Institut für Geoökologie
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Institute
The functioning of the surface water-groundwater interface as buffer, filter and reactive zone is important for water quality, ecological health and resilience of streams and riparian ecosystems. Solute and heat exchange across this interface is driven by the advection of water. Characterizing the flow conditions in the streambed is challenging as flow patterns are often complex and multidimensional, driven by surface hydraulic gradients and groundwater discharge. This thesis presents the results of an integrated approach of studies, ranging from the acquisition of field data, the development of analytical and numerical approaches to analyse vertical temperature profiles to the detailed, fully-integrated 3D numerical modelling of water and heat flux at the reach scale. All techniques were applied in order to characterize exchange flux between stream and groundwater, hyporheic flow paths and temperature patterns.
The study was conducted at a reach-scale section of the lowland Selke River, characterized by distinctive pool riffle sequences and fluvial islands and gravel bars. Continuous time series of hydraulic heads and temperatures were measured at different depths in the river bank, the hyporheic zone and within the river. The analyses of the measured diurnal temperature variation in riverbed sediments provided detailed information about the exchange flux between river and groundwater. Beyond the one-dimensional vertical water flow in the riverbed sediment, hyporheic and parafluvial flow patterns were identified. Subsurface flow direction and magnitude around fluvial islands and gravel bars at the study site strongly depended on the position around the geomorphological structures and on the river stage. Horizontal water flux in the streambed substantially impacted temperature patterns in the streambed. At locations with substantial horizontal fluxes the penetration depths of daily temperature fluctuations was reduced in comparison to purely vertical exchange conditions.
The calibrated and validated 3D fully-integrated model of reach-scale water and heat fluxes across the river-groundwater interface was able to accurately represent the real system. The magnitude and variations of the simulated temperatures matched the observed ones, with an average mean absolute error of 0.7 °C and an average Nash Sutcliffe Efficiency of 0.87. The simulation results showed that the water and heat exchange at the surface water-groundwater interface is highly variable in space and time with zones of daily temperature oscillations penetrating deep into the sediment and spots of daily constant temperature following the average groundwater temperature. The average hyporheic flow path temperature was found to strongly correlate with the flow path residence time (flow path length) and the temperature gradient between river and groundwater. Despite the complexity of these processes, the simulation results allowed the derivation of a general empirical relationship between the hyporheic residence times and temperature patterns. The presented results improve our understanding of the complex spatial and temporal dynamics of water flux and thermal processes within the shallow streambed. Understanding these links provides a general basis from which to assess hyporheic temperature conditions in river reaches.
The sustainability of agro-bioenergy systems is dependent on many factors, some local or regional in implementation, some others global in nature. This study assessed the effects of often ignored local and regional factors (e.g. alternative agronomic factor options, alternative agricultural production systems, alternative biomass flows, alternative conversion technologies etc. The results from this study suggests that key to enhancing the energy efficiency (and by extension the sustainability) of agro-bioenergy systems is paying attention to local and regional factors such as biomass conversion technology, alternative agronomic factor options, alternative agricultural production systems and available biomass flows.
Understanding the distribution of species is fundamental for biodiversity conservation, ecosystem management, and increasingly also for climate impact assessment. The presence of a species in a given site depends on physiological limitations (abiotic factors), interactions with other species (biotic factors), migratory or dispersal processes (site accessibility) as well as the continuing
effects of past events, e.g. disturbances (site legacy). Existing approaches to predict species distributions either (i) correlate observed species occurrences with environmental variables describing abiotic limitations, thus ignoring biotic interactions, dispersal and legacy effects (statistical species distribution model, SDM); or (ii) mechanistically model the variety of processes determining species distributions (process-based model, PBM). SDMs are widely used due to their easy applicability and ability to handle varied data qualities. But they fail to reproduce the dynamic response of species distributions to changing conditions. PBMs are expected to be superior in this respect, but they need very specific data unavailable for many species, and are often more complex and require more computational effort. More recently, hybrid models link the two approaches to combine their respective strengths.
In this thesis, I apply and compare statistical and process-based approaches to predict species distributions, and I discuss their respective limitations, specifically for applications in changing environments. Detailed analyses of SDMs for boreal tree species in Finland reveal that nonclimatic predictors - edaphic properties and biotic interactions - are important limitations at the treeline, contesting the assumption of unrestricted, climatically induced range expansion. While the estimated SDMs are successful within their training data range, spatial and temporal model transfer fails. Mapping and comparing sampled predictor space among data subsets identifies spurious extrapolation as the plausible explanation for limited model transferability. Using these findings, I analyze the limited success of an established PBM (LPJ-GUESS) applied to the same problem. Examination of process representation and parameterization in the PBM identifies implemented processes to adjust (competition between species, disturbance) and missing processes that are crucial in boreal forests (nutrient limitation, forest management). Based on climatic correlations shifting over time, I stress the restricted temporal transferability of bioclimatic limits used in LPJ-GUESS and similar PBMs. By critically assessing the performance of SDM and PBM in this application, I demonstrate the importance of understanding the limitations of the
applied methods.
As a potential solution, I add a novel approach to the repertoire of existing hybrid models. By simulation experiments with an individual-based PBM which reproduces community dynamics resulting from biotic factors, dispersal and legacy effects, I assess the resilience of coastal vegetation to abrupt hydrological changes. According to the results of the resilience analysis, I then modify temporal SDM predictions, thereby transferring relevant process detail from PBM to
SDM. The direction of knowledge transfer from PBM to SDM avoids disadvantages of current hybrid models and increases the applicability of the resulting model in long-term, large-scale applications. A further advantage of the proposed framework is its flexibility, as it is readily extended to other model types, disturbance definitions and response characteristics.
Concluding, I argue that we already have a diverse range of promising modelling tools at hand, which can be refined further. But most importantly, they need to be applied more thoughtfully. Bearing their limitations in mind, combining their strengths and openly reporting underlying assumptions and uncertainties is the way forward.