Ice volume and basal topography estimation using geostatistical methods and ground-penetrating radar measurements: application to the Tsanfleuron and Scex Rouge glaciers, Swiss Alps

Ground-penetrating radar (GPR) is widely used for determining mountain glacier thickness. However, this method provides thickness data only along the acquisition lines, and therefore interpolation has to be made between them. Depending on the interpolation strategy, calculated ice volumes can differ and can lack an accurate error estimation. Furthermore, glacial basal topography is often characterized by complex geomorphological features, which can be hard to reproduce using classical interpolation methods, especially when the field data are sparse or when the morphological features are too complex. This study investigates the applicability of multiple-point statistics (MPS) simulations to interpolate glacier bedrock topography using GPR measurements. In 2018, a dense GPR data set was acquired on the Tsanfleuron Glacier (Switzerland). These data were used as the source for a bedrock interpolation. The results obtained with the direct-sampling MPS method are compared against those obtained with kriging and sequential Gaussian simulations (SGSs) on both a synthetic data set – with known reference volume and bedrock topography – and the real data underlying the Tsanfleuron Glacier. Using the MPS modeled bedrock, the ice volume for the Scex Rouge and Tsanfleuron glaciers is estimated to be 113.9 ± 1.6 million cubic meters. The direct-sampling approach, unlike the SGS and kriging, allowed not only an accurate volume estimation but also the generation of a set of realistic bedrock simulations. The complex karstic geomorphological features are reproduced and can be used to significantly improve for example the precision of subglacial flow estimation.

Competing influences of the ocean, atmosphere and solid earth on transient Miocene Antarctic ice sheet variability

Benthic δ18O levels vary strongly during the warmer-than-modern early- and mid-Miocene (23 to 14 Myr ago), suggesting a dynamic Antarctic ice sheet (AIS). So far, however, realistic simulations of the Miocene AIS have been limited to equilibrium states under different CO2 levels and orbital settings. Earlier transient simulations lacked ice-sheet-atmosphere interactions, and used a present-day rather than Miocene Antarctic bedrock topography. Here, we quantify the effect of ice-sheet-atmosphere interactions, running IMAU-ICE using climate forcing from Miocene simulations by the general circulation model GENESIS. Utilising a recently developed matrix interpolation method enables us to interpolate the climate forcing based on CO2 levels (between 280 and 840 ppm) as well as ice sheet configurations (between no ice and a large ice sheet). We furthermore implement recent reconstructions of Miocene Antarctic bedrock topography. We find that the positive albedo-temperature feedback, partly compensated by the negative ice-volume-precipitation feedback, increases hysteresis in the relation between CO2 and ice volume (V). Together, these ice-sheet-atmosphere interactions decrease the amplitude of AIS variability caused by 40-kyr forcing CO2 cycles by 21 % in transient simulations. Thereby, they also diminish the contribution of AIS variability to benthic δ18O fluctuations. Furthermore, we show that under equal atmospheric and oceanic forcing, the amplitude of 40-kyr transient AIS variability becomes 10 % smaller during the early- and mid-Miocene, due to the evolving bedrock topography. Lastly, we quantify the influence of ice shelf formation around the Antarctic margins, by comparing simulations with Last Glacial Maximum (LGM) basal melt conditions, to ones in which ice shelf growth is prevented. Ice shelf formation increases hysteresis in the CO2-V relation, and amplifies 40-kyr AIS variability by 19 % using LGM basal melt rates, and by 5 % in our reference setting.

Derivation of bedrock topography measurement requirements for the reduction of uncertainty in ice sheet model projections of Thwaites Glacier

Determining the future evolution of the Antarctic Ice Sheet is critical for understanding and narrowing the large existing uncertainties in century-scale global mean sea level rise (SLR) projections. One of the most significant glaciers/ice streams in Antarctica, Thwaites Glacier, is at risk of destabilization and, if destabilized, has the potential to be the largest regional-scale contributor of SLR on Earth. This is because Thwaites Glacier is vulnerable to the marine ice sheet instability, as its grounding line is significantly influenced by ocean-driven basal melting rates, and its bedrock topography retrogrades into kilometer deep troughs. In this study, we investigate how bedrock topography features influence the grounding line migration beneath Thwaites Glacier when extreme ocean-driven basal melt rates are applied. Specifically, we design experiments using the Ice-Sheet and Sea-level System Model (ISSM) to quantify the SLR projection uncertainty due to reported errors in the current bedrock topography maps that are often used by ice sheet models. We find that spread in model estimates of sea level rise contribution from Thwaites glacier due to the reported bedrock topography error could be as large as 21.9 cm after 200 years of extreme ocean warming. Next, we perturb the bedrock topography beneath Thwaites Glacier using wavelet decomposition techniques to introduce realistic noise (within error). We explore the model space with multiple realizations of noise to quantify what spatial and vertical resolutions in bedrock topography are required to minimize the uncertainty in our 200-year experiment. We conclude that at least a 2 km spatial and 8 m vertical resolution would independently constrain possible SLR to ±2 cm over 200 years, fulfilling requirements outlined by the 2017 Decadal Survey for Earth Science. Lastly, we perform an ensemble of simulations to determine in which regions our model of Thwaites Glacier is most sensitive to perturbations in bedrock topography. Our results suggest that the retreat of the grounding line is most sensitive to bedrock topography in proximity to the grounding line's initial position. Additionally, we find that the location and amplitude of the bedrock perturbation is more significant than its sharpness and shape. Overall, these findings inform and benchmark observational requirements for future missions that will measure ice sheet bedrock topography, not only in the case of Thwaites Glacier but for Antarctica on the continental scale.

Large-Scale Modeling of Solum Thickness Based on the Local Topographic Attributes of Ground and Bedrock Surfaces

This study was aimed to address the importance of neighborhood scale and using bedrock topography in the soil-landscape modeling in a low-relief large region. For this study, local topographic attributes (slopes and curvatures) of the ground surface (DTM) and bedrock surface (DBM) were derived at five different neighborhood sizes (3×3, 9×9, 15×15, 21×21, and 27×27). Afterward, the topographic attributes were used for multivariate adaptive regression splines (MARS) modeling of solum thickness. The results demonstrate that there are statistical differences among DTM and DBM morphometric variables and their correlation to solum thickness. The MARS analyses revealed that the neighborhood scale could remarkably affect the soil–landscape modeling. We developed a powerful MARS model for predicting soil thickness relying on the multi-scale geomorphometric analysis (R2= 83%; RMSE= 12.70 cm). The MARS fitted model based on DBM topographic attributes calculated at a neighborhood scale of 9×9 has the highest accuracy in the prediction of solum thickness compared to other DBM models (R2 = 61%; RMSE = 19cm). This study suggests that bedrock topography can be potentially utilized in soil-related research, but this idea still needs further investigations.

Ice volume and basal topography estimation using geostatistical methods and GPR measurements : Application on the Tsanfleuron and Scex Rouge glacier, Swiss Alps

Ground Penetrating Radar (GPR) is nowadays widely used for determining glacier thickness. However, this method provides thickness data only along the acquisition lines and therefore interpolation has to be made between them. Depending on the interpolation strategy, calculated ice volumes can differ and can lack an accurate error estimation. Furthermore, glacial basal topography is often characterized by complex geomorphological features, which can be hard to reproduce using classical interpolation methods, especially when the conditioning data are sparse or when the morphological features are too complex. This study investigates the applicability of multiple-point statistics (MPS) simulations to interpolate glacier bedrock topography using GPR measurements. In 2018, a dense GPR data set was acquired on the Tsanfleuron Glacier (Switzerland). The results obtained with the direct sampling MPS method are compared against those obtained with kriging and sequential Gaussian simulations (SGS) on both a synthetic data set – with known reference volume and bedrock topography – and the real data underlying the Tsanfleuron glacier. Using the MPS modelled bedrock, the ice volume for the Scex Rouge and Tsanfleuron Glacier is estimated to be 113.9 ± 1.6 Mio m3. The direct sampling approach, unlike the SGS and the kriging, allowed not only an accurate volume estimation but also the generation of a set of realistic bedrock simulations. The complex karstic geomorphological features are reproduced, and can be used to significantly improve for example the precision of under-glacial flow estimation.

Evaluating the role of topographic inversion in the formation of the Stanislaus Table Mountains in the Sierra Nevada (California, USA)

The Table Mountains, a flat-topped series of ridges capped by a 10.4 Ma latite flow in the Stanislaus River watershed, are considered to be evidence for late Cenozoic uplift-driven landscape rejuvenation in the northern Sierra Nevada range (California, USA). The commonly accepted theory for the formation of these mesas posits that the latite flowed and cooled within a bedrock paleovalley and, since then, the surrounding landscape has eroded away, leaving behind the volcanic deposit as a ridge. Although this theory is accepted by many, it has not been thoroughly tested. In this study, I examine a series of geological cross-sections extracted along the length of the latite deposit to determine whether the evidence supports the existence of bedrock valley walls on both sides of the 10.4 Ma flow. I find that the presence of older Cenozoic deposits adjacent to the latite flow precludes the possibility that the flow would have been constrained within a bedrock valley. Moreover, the cross-section from an 1865 report that has been offered as evidence of topographic inversion (and subsequently reproduced in numerous publications) does not accurately represent the topography at that site. I conclude that there is no evidence that the bedrock topography has been inverted and that instead, the latite flowed within a channel cut into underlying Cenozoic deposits, which have since mostly eroded away. This study, therefore, refutes the hypothesis that the Stanislaus River watershed was rejuvenated in the late Cenozoic and challenges the claim for recent significant uplift of the region.

Subsurface Topographic Modeling Using Geospatial and Data Driven Algorithm

Infrastructures play an important role in urbanization and economic activities but are vulnerable. Due to unavailability of accurate subsurface infrastructure maps, ensuring the sustainability and resilience often are poorly recognized. In the current paper a 3D topographical predictive model using distributed geospatial data incorporated with evolutionary gene expression programming (GEP) was developed and applied on a concrete-face rockfill dam (CFRD) in Guilan province- northern to generate spatial variation of the subsurface bedrock topography. The compared proficiency of the GEP model with geostatistical ordinary kriging (OK) using different analytical indexes showed 82.53% accuracy performance and 9.61% improvement in precisely labeled data. The achievements imply that the retrieved GEP model efficiently can provide accurate enough prediction and consequently meliorate the visualization insights linking the natural and engineering concerns. Accordingly, the generated subsurface bedrock model dedicates great information on stability of structures and hydrogeological properties, thus adopting appropriate foundations.