Refine
Year of publication
Document Type
- Article (43)
- Doctoral Thesis (4)
- Postprint (2)
- Preprint (2)
- Review (2)
- Part of a Book (1)
- Other (1)
Language
- English (55)
Is part of the Bibliography
- yes (55) (remove)
Keywords
- Climate change (55) (remove)
Institute
- Institut für Geowissenschaften (23)
- Institut für Biochemie und Biologie (16)
- Institut für Umweltwissenschaften und Geographie (7)
- Fachgruppe Volkswirtschaftslehre (2)
- Institut für Physik und Astronomie (2)
- Fachgruppe Politik- & Verwaltungswissenschaft (1)
- Hasso-Plattner-Institut für Digital Engineering gGmbH (1)
- Mathematisch-Naturwissenschaftliche Fakultät (1)
- Sozialwissenschaften (1)
- Wirtschaftswissenschaften (1)
Modelling of environmental change impacts on water resources and hydrological extremes in Germany
(2012)
Water resources, in terms of quantity and quality, are significantly influenced by environmental changes, especially by climate and land use changes. The main objective of the present study is to project climate change impacts on the seasonal dynamics of water fluxes, spatial changes in water balance components as well as the future flood and low flow conditions in Germany. This study is based on the modeling results of the process-based eco-hydrological model SWIM (Soil and Water Integrated Model) driven by various regional climate scenarios on one hand. On the other hand, it is supported by statistical analysis on long-term trends of observed and simulated time series. In addition, this study evaluates the impacts of potential land use changes on water quality in terms of NO3-N load in selected sub-regions of the Elbe basin. In the context of climate change, the actual evapotransipration is likely to increase in most parts of Germany, while total runoff generation may decrease in south and east regions in the scenario period 2051-2060. Water discharge in all six studied large rivers (Ems, Weser, Saale, Danube, Main and Neckar) would be 8 – 30% lower in summer and autumn compared to the reference period (1961 – 1990), and the strongest decline is expected for the Saale, Danube and Neckar. The 50-year low flow is likely to occur more frequently in western, southern and central Germany after 2061 as suggested by more than 80% of the model runs. The current low flow period (from August to September) may be extended until the late autumn at the end of this century. Higher winter flow is expected in all of these rivers, and the increase is most significant for the Ems (about 18%). No general pattern of changes in flood directions can be concluded according to the results driven by different RCMs, emission scenarios and multi-realizations. An optimal agricultural land use and management are essential for the reduction in nutrient loads and improvement of water quality. In the Weiße Elster and Unstrut sub-basins (Elbe), an increase of 10% in the winter rape area can result in 12-19% more NO3-N load in rivers. In contrast, another energy plant, maize, has a moderate effect on the water environment. Mineral fertilizers have a much stronger effect on the NO3-N load than organic fertilizers. Cover crops, which play an important role in the reduction of nitrate losses from fields, should be maintained on cropland. The uncertainty in estimating future high flows and, in particular, extreme floods remain high due to different RCM structures, emission scenarios and multi-realizations. In contrast, the projection of low flows under warmer climate conditions appears to be more pronounced and consistent. The largest source of uncertainty related to NO3-N modelling originates from the input data on the agricultural management.
Risk-based insurance is a commonly proposed and discussed flood risk adaptation mechanism in policy debates across the world such as in the United Kingdom and the United States of America. However, both risk-based premiums and growing risk pose increasing difficulties for insurance to remain affordable. An empirical concept of affordability is required as the affordability of adaption strategies is an important concern for policymakers, yet such a concept is not often examined. Therefore, a robust metric with a commonly acceptable affordability threshold is required. A robust metric allows for a previously normative concept to be quantified in monetary terms, and in this way, the metric is rendered more suitable for integration into public policy debates. This paper investigates the degree to which risk-based flood insurance premiums are unaffordable in Europe. In addition, this paper compares the outcomes generated by three different definitions of unaffordability in order to investigate the most robust definition. In doing so, the residual income definition was found to be the least sensitive to changes in the threshold. While this paper focuses on Europe, the selected definition can be employed elsewhere in the world and across adaption measures in order to develop a common metric for indicating the potential unaffordability problem.
Flood disasters severely impact human subjective well-being (SWB). Nevertheless, few studies have examined the influence of flood events on individual well-being and how such impacts may be limited by flood protection measures. This study estimates the long term impacts on individual subjective well-being of flood experiences, individual subjective flood risk perceptions, and household flood preparedness decisions. These effects are monetised and placed in context through a comparison with impacts of other adverse events on well-being. We collected data from households in flood-prone areas in France. The results indicate that experiencing a flood has a large negative impact on subjective well-being that is incompletely attenuated over time. Moreover, individuals do not need to be directly affected by floods to suffer SWB losses since subjective well-being is lower for those who expect their flood risk to increase or who have seen a neighbour being flooded. Floodplain inhabitants who prepared for flooding by elevating their home have a higher subjective well-being. A monetisation of the aforementioned well-being impacts shows that a flood requires Euro150,000 in immediate compensation to attenuate SWB losses. The decomposition of the monetised impacts of flood experience into tangible losses and intangible effects on SWB shows that intangible effects are about twice as large as the tangible direct monetary flood losses. Investments in flood protection infrastructure may be under funded if the intangible SWB benefits of flood protection are not taken into account.
The effect of methods of statistical downscaling of daily precipitation on changes in extreme flow indices under a plausible future climate change scenario was investigated in 11 catchments selected from 9 countries in different parts of Europe. The catchments vary from 67 to 6171 km(2) in size and cover different climate zones. 15 regional climate model outputs and 8 different statistical downscaling methods, which are broadly categorized as change factor and bias correction based methods, were used for the comparative analyses. Different hydrological models were implemented in different catchments to simulate daily runoff. A set of flood indices were derived from daily flows and their changes have been evaluated by comparing their values derived from simulations corresponding to the current and future climate. Most of the implemented downscaling methods project an increase in the extreme flow indices in most of the catchments. The catchments where the extremes are expected to increase have a rainfall dominated flood regime. In these catchments, the downscaling methods also project an increase in the extreme precipitation in the seasons when the extreme flows occur. In catchments where the flooding is mainly caused by spring/summer snowmelt, the downscaling methods project a decrease in the extreme flows in three of the four catchments considered. A major portion of the variability in the projected changes in the extreme flow indices is attributable to the variability of the climate model ensemble, although the statistical downscaling methods contribute 35-60% of the total variance. (C) 2016 Elsevier B.V. All rights reserved.
Elevated annual average temperature has been found to impact macro-economic growth. However, various fundamental elements of the economy are affected by deviations of daily temperature from seasonal expectations which are not well reflected in annual averages. Here we show that increases in seasonally adjusted day-to-day temperature variability reduce macro-economic growth independent of and in addition to changes in annual average temperature. Combining observed day-to-day temperature variability with subnational economic data for 1,537 regions worldwide over 40 years in fixed-effects panel models, we find that an extra degree of variability results in a five percentage-point reduction in regional growth rates on average. The impact of day-to-day variability is modulated by seasonal temperature difference and income, resulting in highest vulnerability in low-latitude, low-income regions (12 percentage-point reduction). These findings illuminate a new, global-impact channel in the climate–economy relationship that demands a more comprehensive assessment in both climate and integrated assessment models.
Evaluating climate geoengineering proposals in the context of the Paris Agreement temperature goals
(2018)
Current mitigation efforts and existing future commitments are inadequate to accomplish the Paris Agreement temperature goals. In light of this, research and debate are intensifying on the possibilities of additionally employing proposed climate geoengineering technologies, either through atmospheric carbon dioxide removal or farther-reaching interventions altering the Earth’s radiative energy budget. Although research indicates that several techniques may eventually have the physical potential to contribute to limiting climate change, all are in early stages of development, involve substantial uncertainties and risks, and raise ethical and governance dilemmas. Based on present knowledge, climate geoengineering techniques cannot be relied on to significantly contribute to meeting the Paris Agreement temperature goals.
Both climate change and land use regimes affect the viability of populations, but they are often studied separately. Moreover, population viability analyses (PVAs) often ignore the effects of large environmental gradients and use temporal resolutions that are too coarse to take into account that different stages of a population's life cycle may be affected differently by climate change. Here, we present the High-resolution Large Environmental Gradient (HiLEG) model and apply it in a PVA with daily resolution based on daily climate projections for Northwest Germany. We used the large marsh grasshopper (LMG) as the target species and investigated (1) the effects of climate change on the viability and spatial distribution of the species, (2) the influence of the timing of grassland mowing on the species and (3) the interaction between the effects of climate change and grassland mowing. The stageand cohort-based model was run for the spatially differentiated environmental conditions temperature and soil moisture across the whole study region. We implemented three climate change scenarios and analyzed the population dynamics for four consecutive 20-year periods. Climate change alone would lead to an expansion of the regions suitable for the LMG, as warming accelerates development and due to reduced drought stress. However, in combination with land use, the timing of mowing was crucial, as this disturbance causes a high mortality rate in the aboveground life stages. Assuming the same date of mowing throughout the region, the impact on viability varied greatly between regions due to the different climate conditions. The regional negative effects of the mowing date can be divided into five phases: (1) In early spring, the populations were largely unaffected in all the regions; (2) between late spring and early summer, they were severely affected only in warm regions; (3) in summer, all the populations were severely affected so that they could hardly survive; (4) between late summer and early autumn, they were severely affected in cold regions; and (5) in autumn, the populations were equally affected across all regions. The duration and start of each phase differed slightly depending on the climate change scenario and simulation period, but overall, they showed the same pattern. Our model can be used to identify regions of concern and devise management recommendations. The model can be adapted to the life cycle of different target species, climate projections and disturbance regimes. We show with our adaption of the HiLEG model that high-resolution PVAs and applications on large environmental gradients can be reconciled to develop conservation strategies capable of dealing with multiple stressors.
Patterns of phenotypic trait variation in two temperate forest herbs along a broad climatic gradient
(2015)
Phenotypic trait variation plays a major role in the response of plants to global environmental change, particularly in species with low migration capabilities and recruitment success. However, little is known about the variation of functional traits within populations and about differences in this variation on larger spatial scales. In a first approach, we therefore related trait expression to climate and local environmental conditions, studying two temperate forest herbs, Milium effusum and Stachys sylvatica, along a similar to 1800-2500 km latitudinal gradient. Within each of 9-10 regions in six European countries, we collected data from six populations of each species and recorded several variables in each region (temperature, precipitation) and population (light availability, soil parameters). For each plant, we measured height, leaf area, specific leaf area, seed mass and the number of seeds and examined environmental effects on within-population trait variation as well as on trait means. Most importantly, trait variation differed both between and within populations. Species, however, differed in their response. Intrapopulation variation in Milium was consistently positively affected by higher mean temperatures and precipitation as well as by more fertile local soil conditions, suggesting that more productive conditions may select for larger phenotypic variation. In Stachys, particularly light availability positively influenced trait variation, whereas local soil conditions had no consistent effects. Generally, our study emphasises that intra-population variation may differ considerably across larger scales-due to phenotypic plasticity and/or underlying genetic diversity-possibly affecting species response to global environmental change.
Gene flow is an important factor determining the evolution of a species, since it directly affects population structure and species’ adaptation. Here, we investigated population structure, population history, and migration among populations covering the entire distribution of the geographically isolated South-West European common lizard (Zootoca vivipara louislantzi) using 34 newly developed polymorphic microsatellite markers. The analyses unravelled the presence of isolation by distance, inbreeding, recent bottlenecks, genetic differentiation, and low levels of migration among most populations, suggesting that Z. vivipara louislantzi is threatened. The results point to discontinuous populations and are in line with physical barriers hindering longitudinal migration south to the central Pyrenean cordillera and latitudinal migration in the central Pyrenees. In contrast, evidence for longitudinal migration exists from the lowlands north to the central Pyrenean cordillera and the Cantabrian Mountains. The locations of the populations south to the central Pyrenean cordillera were identified as the first to be affected by global warming; thus, management actions aimed at avoiding population declines should start in this area.
P>Despite ample research, understanding plant spread and predicting their ability to track projected climate changes remain a formidable challenge to be confronted. We modelled the spread of North American wind-dispersed trees in current and future (c. 2060) conditions, accounting for variation in 10 key dispersal, demographic and environmental factors affecting population spread. Predicted spread rates vary substantially among 12 study species, primarily due to inter-specific variation in maturation age, fecundity and seed terminal velocity. Future spread is predicted to be faster if atmospheric CO2 enrichment would increase fecundity and advance maturation, irrespective of the projected changes in mean surface windspeed. Yet, for only a few species, predicted wind-driven spread will match future climate changes, conditioned on seed abscission occurring only in strong winds and environmental conditions favouring high survival of the farthest-dispersed seeds. Because such conditions are unlikely, North American wind-dispersed trees are expected to lag behind the projected climate range shift.