed from unsatisfactorily to satisfactorily at all scales. Coarsening spectral resolution by up to 10 nm only slightly degrades the models' performance, indicating the potential of characterizing sediment from spectral data captured at lower resolutions, such as by hyperspectral satellite sensors.
Conclusion:
By reducing the costly and time-consuming laboratory analyses, the method helps to promote the sediment reuse as a practice of soil and water conservation.
After a century of semi-restricted floodplain development, Southern Alberta, Canada, was struck by the devastating 2013 Flood. Aging infrastructure and limited property-level floodproofing likely contributed to the $4-6 billion (CAD) losses. Following this catastrophe, Alberta has seen a revival in flood management, largely focused on structural protections. However, concurrent with the recent structural work was a 100,000+ increase in Calgary's population in the 5 years following the flood, leading to further densification of high-hazard areas. This study implements the novel Stochastic Object-based Flood damage Dynamic Assessment (SOFDA) model framework to quantify the progression of the direct-damage flood risk in a mature urban neighborhood after the 2013 Flood. Five years of remote-sensing data, property assessment records, and inundation simulations following the flood are used to construct the model. Results show that in these 5 years, vulnerability trends (like densification) have increased flood risk by 4%; however, recent structural mitigation projects have reduced overall flood risk by 47% for this case study. These results demonstrate that the flood management revival in Southern Alberta has largely been successful at reducing flood risk; however, the gains are under threat from continued development and densification absent additional floodproofing regulations.
Urban surface runoff management via best management practices (BMP) and low impact development (LID) has earned significant recognition owing to positive environmental and ecological impacts. However, due to the complexity of the parameters involved, the estimation of LID efficiency in attenuating the urban surface runoff at the watershed scale is challenging. A planning analysis of employing Green Roofs and Infiltration Trenches as BMPs/LIDs practices for urban surface runoff control is presented in this study. A multi-objective optimization decision-making framework is established by coupling SWMM (Storm Water Management Model) with NSGA-II models to check the performance of BMPs/LIDs concerning the cost-benefit analysis of LID at the watershed scale. Two urbanized areas belonging to Central Delhi in India were used as case studies. The results showed that the SWMM model is useful in simulating optimization problems for managing urban surface runoff. The optimum scenarios efficiently minimized the urban runoff volume while maintaining the BMPs/LIDs implementation costs and size. With BMPs/LIDs implementation, the reduction in runoff volume increases as expenses increase initially; however, there is no noticeable reduction in flood volume after a certain threshold. Contrasted with the haphazard arrangement of BMPs/LIDs, the proposed approach demonstrates 22%-24% runoff reductions for the same expenditures in watershed 1 and 23%-26% in watershed 2. The result of the study provides insights into planning and management of the urban surface runoff control with LID practices. The proposed framework assists the hydrologists in optimum selection and placements of BMPs/LIDs practices to acquire the most extreme ecological advantages with the least expenses.
Van Allen Probes measurements revealed the presence of the most unusual structures in the ultra-relativistic radiation belts. Detailed modeling, analysis of pitch angle distributions, analysis of the difference between relativistic and ultra-realistic electron evolution, along with theoretical studies of the scattering and wave growth, all indicate that electromagnetic ion cyclotron (EMIC) waves can produce a very efficient loss of the ultra-relativistic electrons in the heart of the radiation belts. Moreover, a detailed analysis of the profiles of phase space densities provides direct evidence for localized loss by EMIC waves. The evolution of multi-MeV fluxes shows dramatic and very sudden enhancements of electrons for selected storms. Analysis of phase space density profiles reveals that growing peaks at different values of the first invariant are formed at approximately the same radial distance from the Earth and show the sequential formation of the peaks from lower to higher energies, indicating that local energy diffusion is the dominant source of the acceleration from MeV to multi-MeV energies. Further simultaneous analysis of the background density and ultra-relativistic electron fluxes shows that the acceleration to multi-MeV energies only occurs when plasma density is significantly depleted outside of the plasmasphere, which is consistent with the modeling of acceleration due to chorus waves.
We present two new empirical models of radiation belt electron flux at geostationary orbit. GOES-15 measurements of 0.8 MeV electrons were used to train a Nonlinear Autoregressive with Exogenous input (NARX) neural network for both modeling GOES-15 flux values and an upper boundary condition scaling factor (BF). The GOES-15 flux model utilizes an input and feedback delay of 2 and 2 time steps (i.e., 5 min time steps) with the most efficient number of hidden layers set to 10. Magnetic local time, Dst, Kp, solar wind dynamic pressure, AE, and solar wind velocity were found to perform as predicative indicators of GOES-15 flux and therefore were used as the exogenous inputs. The NARX-derived upper boundary condition scaling factor was used in conjunction with the Versatile Electron Radiation Belt (VERB) code to produce reconstructions of the radiation belts during the period of July-November 1990, independent of in-situ observations. Here, Kp was chosen as the sole exogenous input to be more compatible with the VERB code. This Combined Release and Radiation Effects Satellite-era reconstruction showcases the potential to use these neural network-derived boundary conditions as a method of hindcasting the historical radiation belts. This study serves as a companion paper to another recently published study on reconstructing the radiation belts during Solar Cycles 17-24 (Saikin et al., 2021, ), for which the results featured in this paper were used.
Regional flood frequency analysis (RFFA) is a powerful method for interrogating hydrological series since it combines observational time series from several sites within a region to estimate risk-relevant statistical parameters with higher accuracy than from single-site series. Since RFFA extreme value estimates depend on the shape of the selected distribution of the data-generating stochastic process, there is need for a suitable goodness-of-distributional-fit measure in order to optimally utilize given data. Here we present a novel, least-squares-based measure to select the optimal fit from a set of five distributions, namely Generalized Extreme Value (GEV), Generalized Logistic, Gumbel, Log-Normal Type III and Log-Pearson Type III. The fit metric is applied to annual maximum discharge series from six hydrological stations along the Sava River in South-eastern Europe, spanning the years 1961 to 2020. Results reveal that (1) the Sava River basin can be assessed as hydrologically homogeneous and (2) the GEV distribution provides typically the best fit. We offer hydrological-meteorological insights into the differences among the six stations. For the period studied, almost all stations exhibit statistically insignificant trends, which renders the conclusions about flood risk as relevant for hydrological sciences and the design of regional flood protection infrastructure.
The analysis of event time series is in general challenging. Most time series analysis tools are limited for the analysis of this kind of data. Recurrence analysis, a powerful concept from nonlinear time series analysis, provides several opportunities to work with event data and even for the most challenging task of comparing event time series with continuous time series. Here, the basic concept is introduced, the challenges are discussed, and the future perspectives are summarized.
In this study, 3-D models of P-wave velocity (Vp) and P-wave and S-wave ratio (Vp/Vs) of the crust and upper mantle in the Eastern and eastern Southern Alps (northern Italy and southern Austria) were calculated using local earthquake tomography (LET). The data set includes high-quality arrival times from well-constrained hypocenters observed by the dense, temporary seismic networks of the AlpArray AASN and SWATH-D. The resolution of the LET was checked by synthetic tests and analysis of the model resolution matrix. The small inter-station spacing (average of similar to 15 km within the SWATH-D network) allowed us to image crustal structure at unprecedented resolution across a key part of the Alps. The derived P velocity model revealed a highly heterogeneous crustal structure in the target area. One of the main findings is that the lower crust is thickened, forming a bulge at 30-50 km depth just south of and beneath the Periadriatic Fault and the Tauern Window. This indicates that the lower crust decoupled both from its mantle substratum as well as from its upper crust. The Moho, taken to be the iso-velocity contour of Vp = 7.25 km/s, agrees with the Moho depth from previous studies in the European and Adriatic forelands. It is shallower on the Adriatic side than on the European side. This is interpreted to indicate that the European Plate is subducted beneath the Adriatic Plate in the Eastern and eastern Southern Alps.
Phytoliths in particulate matter released by wind erosion on arable land in La Pampa, Argentina
(2022)
Silicon (Si) is considered a beneficial element in plant nutrition, but its importance on ecosystems goes far beyond that. Various forms of silicon are found in soils, of which the phytogenic pool plays a decisive role due to its good availability. This Si returns to the soil through the decomposition of plant residues, where they then participate in the further cycle as biogenic amorphous silica (bASi) or so-called phytoliths. These have a high affinity for water, so that the water holding capacity and water availability of soils can be increased even by small amounts of ASi. Agricultural land is a considerable global dust source, and dust samples from arable land have shown in cloud formation experiments a several times higher ice nucleation activity than pure mineral dust. Here, particle sizes in the particulate matter fractions (PM) are important, which can travel long distances and reach high altitudes in the atmosphere. Based on this, the research question was whether phytoliths could be detected in PM samples from wind erosion events, what are the main particle sizes of phytoliths and whether an initial quantification was possible.Measurements of PM concentrations were carried out at a wind erosion measuring field in the province La Pampa, Argentina. PM were sampled during five erosion events with Environmental Dust Monitors (EDM). After counting and classifying all particles with diameters between 0.3 and 32 mu m in the EDMs, they are collected on filters. The filters were analyzed by Scanning Electron Microscopy and Energy Dispersive X-Ray analysis (SEM-EDX) to investigate single or ensembles of particles regarding composition and possible origins.The analyses showed up to 8.3 per cent being phytoliths in the emitted dust and up to 25 per cent of organic origin. Particles of organic origin are mostly in the coarse dust fraction, whereas phytoliths are predominately transported in the finer dust fractions. Since phytoliths are both an important source of Si as a plant nutrient and are also involved in soil C fixation, their losses from arable land via dust emissions should be considered and its specific influence on atmospheric processes should be studied in detail in the future.