Search USGS⌕ Search

SEARCH · Search USGS

Results for “Environmental Research”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 307 records · Page 17Linked to original sources
USGS2022

Predicting flood damage probability across the conterminous United States

Floods are the leading cause of natural disaster damages in the United States, with billions of dollars incurred every year in the form of government payouts, property damages, and agricultural losses. The Federal Emergency Management Agency oversees the delineation of floodplains to mitigate damages, but disparities exist between locations designated as high risk and where flood damages occur due to land use and climate changes and incomplete floodplain mapping. We harnessed publicly available geospatial datasets and random forest algorithms to analyze the spatial distribution and underlying drivers of flood damage probability caused by excessive rainfall and overflowing water bodies across the conterminous United States. From this, we produced the first spatially complete map of flood damage probability for the nation, along with spatially explicit standard errors for four selected cities. We trained models using the locations of historical reported flood damage events ( n = 71,434) and a suite of geospatial predictors (e.g., flood severity, climate, socio-economic exposure, topographic variables, soil properties, and hydrologic characteristics). We developed independent models for each hydrologic unit code level 2 watershed and generated a flood damage probability for each 100-m pixel. Our model classified damage or no damage with an average area under the curve accuracy of 0.75; however, model performance varied by environmental conditions, with certain land cover classes (e.g., forest) resulting in higher error rates than others (e.g., wetlands). Our results identified flood damage probability hotspots across multiple spatial and regional scales, with high probabilities common in both inland and coastal regions. The highest flood damage probabilities tended to be in areas of low elevation, in close proximity to streams, with extreme precipitation, and with high urban road density. Given rapid environmental changes, our study demonstrates an efficient approach for updating flood damage probability estimates across the nation.

Environmental Research Letters↗
USGS2022

Sensitivity of headwater streamflow to thawing permafrost and vegetation change in a warming Arctic

Climate change has the potential to impact headwater streams in the Arctic by thawing permafrost and subsequently altering hydrologic regimes and vegetation distribution, physiognomy and productivity. Permafrost thaw and increased subsurface flow have been inferred from the chemistry of large rivers, but there is limited empirical evidence of the impacts to headwater streams. Here we demonstrate how changing vegetation cover and soil thaw may alter headwater catchment hydrology using water budgets, stream discharge trends, and chemistry across a gradient of ground temperature in northwestern Alaska. Colder, tundra-dominated catchments shed precipitation through stream discharge, whereas in warmer catchments with greater forest extent, evapotranspiration and infiltration are substantial fluxes. Forest soils thaw earlier, remain thawed longer, and display seasonal water content declines, consistent with greater evapotranspiration and infiltration. Streambed infiltration and water chemistry indicate that even minor warming can lead to increased infiltration and subsurface flow. Additional warming, permafrost loss, and vegetation shifts in the Arctic will deliver water back to the atmosphere and to subsurface aquifers in many regions, with the potential to substantially reduce discharge in headwater streams, if not compensated by increasing precipitation. Decreasing discharge in headwater streamflow will have important implications for aquatic and riparian ecosystems.

Alaska↗
USGS2022

Sea-level rise and warming mediate coastal groundwater discharge in the Arctic

Groundwater discharge is an important mechanism through which fresh water and associated solutes are delivered to the ocean. Permafrost environments have traditionally been considered hydrogeologically inactive, yet with accelerated climate change and permafrost thaw, groundwater flow paths are activating and opening subsurface connections to the coastal zone. While warming has the potential to increase land-sea connectivity, sea-level change has the potential to alter land-sea hydraulic gradients and enhance coastal permafrost thaw, resulting in a complex interplay that will govern future groundwater discharge dynamics along Arctic coastlines. Here, we use a recently developed permafrost hydrological model that simulates variable-density groundwater flow and salinity-dependent freeze-thaw to investigate the impacts of sea-level change and land and ocean warming on the magnitude, spatial distribution, and salinity of coastal groundwater discharge. Results project both an increase and decrease in discharge with climate change depending on the rate of warming and sea-level change. Under high warming and low sea-level rise scenarios, results show up to a 58% increase in coastal groundwater discharge by 2100 due to the formation of a supra-permafrost aquifer that enhances freshwater delivery to the coastal zone. With higher rates of sea-level rise, the increase in discharge due to warming is reduced to 21% as sea-level rise decreased land-sea hydraulic gradients. Under lower warming scenarios for which supra-permafrost groundwater flow was not established, discharge decreased by up to 26% between 1980 and 2100 for high sea-level rise scenarios and increased only 8% under low sea-level rise scenarios. Thus, regions with higher warming rates and lower rates of sea-level change (e.g. northern Nunavut, Canada) will experience a greater increase in discharge than regions with lower warming rates and higher rates of sea-level change. The magnitude, location and salinity of discharge have important implications for ecosystem function, water quality, and carbon dynamics in coastal zones.

Environmental Research Letters↗
USGS2022

Black carbon dominated dust in recent radiative forcing on Rocky Mountain snowpacks

The vast majority of surface water resources in the semi-arid western United States start as winter snowpack. Solar radiation is a primary driver of snowmelt, making snowpack water resources especially sensitive to even small increases in concentrations of light absorbing particles such as mineral dust and combustion-related black carbon (BC). Here we show, using fresh snow measurements and snowpack modeling at 51 widely distributed sites in the Rocky Mountain region, that BC dominated impurity-driven radiative forcing in 2018. BC contributed three times more radiative forcing on average than dust, and up to 17 times more at individual locations. Evaluation of 2015 to 2018 archived samples from most of the same sites yielded similar results. These findings, together with long-term observations of atmospheric concentrations and atmospheric model studies, indicate that BC rather than dust has dominated radiative forcing by light absorbing impurities on snow for decades, indicating that mitigation strategies to reduce radiative forcing on headwater snow-water resources would need to focus on reducing winter and spring BC emissions.

Colorado, Idaho, Montana, New Mexico, Utah, Wyomin↗
USGS2022

Streambank and floodplain geomorphic change and contribution to watershed material budgets

Stream geomorphic change is highly spatially variable but critical to landform evolution, human infrastructure, habitat, and watershed pollutant transport. However, measurements and process models of streambank erosion and floodplain deposition and resulting sediment fluxes are currently insufficient to predict these rates in all perennial streams over large regions. Here we measured long-term lateral streambank and vertical floodplain change and sediment fluxes using dendrogeomorphology in streams around the U.S. Mid-Atlantic, and then statistically modeled and extrapolated these rates to all 74 133 perennial, nontidal streams in the region using watershed- and reach-scale predictors. Measured long-term rates of streambank erosion and floodplain deposition were highly spatially variable across the landscape from the mountains to the coast. Random Forest regression identified that geomorphic change and resulting fluxes of sediment and nutrients, for both streambank and floodplain, were most influenced by urban and agricultural land use and the drainage area of the upstream watershed. Modeled rates for headwater streams were net erosional whereas downstream reaches were on average net depositional, leading to regional cumulative sediment loads from streambank erosion (−5.1 Tg yr −1 ) being nearly balanced by floodplain deposition (+5.3 Tg yr −1 ). Geomorphic changes in stream valleys had substantial influence on watershed sediment, phosphorus, carbon, and nitrogen budgets in comparison to existing predictions of upland erosion and delivery to streams and of downstream sediment loading. The unprecedented scale of these novel findings provides important insights into the balance of erosion and deposition in streams within disturbed landscapes and the importance of geomorphic change to stream water quality and carbon sequestration, and provides vital understanding for targeting management actions to restore watersheds.

Chesapeake Bay watershed↗
USGS2022

Grassy–herbaceous land moderates regional climate effects on honey bee colonies in the Northcentral US

The lack of seasonally sustained floral resources (i.e. pollen and nectar) is considered a primary global threat to pollinator health. However, the ability to predict the abundance of flowering resources for pollinators based upon climate, weather, and land cover is difficult due to insufficient monitoring over adequate spatial and temporal scales. Here we use spatiotemporally distributed honey bee hive scales that continuously measure hive weights as a standardized method to assess nectar intake. We analyze late summer colony weight gain as the response variable in a random forest regression model to determine the importance of climate, weather, and land cover on honey bee colony productivity. Our random forest model predicted resource acquisition by honey bee colonies with 71% accuracy, highlighting the detrimental effects of warm, wet regions in the Northcentral United States on nectar intake, as well as the detrimental effect of years with high growing degree day accumulation. Our model also predicted that grassy–herbaceous natural land had a positive effect on the summer nectar flow and that large areas of natural grassy–herbaceous land around apiaries can moderate the detrimental effects of warm, wet climates. These patterns characterize multi-scale ecological processes that constrain the quantity and quality of pollinator nutritional resources. That is, broad climate conditions constrain regional floral communities, while land use and weather act to further modify the quantity and quality of pollinator nutritional resources. Observing such broad-scale trends demonstrates the potential for utilizing hive scales to monitor the effects of climate change on landscape-level floral resources for pollinators. The interaction of climate and land use also present an opportunity to manage for climate-resilient landscapes that support pollinators through abundant floral resources under climate change.

Michigan, Minnesota, North Dakota, Ohio, Pennsylva↗
USGS2022

Wind turbine wakes can impact down-wind vegetation greenness

Global wind energy has expanded 5-fold since 2010 and is predicted to expand another 8–10-fold over the next 30 years. Wakes generated by wind turbines can alter downwind microclimates and potentially downwind vegetation. However, the design of past studies has made it difficult to isolate the impact of wake effects on vegetation from land cover change. We used hourly wind data to model wake and non-wake zones around 17 wind facilities across the U.S. and compared remotely-sensed vegetation greenness in wake and non-wake zones before and after construction. We located sampling sites only in the dominant vegetation type and in areas that were not disturbed before or after construction. We found evidence for wake effects on vegetation greenness at 10 of 17 facilities for portions of, or the entire growing season. Evidence included statistical significance in Before After Control Impact statistical models, differences >3% between expected and observed values of vegetation greenness, and consistent spatial patterns of anomalies in vegetation greenness relative to turbine locations and wind direction. Wakes induced both increases and decreases in vegetation greenness, which may be difficult to predict prior to construction. The magnitude of wake effects depended primarily on precipitation and to a lesser degree aridity. Wake effects did not show trends over time following construction, suggesting the changes impact vegetation greenness within a growing season, but do not accrue over years. Even small changes in vegetation greenness, similar to those found in this study, have been seen to affect higher trophic levels. Given the rapid global growth of wind energy, and the importance of vegetation condition for agriculture, grazing, wildlife, and carbon storage, understanding how wakes from wind turbines impact vegetation is essential to exploit or ameliorate these effects.

Environmental Research Letters↗
USGS2022

Simulating burn severity maps at 30 meters in two forested regions in California

Climate change is altering wildfire behavior and vegetation regimes in California’s forested ecosystems. Present day fires are seeing an increase in high burn severity area and high severity patch size. The ability to predict future burn severity patterns would support better policy and land management decisions. Here we demonstrate a methodology to first, statistically estimate individual burn severity classes at 30 meters and second, cluster and smooth high severity patches onto a landscape. Our goal here was not to exactly replicate observed burn severity maps, but rather to utilize observed maps as one realization of a random process dependent on climate, topography, fire weather, and fuels, to inform creation of additional realizations through our simulation technique. We developed two sets of empirical models with two different vegetation datasets to test if coarse vegetation could accurately model for burn severity. While visual acuity can be used to assess the performance of our simulation process, we also employ the Ripley’s K function to compare spatial point processes at different scales to test if the simulation is capturing an appropriate amount of clustering. We utilize FRAGSTATS to obtain high severity patch metrics to test the contiguity of our high severity simulation. Ripley’s K function helped identify the number of clustering iterations and FRAGSTATS showed how different focal window sizes affected our ability to cluster high severity patches. High severity patch simulations was comparable between the coarse and fine resolution vegetation datasets. Improving our ability to simulate burn severity will help advance our understanding of the potential influence of land and fuels management on ecosystem-level response variables that are important for decision-makers. Simulated burn severity maps can support managing habitat and estimating risks of habitat loss, protecting infrastructure and homes, improving future wildfire emissions projections, and better mapping and planning for fuels treatment scenarios.

California↗
USGS2022

Can we avert an Amazon tipping point? The economic and environmental costs

The Amazon biome is being pushed by unsustainable economic drivers towards an ecological tipping point where restoration to its previous state may no longer be possible. This degradation is the result of self-reinforcing interactions between deforestation, climate change and fire. We assess the economic, natural capital and ecosystem services impacts and trade-offs of scenarios representing movement towards an Amazon tipping point and strategies to avert one using the Integrated Economic-Environmental Modeling (IEEM) Platform linked with spatial land use-land cover change and ecosystem services modeling (IEEM + ESM). Our approach provides the first approximation of the economic, natural capital and ecosystem services impacts of a tipping point, and evidence to build the economic case for strategies to avert it. For the five Amazon focal countries, namely, Brazil, Peru, Colombia, Bolivia and Ecuador, we find that a tipping point would create economic losses of US$256.6 billion in cumulative gross domestic product by 2050. Policies that would contribute to averting a tipping point, including strongly reducing deforestation, investing in intensifying agriculture in cleared lands, climate-adapted agriculture and improving fire management, would generate approximately US$339.3 billion in additional wealth and a return on investment of US$29.5 billion. Quantifying the costs, benefits and trade-offs of policies to avert a tipping point in a transparent and replicable manner can support the design of regional development strategies for the Amazon biome, build the business case for action and catalyze global cooperation and financing to enable policy implementation.

Amazon↗
USGS2023

The future of ecosystem assessments is automation, collaboration, and artificial intelligence

Robust and routine ecosystem assessments will be fundamental to track progress towards achieving this decade’s global environmental and sustainability goals. Here we examine four needs that address common failure points of ecosystem assessments. These are (1) developing rapid, reproducible, and repeatable ecological data workflows, (2) harmonizing in situ and remotely sensed data, (3) integrating socioeconomic and biophysical data, and (4) increasing access to the digital resources and cyberinfrastructure needed to perform assessments. These four needs have profound potential to help us achieve our environmental objectives through cross-sector collaborations that leverage advancements in digital resources, remote data streams, and data science.

Environmental Research Letters↗
USGS2023

Trends in tree cover change over three decades related to interannual climate variability and wildfire in California

The U.S. State of California has experienced frequent drought events, hotter temperatures and other disruptions to the climate system whose effects on ecosystems have been widely reported in recent decades. Studies primarily confined to specific vegetation communities or species, individual drought incidents, or analysis over a relatively short intervals, has limited our understanding of the broad-scale effects on tree cover and the spatiotemporal variability of effects across broader regions. We focused analysis on multi-annual land cover and land surface change to assess patterns and trends in tree cover loss in tree-dominated Californian ecoregions from 1986 to 2019. The top three years of total tree cover loss for the state were 2018 (1901 km 2 ), 2015 (1556 km 2 ), and 2008 (1549 km 2 ). Overall, annual tree cover loss had upward trends. Tree cover loss rapidly surged later in the study period and was apparently driven by climate stress and wildfires. Underlying geographic variability was apparent in both non-fire and fire-related tree cover loss that sharply increased during hotter multi-year droughts. The increasingly hotter and drier climate conditions were associated with significant increases in fire-induced mortality. Our findings indicate that a possible effect of future hotter and drier climate would lead to further tree cover loss, thereby endangering California's ecosystem goods and services. Geographic variability in tree cover trends indicates that ecoregion-specific mitigation and adaptation strategies would be useful to conserve the region's forest resources. Such strategies may benefit from consideration of historical disturbances, ecoregion's sensitivity to disturbance types, as well as potential ecoregion-specific climate-vegetation-fire feedbacks.

California↗
USGS2023

Increasing Alaskan river discharge during the cold season is driven by recent warming

Arctic hydrology is experiencing rapid changes including earlier snow melt, permafrost degradation, increasing active layer depth, and reduced river ice, all of which are expected to lead to changes in stream flow regimes. Recently, long-term (>60 years) climate reanalysis and river discharge observation data have become available. We utilized these data to assess long-term changes in discharge and their hydroclimatic drivers. River discharge during the cold season (October–April) increased by 10% per decade. The most widespread discharge increase occurred in April (15% per decade), the month of ice break-up for the majority of basins. In October, when river ice formation generally begins, average monthly discharge increased by 7% per decade. Long-term air temperature increases in October and April increased the number of days above freezing (+1.1 d per decade) resulting in increased snow ablation (20% per decade) and decreased snow water equivalent (−12% per decade). Compared to the historical period (1960–1989), mean April and October air temperature in the recent period (1990–2019) have greater correlation with monthly discharge from 0.33 to 0.68 and 0.0–0.48, respectively. This indicates that the recent increases in air temperature are directly related to these discharge changes. Ubiquitous increases in cold and shoulder-season discharge demonstrate the scale at which hydrologic and biogeochemical fluxes are being altered in the Arctic.

Alaska↗
USGS2023

Livestock removal increases plant cover across a heterogeneous dryland landscape on the Colorado Plateau

Livestock removal is increasingly used as a management option to mitigate the negative impacts of grazing-related disturbances on rangelands. Removal generally increases plant cover, but it is unclear when, where, and by how much plant and soil cover changes can be expected. On the Colorado Plateau, complex geology, topography, soils, and climate all interact to mediate the relationship between land cover, climate, and disturbance. In this study we used new developments in land cover mapping and analysis to assess landscape plant and bare soil cover up to 30 years after livestock removal from two grazing allotments in Capitol Reef National Park, Utah, USA. Results indicate that livestock removal increases plant cover 0.17-0.32% per year and reduces bare soil cover 0.34-0.41% per year, although these rates may be suppressed by warming temperatures. Soils, assessed through Soil Geomorphic Units, played a strong but complex role in mediating land cover changes through time. These results suggest that livestock removal is an effective strategy for increasing plant cover and reducing bare soil on the Colorado Plateau, but including soil information in decision making will enhance efficiency by improving manager's ability to prioritize management actions effectively across space and through time.

Environmental Research Letters↗
USGS2023

Understanding the spatiotemporal distribution of snow refugia in the rain-snow transition zone of north-central Idaho

Knowledge of snow cover distribution and disappearance dates over a wide range of scales is imperative for understanding hydrological dynamics and for habitat management of wildlife species that rely on snow cover. Identification of snow refugia, or places with relatively late snow disappearance dates (SDDs) compared to surrounding areas, is especially important as climate change alters snow cover timing and duration. The purpose of this study was to increase understanding of snow refugia in complex terrain spanning the rain-snow transition zone at fine spatial and temporal scales. To accomplish this objective, we used remote cameras to provide relatively high temporal and spatial resolution measurements on snowpack conditions. We built linear models to relate SDDs at the monitoring sites to topoclimatic and canopy cover metrics. One model to quantify SDDs included elevation, aspect, and an interaction between canopy cover and cold-air pooling potential. High-elevation, north-facing sites in cold-air pools (CAPs) had the latest SDDs, but isolated lower-elevation points also exhibited relatively late potential SDDs. Importantly, canopy cover had a much stronger effect on SDDs in CAPs than in non-CAPs, indicating that best practices in forest management for snow refugia could vary across microtopography. A second model that included in situ hydroclimate observations (December – February (DJF) temperature and March 1 snow depth) indicated that March 1 snow depth had little impact on SDD at the coldest winter temperatures, and that DJF temperatures had a stronger effect on SDD at lower snow depths, implying that the relative importance of snowfall and temperature could vary across hydroclimatic contexts in their impact on snow refugia. This new understanding of factors influencing snow refugia can guide forest management actions to increase snow retention and inform management of snow-dependent wildlife species in complex terrain.

Environmental Research Letters↗
USGS2023

Wind-modulated groundwater discharge along a microtidal Arctic coastline

Groundwater discharge transports dissolved constituents to the ocean, affecting coastal carbon budgets and water quality. However, the magnitude and mechanisms of groundwater exchange along rapidly transitioning Arctic coastlines are largely unknown due to limited observations. Here, using first-of-its-kind coastal Arctic groundwater timeseries data, we evaluate the magnitude and drivers of groundwater discharge to Alaska's Beaufort Sea coast. Darcy flux calculations reveal temporally variable groundwater fluxes, ranging from −6.5 cm d −1 (recharge) to 14.1 cm d −1 (discharge), with fluctuations in groundwater discharge or aquifer recharge over diurnal and multiday timescales during the open-water season. The average flux during the monitoring period of 4.9 cm d −1 is in line with previous estimates, but the maximum discharge exceeds previous estimates by over an order-of-magnitude. While the diurnal fluctuations are small due to the microtidal conditions, multiday variability is large and drives sustained periods of aquifer recharge and groundwater discharge. Results show that wind-driven lagoon water level changes are the dominant mechanism of fluctuations in land–sea hydraulic head gradients and, in turn, groundwater discharge. Given the microtidal conditions, low topographic relief, and limited rainfall along the Beaufort Sea coast, we identify wind as an important forcing mechanism of coastal groundwater discharge and aquifer recharge with implications for nearshore biogeochemistry. This study provides insights into groundwater flux dynamics along this coastline over time and highlights an oft overlooked discharge and circulation mechanism with implications towards refining solute export estimates to coastal Arctic waters.

Alaska↗
USGS2023

Variability in terrestrial characteristics and erosion rates on the Alaskan Beaufort Sea coast

Arctic coastal environments are eroding and rapidly changing. A lack of pan-Arctic observations limits our ability to understand controls on coastal erosion rates across the entire Arctic region. Here, we capitalize on an abundance of geospatial and remotely sensed data, in addition to model output, from the North Slope of Alaska to identify relationships between historical erosion rates and landscape characteristics to guide future modeling and observational efforts across the Arctic. Using existing datasets from the Alaska Beaufort Sea coast and a hierarchical clustering algorithm, we developed a set of 16 coastal typologies that captures the defining characteristics of environments susceptible to coastal erosion. Relationships between landscape characteristics and historical erosion rates show that no single variable alone is a good predictor of erosion rates. Variability in erosion rate decreases with increasing coastal elevation, but erosion rate magnitudes are highest for intermediate elevations. Areas along the Alaskan Beaufort Sea coast (ABSC) protected by barrier islands showed a three times lower erosion rate on average, suggesting that barrier islands are critical to maintaining mainland shore position. Finally, typologies with the highest erosion rates are not broadly representative of the ABSC and are generally associated with low elevation, north- to northeast-facing shorelines, a peaty pebbly silty lithology, and glaciomarine deposits with high ice content. All else being equal, warmer permafrost is also associated with higher erosion rates, suggesting that warming permafrost temperatures may contribute to higher future erosion rates on permafrost coasts. The suite of typologies can be used to guide future modeling and observational efforts by quantifying the distribution of coastlines with specific landscape characteristics and erosion rates.

Alaska↗
USGS2023

Arctic-boreal lakes of interior Alaska dominated by contemporary carbon

Northern high-latitude lakes are critical sites for carbon processing and serve as potential conduits for the emission of permafrost-derived carbon and greenhouse gases. However, the fate and emission pathways of permafrost carbon in these systems remain uncertain. Here, we used the natural abundance of radiocarbon to identify and trace the predominant sources of methane, carbon dioxide, dissolved inorganic and organic carbon in nine lakes within the Yukon Flats National Wildlife Refuge in interior Alaska, a discontinuous permafrost region with high landscape heterogeneity and susceptibility to climate, permafrost, and hydrological changes. We find that although Yukon Flats lakes primarily process young carbon (modern to 1290 ± 60 years before present), permafrost-derived carbon is present in some of the sampled lakes and contributes, at most, 30 ± 10% of the dissolved carbon in lake surface waters. Apportionment of young carbon and legacy carbon (carbon with radiocarbon age ⩾5000 years before present) is decoupled among the dissolved inorganic and organic carbon species, with methane showing a stronger legacy signature. Our observations suggest that permafrost-thaw-related transport of carbon through Yukon Flats lacustrine ecosystems and into the atmosphere is small, and likely regulated by surficial sediments, permafrost distribution, wildfire occurrence, or masked by contemporary carbon processes. The heterogeneity of lakes across our study area and northern landscapes more broadly cautions against using any one region (e.g. Yedoma permafrost lakes) to upscale their contribution across the pan-Arctic.

Alaska↗
USGS2023

Maps of active layer thickness in northern Alaska by upscaling P-band polarimetric synthetic aperture radar retrievals

Extensive, detailed information on the spatial distribution of active layer thickness (ALT) in northern Alaska and how it evolves over time could greatly aid efforts to assess the effects of climate change on the region and also help to quantify greenhouse gas emissions generated due to permafrost thaw. For this reason, we have been developing high-resolution maps of ALT throughout northern Alaska. The maps are produced by upscaling from high-resolution swaths of estimated ALT retrieved from airborne P-band synthetic aperture radar (SAR) images collected for three different years. The upscaling was accomplished by using hundreds of thousands of randomly selected samples from the SAR-derived swaths of ALT to train a machine learning regression algorithm supported by numerous spatial data layers. In order to validate the maps, thousands of randomly selected samples of SAR-derived ALT were excluded from the training in order to serve as validation pixels; error performance calculations relative to these samples yielded root-mean-square errors (RMSEs) of 7.5–9.1 cm, with bias errors of magnitude under 0.1 cm. The maps were also compared to ALT measurements collected at a number of in situ test sites; error performance relative to the site measurements yielded RMSEs of approximately 11–12 cm and bias of 2.7–6.5 cm. These data are being used to investigate regional patterns and underlying physical controls affecting permafrost degradation in the tundra biome.

Environmental Research Letters↗