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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.
Environmental drivers interactively affect individual tree growth across temperate European forests
(2018)
Forecasting the growth of tree species to future environmental changes requires abetter understanding of its determinants. Tree growth is known to respond to global‐change drivers such as climate change or atmospheric deposition, as well as to localland‐use drivers such as forest management. Yet, large geographical scale studiesexamining interactive growth responses to multiple global‐change drivers are relativelyscarce and rarely consider management effects. Here, we assessed the interactiveeffects of three global‐change drivers (temperature, precipitation and nitrogen deposi-tion) on individual tree growth of three study species (Quercus robur/petraea, Fagus syl-vatica and Fraxinus excelsior). We sampled trees along spatial environmental gradientsacross Europe and accounted for the effects of management for Quercus. We collectedincrement cores from 267 trees distributed over 151 plots in 19 forest regions andcharacterized their neighbouring environment to take into account potentially confounding factors such as tree size, competition, soil conditions and elevation. Wedemonstrate that growth responds interactively to global‐change drivers, with species ‐specific sensitivities to the combined factors. Simultaneously high levels of precipita-tion and deposition benefited Fraxinus, but negatively affected Quercus’ growth, high-lighting species‐specific interactive tree growth responses to combined drivers. ForFagus, a stronger growth response to higher temperatures was found when precipita-tion was also higher, illustrating the potential negative effects of drought stress underwarming for this species. Furthermore, we show that past forest management canmodulate the effects of changing temperatures on Quercus’ growth; individuals in plotswith a coppicing history showed stronger growth responses to higher temperatures.Overall, our findings highlight how tree growth can be interactively determined by glo-bal‐change drivers, and how these growth responses might be modulated by past for-est management. By showing future growth changes for scenarios of environmentalchange, we stress the importance of considering multiple drivers, including past man-agement and their interactions, when predicting tree growth.
The forcing from the anthropogenic heat flux (AHF), i.e. the dissipation of primary energy consumed by the human civilisation, produces a direct climate warming. Today, the globally averaged AHF is negligibly small compared to the indirect forcing from greenhouse gas emissions. Locally or regionally, though, it has a significant impact. Historical observations show a constant exponential growth of worldwide energy production. A continuation of this trend might be fueled or even amplified by the exploration of new carbon-free energy sources like fusion power. In such a scenario, the impacts of the AHF become a relevant factor for anthropogenic post-greenhouse gas climate change on the global scale, as well.
This master thesis aims at estimating the climate impacts of such a growing AHF forcing. In the first part of this work, the AHF is built into simple and conceptual, zero- and one-dimensional Energy Balance Models (EBMs), providing quick order of magnitude estimations of the temperature impact. In the one-dimensional EBM, the ice-albedo feedback from enhanced ice melting due to the AHF increases the temperature impact significantly compared to the zero-dimensional EBM.
Additionally, the forcing is built into a climate model of intermediate complexity, CLIMBER-3α. This allows for the investigation of the effect of localised AHF and gives further insights into the impact of the AHF on processes like the ocean heat uptake, sea ice and snow pattern changes
and the ocean circulation.
The global mean temperature response from the AHF today is of the order of 0.010 − 0.016 K in all reasonable model configurations tested. A transient tenfold increase of this forcing heats up the Earth System additionally by roughly 0.1 − 0.2 K in the presented models. Further growth
can also affect the tipping probability of certain climate elements.
Most renewable energy sources do not or only partially contribute to the AHF forcing as the energy from these sources dissipates anyway. Hence, the transition to a (carbon-free) renewable energy mix, which, in particular, does not rely on nuclear power, eliminates the local and global climate impacts from the increasing AHF forcing, independent of the growth of energy production.
Climate change, along with socio-economic development, will increase the economic impacts of floods. While the factors that influence flood risk to private property have been extensively studied, the risk that natural disasters pose to public infrastructure and the resulting implications on public sector budgets, have received less attention. We address this gap by developing a two-staged model framework, which first assesses the flood risk to public infrastructure in Austria. Combining exposure and vulnerability information at the building level with inundation maps, we project an increase in riverine flood damage, which progressively burdens public budgets. Second, the risk estimates are integrated into an insurance model, which analyzes three different compensation arrangements in terms of the monetary burden they place on future governments' budgets and the respective volatility of payments. Formalized insurance compensation arrangements offer incentives for risk reduction measures, which lower the burden on public budgets by reducing the vulnerability of buildings that are exposed to flooding. They also significantly reduce the volatility of payments and thereby improve the predictability of flood damage expenditures. These features indicate that more formalized insurance arrangements are an improvement over the purely public compensation arrangement currently in place in Austria.
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.
The contemporary state of functional traits and species richness in plant communities depends on legacy effects of past disturbances. Whether temporal responses of community properties to current environmental changes are altered by such legacies is, however, unknown. We expect global environmental changes to interact with land-use legacies given different community trajectories initiated by prior management, and subsequent responses to altered resources and conditions. We tested this expectation for species richness and functional traits using 1814 survey-resurvey plot pairs of understorey communities from 40 European temperate forest datasets, syntheses of management transitions since the year 1800, and a trait database. We also examined how plant community indicators of resources and conditions changed in response to management legacies and environmental change. Community trajectories were clearly influenced by interactions between management legacies from over 200 years ago and environmental change. Importantly, higher rates of nitrogen deposition led to increased species richness and plant height in forests managed less intensively in 1800 (i.e., high forests), and to decreases in forests with a more intensive historical management in 1800 (i.e., coppiced forests). There was evidence that these declines in community variables in formerly coppiced forests were ameliorated by increased rates of temperature change between surveys. Responses were generally apparent regardless of sites’ contemporary management classifications, although sometimes the management transition itself, rather than historic or contemporary management types, better explained understorey responses. Main effects of environmental change were rare, although higher rates of precipitation change increased plant height, accompanied by increases in fertility indicator values. Analysis of indicator values suggested the importance of directly characterising resources and conditions to better understand legacy and environmental change effects. Accounting for legacies of past disturbance can reconcile contradictory literature results and appears crucial to anticipating future responses to global environmental change.
A comprehensive understanding of the regional vegetation responses to long-term climate change will help to forecast Earth system dynamics. Based on a new well-dated pollen data set from Kanas Lake and a review on the published pollen records in and around the Altai Mountains, the regional vegetation dynamics and forcing mechanisms are discussed. In the Altai Mountains, the forest optimum occurred during 10-7ka for the upper forest zone and the tree line decline and/or ecological shifts were caused by climatic cooling from around 7ka. In the lower forest zone, the forest reached an optimum in the middle Holocene, and then increased openness of the forest, possibly caused by both climate cooling and human activities, took place in the late Holocene. In the lower basins or plains around the Altai Mountains, the development of protograssland or forest benefited from increasing humidity in the middle to late Holocene. Plain Language Summary In the Altai Mountains and surrounding area of central Asia, the previous studies of the Holocene paleovegetation and paleoclimate studies did not discuss the different ecological limiting factors for the vegetation in high mountains and low-elevation areas due to limited data. With accumulating fossil pollen data and surface pollen data, it is possible to understand better the geomorphological effect on the vegetation and discrepancies of vegetation/forest responses to large-scale climate forcing, and it is also possible to get reliable quantitative reconstructions of climate. Here our new pollen data and review on the published fossil pollen data will help us to look into the past climate change and vertical evolution of vegetation in this important area of the Northern Hemisphere. Based on our study, it can be concluded that the growth of taiga forest in the wetter areas may be promoted under a future warmer climate, while the forest in the relatively dry areas is liable to decline, and the different vegetation dynamics will contribute to future high-resolution coupled vegetation-climate model for Earth system modelling.
Flood risk is impacted by a range of physical and socio-economic processes. Hence, the quantification of flood risk ideally considers the complete flood risk chain, from atmospheric processes through catchment and river system processes to damage mechanisms in the affected areas. Although it is generally accepted that a multitude of changes along the risk chain can occur and impact flood risk, there is a lack of knowledge of how and to what extent changes in influencing factors propagate through the chain and finally affect flood risk. To fill this gap, we present a comprehensive sensitivity analysis which considers changes in all risk components, i.e. changes in climate, catchment, river system, land use, assets, and vulnerability. The application of this framework to the mesoscale Mulde catchment in Germany shows that flood risk can vary dramatically as a consequence of plausible change scenarios. It further reveals that components that have not received much attention, such as changes in dike systems or in vulnerability, may outweigh changes in often investigated components, such as climate. Although the specific results are conditional on the case study area and the selected assumptions, they emphasize the need for a broader consideration of potential drivers of change in a comprehensive way. Hence, our approach contributes to a better understanding of how the different risk components influence the overall flood risk.
In a changing world facing several direct or indirect anthropogenic challenges the freshwater resources are endangered in quantity and quality. An excessive supply of nutrients, for example, can cause disproportional phytoplankton development and oxygen deficits in large rivers, leading to failure of the aims requested by the Water Framework Directive (WFD). Such problems can be observed in many European river catchments including the Elbe basin, and effective measures for improving water quality status are highly appreciated.
In water resources management and protection, modelling tools can help to understand the dominant nutrient processes and to identify the main sources of nutrient pollution in a watershed. They can be effective instruments for impact assessments investigating the effects of changing climate or socio-economic conditions on the status of surface water bodies, and for testing the usefulness of possible protection measures. Due to the high number of interrelated processes, ecohydrological model approaches containing water quality components are more complex than the pure hydrological ones, and their setup and calibration require more efforts. Such models, including the Soil and Water Integrated Model (SWIM), still need some further development and improvement.
Therefore, this cumulative dissertation focuses on two main objectives: 1) the approach-related objectives aiming in the SWIM model improvement and further development regarding nutrient (nitrogen and phosphorus) process description, and 2) the application-related objectives in meso- to large-scale Elbe river basins to support adaptive river basin management in view of possible future changes. The dissertation is based on five scientific papers published in international journals and dealing with these research questions.
Several adaptations were implemented in the model code to improve the representation of nutrient processes including a simple wetland approach, an extended by ammonium nitrogen cycle in the soils, as well as a detailed in-stream module, simulating algal growth, nutrient transformation processes and oxygen conditions in the river reaches, mainly driven by water temperature and light. Although this new approaches created a highly complex ecohydrological model with a large number of additional calibration parameters and rising uncertainty, the calibration and validation of the SWIM model enhanced by the new approaches in selected subcatchment and the entire Elbe river basin delivered satisfactory to good model results in terms of criteria of fit. Thus, the calibrated and validated model provided a sound base for the assessment of possible future changes and impacts in climate, land use and management in the Elbe river (sub)basin(s).
The new enhanced modelling approach improved the applicability of the SWIM model for the WFD related research questions, where the ability to consider biological water quality components (such as phytoplankton) is important. It additionally enhanced its ability to simulate the behaviour of nutrients coming mainly from point sources (e.g. phosphate phosphorus). Scenario results can be used by decision makers and stakeholders to find and understand future challenges and possible adaptation measures in the Elbe river basin.
Organic matter characteristics in yedoma and thermokarst deposits on Baldwin Peninsula, west Alaska
(2018)
As Arctic warming continues and permafrost thaws, more soil and sedimentary organic matter (OM) will be decomposed in northern high latitudes. Still, uncertainties remain in the quality of the OM and the size of the organic carbon (OC) pools stored in different deposit types of permafrost landscapes. This study presents OM data from deep permafrost and lake deposits on the Baldwin Peninsula which is located in the southern portion of the continuous permafrost zone in west Alaska. Sediment samples from yedoma and drained thermokarst lake basin (DTLB) deposits as well as thermokarst lake sediments were analyzed for cryostratigraphical and biogeochemical parameters and their lipid biomarker composition to identify the below-ground OC pool size and OM quality of ice-rich permafrost on the Baldwin Peninsula. We provide the first detailed characterization of yedoma deposits on Baldwin Peninsula. We show that three-quarters of soil OC in the frozen deposits of the study region (total of 68 Mt) is stored in DTLB deposits (52 Mt) and one-quarter in the frozen yedoma deposits (16 Mt). The lake sediments contain a relatively small OC pool (4 Mt), but have the highest volumetric OC content (93 kgm(-3)) compared to the DTLB (35 kgm(-3)) and yedoma deposits (8 kgm(-3)), largely due to differences in the ground ice content. The biomarker analysis indicates that the OM in both yedoma and DTLB deposits is mainly of terrestrial origin. Nevertheless, the relatively high carbon preference index of plant leaf waxes in combination with a lack of a degradation trend with depth in the yedoma deposits indi-cates that OM stored in yedoma is less degraded than that stored in DTLB deposits. This suggests that OM in yedoma has a higher potential for decomposition upon thaw, despite the relatively small size of this pool. These findings show that the use of lipid biomarker analysis is valuable in the assessment of the potential future greenhouse gas emissions from thawing permafrost, especially because this area, close to the discontinuous permafrost boundary, is projected to thaw substantially within the 21st century.