@phdthesis{Kneier2019, author = {Kneier, Fabian}, title = {Subsea permafrost in the Laptev Sea}, school = {Universit{\"a}t Potsdam}, pages = {220}, year = {2019}, abstract = {During lower sea levels in glacial periods, deep permafrost formed on large continental shelf areas of the Arctic Ocean. Subsequent sea level rise and coastal erosion created subsea permafrost, which generally degrades after inundation under the influence of a complex suite of marine, near-shore processes. Global warming is especially pronounced in the Arctic, and will increase the transition to and the degradation of subsea permafrost, with implications for atmospheric climate forcing, offshore infrastructure, and aquatic ecosystems. This thesis combines new geophysical, borehole observational and modelling approaches to enhance our understanding of subsea permafrost dynamics. Three specific areas for advancement were identified: (I) sparsity of observational data, (II) lacking implementation of salt infiltration mechanisms in models, and (III) poor understanding of the regional differences in key driving parameters. This study tested the combination of spectral ratios of the ambient vibration seismic wavefield, together with estimated shear wave velocity from seismic interferometry analysis, for estimating the thickness of the unfrozen sediment overlying the ice-bonded permafrost offshore. Mesoscale numerical calculations (10^1 to 10^2 m, thousands of years) were employed to develop and solve the coupled heat diffusion and salt transport equations including phase change effects. Model soil parameters were constrained by borehole data, and the impact of a variety of influences during the transgression was tested in modelling studies. In addition, two inversion schemes (particle swarm optimization and a least-square method) were used to reconstruct temperature histories for the past 200-300 years in the Laptev Sea region in Siberia from two permafrost borehole temperature records. These data were evaluated against larger scale reconstructions from the region. It was found (I) that peaks in spectral ratios modelled for three-layer, one-dimensional systems corresponded with thaw depths. Around Muostakh Island in the central Laptev Sea seismic receivers were deployed on the seabed. Derived depths of the ice-bonded permafrost table were between 3.7-20.7 m ± 15 \%, increasing with distance from the coast. (II) Temperatures modelled during the transition to subsea permafrost resembled isothermal conditions after about 2000 years of inundation at Cape Mamontov Klyk, consistent with observations from offshore boreholes. Stratigraphic scenarios showed that salt distribution and infiltration had a large impact on the ice saturation in the sediments. Three key factors were identified that, when changed, shifted the modelled permafrost thaw depth most strongly: bottom water temperatures, shoreline retreat rate and initial temperature before inundation. Salt transport based on diffusion and contribution from arbitrary density-driven mechanisms only accounted for about 50 \% of observed thaw depths at offshore sites hundreds to thousands of years after inundation. This bias was found consistently at all three sites in the Laptev Sea region. (III) In the temperature reconstructions, distinct differences in the local temperature histories between the western Laptev Sea and the Lena Delta sites were recognized, such as a transition to warmer temperatures a century later in the western Laptev Sea as well as a peak in warming three decades later. The local permafrost surface temperature history at Sardakh Island in the Lena Delta was reminiscent of the circum-Arctic regional average trends. However, Mamontov Klyk in the western Laptev Sea was consistent to Arctic trends only in the most recent decade and was more similar to northern hemispheric mean trends. Both sites were consistent with a rapid synoptic recent warming. In conclusion, the consistency between modelled response, expected permafrost distribution, and observational data suggests that the passive seismic method is promising for the determination of the thickness of unfrozen sediment on the continental Arctic shelf. The quantified gap between currently modelled and observed thaw depths means that the impact of degradation on climate forcing, ecosystems, and infrastructure is larger than current models predict. This discrepancy suggests the importance of further mechanisms of salt penetration and thaw that have not been considered - either pre-inundation or post-inundation, or both. In addition, any meaningful modelling of subsea permafrost would have to constrain the identified key factors and their regional differences well. The shallow permafrost boreholes provide missing well-resolved short-scale temperature information in the coastal permafrost tundra of the Arctic. As local differences from circum-Arctic reconstructions, such as later warming and higher warming magnitude, were shown to exist in this region, these results provide a basis for local surface temperature record parameterization of climate and, in particular, permafrost models. The results of this work bring us one step further to understanding the full picture of the transition from terrestrial to subsea permafrost.}, language = {en} } @article{CarusHeunerPauletal.2017, author = {Carus, Jana and Heuner, Maike and Paul, Maike and Schr{\"o}der, Boris}, title = {Plant distribution and stand characteristics in brackish marshes}, series = {Estuarine, Coastal and Shelf Science}, volume = {196}, journal = {Estuarine, Coastal and Shelf Science}, publisher = {Elsevier}, address = {London}, issn = {0272-7714}, doi = {10.1016/j.ecss.2017.06.038}, pages = {237 -- 247}, year = {2017}, abstract = {Due to increasing pressure on estuarine marshes from sea level rise and river training, there is a growing need to understand how species-environment relationships influence the zonation and growth of tidal marsh vegetation. In the present study, we investigated the distribution and stand characteristics of the two key brackish marsh species Bolboschoenus maritimus and Phragmites australis in the Elbe estuary together with several abiotic habitat factors. We then tested the effect of these habitat factors on plant growth and zonation with generalised linear models (GLMs). Our study provides detailed information on the importance of single habitat factors and their interactions for controlling the distribution patterns and stand characteristics of two key marsh species. Our results suggest that flow velocity is the main factor influencing species distribution and stand characteristics and together with soil-water salinity even affects the inundation tolerance of the two specie investigated here. Additionally, inundation height and duration as well as interspecific competition helped explain the distribution patterns and stand characteristics. By identifying the drivers of marsh zonation and stand characteristics and quantifying their effects, this study provides useful information for evaluating a future contribution of tidal marsh vegetation to ecosystem-based shore protection.}, language = {en} } @article{MalinowskiHoefleKoenigetal.2016, author = {Malinowski, Radostaw and H{\"o}fle, Bernhard and Koenig, Kristina and Groom, Geoff and Schwanghart, Wolfgang and Heckrath, Goswin}, title = {Local-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data}, series = {ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing}, volume = {119}, journal = {ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0924-2716}, doi = {10.1016/j.isprsjprs.2016.06.009}, pages = {267 -- 279}, year = {2016}, abstract = {Knowledge about the magnitude of localised flooding of riverine areas is crucial for appropriate land management and administration at regional and local levels. However, detection and delineation of localised flooding with remote sensing techniques are often hampered on floodplains by the presence of herbaceous vegetation. To address this problem, this study presents the application of full waveform airborne laser scanning (ALS) data for detection of floodwater extent. In general, water surfaces are characterised by low values of backscattered energy due to water absorption of the infrared laser shots, but the exact strength of the recorded laser pulse depends on the area covered by the targets located within a laser pulse footprint area. To account for this we analysed the physical quantity of radio metrically calibrated ALS data, the backscattering coefficient, in relation to water and vegetation coverage within a single laser footprint. The results showed that the backscatter was negatively correlated to water coverage, and that of the three distinguished classes of water coverage (low, medium, and high) only the class with the largest extent of water cover (>70\%) had relatively distinct characteristics that can be used for classification of water surfaces. Following the laser footprint analysis, three classifiers, namely AdaBoost with Decision Tree, Naive Bayes and Random Forest, were utilised to classify laser points into flooded and non-flooded classes and to derive the map of flooding extent. The performance of the classifiers is highly dependent on the set of laser points features used. Best performance was achieved by combining radiometric and geometric laser point features. The accuracy of flooding maps based solely on radiometric features resulted in overall accuracies of up to 70\% and was limited due to the overlap of the backscattering coefficient values between water and other land cover classes. Our point-based classification methods assure a high mapping accuracy (similar to 89\%) and demonstrate the potential of using full-waveform ALS data to detect water surfaces on floodplain areas with limited water surface exposition through the vegetation canopy. (C) 2016 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.}, language = {en} }