Climate induced sea-level rise poses a risk to coastal areas on the Island of Hawai’i, and many of the island’s historic cultural lands are in danger of becoming overtaken by wetlands or inundation. In partnership with the County of Hawai’i, State of Hawai’i Department of Land and Natural Resources, and Arizona State University, NASA DEVELOP mapped wetland extent and short-term sea-level rise inundation risk. We utilized Earth observations over a 10-year span (2013 – 2022) that included the NASA MEaSUREs Gridded Sea Surface Height Anomalies and MEaSUREs Group for High Resolution Sea Surface Temperature datasets, United States Geological Survey (USGS) Hawai'i Digital Elevation Models (DEM), and in-situ tidal gauge data. Flood risk index values were acquired for five known Hawai’i flood events between 2019 – 2021 from the Global Flood Mapper tool on Google Earth Engine. We used a random forest model to predict short-term sea-level rise inundation risk along the entire coast of Hawai’i. Current wetland extents and probabilistic locations of new wetlands were modeled with the most recently available data from PlanetScope Surface Reflectance optical imagery (2022), USGS 3D Elevation Program (3DEP) 10m DEM (2013), temperature and precipitation data from the Hawai’i Climate Atlas, and soils data from the Hawai’i Soil Atlas (2014) using the Wetland Intrinsic Potential tool. Results indicated locations that had the highest probability of wetland creation. The end products aimed to help the partners prioritize efforts to meeting regulation requirements for wetlands protection, evaluate the inundation risk to historical features, and support decision-making for their Shoreline Setback and Climate Adaption plans.
We seek to calibrate the flow law for polythermal ice through shear strain analysis. In a warming climate, increased melting of glaciers and ice caps play a big role in sea level rise. Approximately 60% of the current contribution to sea level rise from ice loss is attributed to glaciers and ice caps, raising the urgency of sharpening mass balance change predictions in regions of streaming flow. Polythermal glaciers constitute a significant portion of these contributing glaciers, though our knowledge of their flow dynamics is incomplete. Thermally complex polythermal glaciers have both warm and cold ice which lead to weak wet-based beds, with significant amounts of basal sliding and deformable till. Consequently, polythermal glaciers experience significant shear strain as their lateral shear margins sustain the majority of the resisting stress. Most in-situ and in-lab studies of natural ice over recent years have focused on bodies of ice with frozen beds that experience minimal shear strain downglacier and across vertical planes (with depth) relative to the bed. The lack of studies on wet-based polythermal glaciers causes uncertainties in the flow law, as differences in flow law factors between polythermal ice and bodies of ice with frozen beds have the potential to induce more than an order of magnitude difference in ice velocity. To improve calibration of the flow law for polythermal ice, we seek to improve our understanding of their shear strain regimes. We developed and deployed tilt sensor systems on the polythermal Jarvis Glacier in Alaska, where we drilled multiple boreholes close to Jarvis’ shear margin and installed three boreholes with our tilt sensor systems. The tilt sensors measure gravity, magnetic and temperature data, and each system consists of multiple sensors connected along a cable and serially communicating along a common data bus with a datalogger. We have recently retrieved a year of Jarvis tilt sensor data and calculated the at-depth shear strain rates in the boreholes, allowing evaluation of the at-depth shear strain rate regimes of polythermal ice against theoretical models developed using Glen’s flow law. We present the development of our data collection methodology and the results of our shear strain analysis, with suggestions for potential calibrations of the flow law for polythermal ice.
The nucleation and triggering of basal microseisms, or icequakes, at the bottom of glaciers as the ice flows over it can grant us valuable insights about deformation processes that occur at the bed. The collaborative efforts of Penn State University and the British Antarctic Survey (BAS) during the 2018/2019 austral summer enabled the deployment of several seismic arrays over 3 months in the Rutford Ice Stream in West Antarctica for monitoring natural source seismicity. Using the earthquake detection and location software QuakeMigrate, we generated unique high-resolution icequake catalogs, particularly at Rutford’s grounding line. Our data showed an unprecedented number of detected events which we used to resolve key topographical features and characteristics at the bed like sticky spots, and how they related to the continuous ice loading-slipping process at the bed. To properly quantify relations between events, we performed rigorous testing via manual event inspection at each array to determine a trigger threshold that aims to balance event coverage with artefact minimization. To handle the massive amounts of incoming seismic data and subsequent located icequakes, we also created a systematic data processing pipeline, and used machine learning clustering algorithms to resolve inter- & intra-clusters spatial and temporal relations. We present our pre-processing methods on handling similarly large datasets and present findings from our seismic data in combination with other data sources, like GPR and tidal gauge data, that improves our understanding of ice flow dynamics in the region.
We present a cost-efficient tilt sensor that was originally developed by our team at Dartmouth College to study ice deformation as part of the Jarvis Glacier Project, and we showcase our successful initial run that includes the development, deployment, and data collection processes. In this case study, we installed our tilt sensor system in two boreholes drilled close to the lateral shear margin of Jarvis Glacier in Alaska and successfully collected over 16 months of uninterrupted borehole deformation data in a harsh polythermal glacial environment. The data included gravity and magnetic data that we used to track the orientation of our sensors in the boreholes over time, and the resultant kinematic measurements enabled us to compute borehole deformation. While our sensors were applied under polythermal thermal regime conditions, we present use cases for our sensors in a variety of glacier thermal regimes including Athabasca glacier, a temperate glacier in Canada, and in Antarctic regions with similar polythermal regimes such as ice streams and outlet glaciers. Sensors embedded in our tilt sensors can be modified to suit different needs, and the tilt sensor can also be modified for different boreholes and glacier conditions. Our goal is to improve the accessibility of borehole geophysics research mainly through supporting production efforts of our sensor for various research needs. With an established sensor development plan, successful applications in the field, and years of experience, our team is open to potential research collaborations with researchers who are interested in using our tilt sensors. Our team is working with Polar Research Equipment, a Dartmouth alumni founded company that specializes in the development of polar research tools, that will serve as a commercial resource for researchers who may require support during the development process or mass-production of our cost-efficient (~20% the price of other commercial versions) yet effective tilt sensors.
Microseismicity, induced by the sliding of a glacier over its bed, can be used to characterize frictional properties of the ice-bed interface, which are a key parameter controlling ice stream flow. We use naturally occurring seismicity to monitor spatiotemporally varying bed properties at Rutford Ice Stream, West Antarctica. We locate 230000 micro-earthquakes with local magnitudes from –2.0 to –0.3 using 90 days of recordings from a 35-station seismic network located ~40 km upstream of the grounding line. Events exclusively occur near the ice-bed interface and indicate predominantly flow-parallel stick-slip. They mostly lie within a region of interpreted stiff till and along the likely stiffer part of mega-scale glacial landforms. Within these regions, micro-earthquakes occur in spatially (<100 m radius) and temporally (mostly 1-5 days activity) restricted event-clusters (up to 4000 events), which exhibit an increase, followed by a decrease, in event magnitude with time. This may indicate event triggering once activity is initiated. Although ocean tides modulate the surface ice flow velocity, we observe little periodic variation in overall event frequency over time and conclude that water content, bed topography and stiffness are the major factors controlling microseismicity. Based on variable rupture mechanisms and spatiotemporal characteristics, we suggest the event-clusters relate to three end-member types of bed deformation: (1) continuous creation and seismogenic destruction of small-scale bed-roughness, (2) ploughed clasts and (3) flow-oblique deformation during landform-formation or along bedrock outcrops. This indicates that multiple processes, simultaneously active during glacial sliding, can accommodate stick-slip behaviour and that the bed continuously reorganizes.
Basal microseisms in Antarctica, or icequakes, are valuable data sources that we can use to determine features and processes at the bed to improve our understanding of ice flow dynamics in the region. In the 2018/19 austral summer, we collaborated with the British Antarctic Survey (BAS) to deploy several seismic arrays of short period instruments over ~2 months in Rutford Ice Stream in West Antarctica to monitor natural source seismicity. During this recording period, we detected several swarms of repeating icequakes (~40 s interevent time) at our grounding line array that originate from a common basal source, which we hypothesize to be stick-slip motion over sticky spots/asperities. Smaller scale repeating icequakes, both in terms of amplitude and interevent times, also exist among the original larger repeating icequakes and are also hypothesized to originate from multiple smaller sticky spots that had less consistent loading and slipping. We built an auto-picker to detect these repeating icequakes over our recording period and located them using the automatic earthquake location Python package QuakeMigrate, and here we present our results as well as what they tell us about the basal topography. Further investigation of the interevent offsets between repeating signals of varying amplitudes and their frequency characteristics via FFT will provide more insights into the basal features, which we will corroborate with GPR basal topography data. Relations of the repeating icequakes to aseismic slip and tides will also be investigated. The findings at our grounding line array, where the repeating icequakes were first detected, can later support similar searches at the inland arrays. Antarctic ice streams remain a major source of uncertainty in projections of sea level rise, and our work seeks to constrain this uncertainty by improving our understanding of ice stream dynamics through basal conditions.
The Antarctic Ice Sheet remains one of the greatest sources of uncertainty for improving predictions of sea level rise, and constraining this uncertainty has long been a difficult challenge within glaciology and climate science. Cryoseismology, paired with the meteoric rise of data science applications within the geosciences, has emerged as a promising field well suited to answering these challenges as the improvement of sampling technology and access have resulted in a proliferation of Antarctic seismic data. Ice flow dynamics in Antarctica are significantly influenced by features and processes at the bed, and basal microseismicity from tremors as ice moves across the bed can yield valuable information for resolving the glacier subsurface. We deployed high-frequency (up to 1000 Hz) geophone arrays at Rutford Ice Stream over the 2018-2019 austral summer to monitor the natural source seismicity from the base of the ice and generate an event catalog. To efficiently process the enormous volumes of cryoseismic data to locate events, we used the Python package QuakeMigrate which utilizes a parallelized waveform stacking algorithm to detect coherent seismic phase arrivals across our network. Over three months of data, we located over 1,700,000 seismic events (majority which were microseismic) within a 4 km x 4 km square grid around our 13-station, ~3.25 km2 area array. The detection and location of icequakes at this resolution provides a unique opportunity to investigate the temporal, location, and size relations between events, and we present the findings from our data mined event catalog and document the QuakeMigrate parameter tuning to optimize event location. The significant amounts of data collected of the region over the past decades mean that the literature and documentation of conditions at Rutford is more complete relative to most of Antarctica, and our work aims to contribute towards a comprehensive survey of an Antarctic region.