{"id":"64b33c6f-71b3-4db6-814a-efb669152bfd","arxiv_id":"2501.10618","paper_version":1,"verdict":"CONDITIONAL","confidence":"MODERATE","novelty_score":6.0,"correctness_risk":"medium","formal_verification":"none","parameter_count":5,"one_line_summary":"Passive traffic noise on a fiber-optic cable, inverted daily with elastic full-waveform inversion, tracked S-wave velocity changes that follow groundwater table fluctuations along a 1 km urban section.","lead":"Researchers turned a roadside fiber-optic cable into a daily seismic scanner, using passing cars as sound sources to watch groundwater rise and fall beneath a California road for two years. If the approach holds up, cities could monitor hidden aquifers daily with existing telecom cables instead of drilling new wells.","discovery_kind":"new_application","skeptic_critique":{"model":"deepseek-v4-flash","headline":"The 14-day moving average in Methods makes the 'single-day' EPE response and the daily temporal-resolution claim unsupported; a re-inversion of unsmoothed daily VSGs would settle it.","rationale":"The paper is otherwise well-executed: the shared code and data, the baseline FWI waveform fits, the checkerboard resolution tests, and the seasonal velocity-reduction signal are credible independent evidence. The weakest step is the temporal-resolution claim, because the 14-day moving average is explicitly in the processing chain and directly undermines the headline 'daily monitoring' and 'within one single day' statements. The reader's weakest_assumption identified exactly this issue, and I agree. A CONDITIONAL verdict remains appropriate: if the proposed re-inversion test shows that unsmoothed daily VSGs recover the EPE response with comparable amplitude, the central claim survives; if not, the title, abstract, and Results must be revised to describe ~14-day (or at best weekly) effective temporal resolution rather than daily resolution, and the one-day event attribution must be withdrawn. Since the reader already judged the paper CONDITIONAL on this issue, I recommend no change to that verdict.","tokens_in":14769,"tokens_out":5383,"duration_ms":56711,"concrete_test":"Re-run the monitor FWI for Dec 15, 2022 to Jan 15, 2023 using four inputs: (i) single-day VSGs with no 14-day smoothing; (ii) the published 14-day moving-average VSGs; (iii) a 14-day window averaging all days except Dec 31; and (iv) a 14-day window ending Dec 30. Compare the daily dv/v time series averaged over 200-400 m distance and 20-30 m depth. If the Dec 31 spike appears only in (ii) and not in (i), or if (ii) and (iii) are equal within the estimated noise, then the one-day EPE attribution is an artifact of smoothing; if the spike persists in (i) with amplitude comparable to (ii), then the daily-resolution claim is supported.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The central claim of daily monitoring and the one-day response to the Dec 31, 2022 EPE depends on the time-lapse VSGs actually representing single days. The Methods state: 'a 14-day moving window average was applied to the daily data to enhance SNR further' (Materials and Methods, Time-lapse targeted interferometry). This filter is applied to the data that are then fed into the daily monitor FWI; it is not described as a display-only operation. A 14-day moving average has a half-width of 7 days (or 13 days if trailing), so the resulting velocity-change time series has an effective temporal resolution of at least ~14 days. The Dec 31, 2022 'daily' velocity change therefore averages over a window that includes the preceding and succeeding atmospheric-river precipitation; it cannot distinguish a one-day water-table rise from a multi-day response. The absence of a stated centered/trailing convention makes the ambiguity worse. If the 14-day smoothing is required to obtain stable VSGs, then the paper should state the effective temporal resolution as ~14 days and cannot claim 'within one single day' or 'daily analysis' without additional evidence.","agreement_with_reader":"agree"},"referee_report":{"model":"deepseek-v4-flash","summary":"This paper presents a 27-month (December 2021 to March 2024) case study along Sandhill Road, California, in which virtual source gathers (VSGs) retrieved from vehicle-induced DAS signals by targeted interferometry are inverted with time-lapse elastic full-waveform inversion (FWI) to image S-wave velocity changes. The authors report a 2.9% Vs reduction during Water Year 2023, corresponding to a roughly 9 m water-table rise, lateral differences between grassy and paved areas, and a claimed one-day response to a December 31, 2022 extreme precipitation event. They validate the velocity changes against well measurements and precipitation records, and support the interpretation with a 1D poroelastic pore-pressure model. The paper also shares the targeted-interferometry code, daily FWI models, and selected VSGs via GitHub and Zenodo.","tokens_in":14990,"tokens_out":6441,"duration_ms":64481,"significance":"If the claims hold, this work is significant: it demonstrates that non-uniform vehicle traffic recorded on dark fiber can be converted into repeatable virtual-source surveys and inverted with FWI at a cadence and cost far below active-source monitoring, while providing lateral and depth localization that coda-wave monitoring cannot. The study is strengthened by the use of independent well and precipitation data, checkerboard resolution tests, and a poroelastic interpretation that is not itself used to construct the velocity-change field. The open release of code, daily FWI models, and selected VSGs is a further strength. However, the central novelty is the claimed daily temporal resolution, and that claim is not supported by the processing description as written.","major_comments":[{"comment":"The Methods state that 'a 14-day moving window average was applied to the daily data to enhance SNR further.' The Results (Fig. 4d) and the accompanying text attribute a rapid groundwater-table rise to the December 31, 2022 EPE 'within one single day.' A 14-day moving average has an effective temporal resolution of roughly 14 days (half-width 7 days, or 13 days if trailing), so a single-day attribution is not recoverable from the smoothed input unless the smoothing is applied only to display curves, which the text does not say. Please clarify the role of the smoothing in the FWI workflow and, if it is part of the data preprocessing, either re-invert unsmoothed daily VSGs or revise the abstract, title, and temporal-resolution claims (including the 'daily analysis' and the >6-month recession-time estimate) to a ~14-day effective resolution.","section":"Materials and Methods, Time-lapse targeted interferometry; Results, Impact of Extreme Precipitation Events"},{"comment":"The quality-control criteria remove monitor traces with time delays exceeding 25 ms and mute traces with NRMS greater than 0.6. Supplementary Fig. S2 shows that NRMS systematically increases during wet periods, so these criteria preferentially reject exactly the traces that carry the largest hydrological signal. This selection can bias the inverted velocity-reduction amplitudes (most plausibly downward) and can distort the grassy-versus-paved comparison if the rejection rate differs by surface type. Please report the fraction of rejected or muted traces as a function of date and location, and provide a sensitivity test of the 2.9% reduction and the spatial patterns in Fig. 3a and Fig. 4a to the 25 ms and 0.6 thresholds.","section":"Materials and Methods, Time-lapse targeted interferometry (trace rejection); Supplementary Fig. S2"},{"comment":"The Discussion claims 'meter-scale spatial resolution,' but the checkerboard resolution tests in Supplementary Fig. S5 recover anomalies of 25 m depth by 50 m lateral and 20 m by 40 m, and the Introduction states 'tens-of-meter resolution in space.' The 'meter-scale' phrasing is inconsistent with the paper's own resolution analysis and should be corrected to the demonstrated resolution.","section":"Discussion, final paragraph; Supplementary Fig. S5"}],"minor_comments":[{"comment":"Equation (8) contains typesetting errors in the erf/erfc arguments (the square-root symbols and fractions are mis-rendered); please ensure the formula is typeset correctly.","section":"Materials and Methods, Eq. (8)"},{"comment":"The caption refers to a 'virtual source at 520 m' while the main text describes the same location as a 'virtual receiver at 520 m'; please clarify which is intended.","section":"Supplementary Fig. S2 caption"},{"comment":"The released continuous DAS recordings are described as 'from December 2022'; please clarify the exact date range of the released data, given the full two-year monitoring period.","section":"Data and materials availability"},{"comment":"The word 'checkboard' in the caption should be 'checkerboard.'","section":"Supplementary Fig. S5 caption"},{"comment":"Please specify whether the 14-day moving average is centered or trailing, and state whether the baseline period of July 7 to August 25, 2022 is also smoothed before being used as the reference.","section":"Materials and Methods, Time-lapse targeted interferometry"}],"recommendation":"major_revision","confidential_remarks":"The paper is a strong candidate if the temporal-resolution issue is resolved. I do not see a circularity problem: the pore-pressure simulation is interpretative and independent of the FWI input. The main risk is overclaiming daily resolution; the authors should either provide a re-inversion of unsmoothed daily VSGs or clearly downgrade the temporal claims. Please also check the conflict between the 'meter-scale' phrase in the Discussion and the checkerboard results."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"Worth a serious look, but the headline daily-resolution claim outruns what the Methods actually support. The paper reports a two-year time-lapse elastic FWI of vehicle-DAS virtual source gathers along a 1 km urban fiber, tracking S-wave velocity changes that follow seasonal rainfall, with a plausible paved-versus-grassy lateral contrast. That is a real new result. The building blocks are prior art, mostly from the same Stanford group, but the integration at daily cadence over two years with independent well and precipitation comparison is a legitimate step forward. Code and data are shared (targeted interferometry code, deepwave workflow, daily FWI models and VSGs), which is a genuine plus.\n\nThe soft spot is the temporal resolution. Methods say 'a 14-day moving window average was applied to the daily data to enhance SNR further' before the monitor FWI. That filter is not display-only. A 14-day moving average gives an effective resolution on the order of two weeks, so the 'within one single day' response to the Dec 31, 2022 EPE (Fig. 4d) cannot be read from these data as a single-day signal. The paper needs to either re-invert unsmoothed daily VSGs or openly restate the effective resolution as ~14 days. This is a load-bearing issue for the 'daily monitoring' headline, not a cosmetic one. The seasonal signal and lateral contrast are robust to that smoothing; they are not what is at stake.\n\nTwo smaller concerns. Trace rejection with delay >25 ms and NRMS >0.6 will preferentially discard the largest true velocity changes, biasing the amplitude of the reported 2.9% reduction. And the poroelastic pore-pressure simulation is interpretative; the matched pressure curve has free parameters (diffusivity, Skempton coefficient, undrained Poisson ratio) and is used for physical plausibility, not calibration. The paper acknowledges this in places, but the recession-time estimate (over six months) and the quantitative water-table inference lean on it.\n\nThe reader's CONDITIONAL verdict is about right. This is a reproducible, well-written applied-geophysics paper that deserves a serious referee. A competent reviewer can push for a re-analysis or a rewritten temporal-resolution claim, and the paper would be stronger for it. I would not desk-reject; I would engage. If the authors can settle the 14-day smoothing question, this becomes a solid contribution.","headline":"A reproducible two-year vehicle-DAS FWI groundwater monitoring study with a genuine seasonal and lateral signal, but the 'daily' and 'single-day' claims are not supported by the stated 14-day moving average.","tokens_in":15539,"tokens_out":2321,"would_cite":true,"duration_ms":22031,"reading_group":"yes","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"This paper claims that daily elastic full-waveform inversion of vehicle-generated surface waves recorded on a fiber-optic cable can localize groundwater-driven S-wave velocity changes at meter scale and daily cadence.","keywords":["groundwater monitoring","distributed acoustic sensing","full-waveform inversion","vehicle-induced seismic sources","time-lapse seismic monitoring","S-wave velocity","poroelasticity","aquifer recharge"],"falsifier":"Rerun the same daily time-lapse full-waveform inversion without the 14-day moving average and inspect the velocity-change time series around December 31, 2022: if no sharp single-day step remains, the claimed daily-resolution detection is an artifact of smoothing. A complementary test would compare daily FWI velocity changes against a continuous pressure-transducer water-level record during a later atmospheric-river event to see whether the seismic response really is same-day.","tokens_in":14573,"feed_emoji":"💧","tokens_out":9000,"duration_ms":82702,"temperature":0.7,"pith_summary":"Using two years of continuous recordings on a 1 km fiber-optic cable along Sandhill Road, California, this paper tries to show that elastic full-waveform inversion of virtual source gathers generated by ordinary vehicular traffic can monitor groundwater dynamics on a daily basis. The key result is a set of daily S-wave velocity models in which a 2.9% velocity reduction tracks a 9.0-meter rise in the water table during Water Year 2023, with the largest changes concentrated at 15–30 m depth beneath grassy areas. If correct, the method would give aquifer managers meter-scale spatial localization and daily temporal sampling without active seismic sources, using only a pre-existing telecommunications cable and the traffic already on the road. The paper also argues that the observed velocity drops are poroelastic: rising pore pressure lowers effective stress and hence S-wave velocity, matching a coupled flow-mechanics simulation.","feed_headline":"Traffic on a fiber cable maps daily aquifer changes","feed_subtitle":"Vehicle-DAS full-waveform inversion spots a one-day water-table response that monthly well readings missed.","key_machinery":"The load-bearing machinery is the combination of targeted interferometry and time-lapse elastic full-waveform inversion. Targeted interferometry tracks individual vehicles from the quasi-static deformation signals in the DAS record, selects coherent surface-wave windows, cross-correlates them, and stacks the results into daily virtual source gathers with 39 virtual sources and receivers spaced every 8.16 m. The inversion builds a baseline model with a multi-scale full-waveform inversion using a global-correlation objective function, then monitors changes with a modified double-difference strategy that inverts differences between baseline and monitor waveforms while normalizing amplitudes. DAS acquisition is modeled as averaged tangential strain over the 16 m gauge length, and S-wave velocity is the only parameter inverted, with P-wave velocity and density coupled through an empirical velocity ratio and density–velocity relation. The physical link to groundwater is the effective-stress relation $P_{\\text{eff}} = P_{\\text{conf}} - P_{\\text{pore}} + S_w\\psi$, by which rising pore pressure reduces S-wave velocity; pore-pressure time series are generated with a diffusive poroelastic solution for surface loading.","core_discovery":"The central discovery claimed is that time-lapse elastic full-waveform inversion applied to daily stacked virtual source gathers from vehicle-induced surface waves resolves absolute, localized S-wave velocity changes tied to aquifer storage. Over the monitoring period the inversion recovers a 2.9% reduction in S-wave velocity during the wet Water Year 2023, coincident with a cumulative 9.0-meter groundwater-table rise, and attributes a rapid velocity change on the day of the December 31, 2022 extreme precipitation event to a fast water-table rise that monthly well measurements missed. Velocity changes appear mainly below the local water table, at 15–30 m depth, are stronger under grassy areas than under a paved parking lot, and correlate with pore-pressure increases simulated from precipitation records. The paper presents this as an advance beyond coda-wave monitoring because full-waveform inversion localizes changes in absolute velocity rather than giving spatially averaged relative values.","pith_inferences":["Inference: if the 14-day moving average is required for stable virtual source gathers, the practically supported temporal resolution may be closer to two weeks than one day; a no-smoothing test would settle which claim survives.","Inference: pairing daily FWI with continuous pressure-transducer water levels at one or more wells would calibrate the velocity-change-to-storage relation, turning the method from a qualitative proxy into a quantitative head or storage estimator.","Inference: transfer to other urban fiber segments will depend on traffic density and low-frequency source content; heavy-truck traffic should reach deeper and stabilize daily gathers, while quiet residential segments may need longer stacking windows.","Inference: because the paper notes that saturation changes above the water table are invisible to S-wave surface-wave inversion, adding P-wave sensitivity to the same DAS data could extend monitoring into the vadose zone."],"forward_implications":["Daily FWI of vehicle-DAS data localizes S-wave velocity changes in depth and along the cable, so groundwater response can be mapped where monitoring wells are too sparse and coda-wave methods give only spatially averaged relative changes.","The same data stream detects a single-day aquifer response to the December 31, 2022 extreme precipitation event, something the monthly hydraulic-head measurements from the nearby well missed.","Because the sources are ordinary vehicles and the sensors are pre-existing telecommunications fibers, the approach can replace costly daily active-source seismic surveys for near-surface aquifer monitoring.","The observed contrast between grassy and paved areas implies that impervious surfaces suppress local recharge, providing a direct geophysical measure of urbanization effects on aquifer recharge.","Extending the approach to fiber-optic networks with 2-D geometries would support 3-D aquifer imaging at daily cadence."],"supporting_citations":[{"why":"Supplies the targeted interferometry workflow that converts tracked vehicle surface waves into repeatable daily virtual source gathers, the data basis for all time-lapse inversions.","marker":"[30]"},{"why":"Identifies vehicle-induced DAS signals as surface-wave sources and characterizes their use for near-surface imaging, establishing the traffic-source premise.","marker":"[44]"},{"why":"Provides the prior surface-wave site characterization used to check consistency of the baseline FWI velocity structure.","marker":"[41]"},{"why":"Introduces the global-correlation objective function used in baseline and monitor FWI to reduce sensitivity to amplitude errors in land surface-wave data.","marker":"[60]"},{"why":"Contributes the double-difference time-lapse inversion strategy that the monitor FWI modifies to invert baseline-minus-monitor waveform differences.","marker":"[65]"},{"why":"Gives the DAS strain-measurement forward modeling (averaged tangential strain over the gauge length) used to compute synthetic DAS data in FWI.","marker":"[63]"},{"why":"Defines the NRMS repeatability metric used to reject non-repeatable monitor traces, the quality-control step that makes time-lapse comparisons credible.","marker":"[57]"},{"why":"Provides the diffusive poroelastic pore-pressure solution used to simulate depth-dependent pore-pressure changes from precipitation and support the mechanism linking pore pressure to velocity.","marker":"[71]"}],"fun_headline_variants":["Daily groundwater maps from road traffic","Traffic vibrations reveal daily water table changes","Fiber-optic traffic sensing tracks aquifers daily","Car waves expose groundwater daily","Daily aquifer shifts from traffic on fiber"],"cache_read_input_tokens":3200,"weakest_assumption_plain":"The claim of daily resolution rests on the assumption that the 14-day moving window average applied to the daily virtual-source gathers to boost signal-to-noise does not blur away the single-day velocity change attributed to the December 31, 2022 storm; if the smoothing is what makes the gathers usable, the one-day attribution cannot be recovered from those data.","fun_headline_variants_meta":{"raw":{"variants":["Daily groundwater maps from road traffic","Traffic vibrations reveal daily water table changes","Fiber-optic traffic sensing tracks aquifers daily","Car waves expose groundwater daily","Daily aquifer shifts from traffic on fiber"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000308,"raw_usage":{"total_tokens":1733,"prompt_tokens":893,"completion_tokens":840,"prompt_tokens_details":{"cached_tokens":384},"prompt_cache_hit_tokens":384,"prompt_cache_miss_tokens":509,"completion_tokens_details":{"reasoning_tokens":778}},"tokens_in":509,"tokens_out":840,"duration_ms":8888,"temperature":1.0,"reasoning_tokens":778,"cache_read_input_tokens":384,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-10T19:02:28.541354+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Rerun the same daily time-lapse full-waveform inversion without the 14-day moving average and inspect the velocity-change time series around December 31, 2022: if no sharp single-day step remains, the claimed daily-resolution detection is an artifact of smoothing. A complementary test would compare daily FWI velocity changes against a continuous pressure-transducer water-level record during a later atmospheric-river event to see whether the seismic response really is same-day.","supporting_citations":[{"cited_title":null,"cited_arxiv_id":null,"evidence_quote":"Provides the diffusive poroelastic pore-pressure solution used to simulate depth-dependent pore-pressure changes from precipitation and support the mechanism linking pore pressure to velocity."}],"review_version":1}