Isostatic Adjustment Research Articles

Impacts of land use change on surface infiltration capacity and urban flood risk in a representative karst mountain city over the last two decades

Urban areas are undergoing rapid expansion, resulting in diminished vegetation cover and an escalating urban flood problem, and posing substantial threats to aquatic ecosystems, human safety, and socioeconomic structures. However, research on urban flood risk using methods like the Analytic Hierarchy Process (AHP), further exploration of spatiotemporal variations is needed, especially within the context of karst mountainous urban clusters. This study focuses on Guiyang city within a karst mountainous urban cluster, investigating fractional vegetation cover (FVC), infiltration capacity, and urban flood risk. Methodologies encompass slope trend analysis, the utilization of the Google Earth Engine, and geographic detectors to assess the dynamics of FVC and infiltration capacity. AHP is employed to assign weights to infiltration capacity, land use and land cover (LULC), FVC, and elevation, culminating in the generation of flood risk maps through linear weighted overlay. The results showed that: (1) The average FVC in Guiyang City was 0.7440 in 21 years, with relatively low levels in the central and southern regions. The FVC increased by 0.21% per year from 2000 to 2020, driven mainly by land use change and human activities. (2) The infiltration capacity of the city of Guiyang has increased as a whole, mainly due to reforestation efforts in specific areas, while the infiltration capacity of impervious areas tends to decrease. (3) The central urban areas exhibit greater vulnerability, with an estimated ten-year average growth rate of 73.36% in very high flood risk areas by 2030, affecting 7.38% of Guiyang's total area. These urban flood risk maps serve as valuable tools for local governments to enhance urban management practices.

Assessing Microbial Diversity in Páramo Soils (Multistrategy Analysis): Effects of Potato Farming and Livestock Grazing in Nevados National Natural Park, Colombia

High Andean Páramos are very fragile neotropical ecosystems. Moreover, biodiversity in these areas is threatened by the anthropic activities of agriculture, cattle raising, and mining and has been little studied. Changes associated with potato farming and livestock grazing on microorganisms of Páramo soil of the Nevados National Natural Park (Nevados NNP) were assessed by (1) determination of physical and chemical properties (physicochemical matrix) and enzymatic activities associated (enzymatic activity matrix) with different biogeochemical cycles (C, N, and P); (2) microbial community functional diversity via evaluation of functional groups associated with carbon, nitrogen, and phosphorus cycles using cultivation-dependent techniques (arable functional group matrix and most probable number matrix); and (3) microbial diversity using cultivation-independent techniques that employ the hypervariable V5–V6 region of the 16S rRNA gene and pyrosequencing (16S-454 genus matrix and 16S-454 OTU matrix). Four of the six evaluated matrices (physicochemical, enzymatic activities, most probable number, and arable functional groups) revealed significant differences according to land use. The strategy adopted by the arable functional group matrix, in which the diversity of nitrogen fixation, phosphate solubilization, and cellulolytic compounds was evaluated, showed the most significant impacts of the different factors (land use, season, and elevation), especially those caused by potato cultivation and livestock. These results indicate that the initial impacts of potato farming and livestock grazing on the microbial community in El Bosque Village are better detected by functional diversity analysis than by molecular analysis of the 16S rRNA gene V5–V6 variable region. The results may have been caused by the type of molecular marker used in the analyses and the type of agricultural practices used by peasant farmers, which affect the functional diversity of the soil community. Among these practices are the maintenance of fallow periods greater than 7 years between each potato crop and the small proportion of cattle in relation to the total land area of the village. As the findings can be interpreted as an indicator of the early impacts of potato cultivation and livestock on microbial diversity, the effects of implementing community management plans, applying agroecological models, retaining biocultural memory, and changing agrarian structure are relevant for mitigating future changes.

Glacial isostatic adjustment reduces past and future Arctic subsea permafrost

Sea-level rise submerges terrestrial permafrost in the Arctic, turning it into subsea permafrost. Subsea permafrost underlies ~ 1.8 million km2 of Arctic continental shelf, with thicknesses in places exceeding 700 m. Sea-level variations over glacial-interglacial cycles control subsea permafrost distribution and thickness, yet no permafrost model has accounted for glacial isostatic adjustment (GIA), which deviates local sea level from the global mean due to changes in ice and ocean loading. Here we incorporate GIA into a pan-Arctic model of subsea permafrost over the last 400,000 years. Including GIA significantly reduces present-day subsea permafrost thickness, chiefly because of hydro-isostatic effects as well as deformation related to Northern Hemisphere ice sheets. Additionally, we extend the simulation 1000 years into the future for emissions scenarios outlined in the Intergovernmental Panel on Climate Change’s sixth assessment report. We find that subsea permafrost is preserved under a low emissions scenario but mostly disappears under a high emissions scenario.

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.

Surface loading on a self-gravitating, linear viscoelastic Earth: moving beyond Maxwell

SUMMARY Constitutive laws are a necessary ingredient in calculations of glacial isostatic adjustment (GIA) or other surface loading problems (e.g. loading by ocean tides). An idealized constitutive law governed by the Maxwell viscoelastic model is widely used but increasing attention is being directed towards more intricate constitutive laws that, in particular, include transient rheology. In this context, transient rheology collectively refers to dissipative mechanisms activated in addition to creep modelled by the Maxwell viscoelastic model. Consideration of such viscoelastic models in GIA is in its infancy and to encourage their wider use, we present constitutive laws for several experimentally derived transient rheologies and outline a flexible method in which to incorporate them into geophysical problems, such as the viscoelastic deformation of the Earth induced by surface loading. To further motivate this need, we demonstrate, via the Love number collocation method, how predictions of crustal displacement depart significantly between Earth models that adopt only Maxwell viscoelasticity and those with transient rheology. Throughout this paper, we highlight the differences in terminology and emphases between the rock mechanics, seismology and GIA communities, which have perhaps contributed towards the relative scarcity in integrating this broader and more realistic class of constitutive laws within GIA. We focus on transient rheology since the associated deformation has been demonstrated to operate on timescales that range from hours to decades. With ice mass loss enhanced at similar timescales as a consequence of anthropogenically caused climate change, the ability to model GIA with more accurate constitutive laws is an important tool to investigate such problems.

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.

On calculating glacial isostatic adjustment

Modeling the earth's fluid and elastic response to the melting of the glaciers of the last ice age is the most direct way to infer the earth's radial viscosity profile. Here, we compare two methods for calculating the viscoelastic response to surface loading. In one, the elastic equation of motion is converted to a viscoelastic equation using the Correspondence Principle. In the other, elastic deformation is added to the viscous flow as isostatic adjustment proceeds. The two modeling methods predict adjustment histories that are different enough to potentially impact the interpretation of the observed glacial isostatic adjustment (GIA). The differences arise from buoyancy and whether fluid displacements are subjected to hydrostatic pre-stress. The methods agree if they use the same equations and boundary conditions. The origin of the differences is determined by varying the boundary conditions and pre-stress application.

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).

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.

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%.