Local Stations Research Articles

Seismogenic structures and active creep in the Granada Basin (S-Spain)

The Granada Basin is a slowly deforming intramountain basin in the Betic Cordillera (S-Spain). Despite historical and paleoseismological evidence for M6 earthquakes, instrumental seismicity lacks large events and the seismotectonic model must be built from small earthquakes (M < 5). Here, we reanalyze 35 years of data from the Granada Basin short period network, and further seismic stations with shorter operating time, to identify seismogenic structures and understand their relationships. We sort events with similar waveforms into multiplet clusters and perform relative location to image active fault patches. Cluster orientations are used as a priori constraint for inverting focal mechanisms from composite cluster polarity measurements. We further estimate moment tensor solutions from full waveform inversion using local and regional broadband stations. We can identify four groups of structures at different positions in the basin: 1) in the northeast sector, we observe shallow, NW-SE striking, high-angle normal faulting, often related with known fault structures; 2) the southern sector shows high-angle normal faulting on unmapped, ∼E-W striking structures at mid-crustal depths; 3) between both groups, we image sub-horizontal fault patches, associated with the basal detachment beneath the basin, showing SSW transport direction; 4) at the western limit of the basin, we find ∼N-S trending, left-lateral strike-slip faults. Groups 2 and 3 are characterized by clusters with overall constant event production rate, indicating ongoing and largely aseismic creep of the basal detachment over the last 35 years. Seismological evidence suggests a locking depth of ∼10 km and a brittle-ductile transition near 15 km, according to the depth range of clusters in groups 2 and 3.

Characterizing Dust and Biomass Burning Events from Sentinel-2 Imagery

The detection and evaluation of biomass burning and dust events are critical for understanding their impact on air quality, climate, and human health, particularly in the Mediterranean region. This research pioneers an innovative methodology that uses Sentinel-2 multispectral (MS) imagery to meticulously pinpoint and analyze long-transport dust outbreaks and biomass burning phenomena, originating both locally and transported from remote areas. We developed the dust/biomass burning (DBB) composite normalized differential index, a tool that identifies clear, dusty, and biomass burning scenarios in the selected region. The DBB index jointly employs specific Sentinel-2 bands: B2-B3-B4 for visible light analysis, and B11 and B12 for short-wave infrared (SWIR), exploiting the specificity of each wavelength to assess the presence of different aerosols. A key feature of the DBB index is its normalization by the surface reflectance of the scene, which ensures independence from the underlying texture, such as streets and buildings, for urban areas. The differentiation involves the comparison of the top-of-atmosphere (TOA) reflectance values from aerosol events with those from clear-sky reference images, thereby constituting a sort of calibration. The index is tailored for urban settings, where Sentinel-2 imagery provides a decametric spatial resolution and revisit time of 5 days. The average values of DBB achieve a 96% match with the coarse-mode aerosol optical depths (AOD), measured by a local station of the AERONET network of sun-photometers. In future studies, the map of DBB could be integrated with that achieved from Sentinel-3 images, which offer similar spectral bands, albeit with much less fine spatial resolution, yet benefit from daily coverage.

Analysing the impacts of extreme torrential events using multi‐temporal LiDAR datasets—The Schöttlbach catchment, Upper Styria, Austria

AbstractExtreme precipitation events in small alpine catchments trigger hazardous hydro‐geomorphic processes that cause considerable damage to settlements and infrastructure. In summer 2011 and 2017, two flood events mobilizing large amounts of sediments struck the town of Oberwölz (Styria, Austria) located at the outlet of the Schöttlbach catchment. We used data from local weather stations and precipitation radar to analyse the meteorological settings that caused the flooding. We compiled a consistent sediment budget for the 2017 event by combining geomorphic mapping, connectivity analysis, high‐resolution airborne LiDAR (ALS) and uncrewed aerial vehicle (UAV)‐borne LiDAR (ULS), data from other authors for the 2011 event and external information (e.g., event analysis and excavation data). The 2017 event mobilized higher sediment volumes than the 2011 event (131 000 m3 vs 90 000 m3) even though 24‐h precipitation and peak discharges were lower in 2017. First assumptions that the larger sediment output was caused by the reworking of the 2011 flood deposits proved to be incorrect. The impacts of the 2011 event affected the resilience of the geomorphic system resulting in a significantly higher hillslope sediment supply. We conclude that sediment transport in alpine catchments can increase disproportionately when recurrence intervals fall below a critical level.

Nocturnal heat exposure and stroke risk.

In recent decades, nighttime temperatures have increased faster than daytime temperatures. The increasing prevalence of nocturnal heat exposure may pose a significant risk to cardiovascular health. This study investigated the association between nighttime heat exposure and stroke risk in the region of Augsburg, Germany, and examined its temporal variations over 15 years. Hourly meteorological parameters, including mean temperature, relative humidity, and barometric pressure, were acquired from a local meteorological station. A data set was obtained consisting of 11 037 clinical stroke cases diagnosed during warmer months (May to October) between the years 2006 and 2020. The average age of cases was 71.3 years. Among these cases, 642 were identified as haemorrhagic strokes, 7430 were classified as ischaemic strokes, and 2947 were transient ischaemic attacks. A time-stratified case-crossover analysis with a distributed lag non-linear model was used to estimate the stroke risk associated with extreme nighttime heat, as measured by the hot night excess (HNE) index after controlling for the potential confounding effects of daily maximum temperature and other climatic variables. Subgroup analyses by age group, sex, stroke subtype, and stroke severity were performed to identify variations in susceptibility to nighttime heat. Results suggested a significant increase in stroke risk on days with extreme nighttime heat (97.5% percentile of HNE) (odds ratio 1.07, 95% confidence interval 1.01-1.15) during the full study period. When comparing the results for 2013-20 with the results for 2006-12, there was a significant increase (P < .05) in HNE-related risk for all strokes and specifically for ischaemic strokes during the more recent period. Furthermore, older individuals, females, and patients with mild stroke symptoms exhibited a significantly increased vulnerability to nighttime heat. This study found nocturnal heat exposure to be related to elevated stroke risk after controlling for maximum daytime temperature, with increasing susceptibility between 2006 and 2020. These results underscore the importance of considering nocturnal heat as a critical trigger of stroke events in a warming climate.

Sources and distribution of trace elements in surface snow from coastal Zhongshan Station to Dome A (East Antarctica)

The spatial distribution and possible sources of Al, As, Cd, Fe, Mn, Pb, Sb, Ti, V, and Zn were investigated in 120 samples of surface snow collected along a ∼1260 km long traverse from coastal Zhongshan Station to the Antarctic ice sheet summit (Dome A or Dome Argus, at 4093 m a.s.l.). The chemical composition of snow samples was analyzed using microwave-assisted acid treatment with HNO3/HF to determine element concentrations, reflecting their abundance in the Earth's crust. The observed relative concentration pattern of elements in snow suggests a predominant contribution from soil and rock dust particles. The spatial distribution of total element concentrations along the traverse revealed higher values in inland areas compared to coastal areas. The annual deposition flux of elements in each sampling site indicates a significant decreasing trend in Al, Ti, Zn, Fe, Cd, As, and Pb from the coast to inland areas. Significant variations in element concentrations and fluxes observed along the Antarctic traverse suggest a notable influence of distance from the coast on snow deposition patterns. Soil dust from coastal ice-free areas and human activities in scientific stations are the primary sources of analyzed elements in coastal snow, with marine biogenic emissions playing a marginal role, likely contributing to As and Cd. The contribution of sea salt spray to surface snow element concentrations in the East Antarctic traverse is negligible. An analysis of backward trajectories confirmed that long-distance transport from the South American continent and local Antarctic research stations potentially contributes to Antarctic snow elements.

Cropland Microclimate and Leaf-nesting Behavior Shape the Growth of Caterpillar under Future Warming.

Predicting performance responses of insects to climate change is crucial for biodiversity conservation and pest management. While most projections on insects' performance under climate change have used macro-scale weather station data, few incorporated the microclimates within vegetation that insects inhabit and their feeding behaviors (e.g., leaf-nesting: building leaf nests or feeding inside). Here, taking advantage of relatively homogenous vegetation structures in agricultural fields, we built microclimate models to examine fine-scale air temperatures within two important crop systems (maize and rice) and compared microclimate air temperatures to temperatures from weather stations. We deployed physical models of caterpillars and quantified effects of leaf-nesting behavior on operative temperatures of two Lepidoptera pests: Ostrinia furnacalis (Pyralidae) and Cnaphalocrocis medinalis (Crambidae). We built temperature-growth rate curves and predicted the growth rate of caterpillars with and without leaf-nesting behavior based on downscaled microclimate changes under different climate change scenarios. We identified widespread differences between microclimates in our crop systems and air temperatures reported by local weather stations. Leaf-nesting individuals in general had much lower body temperatures compared to non-leaf-nesting individuals. When considering microclimates, we predicted leaf-nesting individuals grow slower compared to non-leaf-nesting individuals with rising temperature. Our findings highlight the importance of considering microclimate and habitat-modifying behavior in predicting performance responses to climate change. Understanding the thermal biology of pests and other insects would allow us to make more accurate projections on crop yields and biodiversity responses to environmental changes.

Validation of satellite-derived solar irradiance datasets: a case study in Saudi Arabia

A robust dataset of Surface Solar Irradiance is essential for secure competitive financing for solar energy projects. Rating agencies and lenders alike require verification of the solar-resource dataset for utilizing each solar energy project, as this can be translated directly into expected electrical energy and revenues. The accuracy of the dataset and the variability of solar radiation, as recorded by historical solar data, play a significant role in estimating the future performance of the project and its budget. The historical observed solar irradiance datasets by local stations are the best and most reliable for a specific site, but they are not always available for long and continuous periods in any location, especially in arid areas. So, the importance of historical solar radiation datasets derived from satellite-based models arises here. This paper validates the historical modeled datasets of the three most famous satellite-based commercial prediction models (SolarGIS, SUNY, and Solcast) against the observed dataset by six ground stations in Saudi Arabia under different climatic zones. The validation method has been implemented using the standard error metrics: Maximum Absolute Error (MAE) and relative Maximum Bias Error (rMBE). The validation process showed that, in the case of GHI, the discrepancy between observed and predicted values is narrow, while in the case of DNI, the discrepancy is wide. Also, the predicted GHI values are more accurate than predicted DNI values, and -in general- the values predicted by the SUNY model are less accurate than those predicted by SolarGIS and Solcast models for both GHI and DNI. The resultant of this validation process could be accepted not for the six locations under study only but, also for deserts and arid areas across Saudi Arabia and might be extended to similar arid areas around the world.

Urban microclimate prediction based on weather station data and artificial neural network

Urban microclimate has a significant impact on building energy consumption. Building energy modeling (BEM) requires accurate local weather conditions near a target building, whereas Typical Meteorological Year (TMY) weather inputs often use remote airport weather data. An artificial neural network (ANN) model is presented in this study to predict urban microclimates based on long-term measurements from local weather stations near urban buildings and their significance in analyzing building energy consumption. By utilizing only a few months of data, the ANN model could connect local and remote meteorological parameters for a whole year. The 20-year historical weather data at the airport was then used to generate a local TMY. Based on the original and local TMYs, this study compared building heating and cooling loads. This method was evaluated for five weather stations within the city of Montreal to assess the impact of the local microclimate on the energy consumption of buildings. Based on locations, urban microclimate contributed to an additional 2 % to 14 % cooling energy consumption and a reduction of 1 % to 10 % winter heating energy consumption.

Dune behavior in the Source Area of the Yellow River under climate changes observed from various remote sensing datasets

Sand dunes are a landscape feature with a quick response time to climate change and human influences (e.g. grazing, greening projects, and fixation structures). Their migration rates and their development can help to gather information about changing environmental conditions over time. The Source Area of the Yellow River (SAYR), located upon the Tibetan Plateau, is highly complex with topographical, hydrological, and climatological influences on active dunes, making it a good study area for these interactions. Based on remote sensing datasets, spanning the last 54 years, 415 dunes were mapped for migration rate calculations. Further, climate data from ERA-5 reanalysis and a local climate station was used to assess their changes within a changing climate. Generally, dune migration rates are rather slow with an average of 3.62 m y-1. In accordance, the averaged resultant drift potential (RDP) values are lower than 10 m3/s−3(−|-). Further, we assessed the density development of the main active barchan dune field in direct premise of the Yellow River. Throughout the past 54 years, we observed the emergence of more than 5 new barchans per square kilometer. This increase is likely attributed to higher sand flux from the Yellow River, which has resulted from increased discharge due to declining snowfall and rising precipitation levels.

A Study on the People's Character of Chinese TV Drama in the New Era

With the arrival of the new era, the creation of TV dramas should keep up with the pace of the times, and fully reflect the expression of the people's character based on the creative concept of putting the people at the center under the premise of the needs of the times. As a mainstream media, television stations should adhere to the principle of people-orientation when creating television literature and art. It is not only a basic principle that local broadcasting and television stations need to follow, but also a mission and responsibility that the media needs to undertake. Therefore, TV drama directors should actively create TV dramas that are truly close to the masses, society, and life, fully reflecting the influence of a "cultural power".

Battery Management System Using IoT

Abstract: This study presents an Arduino-based system for advising users of nearby EV stations and tracking the status of their automobile batteries. The MQ-2 gas sensor, DHT11 temperature sensor, and DC voltage sensor are the three main sensors that the system interfaces with through the use of an Arduino Uno microcontroller as the central controller. When the battery temperature rises over safe limits, the DHT11 sensor monitors it and sends out alarms. By detecting gases being released into the atmosphere, the MQ-2 gas sensor warns customers of possible battery problems. Through the use of a Java web application, the DC voltage sensor suggests local EV stations and notifies users when levels are low. The sensor measures voltage and percentage. By delivering timely alerts and making charging facilities easier to use, this integrated solution raises user awareness of battery health and promotes safer driving. By fusing Arduino technology with sensor data and web application capability, it illustrates how IoT can be used practically in the automotive industry.

Seismicity and Focal Mechanism Analysis of The Local Earthquakes in the Zagros Fold-Thrust Belt of the Iraqi Kurdistan Region

During the period of 2020 to May 2022, the Iraqi Kurdistan region experienced several small to moderate size earthquakes. The seismic waveform data of these earthquakes were collected from regional and local broadband seismic stations. Waveform data was analyzed for seventy earthquakes to determine their source parameters, which may contribute to the active tectonics in those areas. Moment tensor inversion is estimated for the detected local earthquakes by analysis of observed seismic waveforms in different selected areas. The waveform inversion determines the seismic moment, depth, and kind of rupturing fault at the source. A grid search is employed as part of the inversion procedure across the strike, dip, and rake angles for each depth between 0.5 and 40 Km in increments of 1 Km. Waveform modeling is used to correlate the observed and created waveforms by applying bandpass filters and a suitable velocity model for Green's function using computer programs in seismology and the ISOLA code" Isolated asperities" for multiple-point source modeling. The results show that the earthquakes with M ≥ 4 have a focal depth ranging between 7 and 20 Km. Furthermore, the regional stresses were identified and the mechanism for the optimum fit was determined. The source mechanisms in the study area are most likely a combination of strike-slip, oblique-slip, and thrust.

Vineyard Microclimatic Zoning as a Tool to Promote Sustainable Viticulture under Climate Change

Understanding microclimate spatial variability is crucial for sustainable and optimised grape production within vineyard plots. By employing a combination of a microclimate model (NicheMapR) and multiple climate data sources, this study aimed to achieve microclimatic analysis in two vineyard plots, Quinta do Bomfim (northern Portugal) and Herdade do Esporão (southern Portugal). This approach provides an innovative 10 m spatial resolution for climate variables. This study incorporated local station hourly data with quantile mapping bias correction on the ERA5-land data. The microclimate model output was employed to perform bias correction on a EURO-CORDEX model ensemble. Climate extreme and bioclimatic indices specifically targeted to viticulture were calculated for each vineyard plot. The 10 m scale was analysed to identify potential shifts in temperature extremes, precipitation patterns, and other crucial climatic variables for grape cultivation within each specific plot. The significance of microclimate analyses was higher in areas with intricate topography, while in areas with smooth slopes, the variation of climatic variables was determined to be negligible. There was a projected increase in the median temperature of approximately 3.5 °C and 3.6 °C and a decrease in precipitation of approximately 98 mm and 105 mm in Quinta do Bomfim and Herdade do Esporão, respectively, when comparing a future scenario for the period 2071–2100 against the historical period (1981–2010). Hence, this study offers a comprehensive and future-oriented method for analysing microclimates in vineyard plots. By incorporating geospatial data, ERA5-land data, and the microclimate NicheMapR model, this research aimed to enhance the understanding of current microclimates and future climate scenarios for viticulturists.

ICT acceptance, language use and information culture as tools for enhancing information literacy within smallholder maize farmers in Uganda

PurposeThis study aims to examine the relationship between tool adoption and information literacy within smallholder farmers (SHFs).Design/methodology/approachA structured questionnaire was used to gather data for this quantitative study from 225 SHFs. Structural equation modelling was done to test the hypotheses.FindingsThe findings established that tool adoption dimensions (Information and communication technologies (ICT) acceptance, language use and information culture) positively and significantly influenced information literacy. Information culture had the strongest impact.Research limitations/implicationsThe study enriches the situated learning theory (SLT) literature by introducing tool adoption as a predictor of information literacy in a new context of SHFs. Use of tools as independent variables is a positive deviation from previous studies that have used them as mediating variables. Despite the contributions, the cross-sectional design study undermines the ability to solicit more detailed perspectives from the lived in experience of the respondents.Practical implicationsManagers should promote usage of context-specific tools like local radio stations and mobile phones, but also use language tailored to farmer contexts when disseminating information. Policymakers should leverage on social and cultural settings when designing information interventions.Social implicationsThe study highlights critical factors that significantly promote information use for improved productivity for SHFs, cumulatively increasing the country’s gross domestic product (GDP). Socially, findings may reduce on their poverty levels of farmers.Originality/valueThis study offers a novel perspective in information literacy domain by using the SLT to delineate contextual tools that are paramount in predicting of information literacy in an under research informal context of SHFs.

The news hour: Welfare estimation in the market for local television news

We estimate the welfare consequences of local news broadcasting decisions in advertiser-funded television, a central question in media regulation. We model programming decisions as the outcome of a discrete game played by rival stations competing for advertising revenue (which depends on viewing) by choosing lineups of local news and entertainment broadcasts. Using program-level data on television viewing and advertising prices, we find modest under-provision of local news relative to the level that maximizes television viewing. Counterfactual simulations indicate an average deficit of 7.4 broadcasts per market, or 12.8% of local station broadcasts during the evening news hours. Most of this shortfall is in the 7:30 timeslot leading into prime time. We distinguish two sources of inefficiency: losses due to advertiser valuation of local news and entertainment viewers, and losses from classic business stealing. Losses from competition represent about one third of the estimated shortfall, suggesting gains to cooperation among competing stations.

Post-Pandemic Hiring Practices and Skills Requested by Local U.S. TV Stations

ABSTRACT Job ads are meant to capture the daily responsibilities of the position, as well as let candidates know the skills and qualities the right candidate for the job needs to demonstrate from the employer’s perspective. While Aupperle and Grzeslo (2020) studied job ads of legacy media stations, Deavours and Grzeslo (2020) were among the first to explore local broadcast television station job ads. Yet, after the “Great Resignation” following the COVID-19 pandemic, as well as recent technology and business model changes, researchers need to continue to update and monitor the rapidly evolving needs of local newsrooms. This study seeks to provide insight through a content analysis of job postings from U.S. local television stations, exploring the experience, skills, and experience requirements necessary to be competitive in today’s market, while also looking at how companies are working harder to attract talent. Using the theoretical lens of skills theory of leadership, the study also provides insight in hiring differences in station ownership, market size, and position type. Through content analysis of 349 job ads from 21 local news Designated Market Areas, findings suggest the field is embracing more convergent, digital reporting tactics, while still emphasizing the foundations of broadcast writing and visual storytelling. However, some of the most dramatic shifts in the industry toward innovation, emerging media, digital legal and ethical skills, and diversity are not reflected in job ads, creating little guidance for individuals and educators on how to prepare for an ever-changing job market.

Development of GNSS measurement models with the use of base stations and radio modules

Global navigation satellite systems (GNSS) historically been known as one of the newest technologies since the 1970s. GNSS originally developed for military purposes in the USA (GPS – Global Position System). There are several satellite systems in the world. Satelites, International Research Base Stations, regional/national and local base stations form a permanent geodetic frame. Research on the size and shape of the Earth-planet, climate, sea, urban planning. In geodesy, a network of global positioning base stations makes it possible to asses the movements of continents, land plates at international level. GNSS is an important technology in navigation, logistics, economics, land surveying and other “geo” sectors. GNSS equipment/receivers and their manufacturers are applying new designs and electronics. Initially GNSS instruments used with single frequency signal reception, later expanding the number of GNSS signal channels to two frequencies. Such technological improvements nowadays improve the certainty, reliability and accuracy – the overall quality – of GNSS measurements. The GNSS base station enables the surveyors, other user’s GNSS receiver to determine coordinates with an accuracy of two centimeters in real time (RTK) and with an accuracy of five millimetres using the accumulated post-processing data. Various types of factors hamper GNSS measurements. The GNSS signal (radio wave) travels in airspace, in urban environments and is a physical parameter. Any obstacle – tree, building walls, and atmospheric effect – makes GNSS measurements less accurate. The GNSS signal must be strong and free from attenuation and suppression effects. This study develops GNSS models that show the comparison, certainty and reliability of GNSS measurements using different types of GNSS techniques. Evaluation of Latvian Global Positioning Reference Station Network – LatPos system measurements against a corresponding RTK solution method using Latvian Global Positioning Network geodetic point (G2 class).

Eksistensi Radio Melalui Konvergensi Siaran di Era Digital

Radio is a communication medium that must now be able to compete with new media which is currently increasingly massive. The aim of this research is to find out how national private broadcast radio in West Java is able to maintain its existence and the strategies it implements to continue to exist amidst competition with digital information platforms that currently exist. Research respondents were managers of local radio stations in West Java, especially those in Bandung, Cimahi, Sukabumi and Cirebon. This research uses qualitative methods by describing the result of questioners and interviewing and then processing them in the form of descriptive narratives and pie diagram. The results of this research are that almost all private broadcast radio stations in the West Java region that were respondents implemented a convergence strategy to maintain their existence and made changes to their broadcast model management. Some of the convergence strategies implemented are broadcasting via digital streaming, creating more interesting broadcast program content with an audio-visual style such as podcasts, choosing broadcasters who have popularity and character, upgrading broadcast equipment, having social media as a branding and content publication medium, and upload content to YouTube media. This convergence strategy is also carried out to increase interest and the number of advertisers so that they can continue to choose radio as a medium for marketing the products and services offered more widely and in a contemporary style.

Exploring the feasibility of Support Vector Machine for short-term hydrological forecasting in South Tyrol: challenges and prospects

Short-term hydrological forecasting is crucial for suitable multipurpose water resource management involving water uses, hydrological security, and renewable production. In the Alpine Regions such as South Tyrol, characterized by several small watersheds, quick information is essential to feed the decision processes in critical cases such as flood events. Predicting water availability ahead is equally crucial for optimizing resource utilization, such as irrigation or snow-making. The increasing data availability and computational power led to data-driven models becoming a serious alternative to physically based hydrological models, especially in complex conditions such as the Alpine Region and for short predictive horizons. This paper proposes a data-driven pipeline to use the local ground station data to infer information in a Support Vector Regression model, which can forecast streamflow in the main closure points of the area at hourly resolution with 48 h of lead time. The main steps of the pipeline are analysed and discussed, with promising results that depend on available information, watershed complexity, and human interactions in the catchment. The presented pipeline, as it stands, offers an accessible tool for integrating these models into decision-making processes to guarantee real-time streamflow information at several points of the hydrological network. Discussion enhances the potentialities, open challenges, and prospects of short-term streamflow forecasting to accommodate broader studies.

Post-collisional lithospheric delamination in eastern Iran, revealed by non-linear teleseismic tomography and residual topography

The Eastern Iranian Mountain Ranges (EIR) emerged as a consequence of the Late Cretaceous collision between the Afghan and Lut blocks. However, the response of the uppermost mantle to this collision remains enigmatic. Additionally, although petrological evidence suggests that post-collisional delamination is possible, it has not been conclusively identified in prior regional seismic imagery. This observation leads us to further explore this possibility using a dense seismic network. To gain insight into the geodynamic implications for eastern Iran and address knowledge gaps, we extensively investigated the seismic structure of the uppermost mantle beneath the EIR using a dense seismic network of 34 temporary stations, complemented by data from nine additional local permanent stations. By meticulously analyzing 6589 relative arrival time residuals from teleseismic records with favorable signal-to-noise ratios, we applied a non-linear tomography method to map P-wave velocity perturbations in a relative sense. Our tomographic images unveiled distinct instances of rapid high-velocity anomalies beneath low-velocity regions in the shallow mantle, suggesting the potential occurrence of lithospheric dripping, followed by subsequent asthenospheric upwelling. This observation offers a plausible explanation for the observed post-collisional magmatism over the Lut Block. Furthermore, to maintain the approximately 1.5-km positive residual topography across the EIR, beyond the influence of crustal properties, additional support from the hot and buoyant asthenosphere becomes crucial, particularly in the absence of a substantial lithospheric mantle.