As a consequence of the rapid growing worldwide seismic data set, a huge variety of automatized data-processing methods have been developed. To perform automatized waveform-based seismological studies aiming for magnitudes or source process inversion, it is crucial to identify network stations with erroneous transfer functions, gain factors, or component orientations. We developed a new tool dedicated to automated station quality control of dense seismic networks and arrays. The python-based AutoStatsQ toolbox uses the pyrocko seismic data-processing environment. The toolbox automatically downloads data and metadata for selected teleseismic events and performs different tests. As a result, relative gain factors, sensor orientation corrections, and reliable frequency bands are computed for all stations in a chosen time period. Relative gain factors are calculated for all stations and events in a time domain based on maximum P-phase amplitudes. A Rayleigh-wave polarization analysis is used to identify deviating sensor orientations. The power spectra of all stations in a given frequency range are compared with synthetic ones, accessing Global Centroid Moment Tensor (CMT) solutions. Frequency ranges of coinciding synthetic and recorded power spectral densities (PSDs) may serve as guidelines for choosing band-pass filters for moment tensor (MT) inversion and help confirm the corner frequency of the instrument. The toolbox was applied to the permanent and temporary AlpArray networks as well as to the denser SWATH-D network, a total of over 750 stations. Stations with significantly deviating gain factors were identified, as well as stations with inverse polarity and misorientations of the horizontal components. The tool can be used to quickly access network quality and to omit or correct stations before MT inversion. Electronic Supplement: List of teleseismic events and tables of median, mean, and standard deviation of relative gain factors, and figures of relative gain factors of all event-station pairs, waveform example showing inverse polarity of horizontal components on ZS.D125, histograms of median, mean, and standard deviation of the correction angles, examples of synthetic and recorded frequency spectra of ZS.D046 and NI.VINO.

Due to increasing demands for irrigation using groundwater as a source there is an urgent need for efficient methods that shed light on the resulting anthropogenic impacts on the connected aquifers. Thus an innovative approach is introduced, that aims to identify predominant geochemical changes in the groundwater system. The approach involves a principal component analysis as a promising tool to disentangle the effects of different impacts and even to give a quantitative assessment of the respective effect strength at each site. The study was applied in an irrigation region of the Nuthe River Basin, State Brandenburg, Northeast Germany. The results identify the negative impacts on the groundwater quality in the aquifer used for irrigation. A decrease of shallow groundwater quality under irrigation due to contamination with fertilizers (NO3, Cl, K, Na) and a slight shift in the redox system is indicated. Beside this direct impact on the shallow groundwater a long-term impact on a deeper groundwater resource could be identified. There is clear evidence, that the contamination is not restricted to the shallow groundwater but that extraction from deeper wells increasingly includes deeper, uncontaminated groundwater resources into the local irrigation cycle. The approach can be used as a basic tool for the adaptation of sustainable agricultural irrigation management strategies.

Small-scale variations in mineral chemistry, textures, and platinum group element (PGE) mineralization were investigated in the Lower and Middle Group chromitite layers LG6, LG6a, MG1, MG2, and MG2 II from vertical drill core profiles at the Thaba mine in the northwestern limb of the Bushveld Complex. We present detailed geochemical profiles of chromite composition and chromite crystal size distribution curves to shed light on the processes of chromite accumulation and textural modification as well as mineralization. Multiple samples within each layer were assayed for PGE concentrations, and the respective platinum group mineral association was determined by mineral liberation analysis (MLA). There is strong evidence for postcumulus changes in the chromitites. The crystal size distribution curves suggest that the primary chromite texture was coarsened by a combination of adcumulus growth and textural equilibration, while compaction of the crystal mush played only a minor role. Mineral compositions were also modified by postcumulus processes, but because of the very high modal amount of chromite and its local preservation in orthopyroxene oikocrysts, that phase retained much primary information. Vertical variations of chromite composition within chromitite layers and from one layer to another do not support the idea of chromite accumulation from crystal-rich slurries or crystal settling from a large magma chamber. Instead, we favor a successive buildup of chromitite layers by repeated injections of relatively thin layers of chromite-saturated magmas, with in situ crystallization occurring at the crystal mush-magma interface. The adcumulus growth of chromite grains to form massive chromitite required addition of Cr to the layers, which we attribute to downward percolation from the overlying magma. The PGE concentrations are elevated in all chromitite layers compared to adjacent silicate rocks and show a systematic increase upward from LG6 (avg 807 ppb Ir + Ru + Rh + Pt + Pd + Au) to MG2 II (avg 2,062 ppb). There are also significant internal variations in all layers, with enrichments at hanging and/or footwalls. The enriched nature of chromitites in PGEs compared to host pyroxenites is a general feature, independent of the layer thickness. The MLA results distinguish two principal groups of PGE mineral associations: the LG6, LG6, and MG1 are dominated by the malanite series, laurite, and PGE sulfarsenides, while the MG2 and MG2 II layers are characterized by laurite and PGE sulfides as well as Pt-Fe-Sn and PGE-Sb-Bi-Pb alloys. Differences in the PGE associations are attributed to postcumulus alteration of the MG2 and MG2 II layer, while the chromitites below, particularly LG6 and LG6a, contain a more pristine association.

Large-magnitude fluid-injection induced seismic events are a potential risk for geothermal energy developments worldwide. One potential risk mitigation measure is the application of cyclic injection schemes. After validation at small (laboratory) and meso (mine) scale, the concept has now been applied for the first time at field scale at the Pohang Enhanced Geothermal System (EGS) site in Korea. From 7 August until 14 August 2017 a total of 1756 m(3) of surface water was injected into Pohang well PX-1 at flow rates between 1 and 10 l s(-1), with a maximum wellhead pressure (WHP) of 22.8 MPa, according to a site-specific cyclic soft stimulation schedule and traffic light system. A total of 52 induced microearthquakes were detected in real-time during and shortly after the injection, the largest of M-w 1.9. After that event a total of 1771 m(3) of water was produced back from the well over roughly 1 month, during which time no larger-magnitude seismic event was observed. The hydraulic data set exhibits pressure-dependent injectivity increase with fracture opening between 15 and 17 MPa WHP, but no significant permanent transmissivity increase was observed. The maximum magnitude of the induced seismicity during the stimulation period was below the target threshold of M-w 2.0 and additional knowledge about the stimulated reservoir was gained. Additionally, the technical feasibility of cyclic injection at field scale was evaluated. The major factors that limited the maximum earthquake magnitude are believed to be: limiting the injected net fluid volume, flowback after the occurrence of the largest induced seismic event, using a cyclic injection scheme, the application of a traffic light system, and including a priori information from previous investigations and operations in the treatment design.

The novel space-borne Global Navigation Satellite System Reflectometry (GNSS-R) technique has recently shown promise in monitoring the ocean state and surface wind speed with high spatial coverage and unprecedented sampling rate. The L-band signals of GNSS are structurally able to provide a higher quality of observations from areas covered by dense clouds and under intense precipitation, compared to those signals at higher frequencies from conventional ocean scatterometers. As a result, studying the inner core of cyclones and improvement of severe weather forecasting and cyclone tracking have turned into the main objectives of GNSS-R satellite missions such as Cyclone Global Navigation Satellite System (CYGNSS). Nevertheless, the rain attenuation impact on GNSS-R wind speed products is not yet well documented. Evaluating the rain attenuation effects on this technique is significant since a small change in the GNSS-R can potentially cause a considerable bias in the resultant wind products at intense wind speeds. Based on both empirical evidence and theory, wind speed is inversely proportional to derived bistatic radar cross section with a natural logarithmic relation, which introduces high condition numbers (similar to ill-posed conditions) at the inversions to high wind speeds. This paper presents an evaluation of the rain signal attenuation impact on the bistatic radar cross section and the derived wind speed. This study is conducted simulating GNSS-R delay-Doppler maps at different rain rates and reflection geometries, considering that an empirical data analysis at extreme wind intensities and rain rates is impossible due to the insufficient number of observations from these severe conditions. Finally, the study demonstrates that at a wind speed of 30 m/s and incidence angle of 30 degrees, rain at rates of 10, 15, and 20 mm/h might cause overestimation as large as approximate to 0.65 m/s (2%), 1.00 m/s (3%), and 1.3 m/s (4%), respectively, which are still smaller than the CYGNSS required uncertainty threshold. The simulations are conducted in a pessimistic condition (severe continuous rainfall below the freezing height and over the entire glistening zone) and the bias is expected to be smaller in size in real environments.