Isostatic Adjustment Research Articles

Assessing canopy height measurements from ICESat-2 and GEDI orbiting LiDAR across six different biomes with G-LiHT LiDAR

The height of woody plants is a defining characteristic of forest and shrubland ecosystems because height responds to climate, soil and disturbance history. Orbiting LiDAR instruments, Ice, Cloud and land Elevation Satellite-2 (ICESat-2) and Global Ecosystem Dynamics Investigation LiDAR (GEDI), can provide near-global datasets of plant height at plot-level resolution. We evaluate canopy height measurements from ICESat-2 and GEDI with high resolution airborne LiDAR in six study sites in different biomes from dryland shrub to tall forests, with mean canopy height across sites of 0.5–40 m. ICESat-2 and GEDI provide reliable estimates for the relative height with RMSE and mean absolute error (MAE) of 7.49 and 4.64 m (all measurements ICESat-2) and 6.52 and 4.08 m (all measurements GEDI) for 98th percentile relative heights. Both datasets slightly overestimate the height of short shrubs (1–2 m at 5 m reference height), underestimate that of tall trees (by 6–7 m at 40 m reference height) and are highly biased (>3 m) for reference height <5 m, perhaps because of the difficulty of distinguishing canopy from ground signals. Both ICESat-2 and GEDI height estimates were only weakly sensitive to canopy cover and terrain slope (R 2 < 0.06) and had lower error for night compared to day samples (ICESat-2 RMSE night: 5.57 m, day: 6.82 m; GEDI RMSE night: 5.94 m, day: 7.03 m). For GEDI, the day versus night differences varied with differences in mean sample heights for the day and night samples and had little effect on bias. Accuracy of ICESat-2 and GEDI canopy heights varies among biomes, and the highest MAE was observed in the tallest, densest forest (GEDI: 7.85 m; ICESat-2: 7.84 m (night) and 12.83 m (day)). Improvements in canopy height estimation would come from better discrimination of canopy photons from background noise for ICESat-2 and improvements in the algorithm for decomposing ground and canopy returns for GEDI. Both would benefit from methods to distinguish outlier samples.

Spatial variability of marine-terminating ice sheet retreat in the Puget Lowland

Abstract. Understanding drivers of marine-terminating ice sheet behavior is important for constraining ice contributions to global sea level rise. In part, the stability of marine-terminating ice is influenced by solid Earth conditions at the grounded-ice margin. While the Cordilleran Ice Sheet (CIS) contributed significantly to global mean sea level during its final post-Last-Glacial-Maximum (LGM) collapse, the drivers and patterns of retreat are not well constrained. Coastal outcrops in the deglaciated Puget Lowland of Washington State – largely below sea level during glacial maxima, then uplifted above sea level via glacial isostatic adjustment (GIA) – record the late Pleistocene history of the CIS. The preservation of LGM glacial and post-LGM deglacial sediments provides a unique opportunity to assess the variability in marine ice sheet behavior of the southernmost CIS. Based on paired stratigraphic and geochronological work, with a newly developed marine reservoir correction for this region, we identify that the late-stage CIS experienced stepwise retreat into a marine environment between 15 000 and 14 000 years before present, consistent with timing of marine incursion into the region reported in earlier works. Standstill of marine-terminating ice for at least 500 years, paired with rapid vertical landscape evolution, was followed by continued retreat of ice in a subaerial environment. These results suggest rapid rates of solid Earth uplift and topographic support (e.g., grounding zone wedges) stabilized the ice margin, supporting final subaerial ice retreat. This work leads to a better understanding of shallow-marine and coastal-ice-sheet retreat and is relevant to sectors of the contemporary Antarctic and Greenland ice sheets and marine-terminating outlet glaciers.

Game-theoretic optimization of landslide susceptibility mapping: a comparative study between Bayesian-optimized basic neural network and new generation neural network models.

Landslide susceptibility mapping is essential for reducing the risk of landslides and ensuring the safety of people and infrastructure in landslide-prone areas. However, little research has been done on the development of well-optimized Elman neural networks (ENN), deep neural networks (DNN), and artificial neural networks (ANN) for robust landslide susceptibility mapping (LSM). Additionally, there is a research gap regarding the use of Bayesian optimization and the derivation of SHapley Additive exPlanations (SHAP) values from optimized models. Therefore, this study aims to optimize DNN, ENN, and ANN models using Bayesian optimization for landslide susceptibility mapping and derive SHAP values from these optimized models. The LSM models have been validated using the receiver operating characteristics curve, confusion matrix, and other twelve error matrices. The study used six machine learning-based feature selection techniques to identify the most important variables for predicting landslide susceptibility. The decision tree, random forest, and bagging feature selection models showed that slope, elevation, DFR, annual rainfall, LD, DD, RD, and LULC are influential variables, while geology and soil texture have less influence. The DNN model outperformed the other two models, covering 7839.54 km2 under the very low landslide susceptibility zone and 3613.44 km2 under the very high landslide susceptibility zone. The DNN model is better suited for generating landslide susceptibility maps, as it can classify areas with higher accuracy. The model identified several key factors that contribute to the initiation of landslides, including high elevation, built-up and agricultural land use, less vegetation, aspect (north and northwest), soil depth less than 140 cm, high rainfall, high lineament density, and a low distance from roads. The study's findings can help stakeholders make informed decisions to reduce the risk of landslides and ensure the safety of people and infrastructure in landslide-prone areas.

Modeling habitat suitability for the lesser-known populations of endangered mountain nyala (Tragelaphus buxtoni) in the Arsi and Ahmar Mountains, Ethiopia.

Habitat suitability models have become a valuable tool for wildlife conservation and management, and are frequently used to better understand the range and habitat requirements of rare and endangered species. In this study, we employed two habitat suitability modeling techniques, namely Boosted Regression Tree (BRT) and Maximum Entropy (Maxent) models, to identify potential suitable habitats for the endangered mountain nyala (Tragelaphus buxtoni) and environmental factors affecting its distribution in the Arsi and Ahmar Mountains of Ethiopia. Presence points, used to develop our habitat suitability models, were recorded from fecal pellet counts (n = 130) encountered along 196 randomly established transects in 2015 and 2016. Predictor variables used in our models included major landcover types, Normalized Difference Vegetation Index (NDVI), greenness and wetness tasseled cap vegetation indices, elevation, and slope. Area Under the Curve model evaluations for BRT and Maxent were 0.96 and 0.95, respectively, demonstrating high performance. Both models were then ensembled into a single binary output highlighting an area of agreement. Our results suggest that 1864 km2 (9.1%) of the 20,567 km2 study area is suitable habitat for the mountain nyala with land cover types, elevation, NDVI, and slope of the terrain being the most important variables for both models. Our results highlight the extent to which habitat loss and fragmentation have disconnected mountain nyala subpopulations. Our models demonstrate the importance of further protecting suitable habitats for mountain nyala to ensure the species' conservation.

Land use and topographic controls on soil chemical properties in some selected sites of the North West Region of Cameroon

ABSTRACT Land use change affects soil forming processes and modifies site conditioning factors. This paper evaluates land use and topographic controls on soil chemical properties in selected sites of the North West Region of Cameroon. Three topographic zones comprising; low altitude (<1200m), mid-altitude (1200-1500m), and high altitude (˃1500m), under four land use types were studied. 60 soil samples were collected on plots of 30m2, at 0-20cm depth and subjected to chemical analyses. Significant relationships between variables were established via ANOVA and Pearson’s correlation tests. The results revealed significant correlation between soil properties at (P<0.05) and (P<0.01) confident intervals between soil properties with land use and elevation classes. A significant decline (P< 0.01) was observed in the concentrations of pH, Base Saturation (BS), Cation Exchange Capacity (CEC), Total Nitrogen (TN), Soil Organic Carbon (SOC), Soil Organic Matter (SOM), Phosphorus (P) and exchangeable bases in farmlands. Soil chemical properties showed variations across land uses and elevation classes. Soil pH, BS, CEC, SOC, SOM, P, and Ca2+ were statistically significant with topographic variations, while BS, CEC, TN, and Mg2+ varied significantly with land use. Exchangeable potassium (K+) and exchangeable sodium (Na+) showed no significant variations with land use and topographic position.

Assessment of water shortage in underground aquifer in Abuja during dry season

Water shortage is a complex issue with severe implications for human well-being, agriculture, and ecosystems. Climate change, population growth, and inadequate water management practices contribute to this global problem. This study is to identify the causes of ground water scarcity and determine groundwater potential zones in the Abuja community. The research area's borehole coordinates, Landsat 8 satellite imagery, AsterDEM 30m resolution DEM data, and vertical electrical sounding (VES) data were all used to do this. Unsupervised classification of Landsat imagery was used to create a layer of land use and cover, image filtering techniques were used to improve the visualization of lineament extraction, and density analysis was used to quantify lineament density. AsterDEM data was subjected to surface analysis to acquire elevation data, while VES data were interpolated to produce spatial distributions of the resistivity and thickness parameters. To identify groundwater potential zones, multiple criterion analysis using the analytical hierarchical process (AHP) was utilized to reclassify variables such as land use, elevation, lineament density, resistivity, and thickness. To create the zones, these characteristics were weighted and layered. According to the findings, resistivity levels varied from 6.25 m to 676 m, and the geologic ground structure's thickness ranged from 0.27 m to 92.37 m. Elevation varied from 41 meters to 720 meters, while lineament density ranged from 0 to 0.04. 74% of the land was categorized as vegetated, 21% as built up, 2.7% as water bodies, and 2.3% as rock formations. Within Abuja, zones of groundwater potential were identified as being very low (5%), low (26.7%), marginally high (26.3%), moderately high (28.5%), and very high (13.4%)

Analyzing the spatial relationship between land surface temperature and elevation in three gullies locations in southeastern Nigeria

Gully erosion is a dangerous phenomenon that threatened human existence, plants and animals communities. Families are being separated from their ancestral home and livelihood due to gully erosion. Also, available agricultural lands to combat food insecurity are contently depleted on yearly basis across the globe as a result of gullies menace. Southeastern Nigeria is highly vulnerable to gully erosions due to it geology and studies on spatial relationships between gully LST and elevation has not been carried out, particular by applying remote sensing and GIS technique to investigate it variations. Available studies where limited to mapping and causes of gully erosion in the region. The study applies LST and elevation data to investigate correlation on three gullies locations. LST was derived from Landsat data and was first converted to radiance image while the elevation data was obtained from Google Earth image. Elevation data was used to produce raster surface in that cell values equivalent to LST at every point can be extracted. Three sets of paired sample points of LST and elevation was extracted from the three gullies locations and used to compute correlation coefficient (r). The study observed at Nanka gully a strong negative correlation of -0.665. This implies an increase in LST correspond to decrease in elevation within the gully. At Ekwolobia and Aguluezechukwu gullies sites, positive correlation coefficient of 0.692 and 0.910 were obtained. The positive correlation coefficients implied that LST and elevation increase or decrease within the gullies. This might be due to unequal distribution of radiation within gully surface as a result of three canopies. For further study, it is recommended that improve elevation data source like LiDAR elevation data should be use to investigate spatial correlation between LST and elevation at gully location.

Unveiling the Hidden Threat: Drought‐Induced Inelastic Subsidence in Expansive Soils

AbstractExpansive soils pose a significant challenge in geotechnical engineering, especially in coastal areas. While research has mainly focused on their elastic properties, this study explores the overlooked aspect of inelastic subsidence during prolonged droughts, utilizing decade‐long GPS datasets from the University of Houston Coastal Center. Our findings reveal substantial subsidence, approximately one to two dm, during the summer droughts of 2018, 2020, 2022, and 2023, due to compaction within the upper 4 m of expansive soils. Inelastic subsidence constitutes roughly 10% of the total subsidence, resulting in step‐like permanent land elevation loss over time. Notably, drought‐induced subsidence is prominent in open‐field areas with expansive soils but is minor in built‐up areas or in non‐expansive soil regions. The occurrence of inelastic subsidence challenges traditional assessments of relative sea‐level rise and coastal flooding, emphasizing the need to consider it in coastal infrastructure planning for enhanced resilience against climate uncertainties.

Sex and landscape influence spatial genetic variation in a large fossorial mammal, the Bare-nosed Wombat (Vombatus ursinus)

Abstract Dispersal is an important process that is widely studied across species, and it can be influenced by intrinsic and extrinsic factors. Intrinsic factors commonly assessed include the sex and age of individuals, while landscape features are frequently-tested extrinsic factors. Here, we investigated the effects of both sex and landscape composition and configuration on genetic distances among bare-nosed wombats (Vombatus ursinus)—one of the largest fossorial mammals in the world and subject to habitat fragmentation, threats from disease, and human persecution including culling as an agricultural pest. We analyzed a data set comprising 74 Tasmanian individuals (30 males and 44 females), genotyped for 9,064 single-nucleotide polymorphisms. We tested for sex-biased dispersal and the influence of landscape features on genetic distances including land use, water, vegetation, elevation, and topographic ruggedness. We detected significant female-biased dispersal, which may be related to females donating burrows to their offspring due to the energetic cost of excavation, given their large body sizes. Land use, waterbodies, and elevation appeared to be significant landscape predictors of genetic distance. Land use potentially reflects land clearing and persecution over the last 200 years. If our findings based on a limited sample size are valid, retention and restoration of nonanthropogenic landscapes in which wombats can move and burrow may be important for gene flow and maintenance of genetic diversity.

Automated Estimation of Sub-Canopy Topography Combined with Single-Baseline Single-Polarization TanDEM-X InSAR and ICESat-2 Data

TanDEM-X bistatic interferometric system successfully generated a high-precision, high-resolution global digital elevation model (DEM). However, in forested areas, two core problems make it difficult to obtain sub-canopy topography: (1) the penetrability of short-wave signals is limited, and the DEM obtained in dense forest areas contains a significant forest signal, that is, the scattering phase center (SPC) height; and (2) the single-baseline and single-polarization TanDEM-X interferometric synthetic aperture radar (InSAR) data cannot provide sufficient observations to make the existing physical model reversible for estimating the real surface phase, whereas the introduction of optical data makes it difficult to ensure data synchronization and availability of cloud-free data. To overcome these problems in accurately estimating sub-canopy topography from TanDEM-X InSAR data, this study proposes a practical method of sub-canopy topography estimation based on the following innovations: (1) An orthogonal polynomial model was established using TanDEM-X interferometric coherence and slope to estimate the SPC height. Interferometric coherence records forest height and dielectric property information from an InSAR perspective and has spatiotemporal consistency with the InSAR-derived DEM. (2) Introduce Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) data to provide more observational information and automatically screen ICESat-2 control points with similar forest and slope conditions in the local area to suppress forest spatial heterogeneity. (3) A weighted least squares criterion was used to solve this model to estimate the SPC height. The results were validated at four test sites using high-precision airborne light detection and ranging (LiDAR) data as a reference. Compared to the InSAR-derived DEM, the accuracy of the sub-canopy topography was improved by nearly 60%, on average. Furthermore, we investigated the necessity of local modeling, confirming the potential of the proposed method for estimating sub-canopy topography by relying only on TanDEM-X and ICESat-2 data.

The 3D stress field of Nordland, northern Norway - insights from numerical modelling

Abstract The Nordland area in northern Norway is the seismically most active area on mainland Fennoscandia. It exhibits patterns of coastal extension, which contrasts with the first-order regional stress pattern that reflects compression aligned with the North Atlantic ridge-push. The regional stress field has been considered to emanate from the interaction of ridge push and glacial isostatic adjustment; while the local stress pattern can be additionally influenced by gravitational, topographic stresses, as well as the flexural effects of erosion and sediment deposition. We employ finite element numerical models at a crustal scale to study the 3D stress field, using existing geometric constraints from previous geophysical studies. Internal body forces, induced by variations in density, topography or Moho depth, already yield significant deviatoric stresses. In the models tested, these can strongly influence the near-surface stress regime, in particular for the continental margin setting we are investigating. In addition, redistribution of rock mass, which occurred mainly under Pleistocene glaciation, can modify the stress field significantly on a semi-regional scale. We consider this process to be the main driver for the coastal extension, in particular in areas where erosion has been high. The northern Atlantic coast of Norway is an area of neotectonic activity and anomalous patterns in seismicity and land uplift. This study aims to improve our understanding of the present-day stress regime in this area. In addition, our study sheds light on the importance of stresses due to redistribution of sediments, a stress driver that is often neglected in stress studies. An earlier version of this manuscript was included in a non-peer reviewed project report (Gradmann et al., 2018).

Signal Photon Extraction and Classification for ICESat-2 Photon-Counting Lidar in Coastal Areas

The highly accurate data of topography and bathymetry are fundamental to ecological studies and policy decisions for coastal zones. Currently, the automatic extraction and classification of signal photons in coastal zones is a challenging problem, especially the surface type classification without auxiliary data. The lack of classification information limits large-scale bathymetric applications of ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2). In this study, we propose a photon extraction–classification method to process geolocated photons in coastal areas from the ICESat-2 ATL03 product. The basic idea is to extract the signal photons using an adaptive photon clustering algorithm, and the extracted signal photons are classified based on the accumulated histogram and triangular grid. We also generate the bottom profile using the weighted interpolation. In four typical coastal areas (artificial coast, natural coast, island, and reefs), the extraction accuracy of a signal photons exceeds 0.90, and the Kappa coefficients of four surface types exceed 0.75. This method independently extracts and classifies signal photons without relying on auxiliary data, which can greatly improve the efficiency of obtaining bathymetric points in all kinds of coastal areas and provide technical support for other coastal studies using ICESat-2 data.

An interactive visualization and data portal tool (PALTIDE) for relative sea level and palaeotidal simulations of the northwest European shelf seas since the Last Glacial Maximum

ABSTRACTRelative sea level (RSL) predictions based on glacial isostatic adjustment (GIA) simulations and palaeotidal predictions generated by hydrodynamic models using GIA‐generated palaeotopographies are available in the published literature, and datasets are available via data repositories. However, these data are often difficult to extract for specific locations or timeslices, requiring users to request datasets from corresponding authors. To overcome the intractability of these data and to enable users to interrogate datasets themselves without requiring offline requests, we have developed PALTIDE, an online visualization tool with intuitive user interface accessible at https://shiny.bangor.ac.uk/paleotidal/. The model domain for this interactive visualization tool is the northwest European continental shelf, covering the period from the Last Glacial Maximum (LGM) to the present day, and is based on previous GIA simulations by Bradley and colleagues and hydrodynamic simulations using Regional Ocean Modelling System (ROMS) published by Ward and colleagues. The tool is developed in R and utilizes a number of packages including shiny and bslib for the frontend, and arrow, raster and the tidyverse for backend data processing. The tool enables visualizations and data downloads for RSL, tidal amplitude and tide‐dependent parameters for any location within the model domain over 1000‐year timesteps from the LGM to the present.

Lateral and radial viscosity structure beneath Fennoscandia inferred from seismic and magnetotelluric observations

Fennoscandia is continuously uplifting in response to past deglaciation, termed glacial isostatic adjustment or GIA, and its mantle viscosity is well constrained from ice sheet and sea level data. Here, we compare those GIA-constrained viscosities for the Fennoscandian upper mantle with geophysically-constrained viscosities. We construct the upper mantle viscosity structure of Fennoscandia by inferring temperature and water content from seismic and magnetotelluric (MT) data. Using a 1-D MT model for Fennoscandian cratons together with a global seismic model, we infer an upper mantle viscosity (below 250 km) of ∼1021±2 Pa·s, which encompasses the GIA-constrained viscosities of 1020 − 1021 Pa·s. The GIA viscosities are better matched if the Fennoscandian upper mantle is a wet harzburgite or a dry pyrolite, where pyrolite is ∼10 times more viscous than harzburgite. Using the average temperatures and water contents for harzburgitic upper mantle, the GIA viscosities require 1–4 mm grain sizes indicating a diffusion creep regime. In northwestern Fennoscandia, where a high-resolution 2-D resistivity model is available, greater inferred mantle water content implies viscosities that are 10–100 times lower than those for the Fennoscandian Craton. Our work suggests that the combination of seismic and MT observations can improve upper mantle viscosity estimates, especially for regions with laterally-varying viscosity structures or where GIA constraints are not available. Although our method represents an important step forward, viscosity uncertainty can be further reduced by incorporating additional constraints on rock composition, grain size and mantle stress, as well as more accurate geophysical data, into the viscosity calculation.

Decoding the Interplay Between Tidal Notch Geometry and Sea‐Level Variability During the Last Interglacial (Marine Isotope Stage 5e) High Stand

AbstractRelic coastal landforms (fossil corals, cemented intertidal deposits, or erosive features carved onto rock coasts) serve as sea‐level index points (SLIPs), that are widely used to reconstruct past sea‐level changes. Traditional SLIP‐based sea‐level reconstructions face challenges in capturing continuous sea‐level variability and dating erosional SLIPs, such as tidal notches. Here, we propose a novel approach to such challenges. We use a numerical model of cliff erosion embedded within a Monte Carlo simulation to investigate the most likely sea‐level scenarios responsible for shaping one of the best‐preserved tidal notches of Last Interglacial age in Sardinia, Italy. Results align with Glacial Isostatic Adjustment model predictions, indicating that synchronized or out‐of‐sync ice‐volume shifts in Antarctic and Greenland ice sheets can reproduce the notch morphology, with sea level confidently peaking at 6 m and only under a higher than present erosion regime. This new approach yields insight into sea‐level trends during the Last Interglacial.

MAPPING OF FLOOD-PRONE AREA UNDER IMPACT OF TIDAL INFLUENCE IN SINGKAWANG CITY

Flood is a seasonal threat that occurs when a body of water overflows from the existing channel and inundates the surrounding area. In the last three years, Singkawang City has experienced frequent floods. Although they did not cause casualties, the floods caused much harm to the surrounding community, such as educational and office activities that could not run normally. To reduce the impact of the flood disaster in Singkawang City, a complete and integrated flood control and management effort is needed, which maps flood-prone areas in its initial stage. This research aims to provide information about the characteristics of the tides and the level of vulnerability to flooding caused by the influence of the tides in Singkawang City in the form of a zoning map.In this research, the parameters used are the distance from the beach, river buffer, land slope, land elevation, and land cover. Then, flood-prone areas can be mapped using Geographic Information Systems (GIS) and the weight overlay method.This research shows that in Singkawang City, the area considered safe from flooding is 24048.449 Ha or 43.947%. Areas classified as not vulnerable have an area of 19938.498 Ha or 36.436%. Areas classified as vulnerable have an area of 9068.206 Ha or 16.571%. Meanwhile, areas classified as very vulnerable have an area of 1666.860 Ha or only 3.046%. 

Multi-datasets to monitor and assess meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region.

This study analyzed the meteorological and hydrological droughts in a typical basin of the Brazilian semiarid region from 1994 to 2016. In recent decades, this region has faced prolonged and severe droughts, leading to marked reductions in agricultural productivity and significant challenges to food security and water availability. The datasets employed included a digital elevation model, land use and cover data, soil characteristics, climatic data (temperature, wind speed, solar radiation, humidity, and precipitation), runoff data, images from the MODIS/TERRA and AQUA sensors (MOD09A1 and MODY09A1 products), and soil water content. A variety of methods and products were used to study these droughts: the meteorological drought was analyzed using the Standardized Precipitation Index (SPI) derived from observed precipitation data, while the hydrological drought was assessed using the Standardized Soil Index (SSI), the Nonparametric Multivariate Standardized Drought Index (NMSDI), and the Parametric Multivariate Standardized Drought Index (PMSDI). These indices were determined using water balance components, including streamflow and soil water content, from the Soil Water Assessment Tool (SWAT) model, and evapotranspiration data from the Surface Energy Balance Algorithm for Land (SEBAL). The findings indicate that the methodology effectively identified variations in water dynamics and drought periods in a headwater basin within Brazil's semiarid region, suggesting potential applicability in other semiarid areas. This study provides essential insights for water resource management and resilience building in the face of adverse climatic events, offering a valuable guide for decision-making processes.

Crustal shear wave velocity and radial anisotropy beneath the Mississippi embayment from ambient noise tomography

Imaging of shallow multiple basins and middle to lower crustal structure beneath the Mississippi embayment is still limited. No tomography studies have delineated multiple basins as effectively as those from reflection and drilling experiments. Several studies have constructed different velocity models for the middle to lower crust. We take advantage of the Northern Embayment Lithosphere Experiment dataset and long-term deployment of 277 3-component broadband stations installed from 1990 to 2018 to image crustal shear wave velocity and radial anisotropy in the Mississippi embayment. We first construct 5–40s group velocity maps for Rayleigh wave and 5–30s ones for Love wave. In the 5 s group velocity map, we observe that low velocity features correlate spatially with the sediment thickness from the Crust 1.0 model. High velocity anomalies are associated with the Ozark uplift and the Nashville Dome. In the 32 s group velocity map, high-low velocity boundaries align with 40 km crustal thickness contours from the Crust 1.0 model. We then invert Rayleigh and Love group velocity dispersion for shear wave velocity and radial anisotropy at each grid point and construct a 3D model accordingly. At the depth of 0–5 km of the model, we find that low velocity features characterize the Mississippi Valley Graben, Rough Creek Graben, Black Warrior Basin, and coastal flood plain. High velocity features mark thinly sedimented regions, like the Ozark uplift and the Nashville Dome. Regions with high gravity anomalies are characterized with negative anisotropies. At the depth of 5–12 km, we observe low velocity features in the Missouri Batholith, centering around 10 km. This region is characterized with negative radial anisotropy (Vsh < Vsv), inferring possible intrusions. High-low velocity boundaries correlate with the Appalachian-Ouachita thrust front. At the depth of 12–24 km, the Mississippi Valley Graben is filled with high velocity material, which may be related to the formation of the graben due to isostatic equilibrium. At the depth of 24–43 km, high velocity anomalies characterize the lower crust of the Mississippi embayment, consistent with high density features from the inversion of free air anomaly. The high velocity anomaly might be responsible for the formation of the embayment due to isostatic adjustment. The average velocity in the lower crust is approximately 4.3 km/s. Mafic Pikwitonei granulite is a possible material, indicating relative strong lower crust. This work provides useful information to explain earthquake occurrence in the New Madrid Seismic Zone and regional tectonic settings.

Timescales of glacial isostatic adjustment in Greenland: is transient rheology required?

SUMMARY The possibility of a transient rheological response to ice age loading, first discussed in the literature of the 1980s, has received renewed attention. Transient behaviour across centennial to millennial timescales has been invoked to reconcile apparently contradictory inferences of steady-state (Maxwell) viscosity based on two distinct data sets from Greenland: Holocene sea-level curves and Global Navigation Satellite System (GNSS) derived modern crustal uplift data. To revisit this issue, we first compute depth-dependent Fréchet kernels using 1-D Maxwell viscoelastic Earth models and demonstrate that the mantle resolving power of the two Greenland data sets is highly distinct, reflecting the differing spatial scale of the associated surface loading: the sea-level records are sensitive to viscosity structure across the entire upper mantle while uplift rates associated with post-1000 CE fluctuations of the Greenland Ice Sheet have a dominant sensitivity to shallow asthenosphere viscosity. Guided by these results, we present forward models which demonstrate that a moderate low viscosity zone beneath the lithosphere in Maxwell Earth models provides a simple route to simultaneously reconciling both data sets by significantly increasing predictions of present-day uplift rates in Greenland whilst having negligible impact on predictions of Holocene relative sea-level curves from the region. Our analysis does not rule out the possibility of transient deformation, but it suggests that it is not required to simultaneously explain these two data sets. A definitive demonstration of transient behaviour requires that one account for the resolving power of the data sets in modelling the glacial isostatic adjustment process.

Analysis of Flood Inundation Vulnerability to the Deli Watershed of North Sumatra Using Remote Sensing and GIS Techniques

Deli watersheds are listed as one of the most heavily damaged watersheds in Indonesia, and this causes many problems, such as floods, flash floods, and landslides. Studying this watershed becomes essential because the Deli watershed passes through a major city and has become the main source of flood and other natural disasters in the city such as Medan, The study aims to detect the vulnerability level of the areas around the watershed and the most rapid and possible way to study it is by using remote sensing and GIS, the overlay method by considering several parameters that affect the level of vulnerability to flooding in Deli Watershed, North Sumatra. Some of the parameters considered include the topographic wetness index, slope, land elevation, river flow density, land use cover, normalized difference vegetation index, distance to river, and rainfall. Each parameter is given a weight and value according to each classifier. The overlay process is carried out using ArcGIS 10.8.1 software, results are divided into 5 levels of area vulnerabilities all around the area, the study shows that all parts of Medan City in the Deli watershed have a high level of flood vulnerability and some areas with higher ground elevation such as Tanah Karo have spots area that is vulnerable with floods such as Daulu District with 0.45 ha and Semangat Gunung District with 0.63 ha of its areas are vulnerable to floods. The Topographic wetness index, Normalized difference vegetation Index, slope, and land use are the main factors causing flooding with weighting values 16, 13, 11, and 14. The other parameters elevation, flow density, distance to the river, rainfall, and soil class each have weighting values 7, 10, 11, 8, and 10. Slope with a range of 0-8% in most areas of Medan City are classified as very prone to flood inundation. This is due to the area's flat topography and low river flow density, the existing 3.5 km old sewer in the Deli Tua area is unable to accommodate the flood inundation load in the city of Medan and it is necessary to build two new sewers which are more effective and efficient in diverting the flow of water, before entering the city of Medan which makes the area vulnerable to becoming a water catchment area when it rains, thereby increasing the risk of flooding. With this flood-prone map, efforts to manage and mitigate floods in Medan City can be carried out. Information on vulnerable locations can be used to take appropriate preventive and countermeasures, such as building adequate drainage, regulating land use, and controlling river flows.