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We have analysed the microseismic activity within the Rwenzori Mountains area in the western branch of the East African Rift. Seismogram recordings from a temporary array of up to 27 stations reveal approximately 800 events per month with local magnitudes ranging from –0.5 to 5.1. The earthquake distribution is highly heterogeneous. The majority of located events lie within faults zones to the east and west of the Rwenzoris with the highest seismic activity observed in the northeastern area, where the mountains are in contact with the rift shoulders. The hypocentral depth distribution exhibits a pronounced peak of seismic energy release at 15 km depth. The maximum extent of seismicity ranges from 20 to 32 km and correlates well with Moho depths that were derived from teleseismic receiver functions. We observe two general features: (i) beneath the rift shoulders, seismicity extends from the surface down to ca. 30 km depth; (ii) beneath the rift valley, seismicity is confined to depths greater than 10 km. From the observations there is no indication for a crustal root beneath the Rwenzori Mountains. The magnitude frequency distribution reveals a b-value of 1.1, which is consistent with the hypothesis that part of the seismicity is caused by magmatic processes within the crust. Fault plane solutions of 304 events were derived from P-polarities and SV/P amplitude ratios. More than 70 % of the source mechanisms exhibit pure or predominantly normal faulting. T-axis trends are highly uniform and oriented WNW–ESE, which is perpendicular to the rift axis and in good agreement with kinematic rift models. At the northernmost part of the region we observe a rotation of the T-axis trends to NEN–SWS, which may be indicative of a local perturbation of the regional stress field.
In this study, we determine spectral characteristics and amplitude decays of wind turbine induced seismic signals in the far field of a wind farm (WF) close to Uettingen, Germany. Average power spectral densities (PSDs) are calculated from 10 min time segments extracted from (up to) 6 months of continuous recordings at 19 seismic stations, positioned along an 8 km profile starting from the WF. We identify seven distinct PSD peaks in the frequency range between 1 and 8 Hz that can be observed to at least 4 km distance; lower-frequency peaks are detectable up to the end of the profile. At distances between 300 m and 4 km the PSD amplitude decay can be described by a power law with exponent b. The measured b values exhibit a linear frequency dependence and range from b=0.39 at 1.14 Hz to b=3.93 at 7.6 Hz. In a second step, the seismic radiation and amplitude decays are modeled using an analytical approach that approximates the surface wave field. Since we observe temporally varying phase differences between seismograms recorded directly at the base of the individual wind turbines (WTs), source signal phase information is included in the modeling approach. We show that phase differences between source signals have significant effects on the seismic radiation pattern and amplitude decays. Therefore, we develop a phase shift elimination method to handle the challenge of choosing representative source characteristics as an input for the modeling. To optimize the fitting of modeled and observed amplitude decay curves, we perform a grid search to constrain the two model parameters, i.e., the seismic shear wave velocity and quality factor. The comparison of modeled and observed amplitude decays for the seven prominent frequencies shows very good agreement and allows the constraint of shear velocities and quality factors for a two-layer model of the subsurface. The approach is generalized to predict amplitude decays and radiation patterns for WFs of arbitrary geometry.
In this study, we determine spectral characteristics and amplitude decays of wind turbine induced seismic signals in the far field of a wind farm (WF) close to Uettingen/Germany. Average power spectral densities (PSD) are calculated from 10 min time segments extracted from (up to) 6-months of continuous recordings at 19 seismic stations, positioned along an 8 km profile starting from the WF. We identify 7 distinct PSD peaks in the frequency range between 1 Hz and 8 Hz that can be observed to at least 4 km distance; lower-frequency peaks are detectable up to the end of the profile. At distances between 300 m and 4 km the PSD amplitude decay can be described by a power law with exponent b. The measured b-values exhibit a linear frequency dependence and range from b = 0.39 at 1.14 Hz to b = 3.93 at 7.6 Hz. In a second step, the seismic radiation and amplitude decays are modeled using an analytical approach which approximates the surface-wave field. Since we observe temporally varying phase differences between seismograms recorded directly at the base of the individual wind turbines (WTs), source-signal phase information is included in the modeling approach. We show that phase differences between source signals have significant effects on the seismic radiation pattern and amplitude decays. Therefore, we develop a phase-shift-elimination-method to handle the challenge of choosing representative source characteristics as an input for the modeling. To optimize the fitting of modeled and observed amplitude decay curves, we perform a grid search to constrain the two model parameters, i.e., the seismic shear wave velocity and quality factor. The comparison of modeled and observed amplitude decays for the 7 prominent frequencies shows very good agreement and allows to constrain shear velocities and quality factors for a two-layer model of the subsurface. The approach is generalized to predict amplitude decays and radiation patterns for WFs of arbitrary geometry.
We have analysed the microseismic activity within the Rwenzori Mountains area in the western branch of the East African Rift. Seismogram recordings from a temporary array of up to 27 stations reveal approximately 800 events per month with local magnitudes ranging from –0.5 to 5.1. The earthquake distribution is highly heterogeneous. The majority of located events lie within faults zones to the East and West of the Rwenzoris with the highest seismic activity observed in the northeastern area, where the mountains are in contact with the rift shoulders. The hypocentral depth distribution exhibits a pronounced peak of seismic energy release at 15 km depth. The maximum extent of seismicity ranges from 20 to 32 km and correlates well with Moho depths that were derived from teleseismic receiver functions. We observe two general features: (i) beneath the rift shoulders seismicity extends from the surface down to ca. 30 km depth; (ii) beneath the rift valley seismicity is confined to depths greater than 10 km. From the observations there is no indication for a crustal root beneath the Rwenzori Mountains. The magnitude frequency distribution reveals a b-value of 1.1, which is consistent with the hypothesis that part of the seismicity is caused by magmatic processes within the crust. Fault plane solutions of 304 events were derived from P-polarities and SV/P amplitude ratios. More than 70 % of the source mechanisms exhibit pure or predominantly normal faulting. T-axis trends are highly uniform and oriented WNW-ESE, which is perpendicular to the rift axis and in good agreement with kinematic rift models. At the northernmost part of the region we observe a rotation of the T-axis trends to NEN-SWS, which may be indicative of a local perturbation of the regional stress field.
Seismic signals produced by wind turbines can have an adverse effect on seismological measurements up to distances of several kilometres. Based on numerical simulations of the emitted seismic wave field, we study the effectivity of seismic borehole installations as a way to reduce the incoming noise. We analyse the signal amplitude as a function of sensor depth and investigate effects of seismic velocities, damping parameters and geological layering in the subsurface. Our numerical approach is validated by real data from borehole installations affected by wind turbines. We demonstrate that a seismic borehole installation with an adequate depth can effectively reduce the impact of seismic noise from wind turbines in comparison to surface installations. Therefore, placing the seismometer at greater depth represents a potentially effective measure to improve or retain the quality of the recordings at a seismic station. However, the advantages of the borehole decrease significantly with increasing signal wavelength.