Coastal Subsidence in Cape Canaveral, FL, and Surrounding Areas: Shallow Subsidence Induced by Natural and Anthropogenic Processes
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Climate-driven sea-level rise is increasing the frequency of coastal flooding worldwide, exacerbated locally by factors like land subsidence from groundwater and resource extraction. However, a process rarely considered in future sea-level rise scenarios is sudden (over minutes) land subsidence associated with great (>M8) earthquakes, which can exceed 1 m. Along the Washington, Oregon, and northern California coasts, the next great Cascadia subduction zone earthquake could cause up to 2 m of sudden coastal subsidence, dramatically raising sea level, expanding floodplains, and increasing the flood risk to local communities. Here, we quantify the potential expansion of the 1% floodplain (i.e., the area with an annual flood risk of 1%) under low (~0.5 m), medium (~1 m), and high (~2 m) earthquake-driven subsidence scenarios at 24 Cascadia estuaries. If a great earthquake occurred today, floodplains could expand by 90 km 2 (low), 160 km 2 (medium), or 300 km 2 (high subsidence), more than doubling the flooding exposure of residents, structures, and roads under the high subsidence scenario. By 2100, when climate-driven sea-level rise will compound the hazard, a great earthquake could expand floodplains by 170 km 2 (low), 240 km 2 (medium), or 370 km 2 (high subsidence), more than tripling the flooding exposure of residents, structures, and roads under the high subsidence scenario compared to the 2023 floodplain. Our findings can support decision-makers and coastal communities along the Cascadia subduction zone as they prepare for compound hazards from the earthquake cycle and climate-driven sea-level rise and provide critical insights for tectonically active coastlines globally.
We used a model for permafrost hydrology informed by detailed measurements of soil ice content to better understand the potential risk of abrupt permafrost thaw triggered by melting ground ice, a key open question associated with permafrost response to a warming Arctic. Our spatially resolved simulations of a well-characterized site in polygonal tundra near Utqiaġvik, Alaska, agree well with multiple types of observations in the current climate. Projections indicate 63 cm of bulk subsidence from 2006 to 2100 in the strong-warming Representative Concentration Pathway 8.5 climate. Permafrost thaw as measured by the increase in active layer thickness (ALT)—the thickness of the soil layer that thaws each summer—is accelerated by subsidence, but the effect is relatively small. The ALT increases from the current-day value of approximately 50 cm to approximately 180 cm by 2100 when subsidence is included compared to about 160 cm when it is neglected. In these simulations, previously identified positive feedbacks between subsidence and thaw are self-limiting on decadal time frames because landscape runoff and increasing evapotranspiration result in drier tundra with weaker surface/atmosphere coupling. These results for a tundra site that is representative of large swathes of the Alaska North Slope suggest that subsidence is unlikely to lead to abrupt thaw over large areas. However, subsidence does have significant effects on the hydrology of polygonal tundra. Specifically, subsidence increases landscape runoff, which helps maintain streamflow in the face of increased evapotranspiration but also causes drier tundra conditions that could have deleterious effects on sensitive Arctic wetland ecosystems.
In September 2021, differential GPS (dGPS) points were collected in areas of visual subsidence in the Teller watershed near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway on the Seward Peninsula of Alaska. This study aimed to understand how structural permafrost loss is affecting meter-scale ground elevation. As ice thaws, heaving and slumping of the landscape creates new microtopographical features on the landscape that may alter surface hydrology and soil moisture and thus plant community composition and biogeochemical cycling. The Teller 27 field site is underlain with discontinuous permafrost, so the landscape features a variety of permafrost features. We collected ground elevations from eight subsidence areas in two forms: 1) Transects were sampled laterally through areas of ground subsidence to capture the high edges and low spots where the earth slumped. 2) The circumference of the subsidence area was sampled in order to measure the ground area affected by subsidence. These data were collected with an Emlid Reach RS2 dGPS and a base station. This dataset includes one *.csv of dGPS locations of the eight subsidence locations and one *.kml of measurement locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
The Lost Hills and Belridge oil felds are in the San Joaquin Valley, California. The major oil reservoir is high porosity and low permeability diatomite. Extraction of large volumes from shallow depths causes reduction in pore pressure and subsequent compaction, forming a surface subsidence bowl. We measure this subsidence from space using interferometric analysis of SAR (Synthetic Aperture Radar) data collected by the European Space Agency Remote Sensing Satellites (ERS-1 and ERS-2). Maximum subsidence rates are as high as 40 mm in 35 days or > 400 mm/yr, measured from interferograms with time separations ranging from one day to 26 months. The 8- and 26-month interferograms contain areas where the subsidence gradient exceeds the measurement possible with ERS SAR, but shows increased detail in areas of less rapid subsidence. Synoptic mapping of subsidence distribution from satellite data powerfully complements ground-based techniques, permits measurements where access is difficult, and aids identification of underlying causes.
This dataset is a model archive of the paper Permafrost Thaw, Uneven Subsidence and Projected Drying of Ice-wedge Polygon Tundra (in prep) to support a modeling study investigating how projected increases in Arctic temperature and precipitation will jointly influence hydrologic conditions in ice-rich tundra landscapes. With this dataset, this study is to address the research question: Will Arctic tundra landscapes become wetter or drier with increasing precipitation and temperature in the future when thaw-induced ground subsidence and associated microtopographic evolution are represented? The simulations focus on ice-wedge polygon tundra, a widespread form of ice-rich permafrost terrain that is highly sensitive to thaw-driven landscape change. This dataset contains model input and output data for four study watersheds in Alaska: Anaktuvuk, Utqiagvik (formerly Barrow), Brooks Foothills, and Prudhoe Bay. Simulations were performed using the Advanced Terrestrial Simulator (ATS, v1.5), a physics-rich integrated surface–subsurface hydrologic model. For each watershed, ten modeling cases were performed representing two landscape evolution conditions (with subsidence and without subsidence) combined with five climate forcing scenarios derived from Shared Socioeconomic Pathways (SSP5, SSP5 with precipitation trend, SSP2, SSP2 with precipitation trend, and SSP2 with double precipitation trend). Particularly, for each watershed under the forcing SSP2 with precipitation trend, there are two additional simulations considering spatially heterogeneous subsidence distributions: one assumes randomly distributed scaling and the other includes elevation dependent distribution scaling. These simulations span 1980–2099 and include spin-up runs (1980–2009) followed by transient projections (2010–2099). To facilitate reproducibility of simulations, all datasets are organized by watershed. For each study watershed, the dataset contains: (1) Pre-partitioned mesh files for 32-core modeling (.par.32.XX), located in EACH_WATERSHED/mesh/basin; and also a non-partitioned mesh file (.exo) located in EACH_WATERSHED/mesh; (2) Climate forcings corresponding to the five SSP scenarios (.h5), located in EACH_WATERSHED/data; (3) Final states (.h5) from column spin-up modeling used to initialize historical watershed-scale spin-up runs from 1980 to 2009, located in EACH_WATERSHED/PreSpinupHistorical; (4) Final states (.h5) of historical watershed-scale spin-up runs from 1980 to 2009 used to initialize projection runs, located in EACH_WATERSHED/Spinup_daymetERA5; (5) ATS modeling input files (.xml), located in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/inputfiles; (6) ATS modeling output files (.dat), located in in EACH_WATERSHED/EACH_SIMULATION_SCENARIO/combined_obs; (7) For the Brooks Foothills watershed, additional spatial model outputs are provided (.h5) for selected years (2033 and 2093) used to generate spatial figures in this study, located in Brooksfoothills/EACH_SIMULATION_SCENARIO/results-WITH/WITHOUT_SUBSIDENCE-year2033/2093. All data files with suffix .h5 can be accessible through Python h5py, and all data files with suffix of .dat can be imported by Python pandas. Mesh file with .exo can be visualized through Paraview or read by Python netCDF. The Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) project is a research effort to reduce uncertainty in the Department of Energy’s Energy Exascale Earth System Model (E3SM) by developing a predictive understanding of Arctic tundra ecosystems underlain by permafrost and to quantify feedbacks from the Arctic tundra to the Earth system. NGEE Arctic is supported by the Department of Energy's Office of Biological and Environmental Research. Over Phases 1–3, observations made by the NGEE Arctic team across a gradient of permafrost landscapes in Arctic Alaska improved the representation of tundra processes in the land surface component of E3SM (the E3SM Land Model, ELM). Model improvements emphasized unique aspects of permafrost environments and explored reductions in model complexity while retaining predictive power. The Arctic-informed ELM developed by NGEE Arctic has been used to make novel predictions on processes ranging from permafrost thaw to soil biogeochemical cycling to Earth system feedbacks associated with the unique characteristics of tundra plants. In Phase 4, the NGEE Arctic team is evaluating our new predictive understanding under novel conditions across the Arctic domain. In collaboration with partners at long-term pan-Arctic research sites we are examining whether an Arctic-informed ELM can faithfully simulate interactions among surface and subsurface processes at site, regional, and pan-Arctic scales. In turn, we are using variety of tools to dynamically extend and evaluate ELM inference, with an emphasis on data synthesis and pan-Arctic model evaluation, reintegration of code with an evolving E3SM, scaling across heterogeneous Arctic landscapes, and the appropriate representation of the impacts of increasingly frequent Arctic disturbances.
In this study, we analyzed the effects of snow cover changes caused by snow fences (SFs) installed in 2017 in the Alaskan tundra to examine ground subsidence. Digital surface model data obtained through LiDAR-based remote sensing in 2019 and 2022, combined with a field survey in 2021, revealed approximately 0.2 m of ground subsidence around the SF. To investigate the relationship between SF-induced snow cover changes and ground subsidence, geophysical methods, electrical resistivity tomography (ERT) and ground-penetrating radar (GPR), were applied in 2023 to analyze subsurface characteristics. The increased snow cover due to the SF-enhanced insulation, delaying the penetration of winter cold into the subsurface. This delay caused subsurface temperatures to decrease more slowly, melting the upper permafrost and increasing the thickness of the active layer. ERT and GPR surveys well delineated the boundary between the active layer and permafrost, confirming that the increased snow cover thickened the active layer. This thickening led to the melting of pore ice, causing water runoff and ground compaction, which resulted in subsidence. The runoff also formed channels flowing eastward over the SF. This study highlights how changes in snow cover can influence active layer properties, leading to localized environmental changes and ground subsidence.
The construction of hydropower dams is a common strategy to support a country's increasing need for electricity and river water management for industry and agriculture. Although the hydrological and geophysical impacts of water relocation are usually assessed prior to impoundment, their accuracy is generally limited due to the lack of in situ observations, especially in a remote area. This study presents a workflow to quantify the terrestrial water storage change (TWS) and land subsidence induced by a reservoir's water impoundment using multiple satellite observations (GRACE, Landsat), land surface models (CABLE, GLDAS, NCEP, ECMWF), and GPS data. The study site is the Bakun Dam, located in Sarawak, Malaysia, which is the largest hydropower dam in Southeast Asia. Commencing operation in late 2010, the dam induced a change of water mass and lake surface area that was clearly observed by GRACE and Landsat observations, respectively. During the 17-month impounding period (from August 2010 to December 2011), GRACE observed a dramatic increase of approximately 200 mm equivalent water height, while Landsat detected an increased lake extent of around 600 km2. In this paper, a forward model is developed to determine the increased water surface level corresponding to GRACE observations, estimated to be about 120 m. In contrast to GRACE, the TWS derived from land surface models cannot capture the increased TWS, due to the lack of reservoir routing algorithms in the models. In addition, the land subsidence was calculated using the disk load model constructed based on the GRACE-derived lake level and Landsat-derived lake extent; the result is validated with the GPS data from BIN1 station, located at the western coast of Borneo. The commencement stage of the Bakun Dam induces the large-scale land subsidence, which causes the GPS-BIN1 station to subside by ~9 mm, and move toward the Bakun Lake by ~4 mm. Computation of the surface displacements directly from GRACE spherical harmonic coefficient data fails to capture the subsidence feature, mainly due to the truncation error. Overall, this study demonstrates that evaluating GRACE in conjunction with Landsat, LSMs, and GPS data allows the exploitation of the gravity signal at a much smaller spatial scale than its intrinsic resolution. Benefiting from global coverage, the newly developed satellite-based algorithm is a valuable tool for assessing the impacts of reservoir operation on hydrological and geophysical changes from local to regional scales.
A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. UAVSAR and Sentinel-1 seasonal deformation returns produced consistent spatial deformation patterns with residual root mean squared errors of 13 and 21 millimeters, respectively. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution.In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.
A rapidly warming Arctic has compromised the structural integrity of critical infrastructure through accelerated permafrost thaw and thermokarst development underlying these areas. Infrastructure, including roads, bridges, and airports across the state of Alaska are particularly at risk, as permafrost underlies ~85% of the state. However, monitoring the impacts of permafrost thaw on infrastructure is largely limited to in situ observations and frequently identified after the damage is evident. In order to assist transportation and infrastructure decision-makers in Alaska, this project identified and quantified areas of surface subsidence near critical infrastructure. Seasonal interferograms were created using Sentinel-1 C-band Synthetic Aperture Radar (SAR) and L-band Uninhabited Aerial Vehicle SAR (UAVSAR) data to identify areas experiencing surface deformation. Additionally, Light Detection and Ranging (LiDAR) datasets were used to validate select interferograms created between 2017 and 2019. Validation of subsidence detection across platforms was performed over a 7x8 sq. kilometer field site for 2017. The strongest relationship in spatial deformation is observed between Sentinel-1 and UAVSAR with a residual root mean square error of 20 mm. These results suggest that both UAVSAR and Sentinel-1 platforms are capable of detecting surface subsidence. The higher resolution of UAVSAR is better able to resolve localized subsidence features of less than 80 meters, but is limited by temporal resolution. In conjunction, UAVSAR and Sentinel-1 can provide complementary spatial and temporal resolutions for subsidence analysis in the absence of in situ data.
This Modeling Archive is in support of a NGEE Arctic publication in review "Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw". The study used a cryohydrology model to assess the potential risk of abrupt permafrost thaw triggered by melting ground ice, a key open question associated with permafrost response to a warming Arctic. The spatially resolved simulations are for a small catchment 465 ice-wedge polygons in polygonal tundra near Utqiagvik, Alaska in the high-emissions RCP8.5 climate scenario. The simulations are compared to runoff, evapotranspiration and subsidence in the current climate and agree well. The study used the ATS code configured as an intermediate-scale cryohydrology model (Advanced Terrestrial Simulator, Version v2). The archive includes input files for spinup (1985 to 2005) and projections (2006 to 2100 - the manuscript reports 2006 to 2098). Three of the projections include the effects of subsidence and microtopography change with different depth profiles of ice content corresponding to the median, 20th percentile and 80th percentile. The fourth projection has subsidence turnoff and uses the reference case (median) ice content. Spatially averaged or aggregated output variables are included for the projections. Selected checkpoint files for the projections and postprocessing scripts are also included. Files included are *.xml; *.h5; *.exo; *.py; *.sh, *. nb, mesh files, and one file in the original Excel format plus *.csv and *.pdf to conserve formatting contained in the original file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
Biostratigraphic data from the COST B-2 well off New York and four deep commercial wells off Nova Scotia have been used to remove the effect of sediment loading at the Atlantic-type continental margin off the East Coast of North America. The resulting subsidence contains terms due to both 'tectonic' and 'eustatic' effects. By assuming the tectonic subsidence is thermal in origin these effects can be separated. The 'eustatic' effects have been isolated by least squares fitting an exponential curve to the subsidence data. The resulting sea-level curve shows a maximum rise in sea level during the Late Cretaceous era which probably does not exceed 150 m. The tectonic subsidence has been interpreted in terms of a simple thermal model for the cooling lithosphere. Based on this model the thermal thickness of the lithosphere and the total amount of crustal thinning are estimated. These estimates which are consistent with surface ship gravity and GEOS-3 altimeter measurements are used to define the structural elements which control the tectonic evolution of the margin.
A recent article in Reviews of Geophysics explores land subsidence drivers, rates, and impacts across the globe. It also discusses the need for improved process representations and the inclusion of the interplay among land subsidence and climatic extremes, including their effects in models and risk assessments. Here, we asked the lead author to explain the concept of land subsidence, its impacts, and future directions needed for improved mitigation.
InSAR is a key technique used to constrain contributions of diverse processes to coastal subsidence, also known as vertical land motion (VLM). However, coastal environments can pose major challenges for InSAR due to natural disturbances that degrade interferogram quality. We describe a new multi-primary pairing strategy for persistent scatterer InSAR (PS-InSAR) to estimate subsidence in challenging coastal environments. Our method retains only consistent PS candidates across multiprimary substacks and solves for redundant velocity observations using SVD-based inversion, similar to the conventional small baseline subset (SBAS) method. Through simulations and a case study comparing with single-primary PS-InSAR and conventional SBAS techniques, we show that our pairing strategy reduces temporal and spatial uncertainty in subsidence estimates in the presence of strong but temporary decorrelation loss, even with increased distance from the reference point. Moreover, our method visibly dampens time-series variation and decreases standard error in our time series fit by nearly 2x in our case study. Thus, we find that implementing a multi-primary PS-InSAR configuration is a simple method of increasing the robustness of VLM estimates in challenging coastal environments.
Abstract We produced a 10 Myr synthetic stratigraphic section using a forward stratigraphic model that generates marine deltaic stratigraphy over geological timescales. We recursively fit the model using a Bayesian inversion algorithm to test: (1) if it could be accurately reconstructed; (2) if the parameters used to create it could be recovered; and (3) the sensitivity of the model output to given model parameters and the attendant physical processes. The original synthetic stratigraphic section was produced with cyclical sea‐level variations of 40 and 30 m with 2.4 and 10 Myr periods respectively. Sediment was also supplied cyclically, in 2.4 and 10 Myr cycles with amplitudes of 30 and 80 tons/100 kyr, respectively, varying from a mean of 232 tons/100 kyr. Parameter values were sampled to fit the model using a Markov chain Monte Carlo algorithm, resulting in a ±5 m (1σ) variation between the experimental output and the original. Sea level varied by ±7 m (1σ) within the posterior distribution of parameters. As a result, both the 10 Myr and 2.4 Myr sea‐level cycles could be extracted from the original output. The variation in sediment supply was approximately ±38 tons/100 kyr (1σ) and, as a result, only the larger long‐term supply variations could be accurately recovered in refitting the model. The variation in thermal, flexural and total subsidence across those parameter sets is less than ±10 m (1σ). The original section experienced 150 m of total subsidence at the depocentre. Our results demonstrate the distinct and interpretable imprint of sea level and subsidence on continental margin stratigraphy can be quantified. Moreover, we conclude that sea‐level change produces a defined effect on the geometries of stratigraphic architecture, and that techniques applied for the purpose of delineating sea‐level variation from continental margin strata have a well‐founded conceptual basis.
Radar altimeter measurements from the GEOS-3 and SEASAT satellites are being evaluated to assess their potential contribution to terrain mapping. The primary evaluation area is the San Joaquin Valley of southern California; 40,000/sq km of the Valley have been mapped at a contour interval of 10 m from the satellite altimeter measurements. The accuracy of the altimeter derived terrain elevations is being assessed by comparison with 1:24,000 and digitized 1:250,000 maps and by intercomparisons at the crossover altimeter intersections. Comparisons of the altimeter derived elevations with historical maps archived at the U.S. Geological Survey confirms the USGS 1926-1972 subsidence contours for this area. Preliminary results from a similar analysis in the Houston-Galveston area of subsidence also demonstrates a capability of measuring land subsidence by satellite altimetry.
Quantifying the subsidence of the polar winter stratospheric vortex is essential to the analysis of ozone depletion, as chemical destruction often occurs against a large, altitude-dependent background ozone concentration. Using N2O measurements made during SOLVE on a variety of platforms (ER-2, in-situ balloon and remote balloon), the 1999-2000 Arctic winter subsidence is determined from N2O-potential temperature correlations along several N2O isopleths. The subsidence rates are compared to those determined in other winters, and comparison is also made with results from the SLIMCAT stratospheric chemical transport model.
The construction of hydropower dams is a common strategy to support a country's increasing need for electricityand river water management for industry and agriculture. Although the hydrological and geophysical impacts ofwater relocation are usually assessed prior to impoundment, their accuracy is generally limited due to the lack ofin situ observations, especially in a remote area. This study presents a workflow to quantify the terrestrial waterstorage change (TWS) and land subsidence induced by a reservoir's water impoundment using multiple satelliteobservations (GRACE, Landsat), land surface models (CABLE, GLDAS, NCEP, ECMWF), and GPS data. The studysite is the Bakun Dam, located in Sarawak, Malaysia, which is the largest hydropower dam in Southeast Asia.Commencing operation in late 2010, the dam induced a change of water mass and lake surface area that wasclearly observed by GRACE and Landsat observations, respectively. During the 17-month impounding period(from August 2010 to December 2011), GRACE observed a dramatic increase of approximately 200mmequivalent water height, while Landsat detected an increased lake extent of around 600 km2. In this paper, aforward model is developed to determine the increased water surface level corresponding to GRACE observations,estimated to be about 120 m. In contrast to GRACE, the TWS derived from land surface models cannotcapture the increased TWS, due to the lack of reservoir routing algorithms in the models. In addition, the landsubsidence was calculated using the disk load model constructed based on the GRACE-derived lake level andLandsat-derived lake extent; the result is validated with the GPS data from BIN1 station, located at the westerncoast of Borneo. The commencement stage of the Bakun Dam induces the large-scale land subsidence, whichcauses the GPS-BIN1 station to subside by ~9 mm, and move toward the Bakun Lake by ~4 mm. Computation ofthe surface displacements directly from GRACE spherical harmonic coefficient data fails to capture the subsidencefeature, mainly due to the truncation error. Overall, this study demonstrates that evaluating GRACE inconjunction with Landsat, LSMs, and GPS data allows the exploitation of the gravity signal at a much smallerspatial scale than its intrinsic resolution. Benefiting from global coverage, the newly developed satellite-basedalgorithm is a valuable tool for assessing the impacts of reservoir operation on hydrological and geophysicalchanges from local to regional scales.