@phdthesis{Rosenwinkel2018,
  author    = {Rosenwinkel, Swenja},
  title     = {Rock glaciers and natural dams in Central Asia},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-410386},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xvii, 181},
  year      = {2018},
  abstract  = {The formation and breaching of natural dammed lakes have formed the landscapes, especially in seismically active high-mountain regions. Dammed lakes pose both, potential water resources, and hazard in case of dam breaching. Central Asia has mostly arid and semi-arid climates. Rock glaciers already store more water than ice-glaciers in some semi-arid regions of the world, but their distribution and advance mechanisms are still under debate in recent research. Their impact on the water availability in Central Asia will likely increase as temperatures rise and glaciers diminish. This thesis provides insight to the relative age distribution of selected Kyrgyz and Kazakh rock glaciers and their single lobes derived from lichenometric dating. The size of roughly 8000 different lichen specimens was used to approximate an exposure age of the underlying debris surface. We showed that rock-glacier movement differs signifcantly on small scales. This has several implications for climatic inferences from rock glaciers. First, reactivation of their lobes does not necessarily point to climatic changes, or at least at out-of-equilibrium conditions. Second, the elevations of rock-glacier toes can no longer be considered as general indicators of the limit of sporadic mountain permafrost as they have been used traditionally. In the mountainous and seismically active region of Central Asia, natural dams, besides rock glaciers, also play a key role in controlling water and sediment infux into river valleys. However, rock glaciers advancing into valleys seem to be capable of infuencing the stream network, to dam rivers, or to impound lakes. This influence has not previously been addressed. We quantitatively explored these controls using a new inventory of 1300 Central Asian rock glaciers. Elevation, potential incoming solar radiation, and the size of rock glaciers and their feeder basins played key roles in predicting dam appearance. Bayesian techniques were used to credibly distinguish between lichen sizes on rock glaciers and their lobes, and to find those parameters of a rock-glacier system that are most credibly expressing the potential to build natural dams. To place these studies in the region's history of natural dams, a combination of dating of former lake levels and outburst flood modelling addresses the history and possible outburst flood hypotheses of the second largest mountain lake of the world, Issyk Kul in Kyrgyzstan. Megafoods from breached earthen or glacial dams were found to be a likely explanation for some of the lake's highly fluctuating water levels. However, our detailed analysis of candidate lake sediments and outburst-flood deposits also showed that more localised dam breaks to the west of Issyk Kul could have left similar geomorphic and sedimentary evidence in this Central Asian mountain landscape. We thus caution against readily invoking megafloods as the main cause of lake-level drops of Issyk Kul. In summary, this thesis addresses some new pathways for studying rock glaciers and natural dams with several practical implications for studies on mountain permafrost and natural hazards.},
  language  = {en}
}
@phdthesis{Veh2019,
  author    = {Veh, Georg},
  title     = {Outburst floods from moraine-dammed lakes in the Himalayas},
  doi       = {10.25932/publishup-43607},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-436071},
  school      = {Universit{\"a}t Potsdam},
  pages     = {124},
  year      = {2019},
  abstract  = {The Himalayas are a region that is most dependent, but also frequently prone to hazards from changing meltwater resources. This mountain belt hosts the highest mountain peaks on earth, has the largest reserve of ice outside the polar regions, and is home to a rapidly growing population in recent decades. One source of hazard has attracted scientific research in particular in the past two decades: glacial lake outburst floods (GLOFs) occurred rarely, but mostly with fatal and catastrophic consequences for downstream communities and infrastructure. Such GLOFs can suddenly release several million cubic meters of water from naturally impounded meltwater lakes. Glacial lakes have grown in number and size by ongoing glacial mass losses in the Himalayas. Theory holds that enhanced meltwater production may increase GLOF frequency, but has never been tested so far. The key challenge to test this notion are the high altitudes of >4000 m, at which lakes occur, making field work impractical. Moreover, flood waves can attenuate rapidly in mountain channels downstream, so that many GLOFs have likely gone unnoticed in past decades. Our knowledge on GLOFs is hence likely biased towards larger, destructive cases, which challenges a detailed quantification of their frequency and their response to atmospheric warming. Robustly quantifying the magnitude and frequency of GLOFs is essential for risk assessment and management along mountain rivers, not least to implement their return periods in building design codes. Motivated by this limited knowledge of GLOF frequency and hazard, I developed an algorithm that efficiently detects GLOFs from satellite images. In essence, this algorithm classifies land cover in 30 years (~1988-2017) of continuously recorded Landsat images over the Himalayas, and calculates likelihoods for rapidly shrinking water bodies in the stack of land cover images. I visually assessed such detected tell-tale sites for sediment fans in the river channel downstream, a second key diagnostic of GLOFs. Rigorous tests and validation with known cases from roughly 10\% of the Himalayas suggested that this algorithm is robust against frequent image noise, and hence capable to identify previously unknown GLOFs. Extending the search radius to the entire Himalayan mountain range revealed some 22 newly detected GLOFs. I thus more than doubled the existing GLOF count from 16 previously known cases since 1988, and found a dominant cluster of GLOFs in the Central and Eastern Himalayas (Bhutan and Eastern Nepal), compared to the rarer affected ranges in the North. Yet, the total of 38 GLOFs showed no change in the annual frequency, so that the activity of GLOFs per unit glacial lake area has decreased in the past 30 years. I discussed possible drivers for this finding, but left a further attribution to distinct GLOF-triggering mechanisms open to future research. This updated GLOF frequency was the key input for assessing GLOF hazard for the entire Himalayan mountain belt and several subregions. I used standard definitions in flood hydrology, describing hazard as the annual exceedance probability of a given flood peak discharge [m3 s-1] or larger at the breach location. I coupled the empirical frequency of GLOFs per region to simulations of physically plausible peak discharges from all existing ~5,000 lakes in the Himalayas. Using an extreme-value model, I could hence calculate flood return periods. I found that the contemporary 100-year GLOF discharge (the flood level that is reached or exceeded on average once in 100 years) is 20,600+2,200/-2,300 m3 s-1 for the entire Himalayas. Given the spatial and temporal distribution of historic GLOFs, contemporary GLOF hazard is highest in the Eastern Himalayas, and lower for regions with rarer GLOF abundance. I also calculated GLOF hazard for some 9,500 overdeepenings, which could expose and fill with water, if all Himalayan glaciers have melted eventually. Assuming that the current GLOF rate remains unchanged, the 100-year GLOF discharge could double (41,700+5,500/-4,700 m3 s-1), while the regional GLOF hazard may increase largest in the Karakoram. To conclude, these three stages-from GLOF detection, to analysing their frequency and estimating regional GLOF hazard-provide a framework for modern GLOF hazard assessment. Given the rapidly growing population, infrastructure, and hydropower projects in the Himalayas, this thesis assists in quantifying the purely climate-driven contribution to hazard and risk from GLOFs.},
  language  = {en}
}
@phdthesis{Schwanghart2022,
  author    = {Schwanghart, Wolfgang},
  title     = {Digital elevation model analysis in geomorphology and natural hazards research},
  year      = {2022},
  language  = {en}
}
@phdthesis{ArboledaZapata2023,
  author    = {Arboleda Zapata, Mauricio},
  title     = {Adapted inversion strategies for electrical resistivity data to explore layered near-surface environments},
  doi       = {10.25932/publishup-58135},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-581357},
  school      = {Universit{\"a}t Potsdam},
  pages     = {115},
  year      = {2023},
  abstract  = {The electrical resistivity tomography (ERT) method is widely used to investigate geological, geotechnical, and hydrogeological problems in inland and aquatic environments (i.e., lakes, rivers, and seas). The objective of the ERT method is to obtain reliable resistivity models of the subsurface that can be interpreted in terms of the subsurface structure and petrophysical properties. The reliability of the resulting resistivity models depends not only on the quality of the acquired data, but also on the employed inversion strategy. Inversion of ERT data results in multiple solutions that explain the measured data equally well. Typical inversion approaches rely on different deterministic (local) strategies that consider different smoothing and damping strategies to stabilize the inversion. However, such strategies suffer from the trade-off of smearing possible sharp subsurface interfaces separating layers with resistivity contrasts of up to several orders of magnitude. When prior information (e.g., from outcrops, boreholes, or other geophysical surveys) suggests sharp resistivity variations, it might be advantageous to adapt the parameterization and inversion strategies to obtain more stable and geologically reliable model solutions. Adaptations to traditional local inversions, for example, by using different structural and/or geostatistical constraints, may help to retrieve sharper model solutions. In addition, layer-based model parameterization in combination with local or global inversion approaches can be used to obtain models with sharp boundaries. In this thesis, I study three typical layered near-surface environments in which prior information is used to adapt 2D inversion strategies to favor layered model solutions. In cooperation with the coauthors of Chapters 2-4, I consider two general strategies. Our first approach uses a layer-based model parameterization and a well-established global inversion strategy to generate ensembles of model solutions and assess uncertainties related to the non-uniqueness of the inverse problem. We apply this method to invert ERT data sets collected in an inland coastal area of northern France (Chapter~2) and offshore of two Arctic regions (Chapter~3). Our second approach consists of using geostatistical regularizations with different correlation lengths. We apply this strategy to a more complex subsurface scenario on a local intermountain alluvial fan in southwestern Germany (Chapter~4). Overall, our inversion approaches allow us to obtain resistivity models that agree with the general geological understanding of the studied field sites. These strategies are rather general and can be applied to various geological environments where a layered subsurface structure is expected. The flexibility of our strategies allows adaptations to invert other kinds of geophysical data sets such as seismic refraction or electromagnetic induction methods, and could be considered for joint inversion approaches.},
  language  = {en}
}