@phdthesis{Willner2018,
  author    = {Willner, Sven N.},
  title     = {Global economic response to flood damages under climate change},
  school      = {Universit{\"a}t Potsdam},
  pages     = {v, 247},
  year      = {2018},
  abstract  = {Climate change affects societies across the globe in various ways. In addition to gradual changes in temperature and other climatic variables, global warming is likely to increase intensity and frequency of extreme weather events. Beyond biophysical impacts, these also directly affect societal and economic activity. Additionally, indirect effects can occur; spatially, economic losses can spread along global supply-chains; temporally, climate impacts can change the economic development trajectory of countries. This thesis first examines how climate change alters river flood risk and its local socio-economic implications. Then, it studies the global economic response to river floods in particular, and to climate change in general. Changes in high-end river flood risk are calculated for the next three decades on a global scale with high spatial resolution. In order to account for uncertainties, this assessment makes use of an ensemble of climate and hydrological models as well as a river routing model, that is found to perform well regarding peak river discharge. The results show an increase in high-end flood risk in many parts of the world, which require profound adaptation efforts. This pressure to adapt is measured as the enhancement in protection level necessary to stay at historical high-end risk. In developing countries as well as in industrialized regions, a high pressure to adapt is observed - the former to increase low protection levels, the latter to maintain the low risk levels perceived in the past. Further in this thesis, the global agent-based dynamic supply-chain model acclimate is developed. It models the cascading of indirect losses in the global supply network. As an anomaly model its agents - firms and consumers - maximize their profit locally to respond optimally to local perturbations. Incorporating quantities as well as prices on a daily basis, it is suitable to dynamically resolve the impacts of unanticipated climate extremes. The model is further complemented by a static measure, which captures the inter-dependencies between sectors across regions that are only connected indirectly. These higher-order dependencies are shown to be important for a comprehensive assessment of loss-propagation and overall costs of local disasters. In order to study the economic response to river floods, the acclimate model is driven by flood simulations. Within the next two decades, the increase in direct losses can only partially be compensated by market adjustments, and total losses are projected to increase by 17\% without further adaptation efforts. The US and the EU are both shown to receive indirect losses from China, which is strongly affected directly. However, recent trends in the trade relations leave the EU in a better position to compensate for these losses. Finally, this thesis takes a broader perspective when determining the investment response to the climate change damages employing the integrated assessment model DICE. On an optimal economic development path, the increase in damages is anticipated as emissions and consequently temperatures increase. This leads to a significant devaluation of investment returns and the income losses from climate damages almost double. Overall, the results highlight the need to adapt to extreme weather events - local physical adaptation measures have to be combined with regional and global policy measures to prepare the global supply-chain network to climate change.},
  language  = {en}
}
@phdthesis{Hesse2018,
  author    = {Hesse, Cornelia},
  title     = {Integrated water quality modelling in meso- to large-scale catchments of the Elbe river basin under climate and land use change},
  doi       = {10.25932/publishup-42295},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-422957},
  school      = {Universit{\"a}t Potsdam},
  pages     = {ix, 217},
  year      = {2018},
  abstract  = {In einer sich {\"a}ndernden Umwelt sind Fließgew{\"a}sser{\"o}kosysteme vielf{\"a}ltigen direkten und indirekten anthropogenen Belastungen ausgesetzt, die die Gew{\"a}sser sowohl in ihrer Menge als auch in ihrer G{\"u}te beeintr{\"a}chtigen k{\"o}nnen. Ein {\"u}berm{\"a}ßiger Eintrag von N{\"a}hrstoffen verursacht etwa Massenentwicklungen von Algen und Sauerstoffdefizite in den Gew{\"a}ssern, was zum Verfehlen der Ziele der Wasserrahmenrichtlinie (WRRL) f{\"u}hren kann. In vielen europ{\"a}ischen Einzugsgebieten und auch dem der Elbe sind solche Probleme zu beobachten. W{\"a}hrend der letzten Jahrzehnte entstanden diverse computergest{\"u}tzte Modelle, die zum Schutz und Management von Wasserressourcen genutzt werden k{\"o}nnen. Sie helfen beim Verstehen der N{\"a}hrstoffprozesse und Belastungspfade in Einzugsgebieten, bei der Absch{\"a}tzung m{\"o}glicher Folgen von Klima- und Landnutzungs{\"a}nderungen f{\"u}r die Wasserk{\"o}rper, sowie bei der Entwicklung eventueller Kompensationsmaßnahmen. Aufgrund der Vielzahl an sich gegenseitig beeinflussenden Prozessen ist die Modellierung der Wasserqualit{\"a}t komplexer und aufw{\"a}ndiger als eine reine hydrologische Modellierung. {\"O}kohydrologische Modelle zur Simulation der Gew{\"a}sserg{\"u}te, einschließlich des Modells SWIM (Soil and Water Integrated Model), bed{\"u}rfen auch h{\"a}ufig noch einer Weiterentwicklung und Verbesserung der Prozessbeschreibungen. Aus diesen {\"U}berlegungen entstand die vorliegende Dissertation, die sich zwei Hauptanliegen widmet: 1) einer Weiterentwicklung des N{\"a}hrstoffmoduls des {\"o}kohydrologischen Modells SWIM f{\"u}r Stickstoff- und Phosphorprozesse, und 2) der Anwendung des Modells SWIM im Elbegebiet zur Unterst{\"u}tzung eines anpassungsf{\"a}higen Wassermanagements im Hinblick auf m{\"o}gliche zuk{\"u}nftige {\"A}nderungen der Umweltbedingungen. Die kumulative Dissertation basiert auf f{\"u}nf wissenschaftlichen Artikeln, die in internationalen Zeitschriften ver{\"o}ffentlicht wurden. Im Zuge der Arbeit wurden verschiedene Modellanpassungen in SWIM vorgenommen, wie etwa ein einfacher Ansatz zur Verbesserung der Simulation der Wasser- und N{\"a}hrstoffverh{\"a}ltnisse in Feuchtgebieten, ein um Ammonium erweiterter Stickstoffkreislauf im Boden, sowie ein Flussprozessmodul, das Umwandlungsprozesse, Sauerstoffverh{\"a}ltnisse und Algenwachstum im Fließgew{\"a}sser simuliert, haupts{\"a}chlich angetrieben von Temperatur und Licht. Auch wenn dieser neue Modellansatz ein sehr komplexes Modell mit einer Vielzahl an neuen Kalibrierungsparametern und steigender Unsicherheit erzeugte, konnten gute Ergebnisse in den Teileinzugsgebieten und dem gesamten Gebiet der Elbe erzielt werden, so dass das Modell zur Absch{\"a}tzung m{\"o}glicher Folgen von Klimavariabilit{\"a}ten und ver{\"a}nderten anthropogenen Einfl{\"u}ssen f{\"u}r die Gew{\"a}sserg{\"u}te genutzt werden konnte. Das neue Fließgew{\"a}ssermodul ist ein wichtiger Beitrag zur Verbesserung der N{\"a}hrstoffmodellierung in SWIM, vor allem f{\"u}r Stoffe, die haupts{\"a}chlich aus Punktquellen in die Gew{\"a}sser gelangen (wie z.B. Phosphat). Der neue Modellansatz verbessert zudem die Anwendbarkeit von SWIM f{\"u}r Fragestellungen im Zusammenhang mit der WRRL, bei der biologische Qualit{\"a}tskomponenten (wie etwa Phytoplankton) eine zentrale Rolle spielen. Die dargestellten Ergebnisse der Wirkungsstudien k{\"o}nnen bei Entscheidungstr{\"a}gern und anderen Akteuren das Verst{\"a}ndnis f{\"u}r zuk{\"u}nftige Herausforderungen im Gew{\"a}ssermanagement erh{\"o}hen und dazu beitragen, ein angepasstes Management f{\"u}r das Elbeeinzugsgebiet zu entwickeln.},
  language  = {en}
}
@phdthesis{Smith2018,
  author    = {Smith, Taylor},
  title     = {Decadal changes in the snow regime of High Mountain Asia, 1987-2016},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407120},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xiii, 142},
  year      = {2018},
  abstract  = {More than a billion people rely on water from rivers sourced in High Mountain Asia (HMA), a significant portion of which is derived from snow and glacier melt. Rural communities are heavily dependent on the consistency of runoff, and are highly vulnerable to shifts in their local environment brought on by climate change. Despite this dependence, the impacts of climate change in HMA remain poorly constrained due to poor process understanding, complex terrain, and insufficiently dense in-situ measurements. HMA's glaciers contain more frozen water than any region outside of the poles. Their extensive retreat is a highly visible and much studied marker of regional and global climate change. However, in many catchments, snow and snowmelt represent a much larger fraction of the yearly water budget than glacial meltwaters. Despite their importance, climate-related changes in HMA's snow resources have not been well studied. Changes in the volume and distribution of snowpack have complex and extensive impacts on both local and global climates. Eurasian snow cover has been shown to impact the strength and direction of the Indian Summer Monsoon -- which is responsible for much of the precipitation over the Indian Subcontinent -- by modulating earth-surface heating. Shifts in the timing of snowmelt have been shown to limit the productivity of major rangelands, reduce streamflow, modify sediment transport, and impact the spread of vector-borne diseases. However, a large-scale regional study of climate impacts on snow resources had yet to be undertaken. Passive Microwave (PM) remote sensing is a well-established empirical method of studying snow resources over large areas. Since 1987, there have been consistent daily global PM measurements which can be used to derive an estimate of snow depth, and hence snow-water equivalent (SWE) -- the amount of water stored in snowpack. The SWE estimation algorithms were originally developed for flat and even terrain -- such as the Russian and Canadian Arctic -- and have rarely been used in complex terrain such as HMA. This dissertation first examines factors present in HMA that could impact the reliability of SWE estimates. Forest cover, absolute snow depth, long-term average wind speeds, and hillslope angle were found to be the strongest controls on SWE measurement reliability. While forest density and snow depth are factors accounted for in modern SWE retrieval algorithms, wind speed and hillslope angle are not. Despite uncertainty in absolute SWE measurements and differences in the magnitude of SWE retrievals between sensors, single-instrument SWE time series were found to be internally consistent and suitable for trend analysis. Building on this finding, this dissertation tracks changes in SWE across HMA using a statistical decomposition technique. An aggregate decrease in SWE was found (10.6 mm/yr), despite large spatial and seasonal heterogeneities. Winter SWE increased in almost half of HMA, despite general negative trends throughout the rest of the year. The elevation distribution of these negative trends indicates that while changes in SWE have likely impacted glaciers in the region, climate change impacts on these two pieces of the cryosphere are somewhat distinct. Following the discussion of relative changes in SWE, this dissertation explores changes in the timing of the snowmelt season in HMA using a newly developed algorithm. The algorithm is shown to accurately track the onset and end of the snowmelt season (70\% within 5 days of a control dataset, 89\% within 10). Using a 29-year time series, changes in the onset, end, and duration of snowmelt are examined. While nearly the entirety of HMA has experienced an earlier end to the snowmelt season, large regions of HMA have seen a later start to the snowmelt season. Snowmelt periods have also decreased in almost all of HMA, indicating that the snowmelt season is generally shortening and ending earlier across HMA. By examining shifts in both the spatio-temporal distribution of SWE and the timing of the snowmelt season across HMA, we provide a detailed accounting of changes in HMA's snow resources. The overall trend in HMA is towards less SWE storage and a shorter snowmelt season. However, long-term and regional trends conceal distinct seasonal, temporal, and spatial heterogeneity, indicating that changes in snow resources are strongly controlled by local climate and topography, and that inter-annual variability plays a significant role in HMA's snow regime.},
  language  = {en}
}