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Abstract Urban karst geology poses significant geohazard risks, most notably sinkholes and surface depression stemming from soluble and fractured bedrock that is prone to dissolution and collapse. However, mapping and characterizing these hazards using traditional geophysical surveys in cities is challenging due to dense infrastructure and high levels of human activity. In this work, we demonstrate how distributed acoustic sensing (DAS), deployed via preexisting telecommunication fiber‐optic cables, can be leveraged to detect fractured weak zones in a populated setting. By recording traffic noises, we are able to conduct large‐scale, cost‐effective, and minimally intrusive subsurface investigations. Our workflow integrates ambient noise interferometry with advanced signal enhancement techniques, specifically frequency‐wavenumber (F‐K) filtering and bin‐offset stacking. F‐K filtering isolates wavefields traveling in opposite directions to suppress localized noise, while bin‐offset stacking further enhances signal coherency by superposing channels with common offsets. The resulting Noise Cross‐correlation Functions exhibit unique inverse‐dispersion patterns that signify the presence of leaky surface waves generated by a low‐velocity half‐space. We invert the corresponding dispersion curves to derive a 2D S‐wave velocity model, highlighting a prominent low‐velocity anomaly indicative of a fractured zone. To confirm the karstic nature of this anomaly, rock physics modeling is employed to estimate spatial variations in fracture density, revealing marked heterogeneity in the fractured zone. Our findings underscore the power of DAS‐based ambient noise interferometry for delineating karst features and diagnosing potential sinkhole risks in urban environments. By exploiting widely available fiber‐optic networks, this approach significantly broadens the practicality of near‐surface geohazard mapping at the city scale. 

Seismic imaging and monitoring of the near-surface structure are crucial for the sustainable development of urban areas. However, standard seismic surveys based on cabled or autonomous geophone arrays are expensive and hard to adapt to noisy metropolitan environments. Distributed acoustic sensing (DAS) with pre-existing telecom fiber optic cables, together with seismic ambient noise interferometry, have the potential to fulfill this gap. However, a detailed noise wavefield characterization is needed before retrievingcoherent waves from chaotic noise sources. We analyze local seismic ambient noise by tracking five-month changes in signal-to-noise ratio (SNR) of Rayleigh surface wave estimated from traffic noise recorded by DAS along the straight university campus busy road. We apply the seismic interferometry method to the 800 m long part of the Penn State Fiber-Optic For Environment Sensing (FORESEE) array. We evaluate the 160 virtual shot gathers (VSGs) by determining the SNR using the slant-stack technique. We observe strong SNR variations in time and space. We notice higher SNR for virtual source points close to road obstacles. The spatial noise distribution confirms that noise energy focuses mainly on bumps and utility holes. We also see the destructive impact of precipitation, pedestrian traffic, and traffic along main intersections on VSGs. A similar processing workflow can be applied to various straight roadside fiber optic arrays in metropolitan areas. 

Two major barriers hinder the holistic understanding of subsurface critical zone (CZ) evolution and its impacts: (a) an inability to measure, define, and share information and (b) a societal structure that inhibits inclusivity and creativity. In contrast to the aboveground portion of the CZ, which is visible and measurable, the bottom boundary is difficult to access and quantify. In the context of these barriers, we aim to expand the spatial reach of the CZ by highlighting existing and effective tools for research as well as the “human reach” of CZ science by expanding who performs such science and who it benefits. We do so by exploring the diversity of vocabularies and techniques used in relevant disciplines, defining terminology, and prioritizing research questions that can be addressed. Specifically, we explore geochemical, geomorphological, geophysical, and ecological measurements and modeling tools to estimate CZ base and thickness. We also outline the importance of and approaches to developing a diverse CZ workforce that looks like and harnesses the creativity of the society it serves, addressing historical legacies of exclusion. Looking forward, we suggest that to grow CZ science, we must broaden the physical spaces studied and their relationships with inhabitants, measure the “deep” CZ and make data accessible, and address the bottlenecks of scaling and data‐model integration. What is needed—and what we have tried to outline—are common and fundamental structures that can be applied anywhere and used by the diversity of researchers involved in investigating and recording CZ processes from a myriad of perspectives. 

We have formulated the Fréchet kernel computation using the adjoint-state method based on a fractional viscoacoustic wave equation. We first numerically prove that the 1/2- and the 3/2-order fractional Laplacian operators are self-adjoint. Using this property, we find that the adjoint wave propagator preserves the dispersion and compensates the amplitude, whereas the time-reversed adjoint wave propagator behaves identically to the forward propagator with the same dispersion and dissipation characters. Without introducing rheological mechanisms, this formulation adopts an explicit [Formula: see text] parameterization, which avoids the implicit [Formula: see text] in the conventional viscoacoustic/viscoelastic full-waveform inversion ([Formula: see text]-FWI). In addition, because of the decoupling of operators in the wave equation, the viscoacoustic Fréchet kernel is separated into three distinct contributions with clear physical meanings: lossless propagation, dispersion, and dissipation. We find that the lossless propagation kernel dominates the velocity kernel, whereas the dissipation kernel dominates the attenuation kernel over the dispersion kernel. After validating the Fréchet kernels using the finite-difference method, we conduct a numerical example to demonstrate the capability of the kernels to characterize the velocity and attenuation anomalies. The kernels of different misfit measurements are presented to investigate their different sensitivities. Our results suggest that, rather than the traveltime, the amplitude and the waveform kernels are more suitable to capture attenuation anomalies. These kernels lay the foundation for the multiparameter inversion with the fractional formulation, and the decoupled nature of them promotes our understanding of the significance of different physical processes in [Formula: see text]-FWI. 

Abstract During the past few years, distributed acoustic sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS—the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., urban centers, underground mines, and seafloor), spanning from several days to several years, offering both continuous and triggered active source recordings, and totaling up to ∼90 TB of data. This article describes these datasets, their metadata, and how to access and download them. Some of these datasets have only been shallowly explored, leaving the door open for new discoveries in Earth sciences and beyond. 

SUMMARY Seismic attenuation (quantified by the quality factor Q) has a significant impact on the seismic waveforms, especially in the fluid-saturated rocks. This dissipative process can be phenomenologically represented by viscoelastic models. Previous seismological studies show that the Q value of Earth media exhibits a nearly frequency-independent behaviour (often referred to as constant-Q in literature) in the seismic frequency range. Such attenuation can be described by the mathematical Kjartansson constant-Q model, which lacks of a physical representation in the viscoelastic sense. Inspired by the fractal nature of the pore fluid distribution in patchy-saturated rocks, here we propose two fractal mechanical network (FMN) models, that is, a fractal tree model and a quasi-fractal ladder model, to phenomenologically represent the frequency-independent Q behaviour. As with the classic viscoelastic models, the FMN models are composed of mechanical elements (spring and dashpots) arranged in different hierarchical patterns. A particular parametrization of each model can produce the same complex modulus as in the Kjartansson model, which leads to the constant-Q. Applying the theory to several typical rock samples, we find that the seismic attenuation signature of these rocks can be accurately represented by either one of the FMN models. Besides, we demonstrate that the ladder model in particular exhibits the realistic multiscale fractal structure of the saturated rocks. Therefore, the FMN models as a proxy could provide a new way to estimate the microscopic rock structure property from macroscopic seismic attenuation observation.