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NASA NTRS2012

Late-glacial and Holocene Vegetation and Climate Variability, Including Major Droughts, in the Sky Lakes Region of Southeastern New York State

Sediment cores from Lakes Minnewaska and Mohonk in the Shawangunk Mountains of southeastern New York were analyzed for pollen, plantmacrofossils, macroscopic charcoal, organic carbon content, carbon isotopic composition, carbon/nitrogen ratio, and lithologic changes to determine the vegetation and landscape history of the greater Catskill Mountain region since deglaciation. Pollen stratigraphy generally matches the New England pollen zones identified by Deevey (1939) and Davis (1969), with boreal genera (Picea, Abies) present during the late Pleistocene yielding to a mixed Pinus, Quercus and Tsuga forest in the early Holocene. Lake Minnewaska sediments record the Younger Dryas and possibly the 8.2 cal kyr BP climatic events in pollen and sediment chemistry along with an ~1400 cal yr interval of wet conditions (increasing Tsuga and declining Quercus) centered about 6400 cal yr BP. BothMinnewaska andMohonk reveal a protracted drought interval in themiddle Holocene, ~5700-4100 cal yr BP, during which Pinus rigida colonized the watershed, lake levels fell, and frequent fires led to enhanced hillslope erosion. Together, the records show at least three wet-dry cycles throughout the Holocene and both similarities and differences to climate records in New England and central New York. Drought intervals raise concerns for water resources in the New York City metropolitan area and may reflect a combination of enhanced La Niña, negative phase NAO, and positive phase PNA climatic patterns and/or northward shifts of storm tracks.

Drought↗

NASA NTRSDate not supplied

Towards Real-time Global Assessment of Post-fire Debris Flow Hazard

As the risk of wildfires increases worldwide, burned steeplands are vulnerable to the secondary hazard of widespread sediment mobilization through debris flows. Following an initial burn, sediment and soil previously restrained by vegetation are no longer consolidated, allowing for easy mobilization into channels and along steep hillslopes through runoff. Sufficiently powerful rainfall incorporates entrained material into turbulent flows and serves as the primary trigger for debris flow initiation. There is thus an ongoing need to establish the relationship between rainfall and debris flow initiation based on a variety of spatiotemporal preconditions. Previous work establishes regional and local thresholds to constrain the effect of rainfall in recently burned areas, but no empirical or numerical solution has worldwide application. Building from regionally-based efforts in the U.S., this work considers how remote sensing data can be applied to better approximate the post-fire debris flow hazards worldwide using freely available global datasets and software. Our work assesses the utility of remote sensing resources for analyzing burn characteristics, topography, rainfall intensity/duration, and, thus, debris flow initiation. Early results show that global observations are sufficient to delineate background rainfall rates from storms likely to cause debris flows across a variety of burn severity and topographic conditions. However, the dearth of publicly-available post-fire debris flow inventories globally limit the ability to test how the model framework performs within different climatologic and morphologic areas. This work will present preliminary analysis over the Western United States and demonstrate the feasibility of a global, near-real time model to provide situational awareness of potential hazards within recently burned areas worldwide. Future work will also consider how global or regional precipitation forecasts may increase the lead time for improved early warning of these hazards.

Elijah Orland↗

NASA NTRS2021

Satellites Support Disaster Response to Storm-Driven Landslides

High winds and flooding storm surges driven by tropical cyclones cause some of the deadliest and most damaging weather-related conditions around the world. The rainfall that cyclones bring compounds these conditions and, in hilly or mountainous areas, can trigger landslides that cause even more widespread and devastating impacts. When extreme precipitation occurs over short time frames, hillslopes may become saturated and critically unstable. The most intense storms can trigger thousands of landslides in mountainous areas, as was dramatically illustrated in Puerto Rico in September 2017, when Hurricane Maria’s rains left the landscape scarred by roughly 40,000 landslides. Before and during a major cyclone, disaster responders need information about where landslides are likely to occur. In the aftermath, locating landslides quickly helps authorities direct resources to where they are most needed to save people and critical infrastructure. However, this information is often unavailable during an event response or is presented only for small regions, constraining the effectiveness of response efforts.

Robert Emberson↗

NASA NTRSDate not supplied

The Mineralogy and Cation Exchange of Sediments in Don Juan Pond, Antarctica Dry Valley: Implications for Mars

Located in the McMurdo Dry Valleys of Antarctica (MDV) is among of the saltiest bodies of water of Earth, Don Juan Pond (DJP)[1]. DJP pond waters are unique in that they contain nearly 40% salt by weight including 95% CaCl2 [1-5] and they never evaporate or freeze entirely due to the high hygroscopicity and low eutectic temperature of the CaCl2 brine (-52 ̊C) [6]. The source of DJP water is suggested to be due to groundwater upwelling through a weathered dolerite aquifer and/or near-surface runoff, including salt deliquescence in the pond’s watershed [7,8], however the source of water is still a topic of study. During the 2017-2018 field season, we collected soil samples and altered sediments on hillslopes and drainage basins near the pond (Fig. 1). Two drill bores were also acquired in Don Juan Pond sediments in a episodically flooded area of the pond basin. This study's objectives were to characterize the mineralogy of these soils and sediments to determine if there are mineralogical indicators and/or controls for the delivery of salts to DJP and understand the role of salts on Mars on these analog studies.

V M Tu↗

NASA NTRS2024

Applications of ArcticDEM for measuring volcanic dynamics, landslides, retrogressive thaw slumps, snowdrifts, and vegetation heights

Topographical changes are of fundamental interest to a wide range of Arctic science disciplines faced with the need to anticipate, monitor, and respond to the effects of climate change, including geohazard management, glaciology, hydrology, permafrost, and ecology. This study demonstrates several geomorphological, cryospheric, and biophysical applications of ArcticDEM – a large collection of publicly available, time-dependent digital elevation models (DEMs) of the Arctic. Our study illustrates ArcticDEM's applicability across different disciplines and five orders of magnitude of elevation derivatives, including measuring volcanic lava flows, ice cauldrons, post-failure landslides, retrogressive thaw slumps, snowdrifts, and tundra vegetation heights. We quantified surface elevation changes in different geological settings and conditions using the time series of ArcticDEM. Following the 2014–2015 Bárðarbunga eruption in Iceland, ArcticDEM analysis mapped the lava flow field, and revealed the post-eruptive ice flows and ice cauldron dynamics. The total dense-rock equivalent (DRE) volume of lava flows is estimated to be (1431 ± 2) million m 3 . Then, we present the aftermath of a landslide in Kinnikinnick, Alaska, yielding a total landslide volume of (400 ± 8) × 103 m 3 and a total area of 0.025 km 2 . ArcticDEM is further proven useful for studying retrogressive thaw slumps (RTS). The ArcticDEM-mapped RTS profile is validated by ICESat-2 and drone photogrammetry resulting in a standard deviation of 0.5 m. Volume estimates for lake-side and hillslope RTSs range between 40,000 ± 9000 m 3 and 1,160,000 ± 85,000 m 3 , highlighting applicability across a range of RTS magnitudes. A case study for mapping tundra snow demonstrates ArcticDEM's potential for identifying high-accumulation, late-lying snow areas. The approach proves effective in quantifying relative snow accumulation rather than absolute values (standard deviation of 0.25 m, bias of −0.41 m, and a correlation coefficient of 0.69 with snow depth estimated by unmanned aerial systems photogrammetry). Furthermore, ArcticDEM data show its feasibility for estimating tundra vegetation heights with a standard deviation of 0.3 m (no bias) and a correlation up to 0.8 compared to the light detection and ranging (LiDAR). The demonstrated capabilities of ArcticDEM will pave the way for the broad and pan-Arctic use of this new data source for many disciplines, especially when combined with other imagery products. The wide range of signals embedded in ArcticDEM underscores the potential challenges in deciphering signals in regions affected by various geological processes and environmental influences.

Chunli Dai↗