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The East Asian monsoons characterize the modern-day Asian climate, yet their geological history and driving mechanisms remain controversial. The southeasterly summer monsoon provides moisture, whereas the northwesterly winter monsoon sweeps up dust from the arid Asian interior to form the Chinese Loess Plateau. The onset of this loess accumulation, and therefore of the monsoons, was thought to be 8 million years ago (Ma). However, in recent years these loess records have been extended further back in time to the Eocene (56-34 Ma), a period characterized by significant changes in both the regional geography and global climate. Yet the extent to which these reconfigurations drive atmospheric circulation and whether the loess-like deposits are monsoonal remains debated. In this thesis, I study the terrestrial deposits of the Xining Basin previously identified as Eocene loess, to derive the paleoenvironmental evolution of the region and identify the geological processes that have shaped the Asian climate.
I review dust deposits in the geological record and conclude that these are commonly represented by a mix of both windblown and water-laid sediments, in contrast to the pure windblown material known as loess. Yet by using a combination of quartz surface morphologies, provenance characteristics and distinguishing grain-size distributions, windblown dust can be identified and quantified in a variety of settings. This has important implications for tracking aridification and dust-fluxes throughout the geological record.
Past reversals of Earth’s magnetic field are recorded in the deposits of the Xining Basin and I use these together with a dated volcanic ash layer to accurately constrain the age to the Eocene period. A combination of pollen assemblages, low dust abundances and other geochemical data indicates that the early Eocene was relatively humid suggesting an intensified summer monsoon due to the warmer greenhouse climate at this time. A subsequent shift from predominantly freshwater to salt lakes reflects a long-term aridification trend possibly driven by global cooling and the continuous uplift of the Tibetan Plateau. Superimposed on this aridification are wetter intervals reflected in more abundant lake deposits which correlate with highstands of the inland proto-Paratethys Sea. This sea covered the Eurasian continent and thereby provided additional moisture to the winter-time westerlies during the middle to late Eocene.
The long-term aridification culminated in an abrupt shift at 40 Ma reflected by the onset of windblown dust, an increase in steppe-desert pollen, the occurrence of high-latitude orbital cycles and northwesterly winds identified in deflated salt deposits. Together, these indicate the onset of a Siberian high atmospheric pressure system driving the East Asian winter monsoon as well as dust storms and was triggered by a major sea retreat from the Asian interior. These results therefore show that the proto-Paratethys Sea, though less well recognized than the Tibetan Plateau and global climate, has been a major driver in setting up the modern-day climate in Asia.
Applying conservation of energy to estimate earthquake frequencies from strain rates and stresses
(2020)
Estimating earthquake occurrence rates from the accumulation rate of seismic moment is an established tool of seismic hazard analysis. We propose an alternative, fault-agnostic approach based on the conservation of energy: the Energy-Conserving Seismicity Framework (ENCOS). Working in energy space has the advantage that the radiated energy is a better predictor of the damage potential of earthquake waves than the seismic moment release. In a region, ENCOS balances the stationary power available to cause earthquakes with the long-term seismic energy release represented by the energy-frequency distribution's first moment. Accumulation and release are connected through the average seismic efficiency, by which we mean the fraction of released energy that is converted into seismic waves. Besides measuring earthquakes in energy, ENCOS differs from moment balance essentially in that the energy accumulation rate depends on the total stress in addition to the strain rate tensor. To validate ENCOS, we exemplarily model the energy-frequency distribution around Southern California. We estimate the energy accumulation rate due to tectonic loading assuming poroelasticity and hydrostasis. Using data from the World Stress Map and assuming the frictional limit to estimate the stress tensor, we obtain a power of 0.8 GW. The uncertainty range, 0.3-2.0GW, originates mainly from the thickness of the seismogenic crust, the friction coefficient on preexisting faults, and models of Global Positioning System (GPS) derived strain rates. Based on a Gutenberg-Richter magnitude-frequency distribution, this power can be distributed over a range of energies consistent with historical earthquake rates and reasonable bounds on the seismic efficiency.
Sediment transport domains in mountain landscapes are characterized by fundamentally different processes and rates depending on several factors, including geology, climate, and biota. Accurately identifying where transitions between transport domains occur is an important step to quantify the past, present, and future contribution of varying erosion and sedimentation processes and enhance our predictive capabilities. We propose a new methodology based on time series of synthetic aperture radar (SAR) interferometric coherence images to map sediment transport regimes across arid and semiarid landscapes. Using 4 years of Sentinel-1 data, we analyze sediment transport regimes for the south-central Andes in northwestern Argentina characterized by steep topographic and climatic gradients. We observe seasonally low coherence during the regional wet season, particularly on hillslopes and in alluvial channels. The spatial distribution of coherence is compared to drainage areas extracted from digital topography to identify two distinct transitions within watersheds: (a) a hillslope-to-fluvial and (b) a fluvial-to-alluvial transition. While transitions within a given basin can be well-constrained, the relative role of each sediment transport domain varies widely over the climatic and topographic gradients. In semiarid regions, we observe larger relative contributions from hillslopes compared to arid regions. Across regional gradients, the range of coherence within basins positively correlates to previously published millennial catchment-wide erosion rates and to topographic metrics used to indicate long-term uplift. Our study suggests that a dense time series of interferometric coherence can be used as a proxy for surface sediment movement and landscape stability in vegetation-free settings at event to decadal timescales.
The 10th edition of the International Congress on the Application of Raman Spectroscopy in Art and Archaeology (RAA2019) was held in Potsdam (Germany) from 3 to 7 September 2019, with eight keynote lectures, 35 oral presentations and 18 Poster Presentations. The number of active participants was 68 delegates from 20 countries among the 236 authors that presented at least one work.
A local and flexible definition of the monsoon season based on hydrological evidence is important for the understanding and management of Himalayan water resources. Here, we present an objective statistical method to retrieve seasonal hydrometeorological transitions. Applied to daily rainfall data (1951-2015), this method shows an average longitudinal delay of similar to 15 days, with later monsoon onset and earlier withdrawal in the western Himalaya, consistent with the continental progression of wet air masses. This delay leads to seasons of different length along the Himalaya and biased precipitation amounts when using uniform calendric monsoon boundaries. In the Central Himalaya annual precipitation has increased, due primarily to an increase of premonsoon precipitation. These findings highlight issues associated with a static definition of monsoon boundaries and call for a deeper understanding of nonmonsoonal precipitation over the Himalayan water tower. <br /> Plain Language Summary Precipitation in the Himalayas determines water availability for the Indian foreland with large socioeconomic implications. Despite its importance, spatial and temporal patterns of precipitation are poorly understood. Here, we estimate the long-term average and trends of seasonal precipitation at the scale of individual catchments draining the Himalayas. We apply a statistical method to detect the timing of hydrometeorological seasons from local precipitation measurements, focusing on monsoon onset and withdrawal. We identify longitudinal and latitudinal delays, resulting in seasons of different length along and across the Himalayas. These spatial patterns and the annual variability of the monsoon boundaries mean that oft-used, fixed calendric dates, for example, 1 June to 30 September, may be inadequate for retrieving monsoon rainfall totals. Moreover, we find that, despite its prominent contribution to annual rainfall totals, the Indian summer monsoon cannot explain the increase of the annual precipitation over the Central Himalayas. Instead, this appears to be mostly driven by changes in premonsoon and winter rainfall. So far, little attention has been paid to premonsoon precipitation, but governed by evaporative processes and surface water availability, it may be enhanced by irrigation and changed land use in the Gangetic foreland.
Increasingly available high-frequency data during storm events, when hydrological dynamics most likely activate nitrate storage-flux exchanges, reveal insights into catchment nitrate dynamics. In this study, we explored impacts of seasonality and landscape gradients on nitrate concentration-discharge (C-Q) hysteresis patterns in the Selke catchment, central Germany, which has heterogeneous combinations of meteorological, hydrogeological and land use conditions. Three nested gauging stations established along the main Selke River captured flow and nitrate export dynamics from the uppermost subcatchment (mixed forest and arable land), middle subcatchment (pure steep forest) and lowermost subcatchment (arable and urban land). We collected continuous high-frequency (15-min) discharge and nitrate concentration data from 2012 to 2017 and analyzed the 223 events detected at all three stations. A dominant hysteresis pattern in the uppermost and middle subcatchments was counter-clockwise and combined with an accretion effect, indicating many proximal and mobilized distal nitrate sources. However, 66% of all events at the catchment outlet experienced a dilution effect, possibly due to mechanisms that vary seasonally. During wetting/wet periods (October-March), it was combined mainly with a counter-clockwise pattern due to the dominance of event runoff volume from the uppermost and middle subcatchments. During drying/dry periods (April-September), however, it was combined mainly with a clockwise pattern due to occasional quick surface flows from lowland near-stream urban areas. In addition, the clockwise hysteresis occurred mainly from May-October during mostly drying/dry periods at all three sites, indicating little distal nitrate transport in response to the low terrestrial hydrological connectivity, especially in the lowermost dry and flat sub-catchment. This comprehensive analysis (i.e., clockwise vs. counter-clockwise, accretion vs. dilution) enables in-depth analysis of nitrate export mechanisms during certain periods under different landscape conditions. Specific combination of C-Q relationships could identify target locations for agricultural management actions that decrease nitrate output. Therefore, we strongly encourage long-term multisite and high-frequency monitoring strategies in heterogeneous nested catchment(s), which can help understand process mechanisms, generate data for physical-based water-quality modeling and provide guidance for water and agricultural management.
Salt pans are highly dynamic environments that are difficult to study by in situ methods because of their harsh climatic conditions and large spatial areas. Remote sensing can help to elucidate their environmental dynamics and provide important constraints regarding their sedimentological, mineralogical, and hydrological evolution. This study utilizes spaceborne multitemporal multispectral optical data combined with spectral endmembers to document spatial distribution of surface crust types over time on the Omongwa pan located in the Namibian Kalahari. For this purpose, 49 surface samples were collected for spectral and mineralogical characterization during three field campaigns (2014–2016) reflecting different seasons and surface conditions of the salt pan. An approach was developed to allow the spatiotemporal analysis of the salt pan crust dynamics in a dense time-series consisting of 77 Landsat 8 cloud-free scenes between 2014 and 2017, covering at least three major wet–dry cycles. The established spectral analysis technique Sequential Maximum Angle Convex Cone (SMACC) extraction method was used to derive image endmembers from the Landsat time-series stack. Evaluation of the extracted endmember set revealed that the multispectral data allowed the differentiation of four endmembers associated with mineralogical mixtures of the crust’s composition in dry conditions and three endmembers associated with flooded or muddy pan conditions. The dry crust endmember spectra have been identified in relation to visible, near infrared, and short-wave infrared (VNIR–SWIR) spectroscopy and X-ray diffraction (XRD) analyses of the collected surface samples. According these results, the spectral endmembers are interpreted as efflorescent halite crust, mixed halite–gypsum crust, mixed calcite quartz sepiolite crust, and gypsum crust. For each Landsat scene the spatial distribution of these crust types was mapped with the Spectral Angle Mapper (SAM) method and significant spatiotemporal dynamics of the major surface crust types were observed. Further, the surface crust dynamics were analyzed in comparison with the pan’s moisture regime and other climatic parameters. The results show that the crust dynamics are mainly driven by flooding events in the wet season, but are also influenced by temperature and aeolian activity in the dry season. The approach utilized in this study combines the advantages of multitemporal satellite data for temporal event characterization with advantages from hyperspectral methods for the image and ground data analyses that allow improved mineralogical differentiation and characterization.
Salt pans are highly dynamic environments that are difficult to study by in situ methods because of their harsh climatic conditions and large spatial areas. Remote sensing can help to elucidate their environmental dynamics and provide important constraints regarding their sedimentological, mineralogical, and hydrological evolution. This study utilizes spaceborne multitemporal multispectral optical data combined with spectral endmembers to document spatial distribution of surface crust types over time on the Omongwa pan located in the Namibian Kalahari. For this purpose, 49 surface samples were collected for spectral and mineralogical characterization during three field campaigns (2014–2016) reflecting different seasons and surface conditions of the salt pan. An approach was developed to allow the spatiotemporal analysis of the salt pan crust dynamics in a dense time-series consisting of 77 Landsat 8 cloud-free scenes between 2014 and 2017, covering at least three major wet–dry cycles. The established spectral analysis technique Sequential Maximum Angle Convex Cone (SMACC) extraction method was used to derive image endmembers from the Landsat time-series stack. Evaluation of the extracted endmember set revealed that the multispectral data allowed the differentiation of four endmembers associated with mineralogical mixtures of the crust’s composition in dry conditions and three endmembers associated with flooded or muddy pan conditions. The dry crust endmember spectra have been identified in relation to visible, near infrared, and short-wave infrared (VNIR–SWIR) spectroscopy and X-ray diffraction (XRD) analyses of the collected surface samples. According these results, the spectral endmembers are interpreted as efflorescent halite crust, mixed halite–gypsum crust, mixed calcite quartz sepiolite crust, and gypsum crust. For each Landsat scene the spatial distribution of these crust types was mapped with the Spectral Angle Mapper (SAM) method and significant spatiotemporal dynamics of the major surface crust types were observed. Further, the surface crust dynamics were analyzed in comparison with the pan’s moisture regime and other climatic parameters. The results show that the crust dynamics are mainly driven by flooding events in the wet season, but are also influenced by temperature and aeolian activity in the dry season. The approach utilized in this study combines the advantages of multitemporal satellite data for temporal event characterization with advantages from hyperspectral methods for the image and ground data analyses that allow improved mineralogical differentiation and characterization.
Dispersion-curve inversion of Rayleigh waves to infer subsurface shear-wave velocity is a long-standing problem in seismology. Due to nonlinearity and ill-posedness, sophisticated regularization techniques are required to solve the problem for a stable velocity model. We have formulated the problem as a minimization problem with nonlinear operator constraint and then solve it by using an inexact augmented Lagrangian method, taking advantage of the Haney-Tsai Dix-type relation (a global linear approximation of the nonlinear forward operator). This replaces the original regularized nonlinear problem with iterative minimization of a more tractable regularized linear problem followed by a nonlinear update of the phase velocity (data) in which the update can be performed accurately with any forward modeling engine, for example, the finite-element method. The algorithm allows discretizing the medium with thin layers (for the finite-element method) and thus omitting the layer thicknesses from the unknowns and also allows incorporating arbitrary regularizations to shape the desired velocity model. In this research, we use total variation regularization to retrieve the shear-wave velocity model. We use two synthetic and two real data examples to illustrate the performance of the inversion algorithm with total variation regularization. We find that the method is fast and stable, and it converges to the solution of the original nonlinear problem.
An effective strategy for combining variance- and distribution-based global sensitivity analysis
(2020)
We present a new strategy for performing global sensitivity analysis capable to estimate main and interaction effects from a generic sampling design. The new strategy is based on a meaningful combination of varianceand distribution-based approaches. The strategy is tested on four analytic functions and on a hydrological model. Results show that the analysis is consistent with the state-of-the-art Saltelli/Jansen formula but to better quantify the interaction effect between the input factors when the output distribution is skewed. Moreover, the estimation of the sensitivity indices is much more robust requiring a smaller number of simulations runs. Specific settings and alternative methods that can be integrated in the new strategy are also discussed. Overall, the strategy is considered as a new simple and effective tool for performing global sensitivity analysis that can be easily integrated in any environmental modelling framework.
The regional patterns and timing of the Younger Dryas cooling in the North Atlantic realm were complex and are mechanistically incompletely understood. To enhance understanding of regional climate patterns, we present molecular biomarker records at subannual to annual resolution by mass spectrometry imaging (MSI) of sediments from the Lake Meerfelder Maar covering the Allerod-Younger Dryas transition. These analyses are supported by conventional extraction-based molecular-isotopic analyses, which both validate the imaging results and constrain the sources of the target compounds. The targeted fatty acid biomarkers serve as a gauge of the response of the local aquatic and terrestrial ecosystem to climate change. Based on the comparison of our data with existing data from Meerfelder Maar, we analyse the short-term environmental evolution in Western Europe during the studied time interval and confirm the previously reported delayed hydrological response to Greenland cooling. However, despite a detected delay of Western European environmental change of similar to 135 years, our biomarker data show statistically significant correlation with deuterium excess in Greenland ice core at - annual resolution during this time-transgressive cooling. This suggests a coherent atmospheric forcing across the North Atlantic realm during this transition. We propose that Western European cooling was postponed due to major reorganization of the westerlies that were intermittently forcing warmer and wetter air masses from lower latitudes to Western Europe and thus resulted in delayed cooling relative to Greenland.
The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes.
The Cluster mission has produced a large data set of electron flux measurements in the Earth's magnetosphere since its launch in late 2000. Electron fluxes are measured using Research with Adaptive Particle Imaging Detector (RAPID)/Imaging Electron Spectrometer (IES) detector as a function of energy, pitch angle, spacecraft position, and time. However, no adiabatic invariants have been calculated for Cluster so far. In this paper we present a step-by-step guide to calculations of adiabatic invariants and conversion of the electron flux to phase space density (PSD) in these coordinates. The electron flux is measured in two RAPID/IES energy channels providing pitch angle distribution at energies 39.2-50.5 and 68.1-94.5 keV in nominal mode since 2004. A fitting method allows to expand the conversion of the differential fluxes to the range from 40 to 150 keV. Best data coverage for phase space density in adiabatic invariant coordinates can be obtained for values of second adiabatic invariant, K, similar to 10(2), and values of the first adiabatic invariant mu in the range approximate to 5-20 MeV/G. Furthermore, we describe the production of a new data product "LSTAR," equivalent to the third adiabatic invariant, available through the Cluster Science Archive for years 2001-2018 with 1-min resolution. The produced data set adds to the availability of observations in Earth's radiation belts region and can be used for long-term statistical purposes.
We analyze the spatiotemporal evolution of seismicity during a sequence of moderate (an M-w 4.7 foreshock and M-w 5.8 mainshock) earthquakes occurring in September 2019 at the transition between a creeping and a locked segment of the North Anatolian fault in the central Sea of Marmara, northwest Turkey. To investigate in detail the seismicity evolution, we apply a matched-filter technique to continuous waveforms, thus reducing the magnitude threshold for detection. Sequences of foreshocks preceding the two largest events are clearly seen, exhibiting two different behaviors: a long-term activation of the seismicity along the entire fault segment and a short-term concentration around the epicenters of the large events. We suggest a two-scale preparation phase, with aseismic slip preparing the mainshock final rupture a few days before, and a cascade mechanism leading to the nucleation of the mainshock. Thus, our study shows a combination of seismic and aseismic slip during the foreshock sequence changing the strength of the fault, bringing it closer to failure.
Most South Asian countries have challenges in ensuring water, energy, and food (WEF) security, which are often interacting positively or negatively. To address these challenges, the nexus approach provides a framework to identify the interactions of the WEF sectors as an integrated system. However, most nexus studies only qualitatively discuss the interactions between these sectors. This study conducts a systematic analysis of the WEF security nexus in South Asia by using open data sources at the country scale. We analyze interactions between the WEF sectors statistically, defining positive and negative correlations between the WEF security indicators as synergies and trade-offs, respectively. By creating networks of the synergies and trade-offs, we further identify most positively and negatively influencing indicators in the WEF security nexus. We observe a larger share of trade-offs than synergies within the water and energy sectors and a larger share of synergies than trade-offs among the WEF sectors for South Asia. However, these observations vary across the South Asian countries. Our analysis highlights that strategies on promoting sustainable energy and discouraging fossil fuel use could have overall positive effects on the WEF security nexus in the countries. This study provides evidence for considering the WEF security nexus as an integrated system rather than just a combination of three different sectors or securities.
Other than commonly assumed in seismology, the phase velocity of Rayleigh waves is not necessarily a single-valued function of frequency. In fact, a single Rayleigh mode can exist with three different values of phase velocity at one frequency. We demonstrate this for the first higher mode on a realistic shallow seismic structure of a homogeneous layer of unconsolidated sediments on top of a half-space of solid rock (LOH). In the case of LOH a significant contrast to the half-space is required to produce the phenomenon. In a simpler structure of a homogeneous layer with fixed (rigid) bottom (LFB) the phenomenon exists for values of Poisson's ratio between 0.19 and 0.5 and is most pronounced for P-wave velocity being three times S-wave velocity (Poisson's ratio of 0.4375). A pavement-like structure (PAV) of two layers on top of a half-space produces the multivaluedness for the fundamental mode. Programs for the computation of synthetic dispersion curves are prone to trouble in such cases. Many of them use mode-follower algorithms which loose track of the dispersion curve and miss the multivalued section. We show results for well established programs. Their inability to properly handle these cases might be one reason why the phenomenon of multivaluedness went unnoticed in seismological Rayleigh wave research for so long. For the very same reason methods of dispersion analysis must fail if they imply wave number k(l)(omega) for the lth Rayleigh mode to be a single-valued function of frequency.. This applies in particular to deconvolution methods like phase-matched filters. We demonstrate that a slant-stack analysis fails in the multivalued section, while a Fourier-Bessel transformation captures the complete Rayleigh-wave signal. Waves of finite bandwidth in the multivalued section propagate with positive group-velocity and negative phase-velocity. Their eigenfunctions appear conventional and contain no conspicuous feature.
We study the source properties of the 2005 Kashmir earthquake and its aftershocks to unravel the seismotectonics of the NW Himalayan syntaxis. The mainshock and larger aftershocks have been simultaneously relocated using phase data. We use back-projection of high-frequency energy from multiple teleseismic arrays to model the spatio-temporal evolution of the mainshock rupture. Our analysis reveal a bilateral rupture, which initially propagated SE and then NW of the epicenter, with an average rupture velocity of similar to 2 km s(-1). The area of maximum energy release is parallel to and bound by the surface rupture. Incorporating rupture propagation and velocity, we model the mainshock as a line source using P- and SH-waveform inversion. Our result confirms that the mainshock occurred on a NE dipping (similar to 35 degrees) fault plane, with centroid depth of similar to 10 km. Integrated source time function show that majority of the energy was released in the first similar to 20 s, and was confined above the hypocenter. From waveform inverted fault dimension and seismic moment, we argue that the mainshock had an additional similar to 25 km blind rupture beyond the NW Himalayan syntaxis. Combining this with findings from previous studies, we conjecture that the blind rupture propagated NW of the syntaxis underneath a weak detachment overlain by infra-Cambrian salt layer, and terminated in a wedge thrust. All moderate-to-large aftershocks, NW of the mainshock rupture, are concentrated at the edge of the blind rupture termination. Source modeling of these aftershocks reveal thrust mechanism with centroid depths of 2-10 km, and fault planes oriented subparallel to the mainshock rupture. To study the influence of mainshock rupture on aftershock occurrence, we compute Coulomb failure stress on aftershock faults. All these aftershocks lie in the positive Coulomb stress change region. This suggest that the aftershocks have been triggered by either co-seismic or post-seismic slip on the mainshock fault.
Residential assets, comprising buildings and household contents, are a major source of direct flood losses. Existing damage models are mostly deterministic and limited to particular countries or flood types. Here, we compile building-level losses from Germany, Italy and the Netherlands covering a wide range of fluvial and pluvial flood events. Utilizing a Bayesian network (BN) for continuous variables, we find that relative losses (i.e. loss relative to exposure) to building structure and its contents could be estimated with five variables: water depth, flow velocity, event return period, building usable floor space area and regional disposable income per capita. The model's ability to predict flood losses is validated for the 11 flood events contained in the sample. Predictions for the German and Italian fluvial floods were better than for pluvial floods or the 1993 Meuse river flood. Further, a case study of a 2010 coastal flood in France is used to test the BN model's performance for a type of flood not included in the survey dataset. Overall, the BN model achieved better results than any of 10 alternative damage models for reproducing average losses for the 2010 flood. An additional case study of a 2013 fluvial flood has also shown good performance of the model. The study shows that data from many flood events can be combined to derive most important factors driving flood losses across regions and time, and that resulting damage models could be applied in an open data framework.
The steady increase of ground-motion data not only allows new possibilities but also comes with new challenges in the development of ground-motion models (GMMs). Data classification techniques (e.g., cluster analysis) do not only produce deterministic classifications but also probabilistic classifications (e.g., probabilities for each datum to belong to a given class or cluster). One challenge is the integration of such continuous classification in regressions for GMM development such as the widely used mixed-effects model. We address this issue by introducing an extension of the mixed-effects model to incorporate data weighting. The parameter estimation of the mixed-effects model, that is, fixed-effects coefficients of the GMMs and the random-effects variances, are based on the weighted likelihood function, which also provides analytic uncertainty estimates. The data weighting permits for earthquake classification beyond the classical, expert-driven, binary classification based, for example, on event depth, distance to trench, style of faulting, and fault dip angle. We apply Angular Classification with Expectation-maximization, an algorithm to identify clusters of nodal planes from focal mechanisms to differentiate between, for example, interface- and intraslab-type events. Classification is continuous, that is, no event belongs completely to one class, which is taken into account in the ground-motion modeling. The theoretical framework described in this article allows for a fully automatic calibration of ground-motion models using large databases with automated classification and processing of earthquake and ground-motion data. As an example, we developed a GMM on the basis of the GMM by Montalva et al. (2017) with data from the strong-motion flat file of Bastias and Montalva (2016) with similar to 2400 records from 319 events in the Chilean subduction zone. Our GMM with the data-driven classification is comparable to the expert-classification-based model. Furthermore, the model shows temporal variations of the between-event residuals before and after large earthquakes in the region.
A ground motion logic tree for seismic hazard analysis in the stable cratonic region of Europe
(2020)
Regions of low seismicity present a particular challenge for probabilistic seismic hazard analysis when identifying suitable ground motion models (GMMs) and quantifying their epistemic uncertainty. The 2020 European Seismic Hazard Model adopts a scaled backbone approach to characterise this uncertainty for shallow seismicity in Europe, incorporating region-to-region source and attenuation variability based on European strong motion data. This approach, however, may not be suited to stable cratonic region of northeastern Europe (encompassing Finland, Sweden and the Baltic countries), where exploration of various global geophysical datasets reveals that its crustal properties are distinctly different from the rest of Europe, and are instead more closely represented by those of the Central and Eastern United States. Building upon the suite of models developed by the recent NGA East project, we construct a new scaled backbone ground motion model and calibrate its corresponding epistemic uncertainties. The resulting logic tree is shown to provide comparable hazard outcomes to the epistemic uncertainty modelling strategy adopted for the Eastern United States, despite the different approaches taken. Comparison with previous GMM selections for northeastern Europe, however, highlights key differences in short period accelerations resulting from new assumptions regarding the characteristics of the reference rock and its influence on site amplification.