Trends in Surface Elevation and Accretion in a Retrograding Delta in Coastal Mississippi, USA from 2012 – 2016

The Grand Bay estuary is in the north-central Gulf of Mexico and lacks riverine sediment input for marsh elevation maintenance. This study quantified trends in surface elevation change and accretion along an elevation gradient within the estuary. Elevation change rates were compared to short (13.71 mm/yr; 95% CI: -2.38 – 29.81), medium (6.97 mm/yr; 95% CI: 3.31 – 10.64), and long-range (3.50 mm/yr; 95% CI: 2.88 – 4.11) water level rise (WLR) rates for the region. Elevation change rates ranged from 0.54 mm/yr (95% CI: -0.63 – 1.72) to 5.45 mm/yr (95% CI: 4.27 – 6.62) and accretion rates ranged from 0.82 mm/yr (95% CI: -0.16 – 1.80) to 3.89 mm/yr (95% CI: 2.90 – 4.89) among marsh zones. Only the elevation change rate at a Juncus roemerianus marsh located high in the tidal frame was lower than long- ( P <0.001) and medium-range WLR rates ( P <0.01). The elevation change rate at a lower elevation J. roemerianus marsh was higher than the long-range WLR rate ( P <0.05). No marsh zones had elevation change rates that were significantly different from short-range WLR. These results suggest that J. roemerianus marshes higher in the tidal frame with limited sediment delivery are the most vulnerable to increases in sea level. Lower elevation marshes had higher rates of elevation change driven by sediment accretion and biogenic inputs. Other local research suggests that shoreline erosion is a threat to marsh persistence but provides elevation capital to interior marshes. Marsh migration is potential solution for marsh persistence in this relatively undeveloped area of the Gulf Coast.

Predicting changes in molluscan spatial distributions in mangrove forests in response to sea-level rise

Molluscs are an important component of the mangrove ecosystem, and the vertical distributions of molluscan species in this ecosystem are primarily dictated by tidal inundation. Thus, sea-level rise (SLR) may have profound effects on mangrove mollusc communities. Here, we used two dynamic empirical models based on measurements of surface elevation change, sediment accretion and zonation patterns of molluscs to predict changes in molluscan spatial distributions in response to different sea-level rise rates in the mangrove forests of Zhenzhu Bay (Guangxi, China). The change in surface elevation was 4.76–9.61 mm a during the study period (2016–2020), and the magnitude of surface-elevation change decreased exponentially as original surface elevation increased. Based on our model results, we predicted that mangrove molluscs might successfully adapt to a low rate of SLR (marker-horizon model: 2–4.57 mm a; plate model: 2–5.20 mm a) by 2100, with molluscs moving seaward and those in the lower intertidal zones expanding into newly available zones. However, as SLR rate increased (marker-horizon model: 4.57–8.14 mm a; plate model: 5.20–6.88 mm a), our models predicted that surface elevations would decrease beginning in the high intertidal zones and gradually spreading to the low intertidal zones. Finally, at high rates of SLR (marker-horizon model: 8.14–16.00 mm a; plate model: 6.88–16.00 mm a), surface elevations were predicted to decrease across the elevation gradient, with molluscs moving landward and species in higher intertidal zones would be blocked by landward barriers. Tidal inundation and the consequent increase in interspecific competition and predation pressure were predicted to threaten the survival of many molluscan groups in higher intertidal zones, especially species at the landward edge of the mangroves. Thus, future efforts to conserve mangrove floral and faunal diversity should prioritize species restricted to landward mangrove areas.

Surface Elevation Changes Estimation Underneath Mangrove Canopy Using SNERL Filtering Algorithm and DoD Technique on UAV-Derived DSM Data

Estimating surface elevation changes in mangrove forests requires a technique to filter the mangrove canopy and quantify the changes underneath. Hence, this study estimates surface elevation changes underneath the mangrove canopy through vegetation filtering and Difference of DEM (DoD) techniques using two epochs of unmanned aerial vehicle (UAV) data carried out during 2016 and 2017. A novel filtering algorithm named Surface estimation from Nearest Elevation and Repetitive Lowering (SNERL) is used to estimate the elevation height underneath the mangrove canopy. Consequently, DoD technique is used to quantify the elevation change rates at the ground surface, which comprise erosion, accretion, and sedimentation. The significant findings showed that region of interest (ROI) 5 experienced the highest volumetric accretion (surface raising) at 0.566 cm3. The most increased erosion (surface lowering) was identified at ROI 8 at −2.469 cm3. In contrast, for vertical change average rates, ROI 6 experienced the highest vertical accretion (surface raising) at 1.281 m. In comparison, the most increased vertical erosion (surface lowering) was spotted at ROI 3 at −0.568 m. The change detection map and the rates of surface elevation changes at Kilim River enabled authorities to understand the situation thoroughly and indicate the future situation, including its interaction with sea-level rise impacts.

Pre-collapse motion of the February 2021 Chamoli rock-ice avalanche, Indian Himalaya

On the 7th of February 2021, a large rock-ice avalanche triggered a debris flow in Chamoli district, Uttarakhand, India, leaving over 200 dead or missing. The rock-ice avalanche originated from a steep, glacierized north-facing slope. In this work, we assess the precursory signs exhibited by this slope prior to the catastrophic collapse. We evaluate monthly slope motion from 2015 to 2021 through feature tracking of high-resolution optical satellite imagery. We then combine these data with a time series of pre- and post-event DEMs, which we use to evaluate elevation change over the same area. Both datasets show that the 26.9 Mm3 collapse block moved over 10 m horizontally and vertically in the five years preceding collapse, with particularly rapid motion occurring in the summers of 2017 and 2018. We propose that the collapse results from a combination of snow-loading in a deep headwall crack and permafrost degradation in the heavily jointed bedrock. Our observation of a clear precursory signal highlights the potential of satellite imagery for monitoring the stability of high-risk slopes. We find that the timing of the Chamoli rock-ice avalanche could likely not have been forecast from satellite data alone.

Elevation Change of the Antarctic Ice Sheet: 1985 to 2020

The largest uncertainty in future projections of sea level change comes from the uncertain response of the Antarctic Ice Sheet to the warming oceans and atmosphere. The ice sheet gains roughly 2000 km3 of ice from precipitation each year and losses a similar amount through solid ice discharge into the surrounding oceans. Numerous studies have shown that the ice sheet is currently out of long-term equilibrium, losing mass at an accelerated rate and increasing sea levels rise. Projections of sea-level change rely on accurate estimates of the contribution of land ice to the contemporary sea level budget. The longest observational record available to study the mass balance of the Earth’s ice sheets comes from satellite altimeters. This record, however, consists of multiple satellite missions with different life-spans, inconsistent measurement types (radar and laser) and of varying quality. To fully utilize these data, measurements from different missions must be cross-calibrated and integrated into a consistent record of change. Here, we present a novel approach for generating such a record. We describe in detail the advanced geophysical corrections applied and the processes needed to derive elevation change estimates. We processed the full archive record of satellite altimetry data, providing a seamless record of elevation change for the Antarctic Ice Sheet that spans the period 1985 to 2020. The data are produced and distributed as part of the NASA MEaSUREs ITS_LIVE project (Nilsson et al., 2021).

A restitution method to reconstruct the 2001–13 surface evolution of Hurd Glacier, Livingston Island, Antarctica, using surface mass balance data

The surface restitution method we present reconstructs the evolution of a glacier surface between two time-separated surface topographies using seasonal surface mass balance (SMB) data. A conservative and systematic error analysis is included, based on the availability of surface elevation measurements within the period. The method is applied from 2001 to 2013 at Hurd Glacier (a 4 km2 glacier), where we have sufficient SMB and elevation data. We estimate surface elevation changes in two steps: (1) elevation change due to SMB and (2) elevation change due to glacier dynamics. Four different models of the method are compared depending on whether or not accumulation is memorised at each time step and whether they employ balance profiles or SMB maps. Models are validated by comparing a set of surface measurements retrieved in 2007 with the corresponding restituted elevations. Although surface elevation change between 2001 and 2007 was larger than 10 m, more than 80% of the points restituted by the four models showed errors below ±1 m compared to only 33% when predicted by a linear interpolator. As error estimates between models differ by 0.10 m, we recommend the simplest model, which does not memorise accumulation and interpolates SMB by elevation profiles.

Seasonal Surface Change of Urumqi Glacier No. 1, Eastern Tien Shan, China, Revealed by Repeated High-Resolution UAV Photogrammetry

The seasonal surface changes of glaciers in Tien Shan have seen little prior investigation despite the increase in geodetic studies of multi-year changes. In this study, we analyzed the potential of an Unmanned Aerial Vehicle (UAV) to analyze seasonal surface change processes of the Urumqi Glacier No. 1 in eastern Tien Shan. We carried out UAV surveys at the beginning and the end of the ablation period in 2018. The high-precision evolution of surface elevation, geodetic mass changes, surface velocity, and terminus change in the surveyed ablation area were correspondingly derived in combination with ground measurements, including stake/snow-pit observation and GPS measurement. The derived mean elevation change in the surveyed ablation area was −1.64 m, corresponding to the geodetic mass balance of approximately −1.39 m w.e. during the ablation period in 2018. The mean surface velocity was 3.3 m/yr and characterized by the spatial change of the velocity, which was less in the East Branch than in the West Branch. The UAV survey results were a little less than those from the ground measurements, and the correlation coefficient was 0.88 for the surface elevation change and 0.87 for surface displacement. The relative error of the glacier terminus change was 4.5% for the East Branch and 6.2% for the West Branch. These results show that UAV photogrammetry is ideal for assessing seasonal glacier surface changes and has a potential application in the monitoring of detailed glacier changes.

Quantifying heterogeneous monsoonal melt on a debris-covered glacier in Nepal Himalaya using repeat uncrewed aerial system (UAS) photogrammetry

The ablation zones of debris-covered glaciers in Himalaya exhibit heterogeneous processes and melt patterns. Although sub-debris melt is measured at ablation stakes, the high variability of debris thickness necessitates distributed melt measurements at the glacier scale. Focusing on Annapurna III Glacier, we used uncrewed aerial system (UAS) photogrammetry to estimate total volume loss and slope-perpendicular glacier melt between May and November 2019 using flow-corrected point clouds. Results indicated the average elevation change was −1.10 ± 0.19 m, while the mean melt was −0.87 m w.e., equating to a mean melt rate of −0.47 cm w.e. d−1. However, the spatial pattern was highly variable due to complex local processes necessitating future study over short intervals. The evaluation of specific areas showed the interplay of debris thickness variability, subseasonal debris redistribution, supraglacial channel reconfiguration and the imprint of relict ice cliffs in leading to contemporary melt rates. Ice cliffs had higher melt distances (mean −3.9 ± 0.19 m) compared to non-cliff areas (mean −0.75 ± 0.19 m) and were the predominant control on the spatial patterns of seasonal melt rates. Crucially, the definition of ice cliff areas from thinning data has a profound impact on derived melt rates and melt enhancement. Our study demonstrates the possibility and utility of deriving fully-distributed slope-perpendicular melt measurements.

Classifying disequilibrium of small mountain glaciers from patterns of surface elevation change distributions

The overall trend of rapid retreat of Alpine glaciers contains considerable variability of responses at the scale of individual glaciers. As a step towards a regional assessment of glacier state that allows a detailed differentiation of single glaciers, we explore the potential of a self-organizing maps (SOM) algorithm to identify and cluster recurring patterns of thickness change at glaciers in western Austria. Using digital elevation models and glacier inventories for three time periods, we compute the frequency distribution of surface elevation change over the area of each glacier in the data set, for each period. The results of the SOM clustering show a distinct pattern shift over time: From 1969 to 1997, surface elevation change occurred at relatively uniform rates across a given glacier. Since 1997, the distribution of surface elevation change at individual glaciers has been far less uniform, indicating accelerated processes of disintegration. Tracking the evolution of individual glaciers throughout the time periods via the clusters highlights both the broader regional trend as well as glaciers that deviate from this trend, e.g. some very small, high elevation glaciers that have reverted to reduced and more uniform volume loss patterns.