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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.
There is already strong evidence that temperate lakes have been highly vulnerable to human induced climate warming during the last century. Hitherto climate impact studies have mainly focussed on the impacts of the recent long-term warming in winter and spring and little is known on the influence of climate warming on temperate lakes in summer. In the present thesis, I studied some aspects, which may have been strongly involved in determining the response of a lake to climate warming in summer. Thereby I have focussed on climate induced impacts on the thermal characteristics and the phenology and abundance of summer plankton in a shallow polymictic lake (Müggelsee, Germany). First, the influence of climate warming on the phenology and abundance of the lake plankton was investigated across seasons. Fast-growing spring phytoplankton and zooplankton (Daphnia) advanced largely synchronously, whereas long-term changes in the phenology of slow-growing summer zooplankton were clearly species-specific and not synchronised. The phenology and/or abundance of several summer copepod species changed according to their individual thermal requirements at decisive developmental stages such as emergence from diapause in spring. The study emphasises that not only the degree of warming, but also its timing within the annual cycle is of great ecological importance. To analyse the impact of climate change on the thermal characteristics of the lake, I examined the long-term development of the daily epilimnetic temperature extrema during summer. The study demonstrated for the first time for lakes that the daily epilimnetic minima (during nighttime) have increased more rapidly than the daily epilimnetic maxima (during daytime), resulting in a distinct decrease in the daily epilimnetic temperature range. This day-night asymmetry in epilimnetic temperature was likely caused by an increased nighttime emission of long-wave radiation from the atmosphere. This underlines that not only increases in air temperature, but also changes in other meteorological variables such as wind speed, relative humidity and cloud cover may play an important role in determining the lake temperature with respect to further climate change. Furthermore, a short-term analysis on the mixing regime of the polymictic lake was conducted to examine the frequency and duration of stratification events and their impacts on dissolved oxygen, dissolved nutrients and summer phytoplankton. Even during the longest stratification events (heatwaves in 2003 and 2006) the thermal characteristics of the lake differed from those typically found in shallow dimictic lakes, which exhibit a continuous stratification during summer. Particularly, hypolimnetic temperatures were higher, favouring the depletion of oxygen and the accumulation of dissolved nutrient in the hypolimnion. Thermal stratification will be very likely amplified in the future, thus, I conclude that polymictic lakes will be very vulnerable to alterations in the thermal regime with respect to projections of further climate change during summer. Finally, a long-term case study on the long and short-term changes in the development of the planktonic larvae of the freshwater mussel Dreissena polymorpha was performed to analyse the impacts of simultaneous changes in the thermal and in the trophic regime of the lake. Both the climate warming and the decrease in external nutrient load were important in determining the abundance of the pelagic larvae by affecting different features of the life-history of this species throughout the warm season. The long-term increase in the abundance and length of larvae was related to the decrease in external nutrient loading and the change in phytoplankton composition. However, the recent heatwaves in 2003 and 2006 have offset this positive effect on larval abundance, due to unfavourable low oxygen concentrations that had resulted from extremely long stratification events, mimicking the effects of nutrient enrichment. Climate warming may thus induce counteracting effects in productive shallow lakes that underwent lake restoration through a decrease in external nutrient loading. I conclude that not only the nature of climate change and thus the timing of climate warming throughout the seasons and the occurrence of climatic extremes as heatwaves, but also site-specific lake conditions as the thermal mixing regime and the trophic state are crucial factors governing the impacts of climate warming on internal lake processes during summer. Consequently, further climate impact research on lake functioning should focus on how the different lake types respond to the complex environmental forcing in summer, to allow for a comprehensive understanding of human induced environmental changes in lakes.
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.
With Arctic ground as a huge and temperature-sensitive carbon reservoir, maintaining low ground temperatures and frozen conditions to prevent further carbon emissions that contrib-ute to global climate warming is a key element in humankind’s fight to maintain habitable con-ditions on earth. Former studies showed that during the late Pleistocene, Arctic ground condi-tions were generally colder and more stable as the result of an ecosystem dominated by large herbivorous mammals and vast extents of graminoid vegetation – the mammoth steppe. Characterised by high plant productivity (grassland) and low ground insulation due to animal-caused compression and removal of snow, this ecosystem enabled deep permafrost aggrad-ation. Now, with tundra and shrub vegetation common in the terrestrial Arctic, these effects are not in place anymore. However, it appears to be possible to recreate this ecosystem local-ly by artificially increasing animal numbers, and hence keep Arctic ground cold to reduce or-ganic matter decomposition and carbon release into the atmosphere.
By measuring thaw depth, total organic carbon and total nitrogen content, stable carbon iso-tope ratio, radiocarbon age, n-alkane and alcohol characteristics and assessing dominant vegetation types along grazing intensity transects in two contrasting Arctic areas, it was found that recreating conditions locally, similar to the mammoth steppe, seems to be possible. For permafrost-affected soil, it was shown that intensive grazing in direct comparison to non-grazed areas reduces active layer depth and leads to higher TOC contents in the active layer soil. For soil only frozen on top in winter, an increase of TOC with grazing intensity could not be found, most likely because of confounding factors such as vertical water and carbon movement, which is not possible with an impermeable layer in permafrost. In both areas, high animal activity led to a vegetation transformation towards species-poor graminoid-dominated landscapes with less shrubs. Lipid biomarker analysis revealed that, even though the available organic material is different between the study areas, in both permafrost-affected and sea-sonally frozen soils the organic material in sites affected by high animal activity was less de-composed than under less intensive grazing pressure. In conclusion, high animal activity af-fects decomposition processes in Arctic soils and the ground thermal regime, visible from reduced active layer depth in permafrost areas. Therefore, grazing management might be utilised to locally stabilise permafrost and reduce Arctic carbon emissions in the future, but is likely not scalable to the entire permafrost region.
Rainfall, snow-, and glacial melt throughout the Himalaya control river discharge, which is vital for maintaining agriculture, drinking water and hydropower generation. However, the spatiotemporal contribution of these discharge components to Himalayan rivers is not well understood, mainly because of the scarcity of ground-based observations. Consequently, there is also little known about the triggers and sources of peak sediment flux events, which account for extensive hydropower reservoir filling and turbine abrasion. We therefore lack basic information on the distribution of water resources and controls of erosion processes. In this thesis, I employ various methods to assess and quantify general characteristics of and links between precipitation, river discharge, and sediment flux in the Sutlej Valley. First, I analyze daily precipitation data (1998-2007) from 80 weather stations in the western Himalaya, to decipher the distribution of rain- and snowfall. Rainfall magnitude frequency analyses indicate that 40% of the summer rainfall budget is attributed to monsoonal rainstorms, which show higher variability in the orogenic interior than in frontal regions. Combined analysis of rainstorms and sediment flux data of a major Sutlej River tributary indicate that monsoonal rainfall has a first order control on erosion processes in the orogenic interior, despite the dominance of snowfall in this region. Second, I examine the contribution of rainfall, snow and glacial melt to river discharge in the Sutlej Valley (s55,000 km2), based on a distributed hydrological model, which covers the period 2000-2008. To achieve high spatial and daily resolution despite limited ground-based observations the hydrological model is forced by daily remote sensing data, which I adjusted and calibrated with ground station data. The calibration shows that the Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall product systematically overestimates rainfall in semi-arid and arid regions, increasing with aridity. The model results indicate that snowmelt-derived discharge (74%) is most important during the pre-monsoon season (April to June) whereas rainfall (56%) and glacial melt (17%) dominate the monsoon season (July-September). Therefore, climate change most likely causes a reduction in river discharge during the pre-monsoon season, which especially affects the orogenic interior. Third, I investigate the controls on suspended sediment flux in different parts of the Sutlej catchments, based on daily gauging data from the past decade. In conjunction with meteorological data, earthquake records, and rock strength measurements I find that rainstorms are the most frequent trigger of high-discharge events with peaks in suspended sediment concentrations (SSC) that account for the bulk of the suspended sediment flux. The suspended sediment flux increases downstream, mainly due to increases in runoff. Pronounced erosion along the Himalayan Front occurs throughout the monsoon season, whereas efficient erosion of the orogenic interior is confined to single extreme events. The results of this thesis highlight the importance of snow and glacially derived melt waters in the western Himalaya, where extensive regions receive only limited amounts of monsoonal rainfall. These regions are therefore particularly susceptible to global warming with major implications on the hydrological cycle. However, the sediment discharge data show that infrequent monsoonal rainstorms that pass the orographic barrier of the Higher Himalaya are still the primary trigger of the highest-impact erosion events, despite being subordinate to snow and glacially–derived discharge. These findings may help to predict peak sediment flux events and could underpin the strategic development of preventative measures for hydropower infrastructures.
With ongoing anthropogenic global warming, some of the most vulnerable components of the Earth system might become unstable and undergo a critical transition. These subsystems are the so-called tipping elements. They are believed to exhibit threshold behaviour and would, if triggered, result in severe consequences for the biosphere and human societies. Furthermore, it has been shown that climate tipping elements are not isolated entities, but interact across the entire Earth system. Therefore, this thesis aims at mapping out the potential for tipping events and feedbacks in the Earth system mainly by the use of complex dynamical systems and network science approaches, but partially also by more detailed process-based models of the Earth system.
In the first part of this thesis, the theoretical foundations are laid by the investigation of networks of interacting tipping elements. For this purpose, the conditions for the emergence of global cascades are analysed against the structure of paradigmatic network types such as Erdös-Rényi, Barabási-Albert, Watts-Strogatz and explicitly spatially embedded networks. Furthermore, micro-scale structures are detected that are decisive for the transition of local to global cascades. These so-called motifs link the micro- to the macro-scale in the network of tipping elements. Alongside a model description paper, all these results are entered into the Python software package PyCascades, which is publicly available on github.
In the second part of this dissertation, the tipping element framework is first applied to components of the Earth system such as the cryosphere and to parts of the biosphere. Afterwards it is applied to a set of interacting climate tipping elements on a global scale. Using the Earth system Model of Intermediate Complexity (EMIC) CLIMBER-2, the temperature feedbacks are quantified, which would arise if some of the large cryosphere elements disintegrate over a long span of time. The cryosphere components that are investigated are the Arctic summer sea ice, the mountain glaciers, the Greenland and the West Antarctic Ice Sheets. The committed temperature increase, in case the ice masses disintegrate, is on the order of an additional half a degree on a global average (0.39-0.46 °C), while local to regional additional temperature increases can exceed 5 °C. This means that, once tipping has begun, additional reinforcing feedbacks are able to increase global warming and with that the risk of further tipping events.
This is also the case in the Amazon rainforest, whose parts are dependent on each other via the so-called moisture-recycling feedback. In this thesis, the importance of drought-induced tipping events in the Amazon rainforest is investigated in detail. Despite the Amazon rainforest is assumed to be adapted to past environmental conditions, it is found that tipping events sharply increase if the drought conditions become too intense in a too short amount of time, outpacing the adaptive capacity of the Amazon rainforest. In these cases, the frequency of tipping cascades also increases to 50% (or above) of all tipping events. In the model that was developed in this study, the southeastern region of the Amazon basin is hit hardest by the simulated drought patterns. This is also the region that already nowadays suffers a lot from extensive human-induced changes due to large-scale deforestation, cattle ranching or infrastructure projects.
Moreover, on the larger Earth system wide scale, a network of conceptualised climate tipping elements is constructed in this dissertation making use of a large literature review, expert knowledge and topological properties of the tipping elements. In global warming scenarios, tipping cascades are detected even under modest scenarios of climate change, limiting global warming to 2 °C above pre-industrial levels. In addition, the structural roles of the climate tipping elements in the network are revealed. While the large ice sheets on Greenland and Antarctica are the initiators of tipping cascades, the Atlantic Meridional Overturning Circulation (AMOC) acts as the transmitter of cascades. Furthermore, in our conceptual climate tipping element model, it is found that the ice sheets are of particular importance for the stability of the entire system of investigated climate tipping elements.
In the last part of this thesis, the results from the temperature feedback study with the EMIC CLIMBER-2 are combined with the conceptual model of climate tipping elements. There, it is observed that the likelihood of further tipping events slightly increases due to the temperature feedbacks even if no further CO$_2$ would be added to the atmosphere.
Although the developed network model is of conceptual nature, it is possible with this work for the first time to quantify the risk of tipping events between interacting components of the Earth system under global warming scenarios, by allowing for dynamic temperature feedbacks at the same time.
Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species’ occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species’ distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species’ distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this ‘virtual ecologist’ approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species’ response to altered environmental conditions and which should hence be considered when trying to project species’ distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species’ response to environmental change, identify key challenges for future research and discuss emerging developments.
While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices.