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Changes in the steepness of river profiles or abrupt vertical steps (i.e. waterfalls) are thought to be indicative of changes in erosion rates, lithology or other factors that affect landscape evolution. These changes are referred to as knickpoints or knickzones and are pervasive in bedrock river systems. Such features are thought to reveal information about landscape evolution and patterns of erosion, and therefore their locations are often reported in the geomorphic literature. It is imperative that studies reporting knickpoints and knickzones use a reproducible method of quantifying their locations, as their number and spatial distribution play an important role in interpreting tectonically active landscapes. In this contribution we introduce a reproducible knickpoint and knickzone extraction algorithm that uses river profiles transformed by integrating drainage area along channel length (the so-called integral or chi method). The profile is then statistically segmented and the differing slopes and step changes in the elevations of these segments are used to identify knickpoints, knickzones and their relative magnitudes. The output locations of identified knickpoints and knickzones compare favourably with human mapping: we test the method on Santa Cruz Island, CA, using previously reported knickzones and also test the method against a new dataset from the Quadrilatero Ferrifero in Brazil. The algorithm allows for the extraction of varying knickpoint morphologies, including stepped, positive slope-break (concave upward) and negative slope-break knickpoints. We identify parameters that most affect the resulting knickpoint and knickzone locations and provide guidance for both usage and outputs of the method to produce reproducible knickpoint datasets.
The Seismic Hazard Inferred from Tectonics based on the Global Strain Rate Map (SHIFT_GSRM) earthquake forecast was designed to provide high-resolution estimates of global shallow seismicity to be used in seismic hazard assessment. This model combines geodetic strain rates with global earthquake parameters to characterize long-term rates of seismic moment and earthquake activity. Although SHIFT_GSRM properly computes seismicity rates in seismically active continental regions, it underestimates earthquake rates in subduction zones by an average factor of approximately 3. We present a complementary method to SHIFT_GSRM to more accurately forecast earthquake rates in 37 subduction segments, based on the conservation of moment principle and the use of regional interface seismicity parameters, such as subduction dip angles, corner magnitudes, and coupled seismogenic thicknesses. In seven progressive steps, we find that SHIFT_GSRM earthquake-rate underpredictions are mainly due to the utilization of a global probability function of seismic moment release that poorly captures the great variability among subduction megathrust interfaces. Retrospective test results show that the forecast is consistent with the observations during the 1 January 1977 to 31 December 2014 period. Moreover, successful pseudoprospective evaluations for the 1 January 2015 to 31 December 2018 period demonstrate the power of the regionalized earthquake model to properly estimate subduction-zone seismicity.
Dynamic earthquake rupture modeling provides information on the rupture physics as the rupture velocity, frictions or tractions acting during the rupture process. Nevertheless, as often based on spatial gridded preset geometries, dynamic modeling is depending on many free parameters leading to both a high non-uniqueness of the results and large computation times. That decreases the possibilities of full Bayesian error analysis.
To assess the named problems we developed the quasi-dynamic rupture model which is presented in this work. It combines the kinematic Eikonal rupture model with a boundary element method for quasi-static slip calculation.
The orientation of the modeled rupture plane is defined by a previously performed moment tensor inversion. The simultanously inverted scalar seismic moment allows an estimation of the extension of the rupture. The modeled rupture plane is discretized by a set of rectangular boundary elements. For each boundary element an applied traction vector is defined as the boundary value.
For insights in the dynamic rupture behaviour the rupture front propagation is calculated for incremental time steps based on the 2D Eikonal equation. The needed location-dependent rupture velocity field is assumed to scale linearly with a layered shear wave velocity field.
At each time all boundary elements enclosed within the rupture front are used to calculate the quasi-static slip distribution. Neither friction nor stress propagation are considered. Therefore the algorithm is assumed to be “quasi-static”. A series of the resulting quasi-static slip snapshots can be used as a quasi-dynamic model of the rupture process.
As many a priori information is used from the earth model (shear wave velocity and elastic parameters) and the moment tensor inversion (rupture extension and orientation) our model is depending on few free parameters as the traction field, the linear factor between rupture and shear wave velocity and the nucleation point and time. Hence stable and fast modeling results are obtained as proven from the comparison to different infinite and finite static crack solutions.
First dynamic applications show promissing results. The location-dependent rise time is automatically derived by the model. Different simple kinematic models as the slip-pulse or the penny-shaped crack model can be reproduced as well as their corresponding slip rate functions. A source time function (STF) approximation calculated from the cumulative sum of moment rates of each boundary element gives results similar to theoretical and empirical known STFs.
The model was also applied to the 2015 Illapel earthquake. Using a simple rectangular rupture geometry and a 2-layered traction regime yields good estimates of both the rupture front propagation and the slip patterns which are comparable to literature results. The STF approximation shows a good fit with previously published STFs.
The quasi-dynamic rupture model is hence able to fastly calculate reproducable slip results. That allows to test full Bayesian error analysis in the future. Further work on a full seismic source inversion or even a traction field inversion can also extend the scope of our model.
The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the onthe-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit - Pyrocko-GF - that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.
Flow accumulation algorithms estimate the steady state of flow on real or modeled topographic surfaces and are crucial for hydrological and geomorphological assessments, including delineation of river networks, drainage basins, and sediment transport processes. Existing flow accumulation algorithms are typically designed to compute flows on regular grids and are not directly applicable to arbitrarily sampled topographic data such as lidar point clouds. In this study we present a random sampling scheme that generates homogeneous point densities, in combination with a novel flow path tracing approach-the Facet-Flow Network (FFN)-that estimates flow accumulation in terms of specific catchment area (SCA) on triangulated surfaces. The random sampling minimizes biases due to spatial sampling and the FFN allows for direct flow estimation from point clouds. We validate our approach on a Gaussian hill surface and study the convergence of its SCA compared to the analytical solution. Here, our algorithm outperforms the multiple flow direction algorithm, which is optimized for divergent surfaces. We also compute the SCA of a 6-km(2)-steep, vegetated catchment on Santa Cruz Island, California, based on airborne lidar point-cloud data. Point-cloud-based SCA values estimated by our method compare well with those estimated by the D-infinity or multiple flow direction algorithm on gridded data. The advantage of computing SCA from point clouds becomes relevant especially for divergent topography and for small drainage areas: These are depicted with much more detail due to the higher sampling density of point clouds.
Frequent and intense rainfall events demand innovative techniques to better predict the extreme rainfall dynamics. This task requires essentially the assessment of the basic types of atmospheric processes that trigger extreme rainfall, and then to examine the differences between those processes, which may help to identify key patterns to improve predictive algorithms. We employ tools from network theory to compare the spatial features of extreme rainfall over the Japanese archipelago and surrounding areas caused by two atmospheric processes: the Baiu front, which occurs mainly in June and July (JJ), and the tropical storms from August to November (ASON). We infer from complex networks of satellite-derived rainfall data, which are based on the nonlinear correlation measure of event synchronization. We compare the spatial scales involved in both systems and identify different regions which receive rainfall due to the large spatial scale of the Baiu and tropical storm systems. We observed that the spatial scales involved in the Baiu driven rainfall extremes, including the synoptic processes behind the frontal development, are larger than tropical storms, which even have long tracks during extratropical transitions. We further delineate regions of coherent rainfall during the two seasons based on network communities, identifying the horizontal (east-west) rainfall bands during JJ over the Japanese archipelago, while during ASON these bands align with the island arc of Japan.
Ancient evaporite deposits are geological archives of depositional environments characterized by a long‐term negative precipitation balance and bear evidence for global ocean element mass balance calculations. Here, Cretaceous selenite pseudomorphs from western Anatolia (‘Rosetta Marble’) — characterized by their exceptional morphological preservation — and their ‘marine’ geochemical signatures are described and interpreted in a process‐oriented context. These rocks recorded Late Cretaceous high‐pressure/low‐temperature, subduction‐related metamorphism with peak conditions of 1·0 to 1·2 GPa and 300 to 400°C. Metre‐scale, rock‐forming radiating rods, now present as fibrous calcite marble, clearly point to selenitic gypsum as the precursor mineral. Stratigraphic successions are recorded along a reconstructed proximal to distal transect. The cyclical alternation of selenite beds and radiolarian ribbon‐bedded cherts in the distal portions are interpreted as a two type of seawater system. During arid intervals, shallow marine brines cascaded downward into basinal settings and induced precipitation. During more humid times, upwelling‐induced radiolarian blooms caused the deposition of radiolarite facies. Interestingly, there is no comparable depositional setting known from the Cenozoic world. Meta‐selenite geochemical data (δ13C, δ18O and 87Sr/86Sr) plot within the range of reconstructed middle Cretaceous seawater signatures. Possible sources for the 13C‐enriched (mean 2·2‰) values include methanogenesis, gas hydrates and cold seep fluid exhalation. Spatially resolved component‐specific analysis of a rock slab displays isotopic variances between meta‐selenite crystals (mean δ13C 2·2‰) and host matrix (mean δ13C 1·3‰). The Cretaceous evaporite‐pseudomorphs of Anatolia represent a basin wide event coeval with the Aptian evaporites of the Proto‐Atlantic and the pseudomorphs share many attributes, including lateral distribution of 600 km and stratigraphic thickness of 1·5 to 2·0 km, with the evaporites formed during the younger Messinian salinity crisis. The Rosetta Marble of Anatolia may represent the best‐preserved selenite pseudomorphs worldwide and have a clear potential to act as a template for the study of meta‐selenite in deep time.
Growing attention to phytoplankton mixotrophy as a trophic strategy has led to significant revisions of traditional pelagic food web models and ecosystem functioning. Although some empirical estimates of mixotrophy do exist, a much broader set of in situ measurements are required to (i) identify which organisms are acting as mixotrophs in real time and to (ii) assess the contribution of their heterotrophy to biogeochemical cycling. Estimates are needed through time and across space to evaluate which environmental conditions or habitats favour mixotrophy: conditions still largely unknown. We review methodologies currently available to plankton ecologists to undertake estimates of plankton mixotrophy, in particular nanophytoplankton phago-mixotrophy. Methods are based largely on fluorescent or isotopic tracers, but also take advantage of genomics to identify phylotypes and function. We also suggest novel methods on the cusp of use for phago-mixotrophy assessment, including single-cell measurements improving our capacity to estimate mixotrophic activity and rates in wild plankton communities down to the single-cell level. Future methods will benefit from advances in nanotechnology, micromanipulation and microscopy combined with stable isotope and genomic methodologies. Improved estimates of mixotrophy will enable more reliable models to predict changes in food web structure and biogeochemical flows in a rapidly changing world.
Advances in the field of seismic interferometry have provided a basic theoretical interpretation to the full spectrum of the microtremor horizontal-to-vertical spectral ratio [H/V(f)]. The interpretation has been applied to ambient seismic noise data recorded both at the surface and at depth. The new algorithm, based on the diffuse wavefield assumption, has been used in inversion schemes to estimate seismic wave velocity profiles that are useful input information for engineering and exploration seismology both for earthquake hazard estimation and to characterize surficial sediments. However, until now, the developed algorithms are only suitable for on land environments with no offshore consideration. Here, the microtremor H/V(z, f) modelling is extended for applications to marine sedimentary environments for a 1-D layered medium. The layer propagator matrix formulation is used for the computation of the required Green’s functions. Therefore, in the presence of a water layer on top, the propagator matrix for the uppermost layer is defined to account for the properties of the water column. As an application example we analyse eight simple canonical layered earth models. Frequencies ranging from 0.2 to 50 Hz are considered as they cover a broad wavelength interval and aid in practice to investigate subsurface structures in the depth range from a few meters to a few hundreds of meters. Results show a marginal variation of 8 per cent at most for the fundamental frequency when a water layer is present. The water layer leads to variations in H/V peak amplitude of up to 50 per cent atop the solid layers.
The Upper Cretaceous (Campanian-Maastrichtian) bioclastic wedge of the Orfento Formation in the Montagna della Maiella, Italy, is compared to newly discovered contourite drifts in the Maldives. Like the drift deposits in the Maldives, the Orfento Formation fills a channel and builds a Miocene delta-shaped and mounded sedimentary body in the basin that is similar in size to the approximately 350 km(2) large coarse-grained bioclastic Miocene delta drifts in the Maldives. The composition of the bioclastic wedge of the Orfento Formation is also exclusively bioclastic debris sourced from the shallow-water areas and reworked clasts of the Orfento Formation itself. In the near mud-free succession, age-diagnostic fossils are sparse. The depositional textures vary from wackestone to float-rudstone and breccia/conglomerates, but rocks with grainstone and rudstone textures are the most common facies. In the channel, lensoid convex-upward breccias, cross-cutting channelized beds and thick grainstone lobes with abundant scours indicate alternating erosion and deposition from a high-energy current. In the basin, the mounded sedimentary body contains lobes with a divergent progradational geometry. The lobes are built by decametre thick composite megabeds consisting of sigmoidal clinoforms that typically have a channelized topset, a grainy foreset and a fine-grained bottomset with abundant irregular angular clasts. Up to 30 m thick channels filled with intraformational breccias and coarse grainstones pinch out downslope between the megabeds. In the distal portion of the wedge, stacked grainstone beds with foresets and reworked intraclasts document continuous sediment reworking and migration. The bioclastic wedge of the Orfento Formation has been variously interpreted as a succession of sea-level controlled slope deposits, a shoaling shoreface complex, or a carbonate tidal delta. Current-controlled delta drifts in the Maldives, however, offer a new interpretation because of their similarity in architecture and composition. These similarities include: (i) a feeder channel opening into the basin; (ii) an excavation moat at the exit of the channel; (iii) an overall mounded geometry with an apex that is in shallower water depth than the source channel; (iv) progradation of stacked lobes; (v) channels that pinch out in a basinward direction; and (vi) smaller channelized intervals that are arranged in a radial pattern. As a result, the Upper Cretaceous (Campanian-Maastrichtian) bioclastic wedge of the Orfento Formation in the Montagna della Maiella, Italy, is here interpreted as a carbonate delta drift.