Surface Displacement Measurements Research Articles

Machine learning-based laser heterodyne photothermal displacement method: simultaneous estimation of silicon thermal diffusivity and carrier lifetime

Abstract The laser heterodyne photothermal displacement (LH-PD) method, a recently developed photothermal technique, enables measurement of absolute surface displacements, which are otherwise challenging to measure with other photothermal methods. This method offers significant potential for quantifying physical properties that are difficult to achieve with traditional photothermal methods. In this study, we aimed to estimate the thermal diffusivity and carrier lifetime of Si using a machine learning model based on the time variation of the displacement obtained using the LH-PD method. By leveraging the machine learning model, we generated predictive mappings of thermal diffusivity and carrier lifetime of a pattern-etched Si wafer from the displacement mappings. Furthermore, our findings demonstrated that fine-tuning the model enabled accurate predictions of the carrier lifetime. While traditional simulations require tens of hours to estimate the material parameters, machine learning reduced this process to only a few seconds.

Estimation of Terrestrial Water Storage Changes in Brazil From the Joint Inversion of GRACE‐Based Geopotential Difference and GNSS Vertical Displacement Data

AbstractGravity Recovery and Climate Experiment (GRACE) satellite gravimetry and Global Navigation Satellite System (GNSS) surface displacement measurements offer complementary advantages for monitoring terrestrial water storage (TWS) changes. We propose a new joint inversion model based on the combination of GRACE‐based geopotential difference (GPD) observations using the mascon method and GNSS vertical displacements through the Green's function method to obtain reliable TWS changes in Brazil. The performance of the jointly inverted TWS changes is assessed through closed‐loop simulations and comparisons with hydrometeorological data (precipitation‐P, evapotranspiration‐ET, and runoff‐R) using water budget closure (P‐ET‐R) and river water level observations from satellite altimetry. The simulation results indicate that the joint inversion results exhibit higher accuracy and reliability than GRACE GPD‐based mascon (GPD‐mascon) and GNSS solutions, and the standard deviations (STDs) of joint results decrease by ∼6.98 and ∼37.5 mm compared to those from GPD‐mascon and GNSS solutions. The joint inversion of real GRACE and GNSS data demonstrates notably lower uncertainty than that of GPD‐mascon solutions and exhibits significant improvement than GNSS‐only solutions. The STDs and correlation coefficients between monthly R time series derived from three inversion methods (joint inversion, GPD‐mascon and GNSS solutions, combined with P and ET through water budget closure) and in situ observations are 19.607 mm and 0.912, 20.879 mm and 0.904, and 31.370 mm and 0.778, respectively. The joint estimates also yield better correlation with river water level observations compared to GPD‐mascon and GNSS solutions. Furthermore, at the weekly time scale, the joint inversion results show better consistency with P‐ET‐R data than those from GPD‐mascon and GNSS solutions.

Are Field Observations of Surface Rupture Useful? An Example from the 2023 Mw 7.8 Pazarcık, Turkey (Türkiye), Earthquake

Abstract Field investigations have long been an important component of the scientific response to surface-faulting earthquakes. However, in light of advances in remote data and models, the question arises whether field-based observations of surface rupture remain useful for understanding rupture processes and seismic hazards. We approach this question using a field-based study of the central 2023 Mw 7.8 Pazarcık, Turkey (Türkiye), earthquake rupture, at the intersection of the east Anatolian fault (EAF) and Narlı fault. Our field observations include the surface rupture expression and extent of the central EAF and northernmost Narlı fault in generally forested and steep terrain and 68 measurements of left-lateral surface displacement. These data improve our understanding of the Pazarcık rupture complexity, resolve the surface geometry of the Narlı fault–EAF connection, and exhibit a clear (>2 m) change in surface displacement across this intersection zone that confirms remote-based coseismic slip models. Our study shows that focusing field efforts in areas of obscured or low-resolution remote data can yield essential data for refining rupture extent, documenting perishable on-fault displacement, and improving postearthquake situational awareness. A comparison of similarly large-magnitude continental surface-rupturing earthquakes indicates that displacement uncertainties relate to a complex set of factors, including measurement methods, rupture complexity, and displacement magnitude. Our study validates the need for postearthquake field observations, which, when driven by clear motivating questions and knowledge of methodological strengths and limitations, provide high-resolution rupture data that complement remote-based models.

Two-dimensional thermal and dynamical strain in landfast sea ice from InSAR: results from a new analytical inverse method and field observations

Abstract Observing continuous strain in sea ice at geophysical scales of tens of meters to kilometers requires displacement measurements made with millimeter-scale precision. Satellite-based interferometric synthetic aperture radar (InSAR) provides such precise measurements of relative surface displacement over broad spatial areas at regular intervals and, unlike point displacement measurements, it allows confident delineation of continuously deforming regions. However, InSAR only captures the 1-D component of surface displacement parallel to a radar's lines-of-sight. Additional analysis is required to translate between these 1-D observations and the horizontal or vertical displacements they arose from. Previous studies utilize an iterative inverse model to constrain estimates of horizontal surface displacement from InSAR. Here we build upon that work outlining a new analytical inverse modeling method for quantifying displacement and strain over continuous regions of sea ice and provide comparison between model results and independent displacement observations. We demonstrate the inverse method over both landfast and drifting ice along the Alaskan coastline. These intercomparisons highlight environments in which displacements inverted from interferograms may be used as an independent estimator of surface strain, as well as the potential for the outlined inverse methods to be used in conjunction with other observing methods.

Advances in InSAR Analysis of Permafrost Terrain

ABSTRACTDifferential interferometric synthetic aperture radar (InSAR) is a remote sensing technique for measuring surface displacements with precision down to millimeters, most commonly from satellites. In permafrost landscapes, InSAR measurements can provide valuable information on geomorphic processes and hazards, including thaw subsidence and frost heave, thermokarst, and permafrost creep. We first review recent progress in InSAR data availability, InSAR processing and uncertainty analysis methods relevant to permafrost studies. These technical advances have contributed to our understanding of surface deformation in flat and sloping terrain in polar and mountainous regions. We emphasize two emerging trends. First, InSAR increasingly enables insight into the mechanisms, controls, and drivers of permafrost landscape dynamics on subseasonal to decadal time scales. Second, InSAR observations in conjunction with models enable novel ways to infer subsurface parameters, such as near‐surface ground ice content and active layer thickness. We anticipate that in the coming decade, InSAR will mature into a widely used operational tool for monitoring, modeling, and planning across rapidly changing permafrost landscapes.

Spatiotemporal dominance of afterslip and viscoelastic relaxation revealed by four decades of post-1973 Luhuo earthquake observations

Measuring surface displacements driven by afterslip and viscoelastic relaxation following large earthquakes enables inferring frictional and rheological properties of Earth's outermost layers where hazardous earthquakes occur. However, the two concurrent mechanisms generate similar and intertwined surface deformations, complicating the extraction of physical information from the measurements. Here, we quantify the spatiotemporal dominance of co-evolving afterslip and viscoelastic relaxation following the 1973 Ms 7.6 Luhuo earthquake in eastern Tibet, using 42 years (1976‒2018) of fault-crossing short-baseline observations. The finite-fault slip of this M7+ earthquake was constructed from triangulation data measured in 1961‒1975. Based on the model incorporating two postseismic relaxation mechanisms and calibrated by the measurements over four decades, we show that, in the temporal domain, afterslip may produce geodetically measurable deformations (>1.5 mm/yr) in local near-field regions even 20 years after the mainshock, with spatially broader impact within ∼10 years. Viscoelastic relaxation may last for nearly six decades, imposing a broad influence for three decades. In the spatial domain, afterslip may produce deformations within ∼2 times the seismogenic depth (SD; 20 km) from the fault, but dominantly in the near-field of ∼1 times the SD. In contrast, viscoelastic relaxation may affect a much wider region reaching 200 km. While afterslip and viscoelastic relaxation collectively affected the region ∼2 times the SD from the fault in the early postseismic period, their resulting deformations gradually separated in space with time, with afterslip-induced deformation shrinking toward the fault, and surface deformation caused by viscoelastic relaxation concentrating in the mid-field, ∼2–3 times the SD from the fault. Their spatiotemporal partitioning helps better learn fault frictional properties and lithospheric rheology based on geodetic data acquired from different domains.

Surface displacement measurement and modeling of the Shah-Gheyb salt dome in southern Iran using InSAR and machine learning techniques

Salt domes play a crucial role in hydrocarbon storage, underground construction, solution mining, and mineralization. Therefore, deformation monitoring is essential for analyzing the kinematics and impact of salt domes. This study aims to measure the temporal displacements of the Shah-Gheyb salt dome from 2016 to 2019 and from 2020 to 2022 using the New Small Baseline Subset (NSBAS) Interferometric Synthetic Aperture Radar (InSAR) technique and to predict future displacements through machine learning models. A total of 14 data layers, including topography, remote sensing, hydrology, and geology group were used in Machine Learning (ML). Random Forest Regression (RFR) and Support Vector Regression (SVR) models were employed to project displacements in both the East-West (E-W) and Up-Down (U-D) components through 29 scenarios.In the E-W direction, the salt dome exhibits a displacement rate of 39 mm/year, while in the U-D direction, it varies between −18 and +6 mm/year. ML predictions and SAR interferometry data processing results for the period 2020–2022 were validated using Root Mean Square Error (RMSE) and the correlation coefficient (R). The RFR model demonstrated the lowest RMSE of 1.9 mm for the E-W component, achieving a maximum R-value of 97.3 %. For the U-D component, the RMSE was 2.8 mm, with an R-value of 55.8 %. Evaluation of the predictive performance of the ML models and a comparison of InSAR and ML outcomes indicated that the RFR model predicted displacement along the E-W and U-D directionsbetween 2020 and 2022 with greater accuracy than the SVR. Furthermore, comparing the displacement predictedby the RFR model using SAR interferometry along two perpendicular profiles confirmedthe model's precision.

Vortex phase-based adaptive moiré technique accommodating micro displacement measurement of freeform surfaces.

The traditional displacement measurement interferometer (DMI) provides elegant performance by straight interference fringe movement counting to convert a phase calculation into an image motion calculation. However, it cannot be applied to a curve surface displacement measurement. The counting of the movement of irregular fringes is not achievable. We provide an adaptive moiré technique with a vortex phase to realize micro displacement measurement of a freeform surface with any continuous shape. The technique produces straight moiré fringes that rotate in a circle regardless of the shape of interference fringes and tested surface shapes. The vortex phase is used to record only one interferogram before the measurement for subsequent data processing, and then it no longer participates in the displacement measurement process. Therefore, this technology can be employed to remold traditional DMIs. Simulations and experiments validating the method are presented.

Centrifuge study on the uplift behavior of spread foundation for transmission tower in sand

Realistic simulation of in-situ stresses is an essential consideration in evaluating the bearing capacities of spread foundations. Therefore, this study aimed to investigate the uplift behavior of large spread foundations by performing a series of centrifuge tests. A total of 12 centrifuge test models were constructed considering the variation in the foundation width (3.5–6.5 m), embedment depth ratio (0.67–1.39), and relative density of dry silica sandy soil (40%, 80%). The measured load–displacement curves indicated that the uplift bearing capacity and the corresponding uplift displacement increased with the foundation width at a certain embedment depth ratio. Two sets of empirical equations were proposed by adopting genetic programming to estimate the uplift resistance factor and uplift displacement with consideration of field stress conditions. The proposed equations reasonably matched these parameters under various conditions reported in the literature. Furthermore, a simplified empirical influence zone was proposed on the basis of the measurement of the ground surface displacement. The empirical influence zone, which was a straight line with an inclination angle of ~0.9 times the soil friction angle measured from vertical, could be considered a significant reference for predicting the failure surface of the shallow foundation under uplift loading.

Exploring the InSAR Deformation Series Using Unsupervised Learning in a Built Environment

As a city undergoes large-scale construction and expansion, there is an urgent need to monitor the stability of the ground and infrastructure. The time-series InSAR technique is an effective tool for measuring surface displacements. However, interpreting these displacements in a built environment, where observed displacements consist of mixed signals, poses a challenge. This study uses principal component analysis (PCA) and the k-means clustering method for exploring deformation series within an unsupervised learning context. The PCA method extracts the dominant components in deformation series, whereas the clustering method identifies similar deformation series. This method was tested on Kunming City (KMC) using C-band Sentinel-1, X-band TerraSAR-X, and L-band ALOS-2 PALSAR-2 data acquired between 2017 to 2022. The experiment demonstrated that the suggested unsupervised learning approach can group PS points with similar kinematic characteristics. Five types of deformation kinematic characteristics were discovered in the three SAR datasets: upward, slight upward, stability, slight downward, and downward. According to the results, less than 20% of points exhibit significant motion trends, whereas 50% show small velocity values but still demonstrate movement trends. The remaining 30% are relatively stable. Similar clustering results were obtained from the three datasets using unsupervised methods, highlighting the effectiveness of identifying spatial–temporal patterns over the study area. Moreover, It was found that clustering based on kinematic characteristics enhances the interpretation of InSAR deformation, particularly for points with small deformation velocities. Finally, the significance of PCA decomposition in interpreting InSAR deformation was discussed, as it can better represent series with noise, enabling their accurate identification.

Stereo Camera Setup for 360° Digital Image Correlation to Reveal Smart Structures of Hakea Fruits.

About forty years after its first application, digital image correlation (DIC) has become an established method for measuring surface displacements and deformations of objects under stress. To date, DIC has been used in a variety of in vitro and in vivo studies to biomechanically characterise biological samples in order to reveal biomimetic principles. However, when surfaces of samples strongly deform or twist, they cannot be thoroughly traced. To overcome this challenge, different DIC setups have been developed to provide additional sensor perspectives and, thus, capture larger parts of an object's surface. Herein, we discuss current solutions for this multi-perspective DIC, and we present our own approach to a 360° DIC system based on a single stereo-camera setup. Using this setup, we are able to characterise the desiccation-driven opening mechanism of two woody Hakea fruits over their entire surfaces. Both the breaking mechanism and the actuation of the two valves in predominantly dead plant material are models for smart materials. Based on these results, an evaluation of the setup for 360° DIC regarding its use in deducing biomimetic principles is given. Furthermore, we propose a way to improve and apply the method for future measurements.

100 years of monitoring in the Swiss National Park reveals overall decreasing rock glacier velocities

The rock glaciers of the Swiss National Park were the first in the world where in-situ measurements of surface displacement were undertaken, starting with the pioneering work of Chaix in 1918. Our research is focused on the four rock glaciers described by Chaix, bridging the historical data gap that existed between their early 20th-century measurements and the most recent observations. Through the application of photogrammetric techniques, we geomorphologically analyze the spatiotemporal evolution of rock glaciers in the region, and disentangle the interplay with their adjacent glaciers. We show that these rock glaciers are in different phases of degradation with a general trend of deceleration and loss of volume. Our findings reveal historical kinematic changes influenced by the hydrological contributions of adjacent glaciers, which were closely connected since the Little Ice Age but are now severely degraded. The observed hydrological control, suggests that ongoing climate-induced glacier degradation will likely result in a future scenario with limited new accelerations. Instead, a steady water flow from adjacent glaciers may sustain a gradual secondary creep, progressively slowing as permafrost degradation continues, driven by predicted warming and dry climatic conditions in the Alps.

Combined ambient vibration and surface displacement measurements for improved progressive failure monitoring at a toppling rock slab in Utah, USA

Seismic resonance and surface displacement measurements can be implemented in tandem to improve landslide characterization and progressive failure monitoring. Crack aperture data are frequently used in rock slope stability monitoring and often exhibit recognizable trends prior to failure, such as accelerated crack opening. Alternatively, ambient resonance data offer multiple parameters including modal frequencies, damping, and polarization that can be monitored alongside crack aperture and may respond differently to environmental forcings and complex failure evolution. We analyzed data from continuous ambient vibration monitoring and concomitant crack aperture measurements at the Courthouse Mesa instability, a large toppling sandstone slab in Utah, USA. Three years of data revealed crack aperture increases of 2–4 mm/year with no clearly detectable irreversible changes in modal parameters, including frequency. Annually, frequency and displacement varied by 29% and 19% of the mean, respectively, with average and maximum daily frequency fluctuations of 6.5% and 16%, respectively. These reversible cyclic changes were primarily temperature-driven, but annually, frequency was in-phase with temperature whereas crack aperture lagged temperature changes by ∼37 days. Polarization and damping also varied seasonally but were less strongly correlated with temperature. Conceptual 3D finite element modeling demonstrated consistent frequency decreases associated with crack propagation but variable changes in crack aperture measured at a single point; i.e., crack propagation did not always result in increased crack opening but always generated a resonance frequency decrease. Taken together, our data suggest a possible thermal wedging-ratcheting mechanism at the Courthouse Mesa instability, where annual thermoelastic crack closure is impeded by debris infill but the absence of downward crack propagation during the monitoring period is evidenced by no permanent resonance frequency changes. Our study demonstrates that combined seismic resonance and crack aperture data provide an improved description of rock slope instability behavior, supporting refined characterization and monitoring of changes accompanying progressive failure.

Elastic deformation as a tool to investigate watershed storage connectivity

Storage-discharge relationships and dynamic changes in storage connectivity remain key unknowns in understanding and predicting watershed behavior. In this study, we use Global Positioning System measurements of load-induced Earth surface displacement as a proxy for total water storage change in four climatologically diverse mountain watersheds in the western United States. Comparing total water storage estimates with stream-connected storage derived from hydrograph analysis, we find that each of the investigated watersheds exhibits a characteristic seasonal pattern of connection and disconnection between total and stream-connected storage. We investigate how the degree and timing of watershed-scale connectivity is related to the timing of precipitation and seasonal changes in dominant hydrologic processes. Our results show that elastic deformation of the Earth due to water loading is a powerful new tool for elucidating dynamic storage connectivity and watershed discharge response across scales in space and time.

Observation of Catalyst Layer Structure Formation from Electrode Slurry By White Light Confocal Microscopy

Mass transport in the catalyst layers (CLs) is an important factor to improve the cell performance of polymer electrolyte fuel cells (PEFCs). Transport properties in the CLs are determined by their structure and material distributions. The CLs are usually fabricated from electrode slurry in which Pt/C and ionomer are contained through applying and drying processes. Therefore, the structure and material distributions in the CLs are determined in these fabrication processes. However, these fabrication processes have been developed through trial-and-error approaches. A fundamental understanding of the structure formation mechanisms during the fabrication processes is required.The authors have performed impedance measurement and surface displacement measurement of electrode slurry during the drying process at the same time and detected the particle packing process (1, 2). For a further understanding of the fabrication process, observation of the structure formation of electrode slurry during drying by white light confocal microscopy was conducted in this study to break down the structure formation regimes. The observation of flow mode on the surface of the slurry and measurement of surface displacement were performed at the same time.Figure 1 shows confocal images of the electrode slurry during drying. Three different regimes were observed. At the initial state of drying, convection flow was observed. Then, the shrinking of the slurry was observed. After shrinking stopped, the solvent was evaporated from the porous media and finally, the structure of the catalyst layer was formed. Understanding the relationships between the variation of the flow regimes during the drying of electrode slurry and fabrication conditions including materials and process parameters can contribute to revealing the methodology for controlling porous structure and material distributions in the catalyst layers.AcknowledgmentsA part of this work was supported by JST PRESTO JPMJPR22O4.References(1) T. Suzuki et al., ECS Trans., 67(17), 465 (2015).(2) T. Suzuki et al., J. Therm. Sci. Technol., 16(1), 20-00259 (2021). Figure 1

A Digital Image Correlation Technique for Laboratory Structural Tests and Applications: A Systematic Literature Review

Digital image correlation (DIC) is an optical technique used to measure surface displacements and strains in materials and structures. This technique has demonstrated significant utility in structural examination and monitoring. This manuscript offers a comprehensive review of the contemporary research and applications that have leveraged the DIC technique in laboratory-based structural tests. The reviewed works encompass a broad spectrum of structural components, such as concrete beams, columns, pillars, masonry walls, infills, composite materials, structural joints, steel beams, slabs, and other structural elements. These investigations have underscored the efficacy of DIC as a metrological instrument for the precise quantification of surface deformation and strain in these structural components. Moreover, the constraints of the DIC technique have been highlighted, especially in scenarios involving extensive or complex test configurations. Notwithstanding these constraints, the effectiveness of the DIC methodology has been validated as a strain measurement instrument, offering numerous benefits such as non-invasive operation, full-field measurement capability, high precision, real-time surveillance, and compatibility with integration into other measurement instruments and methodologies.

Mechanical behavior analysis using small-size graphite disc compression testing with digital image correlation methods

The ASTM InternationalStandard Test Method for Tensile Stress-Strain of Carbon and Graphite (ASTM C749) requires dog-bone shaped specimens. Unfortunately, specimen sizes required in ASTM C749 are much too large for irradiation within a test reactor and are incompatible with irradiation capsule volumes, molten salt degradation facilities, or oxidation apparatus. The ASTM InternationalStandard Test Method for Tensile Strength Estimate by Disc Compression of Manufactured Graphite (ASTM D8289) was developed as an alternative that provides a means for testing tensile properties using smaller specimens when geometric constraints are present. However, the important stress–strain relation throughout the test loading history that could be recorded using ASTM C749 is lost by using ASTM D8289 because of the difficulties involved with using traditional strain gauges or extensometers on such a small specimen. In this work, a digital image correlation (DIC) method, which uses a full-field noncontact surface displacement measurement technique, was applied along with the ASTM D8289 splitting tensile test on eight small samples of graphite grade Mersen 2114 to track their deformation during compressive loading. Initial results showed that the DIC technique can measure the surface displacement/strain on these small (Ø6 × 3 mm) graphite specimens with high accuracy and good repeatability, indicating that the DIC technique, combined with the small-disc splitting tensile test in ASTM D8289, can capture the strain evolution in the test. Further comparison of measured strains with analytical and numerical simulation results provides additional understanding of the mechanical behaviour of this nuclear graphite material in complex stress states.

Dynamic surface displacement measurement using carrier optical vortex interferometer: A numerical study

The measurement of dynamic surface displacement is crucial in understanding mechanical and thermophysical dynamics at nanometre to micrometer-scale. Interferometers using optical vortices are gaining attention due to their ability to demodulate fringe patterns with helical phase profiles. In this paper, we propose a novel carrier optical vortex interferometer (COVI) that overcomes the limitations of conventional pixelated morphological operations for demodulating fringe patterns. The COVI introduces a carrier frequency by placing a rotating chopper, a collecting lens and a point photodetector at the exit of the interferometer when there is no surface displacement. When the surface moves, the time-dependent total intensity of the chopped fringe pattern produces a Doppler frequency shift with respect to the carrier frequency. Moreover, a high-order Laguerre-Gaussian (LG) beam exhibiting multiple concentric rings is employed to extend the COVI to the dynamic measurement of non-uniform surface displacement with an axisymmetric profile. In this case, the Doppler frequency shift splits into multiple peaks corresponding to the radii of the rings of the LG beam. Locating the Doppler frequency peaks gives an immediate indication of the surface displacement velocities at those radii. Accordingly, the dynamic surface displacement can be retrieved by integrating the velocities over time. The basic principle and the performance of the COVI are theoretically analysed and numerically demonstrated. In addition, the effect of surface misalignment on the displacement measurement is studied thoroughly and the limitations of the measurable velocity are discussed. Although the proposed approach requires further development to make it more applicable in practice, our study provides a first insight into how to measure a dynamic surface displacement using the COVI.

MONITORING GROUNDWATER STORAGE BASINS AND HYDROLOGICAL CHANGES USING THE GRACE SATELLITE AND SENTINEL-1 FOR THE GANGA RIVER BASIN

Abstract. Groundwater depletion-related subsidence is a significant issue in many parts of the world. It can permanently reduce the amount of groundwater stored in an aquifer and even cause structural damage to the Earth’s surface. The Ganga Basin in the northwestern region of India is no exception, with around a meter of subsidence occurring between 2018 and 2023. However, understanding the connection between variations in groundwater quantities and ground deformation has been challenging. We used surface displacement measurements from InSAR and gravimetric terrestrial water storage estimates from the GRACE satellite pair to characterize the hydrological dynamics within the Ganga Basin. Sentinel-1 was used to map the entire Ganga River basin in the inundated zone. The InSAR time series shows coherent short-term changes that coincide with hydrological features when the long-term aquifer compaction is removed. For instance, an uplift is seen at the confluence of multiple rivers and streams that drain into the southeastern margin of the basin in the winters of 2018–2019 and 2021–2022. Imaging the monthly spatial variations in water volumes is based on these data and calculations of mass changes from the orbiting of Sentinel-1 and GRACE satellites. We even employ machine learning techniques as evaluative methods to make it simple to combine InSAR quickly and convincingly with gravimetric datasets, which will help advance global efforts to understand better and manage groundwater resources.

Investigating high-speed liquid impingement with full-field measurements

Repeated high-speed liquid impingement on solid surfaces results in erosion that can have undesirable consequences. In recent years, the capacity of model predictions has exceeded the experimental measurements of an impingement; this work closes the gap. Using the grid method, tens of thousands of individual measurements of surface displacement were taken of the response of a polymethylmethacrylate test specimen to the impingement of a high-speed ( 233 m s − 1 ) curved-fronted water jet. The full-field measurements were taken at a rate of 5 MHz and interpreted using two models based on differing sets of assumptions. The results support the current qualitative description of a high-speed impingement. However, the widespread assumption of a rigid solid surface in existing analysis and modelling was found to be inaccurate: only the model that recognized the effect of the compliance of the solid surface was successful in predicting the measured temporal and spatial variation in displacement and acceleration. This model predicted that the energy absorbed by the solid surface was less than 0.3% of the total kinetic energy of the equivalent droplet impingement.