Depth-dependent seismic sensing of groundwater recovery from the atmospheric-river storms of 2023

Science, Год журнала: 2025, Номер 387(6735), С. 758 - 763

Опубликована: Янв. 2, 2025

In early 2023, a series of intense atmospheric-river storms eased California’s historic drought, yet the spatiotemporal extent groundwater recovery remains poorly understood. We tracked two-decadal changes in Greater Los Angeles using seismic ambient-field interferometry. The derived hydrographs reveal distinct expressions and surficial water droughts: Whereas surface near-surface storage nearly fully recovered epic wet season only about 25% lost since 2006 was restored. On decadal scale, we find substantial depletion aquifers below 50-meter depth, with limited storm-related recovery. Our analysis underscores need to monitor deep for more complete assessment total deficits, high-resolution tools such as sensing.

Язык: Английский

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Energy-related contaminants in subterranean waterbodies: The role of geocolloids on facilitated and hindered transport

Next Sustainability, Год журнала: 2025, Номер 6, С. 100094 - 100094

Опубликована: Янв. 1, 2025

Язык: Английский

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Fiber-optic seismic sensing of vadose zone soil moisture dynamics

Nature Communications, Год журнала: 2024, Номер 15(1)

Опубликована: Авг. 5, 2024

Abstract Vadose zone soil moisture is often considered a pivotal intermediary water reservoir between surface and groundwater in semi-arid regions. Understanding its dynamics response to changes meteorologic forcing patterns essential enhance the climate resiliency of our ecological agricultural system. However, inability observe high-resolution vadose over large spatiotemporal scales hinders quantitative characterization. Here, utilizing pre-existing fiber-optic cables as seismic sensors, we demonstrate sensing principle robustly capture dynamics. Our observations Ridgecrest, California reveal sub-seasonal precipitation replenishments prolonged drought zone, consistent with zero-dimensional hydrological model. results suggest significant loss 0.25 m/year through evapotranspiration at field side, validated by nearby eddy-covariance based measurements. Yet, detailed discrepancies modeling highlight necessity for complementary in-situ validations. Given escalated regional risk under change, findings underscore promise facilitate resource management

Язык: Английский

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State-of-The-Art application and challenges of optical fibre distributed acoustic sensing in civil engineering

Optical Fiber Technology, Год журнала: 2024, Номер 87, С. 103911 - 103911

Опубликована: Июль 19, 2024

Distributed Acoustic Sensing (DAS) technology has rapidly gained prominence across various applications. Integrating DAS with fibre-optic cables can bolster critical aspects such as wellbore integrity and pipeline security in oil gas, geophysical exploration, enhances perimeter security, structural health monitoring. Its groundbreaking ability to provide real-time data along the entire length of optical fibres signifies a paradigm shift monitoring practices, allowing for more proactive informed approach infrastructure management. This manuscript comprehensively reviews applications delves into specific challenges associated its implementation civil engineering. Examples engineering include but are not limited bridge dam monitoring, tunnel leakage detection, construction site geohazards sensing. In addition, engaging discussions about potential solutions areas improvement within engineering, this forward-looking perspective contributes holistic understanding current state, challenges, future possibilities Sensors scientific research Furthermore, article emphasises role continuous equipment innovative tools advancing research. Within context, fibre-based sensors, notably distributed acoustic sensing, have emerged advanced instruments revolutionise diverse domains field.

Язык: Английский

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The Seismic Signature of California's Earthquakes, Droughts, and Floods

Journal of Geophysical Research Solid Earth, Год журнала: 2023, Номер 128(1)

Опубликована: Янв. 1, 2023

Abstract This study investigates changes in seismic velocities the period 1999–2021 using about 700 permanent and temporary broadband stations state of California. We compute single‐station cross‐correlations ambient noise use coda‐wave interferometry to measure ( dv/v ) a stretching technique. focus on 2–4 Hz frequency band upper 500 m near‐surface sensitivity. discuss within context nonlinear elasticity. fit models thermoelastic strains, various hydrological that diffuse rainwater, slow‐dynamics healing for postseismic response earthquakes. In general, we find both strains have similar amplitude impacts . diffusion rainwater drained poroelastic medium explains most data. The best hydraulic diffusivity is high mountains low basin. largest drop velocity occurs during 2004–2005 wet winter 2011–2016. Drought characterized by multiyear marked increase interpret site‐specific variations with land subsidence or inflation detected remote sensing. also decade‐long two major earthquakes bound time scale relaxation processes few years. Together, see long‐term showing positive trend over decades can as lowering groundwater table.

Язык: Английский

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Deciphering the Whisper of Volcanoes: Monitoring Velocity Changes at Kamchatka's Klyuchevskoy Group With Fluctuating Noise Fields

Journal of Geophysical Research Solid Earth, Год журнала: 2023, Номер 128(4)

Опубликована: Март 23, 2023

Abstract Volcanic inflation and deflation often precede eruptions can lead to seismic velocity changes ( ) in the subsurface. Recently, interferometry on coda of ambient noise‐cross‐correlation functions yielded encouraging results detecting these at active volcanoes. Here, we analyze data recorded Klyuchevskoy Group Kamchatka, Russia, between summer 2015 2016 study signals related volcanic activity. However, ubiquitous tremors introduce distortions noise wavefield that cause artifacts estimates masking impact physical mechanisms. To avoid such instabilities, propose a new technique called time‐segmented passive image . In this technique, employ hierarchical clustering algorithm find periods which be considered stationary. For periods, perform separate studies. further increase temporal resolution our results, use an AI‐driven approach stations with similar responses apply spatial stack. The impacts snow load precipitation dominate resulting time series, as demonstrate help simple model. February 2016, observe abrupt drop due M7.2 Zhupanov earthquake. Shortly after, register gradual about 0.3% Bezymianny Volcano coinciding surface deformation observed using remote sensing techniques. We suggest shallow reservoir beginning Bezymianny's 2016/2017 eruptive cycle could have caused local decorrelation correlation function coda.

Язык: Английский

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Monitoring Terrestrial Water Storage, Drought and Seasonal Changes in Central Oklahoma With Ambient Seismic Noise

Geophysical Research Letters, Год журнала: 2023, Номер 50(17)

Опубликована: Сен. 1, 2023

Abstract Significant imbalances in terrestrial water storage (TWS) and severe drought have been observed around the world as a consequence of climate changes. Improving our ability to monitor TWS is critical for water‐resource management water‐deficit estimation. We use continuous seismic ambient noise temporal evolution near‐surface velocity, dv / v , central Oklahoma from 2013 2022. The derived found be negatively correlated with gravitational measurements groundwater depths, showing impact on velocities. hydrological effects involving droughts recharge occur multi‐year time scale dominate overall velocity thermoelastic response atmospheric temperature variations occurs primarily yearly timescale dominates superposed seasonal changes this study. occurrences appear simultaneously local peaks demonstrating sensitivity velocities droughts.

Язык: Английский

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Using Vehicle‐Induced DAS Signals for Near‐Surface Characterization With High Spatiotemporal Resolution

Journal of Geophysical Research Solid Earth, Год журнала: 2024, Номер 129(4)

Опубликована: Апрель 1, 2024

Abstract Vehicle‐induced seismic waves, generated as vehicles traverse the ground surface, carry valuable information for imaging underlying near‐surface structure. These waves propagate differently in subsurface depending on soil properties at various spatial locations. By leveraging wave propagation characteristics, such surface‐wave velocity and attenuation, this study presents a novel method monitoring. Our employs passing active, non‐dedicated sources leverages pre‐existing telecommunication fibers large‐scale cost‐effective roadside sensors empowered by Distributed Acoustic Sensing (DAS) technology. A specialized Kalman filter algorithm is integrated automated DAS‐based traffic monitoring to accurately determine vehicles' location speed. Then, our approach uniquely vehicle trajectories isolate space‐time windows containing high‐quality surface waves. With known (i.e., source) locations, we can effectively mitigate artifacts associated with suboptimal distribution of conventional ambient noise interferometry. Compared interferometry, enables synthesis virtual shot gathers high signal‐to‐noise ratio spatiotemporal resolution reduced computational costs. We validate effectiveness using Stanford DAS‐2 array, focus capturing heterogeneity temporal variations during rainfall events. Specifically, non‐built‐up areas, observed an evident decrease phase group increase attenuation due rainfall. findings illustrate method's sensitivity discerning across different locations demonstrate that promising advancement high‐resolution urban settings.

Язык: Английский

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Identifying large vulnerable water reservoirs using passive seismic monitoring

Earth and Planetary Science Letters, Год журнала: 2025, Номер 653, С. 119223 - 119223

Опубликована: Янв. 21, 2025

Язык: Английский

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Physics‐Guided Deep Learning Model for Daily Groundwater Table Maps Estimation Using Passive Surface‐Wave Dispersion

Water Resources Research, Год журнала: 2025, Номер 61(1)

Опубликована: Янв. 1, 2025

Abstract Monitoring groundwater tables (GWTs) remains challenging due to limited spatial and temporal observations. This study introduces an innovative approach combining artificial neural network, specifically a multilayer perceptron (MLP), with continuous passive Multichannel Analysis of Surface Waves (passive‐MASW) construct GWT depth maps. The geologically well‐constrained site includes two piezometers permanent 2D geophone array recording train‐induced surface waves. At each point the array, dispersion curves (DCs), displaying Rayleigh‐wave phase velocities over frequency range 5–50 Hz, were measured daily from December 2022 September 2023, latter resampled wavelengths 4 15 m, focus on expected depths (1–5 m). Nine months data near one piezometer, spanning both low high water periods, used train MLP model. then estimated across producing model's performance was evaluated by comparing inferred observed measurements at second piezometer. Results show coefficient determination (R 2 ) 80% training piezometer 68% test remarkably root‐mean‐square error (RMSE) 0.03 m locations. These findings highlight potential deep learning estimate maps seismic spatially piezometric information, offering practical efficient solution for monitoring dynamics large extents.

Язык: Английский

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