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The sensitivity of fluvial systems to tectonic and climatic boundary conditions allows us to use the geomorphic and stratigraphic records as quantitative archives of past climatic and tectonic conditions. Thus, fluvial terraces that form on alluvial fans and floodplains as well as the rate of sediment export to oceanic and continental basins are commonly used to reconstruct paleoenvironments. However, we currently lack a systematic and quantitative understanding of the transient evolution of fluvial systems and their associated sediment storage and release in response to changes in base level, water input, and sediment input. Such knowledge is necessary to quantify past environmental change from terrace records or sedimentary deposits and to disentangle the multiple possible causes for terrace formation and sediment deposition. Here, we use a set of seven physical experiments to explore terrace formation and sediment export from a single, braided channel that is perturbed by changes in upstream water discharge or sediment supply, or through downstream base-level fall. Each perturbation differently affects (1) the geometry of terraces and channels, (2) the timing of terrace cutting, and (3) the transient response of sediment export from the basin. In general, an increase in water discharge leads to near-instantaneous channel incision across the entire fluvial system and consequent local terrace cutting, thus preserving the initial channel slope on terrace surfaces, and it also produces a transient increase in sediment export from the system. In contrast, a decreased upstream sediment-supply rate may result in longer lag times before terrace cutting, leading to terrace slopes that differ from the initial channel slope, and also lagged responses in sediment export. Finally, downstream base-level fall triggers the upstream propagation of a diffuse knickzone, forming terraces with upstream-decreasing ages. The slope of terraces triggered by base-level fall mimics that of the newly adjusted active channel, whereas slopes of terraces triggered by a decrease in upstream sediment discharge or an increase in upstream water discharge are steeper compared to the new equilibrium channel. By combining fillterrace records with constraints on sediment export, we can distinguish among environmental perturbations that would otherwise remain unresolved when using just one of these records.
The sensitivity of fluvial systems to tectonic and climatic boundary conditions allows us to use the geomorphic and stratigraphic records as quantitative archives of past climatic and tectonic conditions. Thus, fluvial terraces that form on alluvial fans and floodplains as well as the rate of sediment export to oceanic and continental basins are commonly used to reconstruct paleoenvironments. However, we currently lack a systematic and quantitative understanding of the transient evolution of fluvial systems and their associated sediment storage and release in response to changes in base level, water input, and sediment input. Such knowledge is necessary to quantify past environmental change from terrace records or sedimentary deposits and to disentangle the multiple possible causes for terrace formation and sediment deposition. Here, we use a set of seven physical experiments to explore terrace formation and sediment export from a single, braided channel that is perturbed by changes in upstream water discharge or sediment supply, or through downstream base-level fall. Each perturbation differently affects (1) the geometry of terraces and channels, (2) the timing of terrace cutting, and (3) the transient response of sediment export from the basin. In general, an increase in water discharge leads to near-instantaneous channel incision across the entire fluvial system and consequent local terrace cutting, thus preserving the initial channel slope on terrace surfaces, and it also produces a transient increase in sediment export from the system. In contrast, a decreased upstream sediment-supply rate may result in longer lag times before terrace cutting, leading to terrace slopes that differ from the initial channel slope, and also lagged responses in sediment export. Finally, downstream base-level fall triggers the upstream propagation of a diffuse knickzone, forming terraces with upstream-decreasing ages. The slope of terraces triggered by base-level fall mimics that of the newly adjusted active channel, whereas slopes of terraces triggered by a decrease in upstream sediment discharge or an increase in upstream water discharge are steeper compared to the new equilibrium channel. By combining fillterrace records with constraints on sediment export, we can distinguish among environmental perturbations that would otherwise remain unresolved when using just one of these records.
Volcano dome deformation processes analysed with high resolution InSAR and camera-based techniques
(2017)
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.
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 relationship between climate and forest productivity is an intensively studied subject in forest science. This Thesis is embedded within the general framework of future forest growth under climate change and its implications for the ongoing forest conversion. My objective is to investigate the future forest productivity at different spatial scales (from a single specific forest stand to aggregated information across Germany) with focus on oak-pine forests in the federal state of Brandenburg. The overarching question is: how are the oak-pine forests affected by climate change described by a variety of climate scenarios. I answer this question by using a model based analysis of tree growth processes and responses to different climate scenarios with emphasis on drought events. In addition, a method is developed which considers climate change uncertainty of forest management planning.
As a first 'screening' of climate change impacts on forest productivity, I calculated the change in net primary production on the base of a large set of climate scenarios for different tree species and the total area of Germany. Temperature increases up to 3 K lead to positive effects on the net primary production of all selected tree species. But, in water-limited regions this positive net primary production trend is dependent on the length of drought periods which results in a larger uncertainty regarding future forest productivity. One of the regions with the highest uncertainty of net primary production development is the federal state of Brandenburg.
To enhance the understanding and ability of model based analysis of tree growth sensitivity to drought stress two water uptake approaches in pure pine and mixed oak-pine stands are contrasted. The first water uptake approach consists of an empirical function for root water uptake. The second approach is more mechanistic and calculates the differences of soil water potential along a soil-plant-atmosphere continuum. I assumed the total root resistance to vary at low, medium and high total root resistance levels. For validation purposes three data sets on different tree growth relevant time scales are used. Results show that, except the mechanistic water uptake approach with high total root resistance, all transpiration outputs exceeded observed values. On the other hand high transpiration led to a better match of observed soil water content. The strongest correlation between simulated and observed annual tree ring width occurred with the mechanistic water uptake approach and high total root resistance. The findings highlight the importance of severe drought as a main reason for small diameter increment, best supported by the mechanistic water uptake approach with high root resistance. However, if all aspects of the data sets are considered no approach can be judged superior to the other. I conclude that the uncertainty of future productivity of water-limited forest ecosystems under changing environmental conditions is linked to simulated root water uptake.
Finally my study aimed at the impacts of climate change combined with management scenarios on an oak-pine forest to evaluate growth, biomass and the amount of harvested timber. The pine and the oak trees are 104 and 9 years old respectively. Three different management scenarios with different thinning intensities and different climate scenarios are used to simulate the performance of management strategies which explicitly account for the risks associated with achieving three predefined objectives (maximum carbon storage, maximum harvested timber, intermediate). I found out that in most cases there is no general management strategy which fits best to different objectives. The analysis of variance in the growth related model outputs showed an increase of climate uncertainty with increasing climate warming. Interestingly, the increase of climate-induced uncertainty is much higher from 2 to 3 K than from 0 to 2 K.
Fluxes of organic and inorganic carbon within the Amazon basin are considerably controlled by annual flooding, which triggers the export of terrigenous organic material to the river and ultimately to the Atlantic Ocean. The amount of carbon imported to the river and the further conversion, transport and export of it depend on temperature, atmospheric CO2, terrestrial productivity and carbon storage, as well as discharge. Both terrestrial productivity and discharge are influenced by climate and land use change. The coupled LPJmL and RivCM model system (Langerwisch et al., 2016) has been applied to assess the combined impacts of climate and land use change on the Amazon riverine carbon dynamics. Vegetation dynamics (in LPJmL) as well as export and conversion of terrigenous carbon to and within the river (RivCM) are included. The model system has been applied for the years 1901 to 2099 under two deforestation scenarios and with climate forcing of three SRES emission scenarios, each for five climate models. We find that high deforestation (business-as-usual scenario) will strongly decrease (locally by up to 90 %) riverine particulate and dissolved organic carbon amount until the end of the current century. At the same time, increase in discharge leaves net carbon transport during the first decades of the century roughly unchanged only if a sufficient area is still forested. After 2050 the amount of transported carbon will decrease drastically. In contrast to that, increased temperature and atmospheric CO2 concentration determine the amount of riverine inorganic carbon stored in the Amazon basin. Higher atmospheric CO2 concentrations increase riverine inorganic carbon amount by up to 20% (SRES A2). The changes in riverine carbon fluxes have direct effects on carbon export, either to the atmosphere via outgassing or to the Atlantic Ocean via discharge. The outgassed carbon will increase slightly in the Amazon basin, but can be regionally reduced by up to 60% due to deforestation. The discharge of organic carbon to the ocean will be reduced by about 40% under the most severe deforestation and climate change scenario. These changes would have local and regional consequences on the carbon balance and habitat characteristics in the Amazon basin itself as well as in the adjacent Atlantic Ocean.
Peak oil is forcing our society to shift from fossil to renewable resources. However, such renewable resources are also scarce, and they too must be used in the most efficient and sustainable way possible. Biorefining is a concept that represents both resource efficiency and sustainability. This approach initiates a cascade use, which means food and feed production before material use, and an energy-related use at the end of the value-added chain. However, sustainability should already start in the fields, on the agricultural side, where the industrially-used biomass is produced. Therefore, the aim of my doctoral thesis is to analyse the sustainable feedstock supply for biorefineries. In contrast to most studies on biorefineries, I focus on the sustainable provision of feedstock and not on the bioengineering processing of whatever feedstock is available.
Grasslands provide a high biomass potential. They are often inefficiently used, so a new utilisation concept based on the biorefining approach can increase the added value from grasslands. Fodder legumes from temporary and permanent grasslands were chosen for this study. Previous research shows that they are a promising feedstock for industrial uses, and their positive environmental impact is an important byproduct to promote sustainable agricultural production systems.
Green Biorefineries are a class of biorefineries that use fresh green biomass, such as grasses or fodder legumes, as feedstock. After fractionation, an organic solution (press juice) forms; this is used for the production of organic acids, chemicals and extracts, as well as fertilisers. A fibre component (press cake) is also created to produce feed, biomaterials and biogas. This thesis examines a specific value chain, using alfalfa and clover/grass as feedstock and generating lactic acid and one type of cattle feed from it. The research question is if biomass production needs to be adapted for the utilisation of fodder legumes in the Green Biorefinery approach. I have attempted to give a holistic analysis of cultivation, processing and utilisation of two specific grassland crops. Field trials with alfalfa and clover/grass at different study sites were carried out to obtain information on biomass quality and quantity depending on the crop, study site and harvest time. The fresh biomass was fractionated with a screw press and the composition of press juices and cakes was analysed. Fermentation experiments took place to determine the usability of press juices for lactic acid production. The harvest time is not of high importance for the quality of press juices as a fermentation medium. For permanent grasslands, late cuts, often needed for reasons of nature conservation, are possible without a major influence on feedstock quality. The press cakes were silaged for feed-value determination.
Following evidence that both intermediate products are suitable feedstocks in the Green Biorefinery approach, I developed a cost-benefit analysis, comparing different production scenarios on a farm. Two standard crop rotations for Brandenburg, producing either only market crops or market crops and fodder legumes for ruminant feed production, were compared to a system that uses the cultivated fodder legumes for the Green Biorefinery value chain instead of only feed production. Timely processing of the raw material is important to maintain quality for industrial uses, so on-site processing at the farm is assumed in Green Biorefinery scenario. As a result, more added value stays in the rural area. Two farm sizes, common for many European regions, were chosen to examine the influence of scale. The cost site of farmers has also been analysed in detail to assess which farm characteristics make production of press juices for biochemical industries viable. Results show that for large farm sizes in particular, the potential profits are high. Additionally, the wider spectrum of marketable products generates new sources of income for farmers.
The holistic analysis of the supply chain provides evidence that the cultivation processes for fodder legumes do not need to be adapted for use in Green Biorefineries. In fact, the new utilisation approach even widens the cultivation and processing spectrum and can increase economic viability of fodder legume production in conventional farming.
The sea level rise induced intensification of coastal floods is a serious threat to many regions in proximity to the ocean. Although severe flood events are rare they can entail enormous damage costs, especially when built-up areas are inundated. Fortunately, the mean sea level advances slowly and there is enough time for society to adapt to the changing environment. Most commonly, this is achieved by the construction or reinforcement of flood defence measures such as dykes or sea walls but also land use and disaster management are widely discussed options. Overall, albeit the projection of sea level rise impacts and the elaboration of adequate response strategies is amongst the most prominent topics in climate impact research, global damage estimates are vague and mostly rely on the same assessment models. The thesis at hand contributes to this issue by presenting a distinctive approach which facilitates large scale assessments as well as the comparability of results across regions. Moreover, we aim to improve the general understanding of the interplay between mean sea level rise, adaptation, and coastal flood damage.
Our undertaking is based on two basic building blocks. Firstly, we make use of macroscopic flood-damage functions, i.e. damage functions that provide the total monetary damage within a delineated region (e.g. a city) caused by a flood of certain magnitude. After introducing a systematic methodology for the automatised derivation of such functions, we apply it to a total of 140 European cities and obtain a large set of damage curves utilisable for individual as well as comparative damage assessments. By scrutinising the resulting curves, we are further able to characterise the slope of the damage functions by means of a functional model. The proposed function has in general a sigmoidal shape but exhibits a power law increase for the relevant range of flood levels and we detect an average exponent of 3.4 for the considered cities. This finding represents an essential input for subsequent elaborations on the general interrelations of involved quantities.
The second basic element of this work is extreme value theory which is employed to characterise the occurrence of flood events and in conjunction with a damage function provides the probability distribution of the annual damage in the area under study. The resulting approach is highly flexible as it assumes non-stationarity in all relevant parameters and can be easily applied to arbitrary regions, sea level, and adaptation scenarios. For instance, we find a doubling of expected flood damage in the city of Copenhagen for a rise in mean sea levels of only 11 cm. By following more general considerations, we succeed in deducing surprisingly simple functional expressions to describe the damage behaviour in a given region for varying mean sea levels, changing storm intensities, and supposed protection levels. We are thus able to project future flood damage by means of a reduced set of parameters, namely the aforementioned damage function exponent and the extreme value parameters. Similar examinations are carried out to quantify the aleatory uncertainty involved in these projections. In this regard, a decrease of (relative) uncertainty with rising mean sea levels is detected. Beyond that, we demonstrate how potential adaptation measures can be assessed in terms of a Cost-Benefit Analysis. This is exemplified by the Danish case study of Kalundborg, where amortisation times for a planned investment are estimated for several sea level scenarios and discount rates.
Anthropogenic activities have transformed the Earth's environment, not only on local level, but on the planetary-scale causing global change. Besides industrialization, agriculture is a major driver of global change. This change in turn impairs the agriculture sector, reducing crop yields namely due to soil degradation, water scarcity, and climate change. However, this is a more complex issue than it appears. Crop yields can be increased by use of agrochemicals and fertilizers which are mainly produced by fossil energy. This is important to meet the increasing food demand driven by global demographic change, which is further accelerated by changes in regional lifestyles. In this dissertation, we attempt to address this complex problem exploring agricultural potential globally but on a local scale. For this, we considered the influence of lifestyle changes (dietary patterns) as well as technological progress and their effects on climate change, mainly greenhouse gas (GHG) emissions. Furthermore, we examined options for optimizing crop yields in the current cultivated land with the current cropping patterns by closing yield gaps. Using this, we investigated in a five-minute resolution the extent to which food demand can be met locally, and/or by regional and/or global trade. Globally, food consumption habits are shifting towards calorie rich diets. Due to dietary shifts combined with population growth, the global food demand is expected to increase by 60-110% between 2005 and 2050. Hence, one of the challenges to global sustainability is to meet the growing food demand, while at the same time, reducing agricultural inputs and environmental consequences. In order to address the above problem, we used several freely available datasets and applied multiple interconnected analytical approaches that include artificial neural network, scenario analysis, data aggregation and harmonization, downscaling algorithm, and cross-scale analysis.
Globally, we identified sixteen dietary patterns between 1961 and 2007 with food intakes ranging from 1,870 to 3,400 kcal/cap/day. These dietary patterns also reflected changing dietary habits to meat rich diets worldwide. Due to the large share of animal products, very high calorie diets that are common in the developed world, exhibit high total per capita emissions of 3.7-6.1 kg CO2eq./day. This is higher than total per capita emissions of 1.4-4.5 kg CO2eq./day associated with low and moderate calorie diets that are common in developing countries. Currently, 40% of the global crop calories are fed to livestock and the feed calorie use is four times the produced animal calories. However, these values vary from less than 1 kcal to greater 10 kcal around the world. On the local and national scale, we found that the local and national food production could meet demand of 1.9 and 4.4 billion people in 2000, respectively. However, 1 billion people from Asia and Africa require intercontinental agricultural trade to meet their food demand. Nevertheless, these regions can become food self-sufficient by closing yield gaps that require location specific inputs and agricultural management strategies. Such strategies include: fertilizers, pesticides, soil and land improvement, management targeted on mitigating climate induced yield variability, and improving market accessibility. However, closing yield gaps in particular requires global N-fertilizer application to increase by 45-73%, P2O5 by 22-46%, and K2O by 2-3 times compare to 2010. Considering population growth, we found that the global agricultural GHG emissions will approach 7 Gt CO2eq./yr by 2050, while the global livestock feed demand will remain similar to 2000. This changes tremendously when diet shifts are also taken into account, resulting in GHG emissions of 20 Gt CO2eq./yr and an increase of 1.3 times in the crop-based feed demand between 2000 and 2050. However, when population growth, diet shifts, and technological progress by 2050 were considered, GHG emissions can be reduced to 14 Gt CO2eq./yr and the feed demand to nearly 1.8 times compare to that in 2000. Additionally, our findings shows that based on the progress made in closing yield gaps, the number of people depending on international trade can vary between 1.5 and 6 billion by 2050. In medium term, this requires additional fossil energy. Furthermore, climate change, affecting crop yields, will increase the need for international agricultural trade by 4% to 16%.
In summary, three general conclusions are drawn from this dissertation. First, changing dietary patterns will significantly increase crop demand, agricultural GHG emissions, and international food trade in the future when compared to population growth only. Second, such increments can be reduced by technology transfer and technological progress that will enhance crop yields, decrease agricultural emission intensities, and increase livestock feed conversion efficiencies. Moreover, international trade dependency can be lowered by consuming local and regional food products, by producing diverse types of food, and by closing yield gaps. Third, location specific inputs and management options are required to close yield gaps. Sustainability of such inputs and management largely depends on which options are chosen and how they are implemented. However, while every cultivated land may not need to attain its potential yields to enable food security, closing yield gaps only may not be enough to achieve food self-sufficiency in some regions. Hence, a combination of sustainable implementations of agricultural intensification, expansion, and trade as well as shifting dietary habits towards a lower share of animal products is required to feed the growing population.
Water resources from Central Asia’s mountain regions have a high relevance for the water supply of the water scarce lowlands. A good understanding of the water cycle in these mountain regions is therefore needed to develop water management strategies. Hydrological modeling helps to improve our knowledge of the regional water cycle, and it can be used to gain a better understanding of past changes or estimate future hydrologic changes in view of projected changes in climate. However, due to the scarcity of hydrometeorological data, hydrological modeling for mountain regions in Central Asia involves large uncertainties.
Addressing this problem, the first aim of this thesis was to develop hydrological modeling approaches that can increase the credibility of hydrological models in data sparse mountain regions. This was achieved by using additional data from remote sensing and atmospheric modeling. It was investigated whether spatial patterns from downscaled reanalysis data can be used for the interpolation of station-based precipitation data. This approach was compared to other precipitation estimates using a hydrologic evaluation based on hydrological modeling and a comparison of simulated and observed discharge, which demonstrated a generally good performance of this method. The study further investigated the value of satellite-derived snow cover data for model calibration. Trade-offs of good model performance in terms of discharge and snow cover were explicitly evaluated using a multiobjective optimization algorithm, and the results were contrasted with single-objective calibration and Monte Carlo simulations. The study clearly shows that the additional use of snow cover data improved the internal consistency of the hydrological model. In this context, it was further investigated for the first time how many snow cover scenes were required for hydrological model calibration.
The second aim of this thesis was the application of the hydrological model in order to investigate the causes of observed streamflow increases in two headwater catchments of the Tarim River over the recent decades. This simulation-based approach for trend attribution was complemented by a data-based approach. The hydrological model was calibrated to discharge and glacier mass balance data and considered changes in glacier geometry over time. The results show that in the catchment with a lower glacierization, increasing precipitation and temperature both contributed to the streamflow increases, while in the catchment with a stronger glacierization, increasing temperatures were identified as the dominant driver.
One challenging question in ecology is to explain species coexistence in highly diverse temperate grassland plant communities. Within this context, a clear understanding of the consequences of belowground herbivory for the composition and the diversity of plant communities continue to elude ecologists. The existing body of empirical evidence reveals partly contradictory responses ranging from negative to neutral or positive effects of belowground herbivory on grassland diversity.
To reveal possible mechanistic grounds for these discrepancies, we extended an existing simulation model of grassland communities based on plant functional types to include root herbivory. This enabled us to test the effects of different feeding modes that represent different herbivore guilds. For each belowground feeding mode, we systematically varied the intensity and frequency of herbivory events for three different levels of soil fertility both in the presence and absence of additional aboveground grazing.
Our modelling approach successfully reproduced various empirically reported diversity responses, merely on the basis of the different feeding modes. Different levels of plant resource availability affected the strength, but not the direction of the belowground herbivory effects. The only exception was the scenario with low resource levels, which promoted neutral (neither positive nor negative) diversity responses for some of the feeding modes. Interestingly, aboveground biomass production was largely unaffected by diversity changes induced by belowground herbivory except in the case of selective feeding modes that were related to specific functional traits.
Our findings provide possible explanations for the broad spectrum of belowground herbivory effects on plant community diversity. Furthermore, the presented theoretical modelling approach provides a suitable conceptual framework to better understand the complex linkage between plant community and belowground herbivory dynamics.
One of the major challenges related with the current practice in seismic hazard studies is the adjustment of empirical ground motion prediction equations (GMPEs) to different seismological environments. We believe that the key to accommodating differences in regional seismological attributes of a ground motion model lies in the Fourier spectrum. In the present study, we attempt to explore a new approach for the development of response spectral GMPEs, which is fully consistent with linear system theory when it comes to adjustment issues. This approach consists of developing empirical prediction equations for Fourier spectra and for a particular duration estimate of ground motion which is tuned to optimize the fit between response spectra obtained through the random vibration theory framework and the classical way. The presented analysis for the development of GMPEs is performed on the recently compiled reference database for seismic ground motion in Europe (RESORCE-2012). Although, the main motivation for the presented approach is the adjustability and the use of the corresponding model to generate data driven host-to-target conversions, even as a standalone response spectral model it compares reasonably well with the GMPEs of Ambraseys et al. (Bull Earthq Eng 3:1-53, 2005), Akkar and Bommer (Seismol Res Lett 81(2):195-206, 2010) and Akkar and Cagnan (Bull Seismol Soc Am 100(6):2978-2995, 2010).
We conducted a PUB (predictions in ungauged basins) experiment looking at hydrology and crop dynamics in the semi-arid rural Mod catchment in India. The experiment was motivated by the aims (a) to develop a coupled eco-hydrological model capable of analysing land-use strategies concerning crop water need, erosion protection, crop yield and resistivity against droughts and floods, and (b) to assess the feasibility of a strategy for collecting the necessary data in a data-scarce region. Our experiment combines parsimonious data assessment and eco-hydrological model coupling at the lower mesoscale. Linking bottom-up sampling of functionally representative soil classes and top-down regionalization based on spectral properties of the same resulted in a comprehensive distributed data basis for the model. A clear focus on the dominating processes and the catena as the organizing landscape element in the given environmental setting enabled this. We employed the WASA (Water Availability in Semi-Arid environments) model for uncalibrated process-based water balance modelling and integrated a crop simulation subroutine based on the SWAP (Soil Water Atmosphere Plant) model to account for crop dynamics, feedbacks and yield estimation. While we found the data assessment strategy and the hydrological model application largely feasible, in terms of its accounting for scale, processes and model concepts, the simulation of feedbacks with crops was problematic. Contributing to the PUB issue, more general conclusions are drawn concerning spatially-distributed structural information and uncalibrated modelling.
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Editor Z.W. Kundzewicz; Associate editor F. Hattermann
Large-scale floodplain sediment dynamics in the Mekong Delta : present state and future prospects
(2014)
The Mekong Delta (MD) sustains the livelihood and food security of millions of people in Vietnam and Cambodia. It is known as the “rice bowl” of South East Asia and has one of the world’s most productive fisheries. Sediment dynamics play a major role for the high productivity of agriculture and fishery in the delta. However, the MD is threatened by climate change, sea level rise and unsustainable development activities in the Mekong Basin. But despite its importance and the expected threats, the understanding of the present and future sediment dynamics in the MD is very limited. This is a consequence of its large extent, the intricate system of rivers, channels and floodplains and the scarcity of observations. Thus this thesis aimed at (1) the quantification of suspended sediment dynamics and associated sediment-nutrient deposition in floodplains of the MD, and (2) assessed the impacts of likely future boundary changes on the sediment dynamics in the MD. The applied methodology combines field experiments and numerical simulation to quantify and predict the sediment dynamics in the entire delta in a spatially explicit manner. The experimental part consists of a comprehensive procedure to monitor quantity and spatial variability of sediment and associated nutrient deposition for large and complex river floodplains, including an uncertainty analysis. The measurement campaign applied 450 sediment mat traps in 19 floodplains over the MD for a complete flood season. The data also supports quantification of nutrient deposition in floodplains based on laboratory analysis of nutrient fractions of trapped sedimentation.The main findings are that the distribution of grain size and nutrient fractions of suspended sediment are homogeneous over the Vietnamese floodplains. But the sediment deposition within and between ring dike floodplains shows very high spatial variability due to a high level of human inference. The experimental findings provide the essential data for setting up and calibration of a large-scale sediment transport model for the MD. For the simulation studies a large scale hydrodynamic model was developed in order to quantify large-scale floodplain sediment dynamics. The complex river-channel-floodplain system of the MD is described by a quasi-2D model linking a hydrodynamic and a cohesive sediment transport model. The floodplains are described as quasi-2D presentations linked to rivers and channels modeled in 1D by using control structures. The model setup, based on the experimental findings, ignored erosion and re-suspension processes due to a very high degree of human interference during the flood season. A two-stage calibration with six objective functions was developed in order to calibrate both the hydrodynamic and sediment transport modules. The objective functions include hydraulic and sediment transport parameters in main rivers, channels and floodplains. The model results show, for the first time, the tempo-spatial distribution of sediment and associated nutrient deposition rates in the whole MD. The patterns of sediment transport and deposition are quantified for different sub-systems. The main factors influencing spatial sediment dynamics are the network of rivers, channels and dike-rings, sluice gate operations, magnitude of the floods and tidal influences. The superposition of these factors leads to high spatial variability of the sediment transport and deposition, in particular in the Vietnamese floodplains. Depending on the flood magnitude, annual sediment loads reaching the coast vary from 48% to 60% of the sediment load at Kratie, the upper boundary of the MD. Deposited sediment varies from 19% to 23% of the annual load at Kratie in Cambodian floodplains, and from 1% to 6% in the compartmented and diked floodplains in Vietnam. Annual deposited nutrients (N, P, K), which are associated to the sediment deposition, provide on average more than 50% of mineral fertilizers typically applied for rice crops in non-flooded ring dike compartments in Vietnam. This large-scale quantification provides a basis for estimating the benefits of the annual Mekong floods for agriculture and fishery, for assessing the impacts of future changes on the delta system, and further studies on coastal deposition/erosion. For the estimation of future prospects a sensitivity-based approach is applied to assess the response of floodplain hydraulics and sediment dynamics to the changes in the delta boundaries including hydropower development, climate change in the Mekong River Basin and effective sea level rise. The developed sediment model is used to simulate the mean sediment transport and sediment deposition in the whole delta system for the baseline (2000-2010) and future (2050-2060) periods. For each driver we derive a plausible range of future changes and discretize it into five levels, resulting in altogether 216 possible factor combinations. Our results thus cover all plausible future pathways of sediment dynamics in the delta based on current knowledge. The uncertainty of the range of the resulting impacts can be decreased in case more information on these drivers becomes available. Our results indicate that the hydropower development dominates the changes in sediment dynamics of the Mekong Delta, while sea level rise has the smallest effect. The floodplains of Vietnamese Mekong Delta are much more sensitive to the changes compared to the other subsystems of the delta. In terms of median changes of the three combined drivers, the inundation extent is predicted to increase slightly, but the overall floodplain sedimentation would be reduced by approximately 40%, while the sediment load to the Sea would diminish to half of the current rates. These findings provide new and valuable information on the possible impacts of future development on the delta, and indicate the most vulnerable areas. Thus, the presented results are a significant contribution to the ongoing international discussion on the hydropower development in the Mekong basin and its impact on the Mekong delta.
Permafrost, defined as ground that is frozen for at least two consecutive years, is a distinct feature of the terrestrial unglaciated Arctic. It covers approximately one quarter of the land area of the Northern Hemisphere (23,000,000 km²). Arctic landscapes, especially those underlain by permafrost, are threatened by climate warming and may degrade in different ways, including active layer deepening, thermal erosion, and development of rapid thaw features. In Siberian and Alaskan late Pleistocene ice-rich Yedoma permafrost, rapid and deep thaw processes (called thermokarst) can mobilize deep organic carbon (below 3 m depth) by surface subsidence due to loss of ground ice. Increased permafrost thaw could cause a feedback loop of global significance if its stored frozen organic carbon is reintroduced into the active carbon cycle as greenhouse gases, which accelerate warming and inducing more permafrost thaw and carbon release. To assess this concern, the major objective of the thesis was to enhance the understanding of the origin of Yedoma as well as to assess the associated organic carbon pool size and carbon quality (concerning degradability). The key research questions were:
- How did Yedoma deposits accumulate?
- How much organic carbon is stored in the Yedoma region?
- What is the susceptibility of the Yedoma region's carbon for future decomposition?
To address these three research questions, an interdisciplinary approach, including detailed field studies and sampling in Siberia and Alaska as well as methods of sedimentology, organic biogeochemistry, remote sensing, statistical analyses, and computational modeling were applied. To provide a panarctic context, this thesis additionally includes results both from a newly compiled northern circumpolar carbon database and from a model assessment of carbon fluxes in a warming Arctic.
The Yedoma samples show a homogeneous grain-size composition. All samples were poorly sorted with a multi-modal grain-size distribution, indicating various (re-) transport processes. This contradicts the popular pure loess deposition hypothesis for the origin of Yedoma permafrost. The absence of large-scale grinding processes via glaciers and ice sheets in northeast Siberian lowlands, processes which are necessary to create loess as material source, suggests the polygenetic origin of Yedoma deposits.
Based on the largest available data set of the key parameters, including organic carbon content, bulk density, ground ice content, and deposit volume (thickness and coverage) from Siberian and Alaskan study sites, this thesis further shows that deep frozen organic carbon in the Yedoma region consists of two distinct major reservoirs, Yedoma deposits and thermokarst deposits (formed in thaw-lake basins). Yedoma deposits contain ~80 Gt and thermokarst deposits ~130 Gt organic carbon, or a total of ~210 Gt. Depending on the approach used for calculating uncertainty, the range for the total Yedoma region carbon store is ±75 % and ±20 % for conservative single and multiple bootstrapping calculations, respectively. Despite the fact that these findings reduce the Yedoma region carbon pool by nearly a factor of two compared to previous estimates, this frozen organic carbon is still capable of inducing a permafrost carbon feedback to climate warming. The complete northern circumpolar permafrost region contains between 1100 and 1500 Gt organic carbon, of which ~60 % is perennially frozen and decoupled from the short-term carbon cycle.
When thawed and reintroduced into the active carbon cycle, the organic matter qualities become relevant. Furthermore, results from investigations into Yedoma and thermokarst organic matter quality studies showed that Yedoma and thermokarst organic matter exhibit no depth-dependent quality trend. This is evidence that after freezing, the ancient organic matter is preserved in a state of constant quality. The applied alkane and fatty-acid-based biomarker proxies including the carbon-preference and the higher-land-plant-fatty-acid indices show a broad range of organic matter quality and thus no significantly different qualities of the organic matter stored in thermokarst deposits compared to Yedoma deposits. This lack of quality differences shows that the organic matter biodegradability depends on different decomposition trajectories and the previous decomposition/incorporation history. Finally, the fate of the organic matter has been assessed by implementing deep carbon pools and thermokarst processes in a permafrost carbon model. Under various warming scenarios for the northern circumpolar permafrost region, model results show a carbon release from permafrost regions of up to ~140 Gt and ~310 Gt by the years 2100 and 2300, respectively. The additional warming caused by the carbon release from newly-thawed permafrost contributes 0.03 to 0.14°C by the year 2100. The model simulations predict that a further increase by the 23rd century will add 0.4°C to global mean surface air temperatures.
In conclusion, Yedoma deposit formation during the late Pleistocene was dominated by water-related (alluvial/fluvial/lacustrine) as well as aeolian processes under periglacial conditions. The circumarctic permafrost region, including the Yedoma region, contains a substantial amount of currently frozen organic carbon. The carbon of the Yedoma region is well-preserved and therefore available for decomposition after thaw. A missing quality-depth trend shows that permafrost preserves the quality of ancient organic matter. When the organic matter is mobilized by deep degradation processes, the northern permafrost region may add up to 0.4°C to the global warming by the year 2300.
This study follows up on a previous downscaling intercomparison for present climate. Using a larger set of eight methods the authors downscale atmospheric fields representing present (1981-2000) and future (2046-65) conditions, as simulated by six global climate models following three emission scenarios. Local extremes were studied at 20 locations in British Columbia as measured by the same set of 27 indices, ClimDEX, as in the precursor study. Present and future simulations give 2 x 3 x 6 x 8 x 20 x 27 = 155 520 index climatologies whose analysis in terms of mean change and variation is the purpose of this study. The mean change generally reinforces what is to be expected in a warmer climate: that extreme cold events become less frequent and extreme warm events become more frequent, and that there are signs of more frequent precipitation extremes. There is considerable variation, however, about this tendency, caused by the influence of scenario, climate model, downscaling method, and location. This is analyzed using standard statistical techniques such as analysis of variance and multidimensional scaling, along with an assessment of the influence of each modeling component on the overall variation of the simulated change. It is found that downscaling generally has the strongest influence, followed by climate model; location and scenario have only a minor influence. The influence of downscaling could be traced back in part to various issues related to the methods, such as the quality of simulated variability or the dependence on predictors. Using only methods validated in the precursor study considerably reduced the influence of downscaling, underpinning the general need for method verification.
The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.
From 6 to 9 August 2012, intense rainfall hit the northern Philippines, causing massive floods in Metropolitan Manila and nearby regions. Local rain gauges recorded almost 1000mm within this period. However, the recently installed Philippine network of weather radars suggests that Metropolitan Manila might have escaped a potentially bigger flood just by a whisker, since the centre of mass of accumulated rainfall was located over Manila Bay. A shift of this centre by no more than 20 km could have resulted in a flood disaster far worse than what occurred during Typhoon Ketsana in September 2009.
Flood loss modeling is an important component within flood risk assessments. Traditionally, stage-damage functions are used for the estimation of direct monetary damage to buildings. Although it is known that such functions are governed by large uncertainties, they are commonly applied - even in different geographical regions - without further validation, mainly due to the lack of real damage data. Until now, little research has been done to investigate the applicability and transferability of such damage models to other regions. In this study, the last severe flood event in the Austrian Lech Valley in 2005 was simulated to test the performance of various damage functions from different geographical regions in Central Europe for the residential sector. In addition to common stage-damage curves, new functions were derived from empirical flood loss data collected in the aftermath of recent flood events in neighboring Germany. Furthermore, a multi-parameter flood loss model for the residential sector was adapted to the study area and also evaluated with official damage data. The analysis reveals that flood loss functions derived from related and more similar regions perform considerably better than those from more heterogeneous data sets of different regions and flood events. While former loss functions estimate the observed damage well, the latter overestimate the reported loss clearly. To illustrate the effect of model choice on the resulting uncertainty of damage estimates, the current flood risk for residential areas was calculated. In the case of extreme events like the 300 yr flood, for example, the range of losses to residential buildings between the highest and the lowest estimates amounts to a factor of 18, in contrast to properly validated models with a factor of 2.3. Even if the risk analysis is only performed for residential areas, our results reveal evidently that a carefree model transfer in other geographical regions might be critical. Therefore, we conclude that loss models should at least be selected or derived from related regions with similar flood and building characteristics, as far as no model validation is possible. To further increase the general reliability of flood loss assessment in the future, more loss data and more comprehensive loss data for model development and validation are needed.
Due to limited public budgets and the need to economize, the analysis of costs of hazard mitigation and emergency management of natural hazards becomes increasingly important for public natural hazard and risk management. In recent years there has been a growing body of literature on the estimation of losses which supported to help to determine benefits of measures in terms of prevented losses. On the contrary, the costs of mitigation are hardly addressed. This paper thus aims to shed some light on expenses for mitigation and emergency services. For this, we analysed the annual costs of mitigation efforts in four regions/countries of the Alpine Arc: Bavaria (Germany), Tyrol (Austria), South Tyrol (Italy) and Switzerland. On the basis of PPP values (purchasing power parities), annual expenses on public safety ranged from EUR 44 per capita in the Free State of Bavaria to EUR 216 in the Autonomous Province of South Tyrol. To analyse the (variable) costs for emergency services in case of an event, we used detailed data from the 2005 floods in the Federal State of Tyrol (Austria) as well as aggregated data from the 2002 floods in Germany. The analysis revealed that multi-hazards, the occurrence and intermixture of different natural hazard processes, contribute to increasing emergency costs. Based on these findings, research gaps and recommendations for costing Alpine natural hazards are discussed.
The impact of inclined faults on the hydrothermal field is assessed by adding simplified structural settings to synthetic models. This study is innovative in carrying out numerical simulations because it integrates the real 3-D nature of flow influenced by a fault in a porous medium, thereby providing a useful tool for complex geothermal modelling. The 3-D simulations for the coupled fluid flow and heat transport processes are based on the finite element method. In the model, one geological layer is dissected by a dipping fault. Sensitivity analyses are conducted to quantify the effects of the fault's transmissivity on the fluid flow and thermal field. Different fault models are compared with a model where no fault is present to evaluate the effect of varying fault transmissivity. The results show that faults have a significant impact on the hydrothermal field. Varying either the fault zone width or the fault permeability will result in relevant differences in the pressure, velocity and temperature field. A linear relationship between fault zone width and fluid velocity is found, indicating that velocities increase with decreasing widths. The faults act as preferential pathways for advective heat transport in case of highly transmissive faults, whereas almost no fluid may be transported through poorly transmissive faults.
The Alborz range of N Iran provides key information on the spatiotemporal evolution and characteristics of the Arabia-Eurasia continental collision zone. The southwestern Alborz range constitutes a transpressional duplex, which accommodates oblique shortening between Central Iran and the South Caspian Basin. The duplex comprises NW-striking frontal ramps that are kinematically linked to inherited E-W-striking, right-stepping lateral to obliquely oriented ramps. New zircon and apatite (U-Th)/He data provide a high-resolution framework to unravel the evolution of collisional tectonics in this region. Our data record two pulses of fast cooling associated with SW-directed thrusting across the frontal ramps at similar to 18-14 and 9.5-7.5 Ma, resulting in the tectonic repetition of a fossil zircon partial retention zone and a cooling pattern with a half U-shaped geometry. Uniform cooling ages of similar to 7-6 Ma along the southernmost E-W striking oblique ramp and across its associated NW-striking frontal ramps suggests that the ramp was reactivated as a master throughgoing, N-dipping thrust. We interpret this major change in fault kinematics and deformation style to be related to a change in the shortening direction from NE to N/NNE. The reduction in the obliquity of thrusting may indicate the termination of strike-slip faulting (and possibly thrusting) across the Iranian Plateau, which could have been triggered by an increase in elevation. Furthermore, we suggest that similar to 7-6-m.y.-old S-directed thrusting predated inception of the westward motion of the South Caspian Basin. Citation: Ballato, P., D. F. Stockli, M. R. Ghassemi, A. Landgraf, M. R. Strecker, J. Hassanzadeh, A. Friedrich, and S. H. Tabatabaei (2012), Accommodation of transpressional strain in the Arabia-Eurasia collision zone: new constraints from (U-Th)/He thermochronology in the Alborz mountains.
Large Central European flood events of the past have demonstrated that flooding can affect several river basins at the same time leading to catastrophic economic and humanitarian losses that can stretch emergency resources beyond planned levels of service. For Germany, the spatial coherence of flooding, the contributing processes and the role of trans-basin floods for a national risk assessment is largely unknown and analysis is limited by a lack of systematic data, information and knowledge on past events. This study investigates the frequency and intensity of trans-basin flood events in Germany. It evaluates the data and information basis on which knowledge about trans-basin floods can be generated in order to improve any future flood risk assessment. In particu-lar, the study assesses whether flood documentations and related reports can provide a valuable data source for understanding trans-basin floods. An adaptive algorithm was developed that systematically captures trans-basin floods using series of mean daily discharge at a large number of sites of even time series length (1952-2002). It identifies the simultaneous occurrence of flood peaks based on the exceedance of an initial threshold of a 10 year flood at one location and consecutively pools all causally related, spatially and temporally lagged peak recordings at the other locations. A weighted cumulative index was developed that accounts for the spatial extent and the individual flood magnitudes within an event and allows quantifying the overall event severity. The parameters of the method were tested in a sensitivity analysis. An intensive study on sources and ways of information dissemination of flood-relevant publications in Germany was conducted. Based on the method of systematic reviews a strategic search approach was developed to identify relevant documentations for each of the 40 strongest trans-basin flood events. A novel framework for assessing the quality of event specific flood reports from a user’s perspective was developed and validated by independent peers. The framework was designed to be generally applicable for any natural hazard type and assesses the quality of a document addressing accessibility as well as representational, contextual, and intrinsic dimensions of quality. The analysis of time-series of mean daily discharge resulted in the identification of 80 trans-basin flood events within the period 1952-2002 in Germany. The set is dominated by events that were recorded in the hydrological winter (64%); 36% occurred during the summer months. The occurrence of floods is characterised by a distinct clustering in time. Dividing the study period into two sub-periods, we find an increase in the percentage of winter events from 58% in the first to 70.5% in the second sub-period. Accordingly, we find a significant increase in the number of extreme trans-basin floods in the second sub-period. A large body of 186 flood relevant documentations was identified. For 87.5% of the 40 strongest trans-basin floods in Germany at least one report has been found and for the most severe floods a substantial amount of documentation could be obtained. 80% of the material can be considered grey literature (i.e. literature not controlled by commercial publishers). The results of the quality assessment show that the majority of flood event specific reports are of a good quality, i.e. they are well enough drafted, largely accurate and objective, and contain a substantial amount of information on the sources, pathways and receptors/consequences of the floods. The inclusion of this information in the process of knowledge building for flood risk assessment is recommended. Both the results as well as the data produced in this study are openly accessible and can be used for further research. The results of this study contribute to an improved spatial risk assessment in Germany. The identified set of trans-basin floods provides the basis for an assessment of the chance that flooding occurs simultaneously at a number of sites. The information obtained from flood event documentation can usefully supplement the analysis of the processes that govern flood risk.
Channel transmission losses in drylands take place normally in extensive alluvial channels or streambeds underlain by fractured rocks. They can play an important role in streamflow rates, groundwater recharge, freshwater supply and channel-associated ecosystems. We aim to develop a process-oriented, semi-distributed channel transmission losses model, using process formulations which are suitable for data-scarce dryland environments and applicable to both hydraulically disconnected losing streams and hydraulically connected losing(/gaining) streams. This approach should be able to cover a large variation in climate and hydro-geologic controls, which are typically found in dryland regions of the Earth. Our model was first evaluated for a losing/gaining, hydraulically connected 30 km reach of the Middle Jaguaribe River (MJR), Ceara, Brazil, which drains a catchment area of 20 000 km(2). Secondly, we applied it to a small losing, hydraulically disconnected 1.5 km channel reach in the Walnut Gulch Experimental Watershed (WGEW), Arizona, USA. The model was able to predict reliably the streamflow volume and peak for both case studies without using any parameter calibration procedure. We have shown that the evaluation of the hypotheses on the dominant hydrological processes was fundamental for reducing structural model uncertainties and improving the streamflow prediction. For instance, in the case of the large river reach (MJR), it was shown that both lateral stream-aquifer water fluxes and groundwater flow in the underlying alluvium parallel to the river course are necessary to predict streamflow volume and channel transmission losses, the former process being more relevant than the latter. Regarding model uncertainty, it was shown that the approaches, which were applied for the unsaturated zone processes (highly nonlinear with elaborate numerical solutions), are much more sensitive to parameter variability than those approaches which were used for the saturated zone (mathematically simple water budgeting in aquifer columns, including backwater effects). In case of the MJR-application, we have seen that structural uncertainties due to the limited knowledge of the subsurface saturated system interactions (i.e. groundwater coupling with channel water; possible groundwater flow parallel to the river) were more relevant than those related to the subsurface parameter variability. In case of the WEGW application we have seen that the non-linearity involved in the unsaturated flow processes in disconnected dryland river systems (controlled by the unsaturated zone) generally contain far more model uncertainties than do connected systems controlled by the saturated flow. Therefore, the degree of aridity of a dryland river may be an indicator of potential model uncertainty and subsequent attainable predictability of the system.
We generated medium-range forecasts of runoff for a 50 km(2) headwater catchment upstream of a reservoir using numerical weather predictions (NWPs) of the past as input to an operational hydrological model. NWP data originating from different sources were tested. For a period of 8.5 years, we computed daily forecasts with a lead time of +120 h based on an empirically downscaled version of the ECMWF's ensemble prediction system. For the last 3.5 years of the test period, we also tried the deterministic COSMO-EU forecast disseminated by the German Weather Service for lead times of up to +72 h. Common measures of skill indicate superiority of the ensemble runoff forecast over single-value forecasts for longer lead times. However, regardless of which NWP data were being used, the probability of event detection (POD) was found to be generally lower than 50%. In many cases, values in the range of 20-30% were obtained. At the same time, the false alarms ratio (FAR) was often found to be considerably high. The observed uncertainties in the hydrological forecasts were shown to originate from both the insufficient quality of precipitation forecasts as well as deficiencies in hydrological modeling and quantitative precipitation estimation. With respect to the anticipatory control of reservoirs in the studied catchment, the value of the tested runoff forecasts appears to be limited. This is due to the unfavorably low POD/FAR ratio in conjunction with a high cost-loss ratio. However, our results indicate that, in many cases, major runoff events related to snow melt can be successfully predicted as early as 4-5 days in advance.
Methane flux rates were measured on a loamy sand soil within perennial and annual energy crops in northeast Germany. The study was performed in closed chambers between 2003 and 2005 with four measurements per week. A mixed linear model including the fixed effects of year, rotation period, crop and fertilisation was applied to determine the influence of climatic factors and soil management on the CH4 flux. Soil water content and air temperature were added as co-variables. With the exception of air temperature, all fixed effects and the co-variable soil water content influenced the CH4 flux. The soil of annual crops consumed 6.1 mu g CH4 m(-2) h(-1), significantly more than the soil of perennial crops with 4.3 mu g CH4 m(-2) h(-1). It is suggested that soil water content plays the key role in CH4 flux between pedosphere and atmosphere. In the range of water contents between 5% and 15%, our model describes that a soil water content increase of 1% induces a net emission of 0.375 mu g CH4 m(-2) h(-1). As the soil of the experimental field was well-drained and aerobic, it represented a net sink for CH4 throughout the study period.
Küsten und Klimawandel in den Augen von Touristen : eine Wahrnehmungsanalyse an der deutschen Ostsee
(2011)
Aufgrund seiner wirtschaftlichen Bedeutung spielt der Tourismus in Mecklenburg-Vorpommern eine große Rolle. Insbesondere die Küstengebiete sind beliebte Reiseziele. In den letzten Jahren konnte ein kontinuierlicher Anstieg der Ankünfte und Übernachtungen verzeichnet werden. Neben anderen Faktoren werden die regionalen Auswirkungen des Klimawandels jedoch in Zukunft eine Herausforderung für den Tourismussektor darstellen. Die globale Erwärmung wird für den Strand- und Badetourismus sowohl negative, als auch positive Folgen haben, auf die reagiert werden muss. Neben vorbeugenden Klimaschutzmaßnahmen werden künftig auch Anpassungsstrategien entwickelt werden müssen, die den zu erwartenden Veränderungen Rechnung tragen. Doch zu welchen tourismusrelevanten Veränderungen wird es überhaupt kommen und was geschieht bereits aktuell? Sind die Folgen des Klimawandels durch Touristen schon jetzt wahrnehmbar? Wie reagieren die Urlauber auf eventuelle Veränderungen? Diese und andere Fragen soll die vorliegende Arbeit, die innerhalb des RAdOST-Vorhabens (Regionale Anpassungsstrategien für die deutsche Ostseeküste) angesiedelt ist, beantworten. Dazu wurde zum einen eine Literaturrecherche zu tourismusrelevanten Klimawandelfolgen an der deutschen Ostseeküste durchgeführt. Zum anderen erfolgte in den Sommermonaten 2010 eine Befragung der Strandgäste in Markgrafenheide, Warnemünde und Nienhagen an der mecklenburgischen Ostseeküste. Im Mittelpunkt der Umfrage stand die Wahrnehmung von Erscheinungen (z.B. viele Quallen oder warmes Ostseewasser) sowie kurz- oder langfristigen Veränderungen an der Küste (z.B. schmalere Strände, vermehrter Strandanwurf) durch die Urlauber. Außerdem wurden die Einstellung und der Informationsgrad der Gäste zum Thema Klimawandel an der Ostseeküste analysiert. Ziel war es, aus den Umfrageergebnissen Handlungsempfehlungen für das lokale Strandmanagement hinsichtlich künftiger Anpassungsstrategien abzuleiten. Die Literaturrecherche zeigte, dass in einigen Bereichen schon jetzt Veränderungen (z.B. der Luft- und Wassertemperatur oder des Meeresspiegels) nachweisbar sind und laut verschiedener Modellprojektionen von weiteren Veränderungen ausgegangen werden kann. Wie die Umfrage deutlich machte, sind die Veränderungen momentan durch Touristen jedoch kaum oder gar nicht wahrnehmbar. Dementsprechend gering ist auch ihre Reaktion auf die einzelnen Phänomene. Generell ist die Wahrnehmung der Urlauber sehr subjektiv und selektiv. Manche Gegebenheiten wie beispielsweise existierende Küstenschutzmaßnahmen werden von einem großen Teil der Touristen gar nicht wahrgenommen. Hinsichtlich anderer Erscheinungen wie Strandanwurf und Quallen sind viele Besucher wiederum sehr sensibel. Es zeigte sich außerdem, dass es für die meisten Urlauber schwierig ist, zu beurteilen, ob bestimmte Gegebenheiten am Strand und an der Küste mit der globalen Erwärmung in Verbindung stehen oder nicht. Es besteht eine große Unsicherheit zu diesem Thema und oft wird der Klimawandel als Ursache für Erscheinungen genannt, auch wenn der kausale Zusammenhang wissenschaftlich nicht nachzuweisen ist. Es zeigte sich, dass die Urlauber sehr wenig über die regionalen Auswirkungen des Klimawandels informiert sind, sich aber Informationen wünschen. Folglich sollte zunächst die Aufklärung und Information der Urlauber über die Folgen der Veränderung des Klimas im Vordergrund stehen. Denn manche Aspekte, wie der Verlust von Strandabschnitten durch Erosion oder eine eventuelle Zunahme von Blaualgen in der Sommersaison, können nicht gänzlich vermieden werden. Durch gezielte Aufklärung könnte jedoch beispielsweise eine Akzeptanz für naturnahe Strände oder für den Rückzug aus einzelnen Gebieten geschaffen werden. Darüber hinaus sollte die zu erwartende Saisonverlängerung systematisch genutzt werden, um sowohl die Küste, als auch das Hinterland durch gezielte Angebote für Touristen attraktiv zu machen. Auf diese Weise könnte eine Entzerrung der Hauptsaison und eine bessere Auslastung der Beherbergungsbetriebe sowie der touristischen Infrastruktur erreicht werden.
Low-cost monitoring of snow height and thermal properties with inexpensive temperature sensors
(2011)
Small, self-recording temperature sensors were installed at several heights along a metal rod at five locations in a case study catchment. For each sensor, the presence or absence of snow cover was determined on the basis of its insulating effect and the resulting reduction of the diurnal temperature oscillations. Sensor coverage was then converted into a time series of snow height for each location. Additionally, cold content was calculated. Snow height and cold content provide valuable information for spring flood prediction.
Good agreement of estimated snow heights with reference measurements was achieved and increased discharge in the study catchment coincided with low cold content of the snow cover. The results of the proposed distributed assessment of snow cover and snow state show great potential for (i) flood warning, (ii) assimilation of snow state data and (iii) modelling snowmelt process.
In this paper we investigate the use of hydrological models as learning tools to help improve our understanding of the hydrological functioning of a catchment. With the model as a hypothetical conceptualization of how dominant hydrological processes contribute to catchment-scale response, we investigate three questions: (1) During which periods does the model (not) reproduce observed quantities and dynamics? (2) What is the nature of the error during times of bad model performance? (3) Which model components are responsible for this error? To investigate these questions, we combine a method for detecting repeating patterns of typical differences between model and observations (time series of grouped errors, TIGER) with a method for identifying the active model components during each simulation time step based on parameter sensitivity (temporal dynamics of parameter sensitivities, TEDPAS). The approach generates a time series of occurrence of dominant error types and time series of parameter sensitivities. A synoptic discussion of these time series highlights deficiencies in the assumptions about the functioning of the catchment. The approach is demonstrated for the Weisseritz headwater catchment in the eastern Ore Mountains. Our results indicate that the WaSiM-ETH complex grid-based model is not a sufficient working hypothesis for the functioning of the Weisseritz catchment and point toward future steps that can help improve our understanding of the catchment.
The quest for improved hydrological models is one of the big challenges in hydrology. When discrepancies are observed between simulated and measured discharge, it is essential to identify which algorithms may be responsible for poor model behavior. Particularly in complex hydrological models, different process representations may dominate at different moments and interact with each other, thus highly complicating this task. This paper investigates the analysis of the temporal dynamics of parameter sensitivity as a way to disentangle the simulation of a hydrological model and identify dominant parameterizations. Three existing methods (the Fourier amplitude sensitivity test, the extended Fourier amplitude sensitivity test, and Sobol's method) are compared by applying them to a TOPMODEL implementation in a small mountainous catchment in the tropics. For the major part of the simulation period, the three methods give comparable results, while the Fourier amplitude sensitivity test is much more computationally efficient. This method is also applied to the complex hydrological model WaSiM-ETH implemented in the Weisseritz catchment, Germany. A qualitative model validation was performed on the basis of the identification of relevant model components. The validation revealed that the saturation deficit parameterization of WaSiM-ETH is highly susceptible to parameter interaction and lack of identifiability. We conclude that temporal dynamics of model parameter sensitivity can be a powerful tool for hydrological model analysis, especially to identify parameter interaction as well as the dominant hydrological response modes. Finally, an open source implementation of the Fourier amplitude sensitivity test is provided.
Saturated hydraulic conductivity (Ks) of the soil is a key variable in the water cycle. For the humid tropics, information about spatial scales of Ks and their relation to soil types deduced from soil map units is of interest, as soil maps are often the only available data source for modelling. We examined the influence of soil map units on the mean and variation in Ks along a transect in a tropical rainforest using undisturbed soil cores at 06 and 612 cm depth. The Ks means were estimated with a linear mixed model fitted by residual maximum likelihood (REML), and the spatial variation in Ks was investigated with the maximum overlap discrete wavelet packet transform (MODWPT). The mean values of Ks did not differ between soil map units. The best wavelet packet basis for Ks at 06 cm showed stationarity at high frequencies, suggesting uniform small-scale influences such as bioturbation. There were substantial contributions to wavelet packet variance over the range of spatial frequencies and a pronounced low frequency peak corresponding approximately to the scale of soil map units. However, in the relevant frequency intervals no significant changes in wavelet packet variance were detected. We conclude that near-surface Ks is not dominated by static, soil-inherent properties for the examined range of soils. Several indicators from the wavelet packet analysis hint at the more dominant dynamic influence of biotic processes, which should be kept in mind when modelling soil hydraulic properties on the basis of soil maps.
Land use and mineral characteristics affect the ability of surface as well as subsurface soils to sequester organic carbon and their contribution to mitigation of the greenhouse effect. There is less information about the effects of land use and soil properties on the amount and composition of organic matter (OM) for subsurface soils as compared with surface soils. Here we aimed to analyse the long-term (>= 100 years) impact of arable and forest land use and soil mineral characteristics on subsurface soil organic carbon (SOC) contents, as well as on amount and composition of OM sequentially separated by Na pyrophosphate solution (OM(PY)) from subsurface soil samples. Seven soils with different mineral characteristics (Albic and Haplic Luvisol, Colluvic and Haplic Regosol, Haplic and Vertic Cambisol, Haplic Stagnosol) were selected from within Germany. Soil samples were taken from subsurface horizons of forest and adjacent arable sites continuously used for > 100 years. The OM(PY) fractions were analysed for their OC content (OC(PY)) and characterized by Fourier transform infrared spectroscopy. Multiple regression analyses for the arable subsurface soils indicated significant positive relationships between the SOC contents and combined effects of the (i) exchangeable Ca (Ca(ex)) and oxalate-soluble Fe (Fe(ox)) and (ii) the Ca(ex) and Al(ox) contents. For these soils the increase in OC (OC(PY) multiplied by the relative C=O content of OM(PY)) and increasing contents of Ca(ex) indicated that OM(PY) mainly interacts with Ca2+. For the forest subsurface soils (pH < 5), the OC(PY) contents were related to the contents of Na-pyrophosphate-soluble Fe and Al. The long-term arable and forest land use seems to result in different OM(PY)-mineral interactions in subsurface soils. On the basis of this, we hypothesize that a long-term land-use change from arable to forest may lead to a shift from mainly OM(PY)-Ca2+ to mainly OM(PY)-Fe3+ and -Al3+ interactions if the pH of subsurface soils significantly decreases to < 5.
The flowpaths by which water moves from watersheds to streams has important consequences for the runoff dynamics and biogeochemistry of surface waters in the Amazon Basin. The clearing of Amazon forest to cattle pasture has the potential to change runoff sources to streams by shifting runoff to more surficial flow pathways. We applied end-member mixing analysis (EMMA) to 10 small watersheds throughout the Amazon in which solute composition of streamwater and groundwater, overland flow, soil solution, throughfall and rainwater were measured, largely as part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia. We found a range in the extent to which streamwater samples fell within the mixing space determined by potential flowpath end-members, suggesting that some water sources to streams were not sampled. The contribution of overland flow as a source of stream flow was greater in pasture watersheds than in forest watersheds of comparable size. Increases in overland flow contribution to pasture streams ranged in some cases from 0% in forest to 27-28% in pasture and were broadly consistent with results from hydrometric sampling of Amazon forest and pasture watersheds that indicate 17- to 18-fold increase in the overland flow contribution to stream flow in pastures. In forest, overland flow was an important contribution to stream flow (45-57%) in ephemeral streams where flows were dominated by stormflow. Overland flow contribution to stream flow decreased in importance with increasing watershed area, from 21 to 57% in forest and 60-89% in pasture watersheds of less than 10 ha to 0% in forest and 27-28% in pastures in watersheds greater than 100 ha. Soil solution contributions to stream flow were similar across watershed area and groundwater inputs generally increased in proportion to decreases in overland flow. Application of EMMA across multiple watersheds indicated patterns across gradients of stream size and land cover that were consistent with patterns determined by detailed hydrometric sampling.
Environmental isotope techniques, hydrogeochemical analysis and hydraulic data are employed to identify the main recharge areas of the Mt. Vulture hydrogeological basin, one of the most important aquifers of southern Italy. The groundwaters are derived from seepage of rainwater, flowing from the highest to the lowest elevations through the shallow volcanic weathered host-rock fracture zones. Samples of shallow and deep groundwater were collected at 48 locations with elevations ranging from 352 to 1,100 m above sea level (a.s.l.), for stable isotope (delta(18)O, delta D) and major ion analyses. A complete dataset of available hydraulic information has been integrated with measurements carried out in the present study. Inferred recharge elevations, estimated on the basis of the local vertical isotopic gradient of delta(18)O, range between 550 and 1,200 m a.s.l. The isotope pattern of the Quaternary aquifer reflects the spatial separation of different recharge sources. Knowledge of the local hydrogeological setting was the starting point for a detailed hydrogeochemical and isotopic study to define the recharge and discharge patterns identifying the groundwater flow pathways of the Mt. Vulture basin. The integration of all the data allowed for the tracing of the groundwater flows of the Mt. Vulture basin.
This study was conducted to evaluate the effect of different wood vermicompost application rates on some soil physical and chemical properties as well as on growth parameters of a grass seed mixture (RSM 7.2.1) in tertiary sand contaminated with coal spoil. The experiment was carried out in a greenhouse over a period of 42 days. Soil was mixed with vermicompost at ratios of 0.0, 3.0, 12.5, and 25.0% and sown with the grass seed mixture. Soil samples and plant material were analyzed to determine the effect of different vermicompost application rates on the physical and chemical properties. Results revealed that the physical and chemical properties of the soil improved with increasing application rates of vermicompost. In addition, soil treated with vermicompost showed significant increases in fresh-and dry-matter yields of the grass, as well as enhanced uptake of nutrients by the grass. This indicated that treatment of contaminated soils with vermicompost may be beneficial for reclamation processes by facilitating revegetation of disturbed areas.
Complete protection against flood risks by structural measures is impossible. Therefore flood prediction is important for flood risk management. Good explanatory power of flood models requires a meaningful representation of bio-physical processes. Therefore great interest exists to improve the process representation. Progress in hydrological process understanding is achieved through a learning cycle including critical assessment of an existing model for a given catchment as a first step. The assessment will highlight deficiencies of the model, from which useful additional data requirements are derived, giving a guideline for new measurements. These new measurements may in turn lead to improved process concepts. The improved process concepts are finally summarized in an updated hydrological model. In this thesis I demonstrate such a learning cycle, focusing on the advancement of model evaluation methods and more cost effective measurements. For a successful model evaluation, I propose that three questions should be answered: 1) when is a model reproducing observations in a satisfactory way? 2) If model results deviate, of what nature is the difference? And 3) what are most likely the relevant model components affecting these differences? To answer the first two questions, I developed a new method to assess the temporal dynamics of model performance (or TIGER - TIme series of Grouped Errors). This method is powerful in highlighting recurrent patterns of insufficient model behaviour for long simulation periods. I answered the third question with the analysis of the temporal dynamics of parameter sensitivity (TEDPAS). For calculating TEDPAS, an efficient method for sensitivity analysis is necessary. I used such an efficient method called Fourier Amplitude Sensitivity Test, which has a smart sampling scheme. Combining the two methods TIGER and TEDPAS provided a powerful tool for model assessment. With WaSiM-ETH applied to the Weisseritz catchment as a case study, I found insufficient process descriptions for the snow dynamics and for the recession during dry periods in late summer and fall. Focusing on snow dynamics, reasons for poor model performance can either be a poor representation of snow processes in the model, or poor data on snow cover, or both. To obtain an improved data set on snow cover, time series of snow height and temperatures were collected with a cost efficient method based on temperature measurements on multiple levels at each location. An algorithm was developed to simultaneously estimate snow height and cold content from these measurements. Both, snow height and cold content are relevant quantities for spring flood forecasting. Spatial variability was observed at the local and the catchment scale with an adjusted sampling design. At the local scale, samples were collected on two perpendicular transects of 60 m length and analysed with geostatistical methods. The range determined from fitted theoretical variograms was within the range of the sampling design for 80% of the plots. No patterns were found, that would explain the random variability and spatial correlation at the local scale. At the watershed scale, locations of the extensive field campaign were selected according to a stratified sample design to capture the combined effects of elevation, aspect and land use. The snow height is mainly affected by the plot elevation. The expected influence of aspect and land use was not observed. To better understand the deficiencies of the snow module in WaSiM-ETH, the same approach, a simple degree day model was checked for its capability to reproduce the data. The degree day model was capable to explain the temporal variability for plots with a continuous snow pack over the entire snow season, if parameters were estimated for single plots. However, processes described in the simple model are not sufficient to represent multiple accumulation-melt-cycles, as observed for the lower catchment. Thus, the combined spatio-temporal variability at the watershed scale is not captured by the model. Further tests on improved concepts for the representation of snow dynamics at the Weißeritz are required. From the data I suggest to include at least rain on snow and redistribution by wind as additional processes to better describe spatio-temporal variability. Alternatively an energy balance snow model could be tested. Overall, the proposed learning cycle is a useful framework for targeted model improvement. The advanced model diagnostics is valuable to identify model deficiencies and to guide field measurements. The additional data collected throughout this work helps to get a deepened understanding of the processes in the Weisseritz catchment.
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.
Influence of land-use change on near-surface hydrological processes : undisturbed forest to pasture
(2010)
Soil compaction that follows the clearing of tropical forest for cattle pasture is associated with lower soil hydraulic conductivity and increased frequency and volume of overland flow. We investigated the frequency of perched water tables, overland flow and stormflow in an Amazon forest and in an adjacent 25-year-old pasture cleared from the same forest. We compared the results with the frequencies of these phenomena estimated from comparisons of rainfall intensity and soil hydraulic conductivity. The frequency of perched water tables based on rainfall intensity and soil hydraulic conductivity was expected to double in pasture compared with forest. This corresponded closely with an approximate doubling of the frequency of stormflow and overland flow in pasture. In contrast, the stormflow volume in pasture increased 17-fold. This disproportional increase of stormflow resulted from overland flow generation over large areas of pasture, while overland flow generation in the forest was spatially limited and was observed only very near the stream channel. In both catchments, stormflow was generated by saturation excess because of perched water tables and near-surface groundwater levels. Stormflow was occasionally generated in the forest by rapid return flow from macropores, while slow return flow from a continuous perched water table was more common in the pasture. These results suggest that deforestation for pasture alters fundamental mechanisms of stormflow generation and may increase runoff volumes over wide regions of Amazonia.