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71.
LiDAR data were used to quantify and analyse a rockfall event which occurred in 2003 in the Western Dolomites (Italian Alps). In addition to previously existing airborne laserscanning (ALS) data, high resolution terrestrial laserscanning (TLS) data were collected. By using the original point clouds, the volume, axial ratio and runout length of single boulders as well as the surface roughness in the runout zone of the rockfall were derived. The total volume of the rockfall event of approximately 10 000 m³ was estimated by a reconstruction of the pre‐event surface at the detachment zone. The analysis of the laser scanning data of the accumulation zone revealed a power law scaling for boulder volumes larger than 8 m³. The dependence of runout length on boulder volume is complex; it is moderated by particle sphericity. In addition, we used ALS and TLS data to derive the spatial distribution of surface roughness on the talus cone. TLS allow for more accurate roughness mapping than ALS data, but for most applications the point density of ALS data seems to be sufficiently high to derive measures of roughness. Different sampling approaches for plane fitting on the scale of 5 m did not show significant effects besides the computational time. The results of our analyses provide important perspectives for rockfall modelling and process understanding with potential applications in both ‘applied’ (natural hazards) and ‘pure’ geomorphological research. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
72.
Brittle magmatic fragmentation plays a crucial role in explosive eruptions. It represents the starting point of hazardous explosive events that can affect large areas surrounding erupting volcanoes. Knowing the initial energy released during this fragmentation process is fundamental for the understanding of the subsequent dynamics of the eruptive gas-particle mixture and consequently for the forecasting of the erupting column’s behavior. The specific kinetic energy (SKE) of the particles quantifies the initial velocity shortly after the fragmentation and is therefore a necessary variable to model the gas-particle conduit flow and eruptive column regime. In this paper, we present a new method for its determination based on fragmentation experiments and identification of the timings of energy release. The results obtained on compositions representative for basaltic and phonolitic melts show a direct dependence on magma material properties: poorly vesiculated basaltic melts from Stromboli show the highest SKE values ranging from 7.3 to 11.8 kJ/kg, while experiments with highly vesiculated samples from Stromboli and Vesuvius result in lower SKE values (3.1 to 3.8 kJ/kg). The described methodology presents a useful tool for quantitative estimation of the kinetic energy release of magmatic fragmentation processes, which can contribute to the improvement of hazard assessment.  相似文献   
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This review and commentary sets out the need for authoritative and concise information on the expected error distributions and magnitudes in observational data. We discuss the necessary components of a benchmark of dominant data uncertainties and the recent developments in hydrology which increase the need for such guidance. We initiate the creation of a catalogue of accessible information on characteristics of data uncertainty for the key hydrological variables of rainfall, river discharge and water quality (suspended solids, phosphorus and nitrogen). This includes demonstration of how uncertainties can be quantified, summarizing current knowledge and the standard quantitative results available. In particular, synthesis of results from multiple studies allows conclusions to be drawn on factors which control the magnitude of data uncertainty and hence improves provision of prior guidance on those uncertainties. Rainfall uncertainties were found to be driven by spatial scale, whereas river discharge uncertainty was dominated by flow condition and gauging method. Water quality variables presented a more complex picture with many component errors. For all variables, it was easy to find examples where relative error magnitudes exceeded 40%. We consider how data uncertainties impact on the interpretation of catchment dynamics, model regionalization and model evaluation. In closing the review, we make recommendations for future research priorities in quantifying data uncertainty and highlight the need for an improved ‘culture of engagement’ with observational uncertainties. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
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Papandayan is a stratovolcano situated in West Java, Indonesia. Since the last magmatic eruption in 1772, only few hydrothermal explosions have occurred. An explosive eruption occurred in November 2002 and ejected ash and altered rocks. The altered rocks show that an advanced argillic alteration took place in the hydrothermal system by interaction between acid fluids and rocks. Four zones of alteration have been defined and are limited in extension and shape along faults or across permeable structures at different levels beneath the active crater of the volcano.  相似文献   
77.
Beobide-Arsuaga  Goratz  Bayr  Tobias  Reintges  Annika  Latif  Mojib 《Climate Dynamics》2021,56(11):3875-3888

There is a long-standing debate on how the El Niño/Southern Oscillation (ENSO) amplitude may change during the twenty-first century in response to global warming. Here we identify the sources of uncertainty in the ENSO amplitude projections in models participating in the Coupled Model Intercomparison Phase 5 (CMIP5) and Phase 6 (CMIP6), and quantify scenario uncertainty, model uncertainty and uncertainty due to internal variability. The model projections exhibit a large spread, ranging from increasing standard deviation of up to 0.6 °C to diminishing standard deviation of up to − 0.4 °C by the end of the twenty-first century. The ensemble-mean ENSO amplitude change is close to zero. Internal variability is the main contributor to the uncertainty during the first three decades; model uncertainty dominates thereafter, while scenario uncertainty is relatively small throughout the twenty-first century. The total uncertainty increases from CMIP5 to CMIP6: while model uncertainty is reduced, scenario uncertainty is considerably increased. The models with “realistic” ENSO dynamics have been analyzed separately and categorized into models with too small, moderate and too large ENSO amplitude in comparison to instrumental observations. The smallest uncertainties are observed in the sub-ensemble exhibiting realistic ENSO dynamics and moderate ENSO amplitude. However, the global warming signal in ENSO-amplitude change is undetectable in all sub-ensembles. The zonal wind-SST feedback is identified as an important factor determining ENSO amplitude change: global warming signal in ENSO amplitude and zonal wind-SST feedback strength are highly correlated across the CMIP5 and CMIP6 models.

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78.
Ground‐penetrating radar (GPR) has become a promising technique in the field of snow hydrological research. It is commonly used to measure snow depth, density, and water equivalent over large distances or along gridded snow courses. Having built and tested a mobile lightweight set‐up, we demonstrate that GPR is capable of accurately measuring snow ablation rates in complex alpine terrain. Our set‐up was optimized for efficient measurements and consisted of a multioffset radar with four pairs of antennas mounted to a plastic sled, which was small enough to permit safe and convenient operations. Repeated measurements at intervals of 2 to 7 days were taken during the 2014/2015 winter season along 10 profiles of 50 to 200 m length within two valleys located in the eastern Swiss Alps. Resulting GPR‐based data of snow depth, density, and water equivalent, as well as their respective change over time, were in good agreement with concurrent manual measurements, in particular if accurate alignment between repeated overpasses could be achieved. Corresponding root‐mean‐square error (RMSE) values amounted to 4.2 cm for snow depth, 17 mm for snow water equivalent, and 22 kg/m3 for snow density, with similar RMSE values for corresponding differential data. With this performance, the presented radar set‐up has the potential to provide exciting new and extensive datasets to validate snowmelt models or to complement lidar‐based snow surveys.  相似文献   
79.
Tight oil siltstones are rocks with complex structure at pore scale and are characterized by low porosity and low permeability at macroscale. The production of tight oil siltstone reservoirs can be increased by hydraulic fracturing. For optimal fracking results, it is desirable to map the ability to fracture based on seismic data prior to fracturing. Brittleness is currently thought to be a key parameter for evaluating the ability to fracture. To link seismic information to the brittleness distribution, a rock physics model is required. Currently, there exists no commonly accepted rock physics model for tight oil siltstones. Based on the observed correlation between porosity and mineral composition and known microstructure of tight oil siltstone in Daqing oilfield of Songliao basin, we develop a rock physics model by combining the Voigt–Reuss–Hill average, self-consistent approximation and differential effective medium theory. This rock physics model allows us to explore the dependence of the brittleness on porosity, mineral composition, microcrack volume fraction and microcrack aspect ratio. The results show that, as quartz content increases and feldspar content decreases, Young's modulus tends to increase and Poisson ratio decreases. This is taken as a signature of higher brittleness. Using well log data and seismic inversion results, we demonstrate the versatility of the rock physics template for brittleness prediction.  相似文献   
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