The effect of sampling effort on estimates of methane ebullition from peat

We investigated the effect of sample size and sampling duration on methane bubble flux (ebullition) estimates from peat using a computer model. A field scale (10 m), seasonal (> 100 days) simulation of ebullition from a two-dimensional structurally-varying peat profile was modelled at fine spatial resolution (1 mm × 1 mm). The spatial and temporal scale of this simulation was possible because of the computational efficiency of the reduced complexity approach that was implemented, and patterns of simulated ebullition were consistent with those found in the field and laboratory. The simulated ebullition from the peat profile suggested that decreases in peat porosity – which cause increases in gas storage – produce ebullition that becomes increasingly patchy in space and erratic in time. By applying different amounts of spatial and temporal sampling effort it was possible to determine the uncertainty in ebullition estimates from the peatland. The results suggest that traditional methods to measure ebullition can equally overestimate and underestimate flux by 20% and large ebullition events can lead to large overestimations of flux when sampling effort is low. Our findings support those of field studies, and we recommend that ebullition should be measured frequently (hourly to daily) and at many locations (n > 14)

Ebullition of methane from peatlands: Does peat act as a signal shredder?

Bubbling (ebullition) of greenhouse gases, particularly methane, from peatlands has been attributed to environmental forcings, such as changes in atmospheric pressure. However, observations from peat soils suggest that ebullition and environmental forcing may not always be correlated and that interactions between bubbles and the peat structure may be the cause of such decoupling. To investigate this possibility, we used a simple computer model (Model of Ebullition and Gas storAge) to simulate methane ebullition from a model peat. We found that lower porosity peat can store methane bubbles for lengthy periods of time, effectively buffering or moderating ebullition so that it no longer reflects bubble production signals. Our results suggest that peat structure may act as a “signal shredder” and needs to be taken into account when measuring and modeling ebullition

Integrated time-lapse geoelectrical imaging of wetland hydrological processes

Wetlands provide crucial habitats, are critical in the global carbon cycle, and act as key biogeochemical and hydrological buffers. The effectiveness of these services is mainly controlled by hydrological processes, which can be highly variable both spatially and temporally due to structural complexity and seasonality. Spatial analysis of 2D geoelectrical monitoring data integrated into the interpretation of conventional hydrological data has been implemented to provide a detailed understanding of hydrological processes in a riparian wetland. This study shows that a combination of processes can define the resistivity signature of the shallow subsurface, highlighting the seasonality of these processes and its corresponding effect on biogeochemical processesthe wetland hydrology. Groundwater exchange between peat and the underlying river terrace deposits, spatially and temporally defined by geoelectrical imaging and verified by point sensor data, highlighted the groundwater dependent nature of the wetland. A 30 % increase in peat resistivity was shown to be caused by a nearly entire exchange of the saturating groundwater. For the first time, we showed that automated interpretation of geoelectrical data can be used to quantify shrink-swell of expandable soils, affecting hydrological parameters, such as, porosity, water storage capacity, and permeability. This study shows that an integrated interpretation of hydrological and geophysical data can significantly improve the understanding of wetland hydrological processes. Potentially, this approach can provide the basis for the evaluation of ecosystem services and may aid in the optimization of wetland management strategies

Characterization of non-Gaussianity in the snow distributions of various landscapes

Seasonal snowpack is an important predictor of the water resources available in the following spring and early-summer melt season. Total basin snow water equivalent (SWE) estimation usually requires a form of statistical analysis that is implicitly built upon the Gaussian framework. However, it is important to characterize the non-Gaussian properties of snow distribution for accurate large-scale SWE estimation based on remotely sensed or sparse ground-based observations. This study quantified non-Gaussianity using sample negentropy; the Kullback–Leibler divergence from the Gaussian distribution for field-observed snow depth data from the North Slope, Alaska; and three representative SWE distributions in the western USA from the Airborne Snow Observatory (ASO). Snowdrifts around lakeshore cliffs and deep gullies can bring moderate non-Gaussianity in the open, lowland tundra of North Slope, Alaska, while the ASO dataset suggests that subalpine forests may effectively suppress the non-Gaussianity of snow distribution. Thus, non-Gaussianity is found in areas with partial snow cover and wind-induced snowdrifts around topographic breaks on slopes and on other steep terrain features. The snowpacks may be considered weakly Gaussian in coastal regions with open tundra in Alaska and alpine and subalpine terrains in the western USA if the land is completely covered by snow. The wind-induced snowdrift effect can potentially be partitioned from the observed snow spatial distribution guided by its Gaussianity.</p

Characterization of non-Gaussianity in the snow distributions of various landscapes

Seasonal snowpack is an important predictor of the water resources available in the following spring and early-summer melt season. Total basin snow water equivalent (SWE) estimation usually requires a form of statistical analysis that is implicitly built upon the Gaussian framework. However, it is important to characterize the non-Gaussian properties of snow distribution for accurate large-scale SWE estimation based on remotely sensed or sparse ground-based observations. This study quantified non-Gaussianity using sample negentropy; the Kullback–Leibler divergence from the Gaussian distribution for field-observed snow depth data from the North Slope, Alaska; and three representative SWE distributions in the western USA from the Airborne Snow Observatory (ASO). Snowdrifts around lakeshore cliffs and deep gullies can bring moderate non-Gaussianity in the open, lowland tundra of North Slope, Alaska, while the ASO dataset suggests that subalpine forests may effectively suppress the non-Gaussianity of snow distribution. Thus, non-Gaussianity is found in areas with partial snow cover and wind-induced snowdrifts around topographic breaks on slopes and on other steep terrain features. The snowpacks may be considered weakly Gaussian in coastal regions with open tundra in Alaska and alpine and subalpine terrains in the western USA if the land is completely covered by snow. The wind-induced snowdrift effect can potentially be partitioned from the observed snow spatial distribution guided by its Gaussianity.</p

Geophysical Observations of Taliks Below Drained Lake Basins on the Arctic Coastal Plain of Alaska

Lakes and drained lake basins (DLBs) together cover up to ∼80% of the western Arctic Coastal Plain of Alaska. The formation and drainage of lakes in this continuous permafrost region drive spatial and temporal landscape dynamics. Postdrainage processes including vegetation succession and permafrost aggradation have implications for hydrology, carbon cycling, and landscape evolution. Here, we used surface nuclear magnetic resonance (NMR) and transient electromagnetic (TEM) measurements in conjunction with thermal modeling to investigate permafrost aggradation beneath eight DLBs on the western Arctic Coastal Plain of Alaska. We also surveyed two primary surface sites that served as nonlake affected control sites. Approximate timing of lake drainage was estimated based on historical aerial imagery. We interpreted the presence of taliks based on either unfrozen water estimated with surface NMR and/or TEM resistivities in DLBs compared to measurements on primary surface sites and borehole resistivity logs. Our results show evidence of taliks below several DLBs that drained before and after 1949 (oldest imagery). We observed depths to the top of taliks between 9 and 45 m. Thermal modeling and geophysical observations agree about the presence and extent of taliks at sites that drained after 1949. Lake drainage events will likely become more frequent in the future due to climate change and our modeling results suggest that warmer and wetter conditions will limit permafrost aggradation in DLBs. Our observations provide useful information to predict future evolution of permafrost in DLBs and its implications for the water and carbon cycles in the Arctic

The presence and degradation of residual permafrost plateaus on the western Kenai Peninsula Lowlands, southcentral Alaska

Permafrost influences roughly 80% of the Alaskan landscape (Jorgenson et al. 2008). Permafrost presence is determined by a complex interaction of climatic, topographic, and ecological conditions operating over long time scales such that it may persist in regions with a mean annual air temperature (MAAT) that is currently above 0 °C (Jorgenson et al. 2010). Ecosystem-protected permafrost may be found in these regions with present day climatic conditions that are no longer conducive to its formation (Shur and Jorgenson, 2007). The perennial frozen deposits typically occur as isolated patches that are highly susceptible to degradation. Press disturbances associated with climate change and pulse disturbances, such as fire or human activities, can lead to immediate and irrevocable permafrost thaw and ecosystem modification in these regions. In this study, we document the presence of residual permafrost plateaus on the western Kenai Peninsula lowlands of southcentral Alaska (Figure 1a), a region with a MAAT of 1.5±1 °C (1981 to 2010). In September 2012, field studies conducted at a number of black spruce plateaus located within herbaceous wetland complexes documented frozen ground extending from 1.4 to 6.1 m below the ground surface, with thaw depth measurements ranging from 0.49 to >1.00 m. Ground penetrating radar surveys conducted in the summer and the winter provided additional information on the geometry of the frozen ground below the forested plateaus. Continuous ground temperature measurements between September 2012 and September 2015, using thermistor strings calibrated at 0 °C in an ice bath before deployment, documented the presence of permafrost. The permafrost (1 m depth) on the Kenai Peninsula is extremely warm with mean annual ground temperatures that range from -0.05 to -0.11 °C. To better understand decadal-scale changes in the residual permafrost plateaus on the Kenai Peninsula, we analyzed historic aerial photography and highresolution satellite imagery from ca. 1950, ca. 1980, 1996, and ca. 2010. Forested permafrost plateaus were mapped manually in the image time series based on our field observations of characteristic landforms with sharply defined scalloped edges, marginal thermokarst moats, and collapse-scar depressions on their summits. Our preliminary analysis of the image time series indicates that in 1950, permafrost plateaus covered 20% of the wetland complexes analyzed in the four change detection study areas, but during the past six decades there has been a 50% reduction in permafrost plateau extent in the study area. The loss of permafrost has resulted in the transition of forested plateaus to herbaceous wetlands. The degradation of ecosystem-protected permafrost on the Kenai Peninsula likely results from a combination of press and pulse disturbances. MAAT has increased by 0.4 °C/decade since 1950, which could be causing top down permafrost thaw in the region. Tectonic activity associated with the Great Alaska Earthquake of 1964 caused the western Kenai Peninsula to lower in elevation by 0.7 to 2.3 m (Plafker 1969), potentially altering groundwater flow paths and influencing lateral as well as bottom up permafrost degradation. Wildfires have burned large portions of the Kenai Peninsula lowlands since 1940 and the rapid loss of permafrost at one site between 1996 and 2011 was in response to fires that occurred in 1996 and 2005. Better understanding the resilience and vulnerability of the Kenai Peninsula ecosystem-protected permafrost to degradation is of importance for mapping and predicting permafrost extent across colder permafrost regions that are currently warming

The above L-band and P-band airborne synthetic aperture radar surveys

Permafrost-affected ecosystems of the Arctic-boreal zone in northwestern North America are undergoing profound transformation due to rapid climate change. NASA\u27s Arctic Boreal Vulnerability Experiment (ABoVE) is investigating characteristics that make these ecosystems vulnerable or resilient to this change. ABoVE employs airborne synthetic aperture radar (SAR) as a powerful tool to characterize tundra, taiga, peatlands, and fens. Here, we present an annotated guide to the L-band and P-band airborne SAR data acquired during the 2017, 2018, 2019, and 2022 ABoVE airborne campaigns. We summarize the g 1/480 SAR flight lines and how they fit into the ABoVE experimental design (Miller et al., 2023; https://doi.org/10.3334/ORNLDAAC/2150). The Supplement provides hyperlinks to extensive maps, tables, and every flight plan as well as individual flight lines. We illustrate the interdisciplinary nature of airborne SAR data with examples of preliminary results from ABoVE studies including boreal forest canopy structure from TomoSAR data over Delta Junction, AK, and the Boreal Ecosystem Research and Monitoring Sites (BERMS) area in northern Saskatchewan and active layer thickness and soil moisture data product validation. This paper is presented as a guide to enable interested readers to fully explore the ABoVE L- and P-band airborne SAR data (https://uavsar.jpl.nasa.gov/cgi-bin/data.pl)

The influence of grouting and reinforcement ratio in the concrete block masonry compressive behavior

This paper presents an experimental investigation on the compressive strength and stress-strain curves of concrete block masonry with varying block and grout strengths and reinforcement ratio. The three-block prisms, built with 8.5 and 15.0 MPa blocks, were tested hollow and filled with 17.0 and 30.0 MPa compressive strength grouts. In addition, prisms and walls with reinforcement rates of 0.15%, 0.40% and 1.0 % were also tested. With the results, it was possible to measure the compressive strength and stress-strain behavior of masonry with inclusion of different grout and reinforcement components, giving parameters for better evaluation of their performance and design. Among the conclusions, it was observed that increasing the compressive strength of masonry is not proportional to the increase of the grouting area and the efficiency of reinforcement to increase compressive strength is low. Stress-strain curves for the several materials combinations are made available