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The energy sector is both affected by climate change and a key sector for climate protection measures. Energy security is the backbone of our modern society and guarantees the functioning of most critical infrastructure. Thus, decision makers and energy suppliers of different countries should be familiar with the factors that increase or decrease the susceptibility of their electricity sector to climate change. Susceptibility means socioeconomic and structural characteristics of the electricity sector that affect the demand for and supply of electricity under climate change. Moreover, the relevant stakeholders are supposed to know whether the given national energy and climate targets are feasible and what needs to be done in order to meet these targets. In this regard, a focus should be on the residential building sector as it is one of the largest energy consumers and therefore emitters of anthropogenic CO 2 worldwide.
This dissertation addresses the first aspect, namely the susceptibility of the electricity sector, by developing a ranked index which allows for quantitative comparison of the electricity sector susceptibility of 21 European countries based on 14 influencing factors. Such a ranking has not been completed to date. We applied a sensitivity analysis to test the relative effect of each influencing factor on the susceptibility index ranking. We also discuss reasons for the ranking position and thus the susceptibility of selected countries. The second objective, namely the impact of climate change on the energy demand of buildings, is tackled by means of a new model with which the heating and cooling energy demand of residential buildings can be estimated. We exemplarily applied the model to Germany and the Netherlands. It considers projections of future changes in population, climate and the insulation standards of buildings, whereas most of the existing studies only take into account fewer than three different factors that influence the future energy demand of buildings. Furthermore, we developed a comprehensive retrofitting algorithm with which the total residential building stock can be modeled for the first time for each year in the past and future.
The study confirms that there is no correlation between the geographical location of a country and its position in the electricity sector susceptibility ranking. Moreover, we found no pronounced pattern of susceptibility influencing factors between countries that ranked higher or lower in the index. We illustrate that Luxembourg, Greece, Slovakia and Italy are the countries with the highest electricity sector susceptibility. The electricity sectors of Norway, the Czech Republic, Portugal and Denmark were found to be least susceptible to climate change. Knowledge about the most important factors for the poor and good ranking positions of these countries is crucial for finding adequate adaptation measures to reduce the susceptibility of the electricity sector. Therefore, these factors are described within this study.
We show that the heating energy demand of residential buildings will strongly decrease in both Germany and the Netherlands in the future. The analysis for the Netherlands focused on the regional level and a finer temporal resolution which revealed strong variations in the future heating energy demand changes by province and by month. In the German study, we additionally investigated the future cooling energy demand and could demonstrate that it will only slightly increase up to the middle of this century. Thus, increases in the cooling energy demand are not expected to offset reductions in heating energy demand. The main factor for substantial heating energy demand reductions is the retrofitting of buildings. We are the first to show that the given German and Dutch energy and climate targets in the building sector can only be met if the annual retrofitting rates are substantially increased. The current rate of only about 1 % of the total building stock per year is insufficient for reaching a nearly zero-energy demand of all residential buildings by the middle of this century. To reach this target, it would need to be at least tripled. To sum up, this thesis emphasizes that country-specific characteristics are decisive for the electricity sector susceptibility of European countries. It also shows for different scenarios how much energy is needed in the future to heat and cool residential buildings. With this information, existing climate mitigation and adaptation measures can be justified or new actions encouraged.
Cities play a vital role in the global climate change mitigation agenda. City population density is one of the key factors that influence urban energy consumption and the subsequent GHG emissions. However, previous research on the relationship between population density and GHG emissions led to contradictory results due to urban/rural definition conundrum and the varying methodologies for estimating GHG emissions. This work addresses these ambiguities by employing the City Clustering Algorithm (CCA) and utilizing the gridded CO2 emissions data. Our results, derived from the analysis of all inhabited areas in the US, show a sub-linear relationship between population density and the total emissions (i.e. the sum of on-road and building emissions) on a per capita basis. Accordingly, we find that doubling the population density would entail a reduction in the total CO2 emissions in buildings and on-road sectors typically by at least 42%. Moreover, we find that population density exerts a higher influence on on-road emissions than buildings emissions. From an energy consumption point of view, our results suggest that on-going urban sprawl will lead to an increase in on-road energy consumption in cities and therefore stresses the importance of developing adequate local policy measures to limit urban sprawl. (C) 2016 Elsevier Ltd. All rights reserved.
A link between chemical weathering and physical erosion exists at the catchment scale over a wide range of erosion rates(1,2). However, in mountain environments, where erosion rates are highest, weathering may be kinetically limited(3-5) and therefore decoupled from erosion. In active mountain belts, erosion is driven by bedrock landsliding(6) at rates that depend strongly on the occurrence of extreme rainfall or seismicity(7). Although landslides affect only a small proportion of the landscape, bedrock landsliding can promote the collection and slow percolation of surface runoff in highly fragmented rock debris and create favourable conditions for weathering. Here we show from analysis of surface water chemistry in the Southern Alps of New Zealand that weathering in bedrock landslides controls the variability in solute load of these mountain rivers. We find that systematic patterns in surface water chemistry are strongly associated with landslide occurrence at scales from a single hillslope to an entire mountain belt, and that landslides boost weathering rates and river solute loads over decades. We conclude that landslides couple erosion and weathering in fast-eroding uplands and, thus, mountain weathering is a stochastic process that is sensitive to climatic and tectonic controls on mass wasting processes.
Pollen influx (number of pollen grains cm−2 year−1) can objectively reflect the dispersal and deposition features of pollen within a certain time and space, and is often used as a basis for the quantitative reconstruction of palaeovegetation; however, little is known about the features and mechanisms of vertical dispersal of pollen. Here we present the results from a 5 year (2006–2010) monitoring program using pollen traps placed at different heights from ground level up to 60 m and surface soil samples in a mixed coniferous and deciduous broad-leaved woodland in the Changbai mountains, northeastern China. The pollen percentages and pollen influx from the traps have very similar characteristics to the highest values for Betula, Fraxinus, Quercus and Pinus, among the tree taxa and Artemisia, Chenopodiaceae and Asteraceae among the herb taxa. Pollen influx values vary significantly with height and show major differences between three distinct layers, above-canopy (≥32 m), within the trunk layer (8 ≤ 32 m) and on the ground (0 m). These differences in pollen influx are explained by differences in (i) the air flows in each of these layers and (ii) the fall speed of pollen of the various taxa. We found that the pollen recorded on the ground surface is a good representation of the major part of the pollen transported in the trunk space of the woodland. Comparison of the pollen influx values with the theoretical, calculated “characteristic pollen source area” (CPSA) of 12 selected taxa indicates that the pollen deposited on the ground surface of the woodland is a fair representation with 85–90 % of the total pollen deposited at a wind speed of 2.4 m s−1 coming from within ca. 1–5 km for Pinus and Quercus, ca. 5–10 km for Ulmus, Tilia, Oleaceae and Betula, ca. 20–40 km for Fraxinus, Poaceae, Chenopodiaceae, Populus and Salix, and ca. 30–60 km for Artemisia; it is also a good representation with 90–98 % of the total pollen deposited coming from within 60 km at a wind speed of 2.4 m s−1, or 100 km at a wind speed: 6 m s−1, for the 12 selected taxa used in the CPSA calculation. Furthermore, comparison with the vegetation map of the area around the sampling site shows that the pollen deposited on the ground represents all plant communities which grow in the study area within 70 km radius of the sampling site. In this study, the pollen percentages obtained from the soil surface samples are significantly biased towards pollen taxa with good preservation due to thick and robust pollen walls. Therefore, if mosses are available instead, soil samples should be avoided for pollen studies, in particular for the study of pollen-vegetation relationships, the estimation of pollen productivities and quantitative reconstruction of past vegetation. The results also indicate that the existing model of pollen dispersal and deposition, Prentice’s model, provides a fair description of the actual pollen dispersal and deposition in this kind of woodland, which suggests that the application of the landscape reconstruction algorithm would be relevant for reconstruction of this type of woodland in the past.
Strong waves in the mid-latitude circulation have been linked to extreme surface weather and thus changes in waviness could have serious consequences for society. Several theories have been proposed which could alter waviness, including tropical sea surface temperature anomalies or rapid climate change in the Arctic. However, so far it remains unclear whether any changes in waviness have actually occurred. Here we propose a novel meandering index which captures the maximum waviness in geopotential height contours at any given day, using all information of the full spatial position of each contour. Data are analysed on different time scale (from daily to 11 day running means) and both on hemispheric and regional scales. Using quantile regressions, we analyse how seasonal distributions of this index have changed over 1979-2015. The most robust changes are detected for autumn which has seen a pronounced increase in strongly meandering patterns at the hemispheric level as well as over the Eurasian sector. In summer for both the hemisphere and the Eurasian sector, significant downward trends in meandering are detected on daily timescales which is consistent with the recently reported decrease in summer storm track activity. The American sector shows the strongest increase in meandering in the warm season: in particular for 11 day running mean data, indicating enhanced amplitudes of quasi-stationary waves. Our findings have implications for both the occurrence of recent cold spells and persistent heat waves in the mid-latitudes.
Carboniferous metagranites with U-Pb zircon crystallization ages of 331-315 Ma crop out in the Afyon zone in the northern margin of the Anatolide-Tauride Block, which is commonly regarded as part of Gondwana during the Late Palaeozoic. They are peraluminous, calc-alkaline and are characterized by increase in Rb and Ba, decrease in Nb-Ta, and enrichment in Sr and high LILE/HFSE ratios compatible with a continental arc setting. The metagranites intrude a metasedimentary sequence of phyllite, metaquartzite and marble; both the Carboniferous metagranites and metasedimentary rocks are overlain unconformably by Lower Triassic metaconglomerates, metavolcanics and Upper Triassic to Cretaceous recrystallized limestones. The low-grade metamorphism and deformation occurred at the Cretaceous-Tertiary boundary. There is no evidence for Carboniferous deformation and metamorphism in the region. Carboniferous arc-type granites and previously described Carboniferous subduction-accretion complexes on the northern margin of the Anatolide-Tauride Block suggest southward subduction of Paleotethys under Gondwana during the Carboniferous. Considering the Variscan-related arc granites in Pelagonian and Sakarya zones on the active southern margin of Laurasia, a dual subduction of Paleotethys can be envisaged between Early Carboniferous and Late Permian. However, the southward subduction was short-lived and by the Late Permian the Gondwana margin became passive. (C) 2016 Elsevier B.V. All rights reserved.
Carbonatites are peculiar magmatic rocks with mantle-related genesis, commonly interpreted as the products of melting of CO2-bearing peridotites, or resulting from the chemical evolution of mantle derived magmas, either through extreme "differentiation or secondary immiscibility. Here we report the first finding of anatectic carbonatites of crustal origin, preserved as calcite-rich polycrystalline inclusions in garnet from low-to-medium pressure migmatites of the Oberpfalz area, SW Bohemian Massif (Central Europe). These inclusions originally trapped a melt of calciocarbonatitic composition with a characteristic enrichment in Ba, Sr and LREE. This interpretation is supported by the results of a detailed microstructural and microchemical investigation, as well as re-melting experiments using a piston cylinder apparatus. Carbonatitic inclusions coexist in the same cluster with crystallized silicate melt inclusions (nanogranites) and COH fluid inclusions, suggesting conditions of primary immiscibility between two melts and a fluid during anatexis. The production of both carbonatitic and granitic melts during the same anatectic event requires a suitable heterogeneous protolith. This may be represented by a sedimentary sequence containing marble lenses of limited extension, similar to the one still visible in the adjacent central Moldanubian Zone. The presence of CO2-rich fluid inclusions suggests furthermore that high CO2 activity during anatexis may be required to stabilize a carbonate-rich melt in a silica-dominated, system. This natural occurrence displays a remarkable similarity with experiments on carbonate-silicate melt immiscibility, where CO2 saturation is a condition commonly imposed. In conclusion, this study shows how the investigation of partial melting through melt inclusion studies may unveil unexpected processes whose evidence, while preserved in stiff minerals such as garnet, is completely obliterated in the rest of the rock due to metamorphic re-equilibration. Our results thus provide invaluable new insights into the processes which shape the geochemical evolution of our planet, such as the redistribution of carbon and strategic metals during orogenesis. (C) 2016 Elsevier B.V. All rights reserved.
Carbon and nutrient cycling in kettle hole sediments depending on hydrological dynamics: a review
(2016)
Kettle holes as a specific group of isolated, small lentic freshwater systems (LFS) often are (i) hot spots of biogeochemical cycling and (ii) exposed to frequent sediment desiccation and rewetting. Their ecological functioning is greatly determined by immanent carbon and nutrient transformations. The objective of this review is to elucidate effects of a changing hydrological regime (i.e., dry-wet cycles) on carbon and nutrient cycling in kettle hole sediments. Generally, dry-wet cycles have the potential to increase C and N losses as well as P availability. However, their duration and frequency are important controlling factors regarding direction and intensity of biogeochemical and microbiological responses. To evaluate drought impacts on sediment carbon and nutrient cycling in detail requires the context of the LFS hydrological history. For example, frequent drought events induce physiological adaptation of exposed microbial communities and thus flatten metabolic responses, whereas rare events provoke unbalanced, strong microbial responses. Different potential of microbial resilience to drought stress can irretrievably change microbial communities and functional guilds, gearing cascades of functional responses. Hence, dry-wet events can shift the biogeochemical cycling of organic matter and nutrients to a new equilibrium, thus affecting the dynamic balance between carbon burial and mineralization in kettle holes.
To understand past flood changes in the Rhine catchment and in particular the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. This approach assumes a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. These presuppositions are unprecedentedly evaluated here using 111 years of daily climate data from 490 stations in the Rhine basin and comprehensively testing the number of classification parameters and GCM weather pattern characteristics. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis of atmospheric fields over central Europe with 40 weather types was found to be the most appropriate for stratifying six local climate variables. The corresponding skill is quite diverse though, ranging from good for radiation to poor for precipitation. Especially for the latter it was apparent that pressure fields alone cannot sufficiently stratify local variability. To test the skill of the latest generation of GCMs from the CMIP5 ensemble in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.
The problem of estimating the maximum possible earthquake magnitude m(max) has attracted growing attention in recent years. Due to sparse data, the role of uncertainties becomes crucial. In this work, we determine the uncertainties related to the maximum magnitude in terms of confidence intervals. Using an earthquake catalog of Iran, m(max) is estimated for different predefined levels of confidence in six seismotectonic zones. Assuming the doubly truncated Gutenberg-Richter distribution as a statistical model for earthquake magnitudes, confidence intervals for the maximum possible magnitude of earthquakes are calculated in each zone. While the lower limit of the confidence interval is the magnitude of the maximum observed event, the upper limit is calculated from the catalog and the statistical model. For this aim, we use the original catalog which no declustering methods applied on as well as a declustered version of the catalog. Based on the study by Holschneider et al. (Bull Seismol Soc Am 101(4): 1649-1659, 2011), the confidence interval for m(max) is frequently unbounded, especially if high levels of confidence are required. In this case, no information is gained from the data. Therefore, we elaborate for which settings finite confidence levels are obtained. In this work, Iran is divided into six seismotectonic zones, namely Alborz, Azerbaijan, Zagros, Makran, Kopet Dagh, Central Iran. Although calculations of the confidence interval in Central Iran and Zagros seismotectonic zones are relatively acceptable for meaningful levels of confidence, results in Kopet Dagh, Alborz, Azerbaijan and Makran are not that much promising. The results indicate that estimating mmax from an earthquake catalog for reasonable levels of confidence alone is almost impossible.
Climate science today makes use of a variety of red globes to explore and communicate findings. These transform the iconography which informs this image: the idealised, even mythical vision of the blue, vulnerable and perfect marble is impaired by the application of the colours yellow and red. Since only predictions that employ a lot of red seem to exist, spectators are confronted with the message that the future Earth that might turn out as envisaged here is undesirable. Here intuitively powerful narrations of the end of the world may connect. By employing methods of art history and visual analysis, and building on examples from current Intergovernmental Panel on Climate Change reports and future scenario maps, this article explores how burning world images bear - intentionally or not - elements of horror and shock. My question explored here is as follows: should 'burning world' images be understood as a new and powerful cosmology?
In March 2015, a new international blueprint for disaster risk reduction (DRR) was adopted in Sendai, Japan, at the end of the Third UN World Conference on Disaster Risk Reduction (WCDRR, 14-18 March 2015). We review and discuss the agreed commitments and targets, as well as the negotiation leading the Sendai Framework for DRR (SF-DRR) and discuss briefly its implication for the later UN-led negotiations on sustainable development goals and climate change.
Rainfall-induced attenuation is a major source of underestimation for radar-based precipitation estimation at C-band. Unconstrained gate-by-gate correction procedures are known to be inherently unstable and thus not suited for unsupervised attenuation correction. In this study, we evaluate three different procedures to constrain gate-by-gate attenuation correction using reflectivity as the only input. These procedures are benchmarked against rainfall estimates from uncorrected radar data, using six years of radar observations from the single-polarized C-band radar in South-West Germany. The precipitation estimation error is obtained by comparing the radar-based estimates to rain gauge observations. All attenuation correction procedures benchmarked in this study lead to an effective improvement of precipitation estimation. The first method caps the corrections if the rain intensity increase exceeds a factor of two. The second method decreases the parameters of the attenuation correction iteratively for every radar beam calculation until attaining a stability criterion. The second method outperforms the first method and leads to a consistent distribution of path-integrated attenuation along the radar beam. As a third method, we propose a slight modification of Kraemer's approach which allows users to exert better control over attenuation correction by introducing an additional constraint that prevents unplausible corrections in cases of dramatic signal losses.
The water cycle of sites with shallow groundwater tables is characterized by complex interactions of hydrological and ecological processes. The water balance components, which are subject to diurnal fluctuations, are best measured with groundwater lysimeters. However, the lower boundary condition of such lysimeters affects most of the hydrological variables, particularly when considering short time scales, and has to be defined in such a way as to facilitate realistic simulations. In this paper, different means of controlling the lower boundary condition of groundwater lysimeters were compared with respect to their ability to simulate the behavior of the water balance components properly. Measurements of rain-free periods from a lysimeter station installed in the Spreewald wetland in north-east Germany were evaluated. The most common groundwater lysimeter type is controlled using a Mariotte bottle and sets the groundwater level in the soil monolith to a constant level, which here caused an alteration of the inflow to the lysimeter, with respect to both its value and diurnal behavior. Still, daily evapotranspiration values were realistic and this simple and robust approach may be used for time intervals not shorter than one day. High-resolution measurements can be gained from lysimeters that automatically adjust the groundwater level by a system of pumps and valves on an hourly basis. Still, reliable results were only obtained when the conditions in the lysimeter and the surrounding field, where the target groundwater level was measured, were in accordance. Otherwise (e.g., when the groundwater level differed) an unrealistic inflow behavior evolved. Reasonable results, even for slightly diverging conditions, were gained with a new approach that defined the lower boundary conditions by controlling the inflows and outflows of the lysimeter. This approach further enabled the groundwater level itself to be the study subject, thereby enlarging the field of possible applications of groundwater lysimeters. (C) 2015 Elsevier B.V. All rights reserved.
Analysis of time-lapse ground-penetrating radar (GPR) data can provide information regarding subsurface hydrological processes, such as preferential flow. However, the analysis of time-lapse data is often limited by data quality; for example, for noisy input data, the interpretation of difference images is often difficult. Motivated by modern image-processing tools, we have developed two robust GPR attributes, which allow us to distinguish amplitude (contrast similarity) and time-shift (structural similarity) variations related to differences between individual time-lapse GPR data sets. We tested and evaluated our attributes using synthetic data of different complexity. Afterward, we applied them to a field data example, in which subsurface flow was induced by an artificial rainfall event. For all examples, we identified our structural similarity attribute to be a robust measure for highlighting time-lapse changes also in data with low signal-to-noise ratios. We determined that our new attribute-based workflow is a promising tool to analyze time-lapse GPR data, especially for imaging subsurface hydrological processes.
Snowfall comprises a significant percentage of the annual water budget in High Mountain Asia (HMA), but snow water equivalent (SWE) is poorly constrained due to lack of in-situ measurements and complex terrain that limits the efficacy of modeling and observations. Over the past few decades, SWE has been estimated with passive microwave (PM) sensors with generally good results in wide, flat, terrain, and lower reliability in densely forested, complex, or high-elevation areas. In this study, we use raw swath data from five satellite - sensors the Special Sensor Microwave/Imager (SSMI) and Special Sensor Microwave Imager/Sounder (SSMIS) (1987-2015, F08, F11, F13, F17), Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E, 2002-2011), AMSR2 (2012-2015), and the Global Precipitation Measurement (GPM, 2014-2015) - in order to understand the spatial and temporal structure of native sensor, topographic, and land cover biases in SWE estimates in HMA. We develop a thorough understanding of the uncertainties in our SWE estimates by examining the impacts of topographic parameters (aspect, relief, hillslope angle, and elevation), land cover, native sensor biases, and climate parameters (precipitation, temperature, and wind speed). HMA, with its high seasonality, large topographic gradients and low relief at high elevations provides an excellent context to examine a wide range of climatic, land-cover, and topographic settings to better constrain SWE uncertainties and potential sensor bias. Using a multi-parameter regression, we compare long-term SWE variability to forest fraction, maximal multiyear snow depth, topographic parameters, and long-term average wind speed across both individual sensor time series and a merged multi-sensor dataset. In regions where forest cover is extensive, it is the strongest control on SWE variability. In those regions where forest density is low (<5%), maximal snow depth dominates the uncertainty signal. In our regression across HMA, we find that forest fraction is the strongest control on SWE variability (75.8%), followed by maximal multi-year snow depth (7.82%), 90th percentile 10-m wind speed of a 10-year December-January-February (DJF) time series (5.64%), 25th percentile DJF 10-m wind speed (5.44%), and hillslope angle (5.24%). Elevation, relief, and terrain aspect show very low influence on SWE variability (<1%). We find that the GPM sensor provides the most robust regression results, and can be reliably used to estimate SWE in our study region. While forest cover and elevation have been integrated into many SWE algorithms, wind speed and long-term maximal snow depth have not. Our results show that wind redistribution of snow can have impacts on SWE, especially over large, flat, areas. Using our regression results, we have developed an understanding of sensor specific SWE uncertainties and their spatial patterns. The uncertainty maps developed in this study provide a first-order approximation of SWE-estimate reliability for much of HMA, and imply that high-fidelity SWE estimates can be produced for many high-elevation areas. (C) 2016 Elsevier Inc. All rights reserved.
This paper assesses the seasonality of the urban heat island (UHI) effect in the Greater London area (United Kingdom). Combining satellite-based observations and urban boundary layer climate modeling with the UrbClim model, the authors are able to address the seasonality of UHI intensity, on the basis of both land surface temperature (LST) and 2-m air temperature, for four individual times of the day (0130, 1030, 1330, and 2230 local time) and the daily means derived from them. An objective of this paper is to investigate whether the UHI intensities that are based on both quantities exhibit a similar hysteresis-like trajectory that is observed for LST when plotting the UHI intensity against the background temperature. The results show that the UrbClim model can satisfactorily reproduce both the observed urban rural LSTs and 2-m air temperatures as well as their differences and the hysteresis in the surface UHI. The hysteresis-like seasonality is largely absent in both the observed and modeled 2-m air temperatures, however. A sensitivity simulation of the UHI intensity to incoming solar radiation suggests that the hysteresis of the LST can mainly be attributed to the seasonal variation in incoming solar radiation.
Variational methods are employed in situations where exact Bayesian inference becomes intractable due to the difficulty in performing certain integrals. Typically, variational methods postulate a tractable posterior and formulate a lower bound on the desired integral to be approximated, e.g. marginal likelihood. The lower bound is then optimised with respect to its free parameters, the so-called variational parameters. However, this is not always possible as for certain integrals it is very challenging (or tedious) to come up with a suitable lower bound. Here, we propose a simple scheme that overcomes some of the awkward cases where the usual variational treatment becomes difficult. The scheme relies on a rewriting of the lower bound on the model log-likelihood. We demonstrate the proposed scheme on a number of synthetic and real examples, as well as on a real geophysical model for which the standard variational approaches are inapplicable.
The analytical evaluation of diurnal temperature variation in riverbed sediments provides detailed information on exchange fluxes between rivers and groundwater. The underlying assumption of the stationary, one-dimensional vertical flow field is frequently violated in natural systems where subsurface water flow often has a significant horizontal component. In this paper, we present a new methodology for identifying the geometry of the subsurface flow field using vertical temperature profiles. The statistical analyses are based on model optimisation and selection and are used to evaluate the shape of vertical amplitude ratio profiles. The method was applied to multiple profiles measured around in-stream geomorphological structures in a losing reach of a gravel bed river. The predominant subsurface flow field was systematically categorised in purely vertical and horizontal (hyporheic, parafluvial) components. The results highlight that river groundwater exchange flux at the head, crest and tail of geomorphological structures significantly deviated from the one-dimensional vertical flow, due to a significant horizontal component. The geometry of the subsurface water flow depended on the position around the geomorphological structures and on the river level. The methodology presented in this paper features great potential for characterising the spatial patterns and temporal dynamics of complex subsurface flow geometries by using measured temperature time series in vertical profiles. (C) 2016 Elsevier B.V. All rights reserved.
An innovative approach to improve SRTM DEM using multispectral imagery and artificial neural network
(2016)
Although the Shuttle Radar Topography Mission [SRTM) data are a publicly accessible Digital Elevation Model [DEM) provided at no cost, its accuracy especially at forested area is known to be limited with root mean square error (RMSE) of approx. 14 m in Singapore's forested area. Such inaccuracy is attributed to the 5.6 cm wavelength used by SRTM that does not penetrate vegetation well. This paper considers forested areas of central catchment of Singapore as a proof of concept of an approach to improve the SRTM data set. The approach makes full use of (1) the introduction of multispectral imagery (Landsat 8), of 30 m resolution, into SRTM data; (2) the Artificial Neural Network (ANN) to flex its known strengths in pattern recognition and; (3) a reference DEM of high accuracy (1 m) derived through the integration of stereo imaging of worldview-1 and extensive ground survey points. The study shows a series of significant improvements of the SRTM when assessed with the reference DEM of 2 different areas, with RMSE reduction of ∼68% (from 13.9 m to 4.4 m) and ∼52% (from 14.2 m to 6.7 m). In addition, the assessment of the resulting DEM also includes comparisons with simple denoising methodology (Low Pass Filter) and commercially available product called NEXTMap® World 30™.
The resonance frequency of the transmission response in layered half-space model is important in the study of site effect because it is the frequency where the shake-ability of the ground is enhanced significantly. In practice, it is often determined by the H/V ratio technique in which the peak frequency of recorded H/V spectral ratio is interpreted as the resonance frequency. Despite of its importance, there has not been any formula of the resonance frequency of the layered half-space structure. In this paper, a simple approximate formula of the fundamental resonance frequency is presented after an exact formula in explicit form of the response function of vertically SH incident wave is obtained. The formula is in similar form with the one used in H/V ratio technique but it reflects several major effects of the model to the resonance frequency such as the arrangement of layers, the impedance contrast between layers and the half-space. Therefore, it could be considered as an improved formula used in H/V ratio technique. The formula also reflects the consistency between two approaches of the H/V ratio technique based on SH body waves or Rayleigh surface waves on the peak frequency under high impedance contrast condition. This formula is in explicit form and, therefore, may be used in the direct and inverse problem efficiently. A numerical illustration of the improved formula for an actual layered half-space model already investigated by H/V ratio technique is presented to demonstrate its new features and its improvement to the currently used formula.
Surveys for more than 9,500 households were conducted in the growing seasons 2002/2003 or 2003/2004 in eleven African countries: Burkina Faso, Cameroon, Ghana, Niger and Senegal in western Africa; Egypt in northern Africa; Ethiopia and Kenya in eastern Africa; South Africa, Zambia and Zimbabwe in southern Africa. Households were chosen randomly in districts that are representative for key agro-climatic zones and farming systems. The data set specifies farming systems characteristics that can help inform about the importance of each system for a country’s agricultural production and its ability to cope with short- and long-term climate changes or extreme weather events. Further it informs about the location of smallholders and vulnerable systems and permits benchmarking agricultural systems characteristics.
Amides as thermo-sensitive tracers for investigating the thermal state of geothermal reservoirs
(2016)
The application of thermo-sensitive tracers is a promising technique for evaluating the thermal state of geothermal reservoirs. To extend the compound spectrum for hydrolyzable compounds to reservoir temperatures between 100 and 200 degrees C carboxamides were studied. The kinetic parameters of 17 self-synthesized amides were determined in hydrothermal batch and autoclave experiments. The influence of the molecular structure and the role of pH/pOH on hydrolysis kinetics were studied. Additionally, the thermal stabilities of the hydrolysis products were evaluated. The results demonstrate the high potential of tracers based on amide hydrolysis for use in medium enthalpy reservoirs. (C) 2016 Elsevier Ltd. All rights reserved.
We applied the geomorphic indices (hypsometry and stream length gradient) to evaluate the differential uplift of the central and southern Longmenshan, a mountain range characterized by rapid erosion, strong tectonic uplift, and devastating seismic hazards. The results of the geomorphic analysis indicate that the Beichuan-Yingxiu fault and the Shuangshi-Dachuan fault act as major tectonic boundaries separating areas experiencing rapid uplift from slow uplift. The results of the geomorphic analysis also suggest that the Beichuan-Yingxiu fault is the most active fault with the largest relative uplift rates compared to the rest of the faults in the Longmenshan fault system. We compared reflected relative uplift rates based on the hypsometry and stream length gradient indices with geological/geodetic absolute rates. Along-strike and across-strike variations in the hypsometry and stream length gradient correlate with the spatial patterns derived from the apatite fission track exhumation rates, the leveling-derived uplift rate, and coseismic vertical displacements during the 2008 Wenchuan earthquake. These data defined multiple fault relationships in a complex thrust zone and provided geomorphic evidence to evaluate the potential seismic hazards of the southern Longmenshan range.
Water research is introduced from the combined perspectives of natural and social science and cases of citizen and stakeholder coproduction of knowledge. Using the overarching notion of transdisciplinarity, we examine how interdisciplinary and participatory water research has taken place and could be developed further. It becomes apparent that water knowledge is produced widely within society, across certified disciplinary experts and noncertified expert stakeholders and citizens. However, understanding and management interventions may remain partial, or even conflicting, as much research across and between traditional disciplines has failed to integrate disciplinary paradigms due to philosophical, methodological, and communication barriers. We argue for more agonistic relationships that challenge both certified and noncertified knowledge productively. These should include examination of how water research itself embeds and is embedded in social context and performs political work. While case studies of the cultural and political economy of water knowledge exist, we need more empirical evidence on how exactly culture, politics, and economics have shaped this knowledge and how and at what junctures this could have turned out differently. We may thus channel the coproductionist critique productively to bring perspectives, alternative knowledges, and implications into water politics where they were not previously considered; in an attempt to counter potential lock-in to particular water policies and technologies that may be inequitable, unsustainable, or unacceptable. While engaging explicitly with politics, transdisciplinary water research should remain attentive to closing down moments in the research process, such as framings, path-dependencies, vested interests, researchers’ positionalities, power, and scale.
We present a new, seismologically consistent expression for the total area and volume of populations of earthquake-triggered landslides. This model builds on a set of scaling relationships between key parameters, such as landslide spatial density, seismic ground acceleration, fault length, earthquake source depth, and seismic moment. To assess the model we have assembled and normalized a catalog of landslide inventories for 40 shallow, continental earthquakes. Low landscape steepness causes systematic overprediction of the total area and volume of landslides. When this effect is accounted for, the model predicts the total landslide volume of 63% of 40 cases to within a factor 2 of the volume estimated from observations (R-2 = 0.76). The prediction of total landslide area is also sensitive to the landscape steepness, but less so than the total volume, and it appears to be sensitive to controls on the landslide size-frequency distribution, and possibly the shaking duration. Some outliers are likely associated with exceptionally strong rock mass in the epicentral area, while others may be related to seismic source complexities ignored by the model. However, the close match between prediction and estimate for about two thirds of cases in our database suggests that rock mass strength is similar in many cases and that our simple seismic model is often adequate, despite the variety of lithologies and tectonic settings covered. This makes our expression suitable for integration into landscape evolution models and application to the anticipation or rapid assessment of secondary hazards associated with earthquakes.
Extra-tropical circulation systems impede poleward moisture advection by the Indian Summer Monsoon. In this context, the Himalayan range is believed to insulate the south Asian circulation from extra-tropical influences and to delineate the northern extent of the Indian Summer Monsoon in central Asia. Paleoclimatic evidence, however, suggests increased moisture availability in the Early Holocene north of the Himalayan range which is attributed to an intensification of the Indian Summer Monsoon. Nevertheless, mechanisms leading to a surpassing of the Himalayan range and the northern maximum extent of summer monsoonal influence remain unknown. Here we show that the Kunlun barrier on the northern Tibetan Plateau [similar to 36 degrees N] delimits Indian Summer Monsoon precipitation during the Holocene. The presence of the barrier relocates the insulation effect 1,000 km further north, allowing a continental low intensity branch of the Indian Summer Monsoon which is persistent throughout the Holocene. Precipitation intensities at its northern extent seem to be driven by differentiated solar heating of the Northern Hemisphere indicating dependency on energy-gradients rather than absolute radiation intensities. The identified spatial constraints of monsoonal precipitation will facilitate the prediction of future monsoonal precipitation patterns in Central Asia under varying climatic conditions.
A partially non-ergodic ground-motion prediction equation is estimated for Europe and the Middle East. Therefore, a hierarchical model is presented that accounts for regional differences. For this purpose, the scaling of ground-motion intensity measures is assumed to be similar, but not identical in different regions. This is achieved by assuming a hierarchical model, where some coefficients are treated as random variables which are sampled from an underlying global distribution. The coefficients are estimated by Bayesian inference. This allows one to estimate the epistemic uncertainty in the coefficients, and consequently in model predictions, in a rigorous way. The model is estimated based on peak ground acceleration data from nine different European/Middle Eastern regions. There are large differences in the amount of earthquakes and records in the different regions. However, due to the hierarchical nature of the model, regions with only few data points borrow strength from other regions with more data. This makes it possible to estimate a separate set of coefficients for all regions. Different regionalized models are compared, for which different coefficients are assumed to be regionally dependent. Results show that regionalizing the coefficients for magnitude and distance scaling leads to better performance of the models. The models for all regions are physically sound, even if only very few earthquakes comprise one region.
In the past, floods were basically managed by flood control mechanisms. The focus was set on the reduction of flood hazard. The potential consequences were of minor interest. Nowadays river flooding is increasingly seen from the risk perspective, including possible consequences. Moreover, the large-scale picture of flood risk became increasingly important for disaster management planning, national risk developments and the (re-) insurance industry. Therefore, it is widely accepted that risk-orientated flood management ap-proaches at the basin-scale are needed. However, large-scale flood risk assessment methods for areas of several 10,000 km² are still in early stages. Traditional flood risk assessments are performed reach wise, assuming constant probabilities for the entire reach or basin. This might be helpful on a local basis, but where large-scale patterns are important this approach is of limited use. Assuming a T-year flood (e.g. 100 years) for the entire river network is unrealistic and would lead to an overestimation of flood risk at the large scale. Due to the lack of damage data, additionally, the probability of peak discharge or rainfall is usually used as proxy for damage probability to derive flood risk. With a continuous and long term simulation of the entire flood risk chain, the spatial variability of probabilities could be consider and flood risk could be directly derived from damage data in a consistent way.
The objective of this study is the development and application of a full flood risk chain, appropriate for the large scale and based on long term and continuous simulation. The novel approach of ‘derived flood risk based on continuous simulations’ is introduced, where the synthetic discharge time series is used as input into flood impact models and flood risk is directly derived from the resulting synthetic damage time series.
The bottleneck at this scale is the hydrodynamic simu-lation. To find suitable hydrodynamic approaches for the large-scale a benchmark study with simplified 2D hydrodynamic models was performed. A raster-based approach with inertia formulation and a relatively high resolution of 100 m in combination with a fast 1D channel routing model was chosen.
To investigate the suitability of the continuous simulation of a full flood risk chain for the large scale, all model parts were integrated into a new framework, the Regional Flood Model (RFM). RFM consists of the hydrological model SWIM, a 1D hydrodynamic river network model, a 2D raster based inundation model and the flood loss model FELMOps+r. Subsequently, the model chain was applied to the Elbe catchment, one of the largest catchments in Germany. For the proof-of-concept, a continuous simulation was per-formed for the period of 1990-2003. Results were evaluated / validated as far as possible with available observed data in this period. Although each model part introduced its own uncertainties, results and runtime were generally found to be adequate for the purpose of continuous simulation at the large catchment scale.
Finally, RFM was applied to a meso-scale catchment in the east of Germany to firstly perform a flood risk assessment with the novel approach of ‘derived flood risk assessment based on continuous simulations’. Therefore, RFM was driven by long term synthetic meteorological input data generated by a weather generator. Thereby, a virtual time series of climate data of 100 x 100 years was generated and served as input to RFM providing subsequent 100 x 100 years of spatially consistent river discharge series, inundation patterns and damage values. On this basis, flood risk curves and expected annual damage could be derived directly from damage data, providing a large-scale picture of flood risk. In contrast to traditional flood risk analysis, where homogenous return periods are assumed for the entire basin, the presented approach provides a coherent large-scale picture of flood risk. The spatial variability of occurrence probability is respected. Additionally, data and methods are consistent. Catchment and floodplain processes are repre-sented in a holistic way. Antecedent catchment conditions are implicitly taken into account, as well as physical processes like storage effects, flood attenuation or channel–floodplain interactions and related damage influencing effects. Finally, the simulation of a virtual period of 100 x 100 years and consequently large data set on flood loss events enabled the calculation of flood risk directly from damage distributions. Problems associated with the transfer of probabilities in rainfall or peak runoff to probabilities in damage, as often used in traditional approaches, are bypassed.
RFM and the ‘derived flood risk approach based on continuous simulations’ has the potential to provide flood risk statements for national planning, re-insurance aspects or other questions where spatially consistent, large-scale assessments are required.
A new view of Ecuador's complex geodynamics has been developed in the course of modeling seismic source zones for probabilistic seismic hazard analysis. This study focuses on two aspects of the plates' interaction at a continental scale: (a) age-related differences in rheology between Farallon and Nazca plates—marked by the Grijalva rifted margin and its inland projection—as they subduct underneath central Ecuador, and (b) the rapidly changing convergence obliquity resulting from the convex shape of the South American northwestern continental margin. Both conditions satisfactorily explain several characteristics of the observed seismicity and of the interseismic coupling. Intermediate-depth seismicity reveals a severe flexure in the Farallon slab as it dips and contorts at depth, originating the El Puyo seismic cluster. The two slabs position and geometry below continental Ecuador also correlate with surface expressions observable in the local and regional geology and tectonics. The interseismic coupling is weak and shallow south of the Grijalva rifted margin and increases northward, with a heterogeneous pattern locally associated to the Carnegie ridge subduction. High convergence obliquity is responsible for the North Andean Block northeastward movement along localized fault systems. The Cosanga and Pallatanga fault segments of the North Andean Block-South American boundary concentrate most of the seismic moment release in continental Ecuador. Other inner block faults located along the western border of the inter-Andean Depression also show a high rate of moderate-size earthquake production. Finally, a total of 19 seismic source zones were modeled in accordance with the proposed geodynamic and neotectonic scheme.
This manuscript proposes a method to assess hydrological drought in semi-arid environments under high impoundment rate and applies it to the semi-arid Jaguaribe River basin in Brazil. It analyzes droughts (1) in the largest reservoir systems; (2) in the Upper Basin, considering 4744 reservoirs, 800 wells and almost 18,000 cisterns; and (3) in reservoirs of different sizes during multiyear droughts. Results show that the water demand is constrained in the basin; hydrological and meteorological droughts are often out of phase; there is a negative correlation between storage level and drought severity; and the small systems cannot cope with long-term droughts.
The molecular biomarker composition of two sediment cores from Sanabria Lake (NW Iberian Peninsula) and a survey of modern plants in the watershed provide a reconstruction of past vegetation and landscape dynamics since deglaciation. During a proglacial stage in Lake Sanabria (prior to 14.7 cal ka BP), very low biomarker concentration and carbon preference index (CPI) values similar to 1 suggest that the n-alkanes could have derived from eroded ancient sediment sources or older organic matter with high degree of maturity. During the Late glacial (14.7-11.7 cal ka BP) and the Holocene (last 11.7 cal ka BP) intervals with higher biomarker and triterpenoid concentrations (high %nC(29) , nC(31) alkanes), higher CPI and average carbon length (ACL), and lower P-aq (proportion of aquatic plants) are indicative of major contribution of vascular land plants from a more forested watershed (e.g. Mid Holocene period 7.0-4.0 cal ka BP). Lower biomarker concentrations (high %nC(27) alkanes), CPI and ACL values responded to short phases with decreased allochthonous contribution into the lake that correspond to centennial-scale periods of regional forest decline (e.g. 4-3 ka BP, Roman deforestation after 2.0 ka, and some phases of the LIA, seventeenth-nineteenth centuries). Human activities in the watershed were significant during early medieval times (1.3-1.0 cal ka BP) and since 1960 CE, in both cases associated with relatively higher productivity stages in the lake (lower biomarker and triterpenoid concentrations, high %nC(23) and %nC(31) respectively, lower ACL and CPI values and higher P-aq). The lipid composition of Sanabria Lake sediments indicates a major allochthonous (watershed-derived) contribution to the organic matter budget since deglaciation, and a dominant oligotrophic status during the lake history. The study constrains the climate and anthropogenic forcings and watershed versus lake sources in organic matter accumulation processes and helps to design conservation and management policies in mountain, oligotrophic lakes.
The importance of cultural ecosystem services in agricultural landscapes is increasingly recognized as agricultural scale enlargement and abandonment affect aesthetic and recreational values of agricultural landscapes. Landscape preference studies addressing these type of values often yield context-specific outcomes, limiting the applicability of their outcomes in landscape policy. Our approach measures the relative importance of landscape features across agricultural landscapes. This approach was applied in the agricultural landscapes of Winterswijk, The Netherlands (n=191) and the Markische Schweiz, Germany (n=113) among visitors in the agricultural landscape. We set up a parallel designed choice experiment, using regionally specific, photorealistic visualizations of four comparable landscape attributes. In the Dutch landscape visitors highly value hedgerows and tree lines, whereas groups of trees and crop diversity are highly valued in the German landscape. Furthermore, we find that differences in relative preference for landscape attributes are, to some extent, explained by socio-cultural background variables such as education level and affinity with agriculture of the visitors. This approach contributes to a better understanding of the cross-regional variation of aesthetic and recreational values and how these values relate to characteristics of the agricultural landscape, which could support the integration of cultural services in landscape policy. (C) 2015 Elsevier B.V. All rights reserved.
Ice complex deposits are characteristic, ice-rich formations in northern East Siberia and represent an important part in the arctic carbon pool. Recently, these late Quaternary deposits are the objective of numerous investigations typically relying on outcrop and borehole data. Many of these studies can benefit from a 3D structural model of the subsurface for upscaling their observations or for constraining estimations of inventories, such as the local carbon stock. We have addressed this problem of structural imaging by 3D ground-penetrating radar (GPR), which, in permafrost studies, has been primarily used for 2D profiling. We have used a 3D kinematic GPR surveying strategy at a field site located in the New Siberian Archipelago on top of an ice complex. After applying a 3D GPR processing sequence, we were able to trace two horizons at depths below 20 m. Taking available borehole and outcrop data into account, we have interpreted these two features as interfaces of major lithologic units and derived a 3D cryostratigraphic model of the subsurface. Our data example demonstrated that a 3D surveying and processing strategy was crucial at our field site and showed the potential of 3D GPR to image geologic structures in complex ice-rich permafrost landscapes.
Here, we study the 3-D subduction initiation process induced by the interaction between a hot thermochemical mantle plume and oceanic lithosphere using thermo-mechanical viscoplastic finite difference marker-in-cell models. Our numerical modeling results show that self-sustaining subduction is induced by plume-lithosphere interaction when the plume is sufficiently buoyant, the oceanic lithosphere is sufficiently old and the plate is weak enough to allow the buoyant plume to. pass through it. Subduction initiation occurs following penetration of the lithosphere by the hot plume and the downward displacement of broken, nearly circular segments of lithosphere (proto-slabs) as a result of partially molten plume rocks overriding the proto-slabs. Our experiments show four different deformation regimes in response to plume-lithosphere interaction: a) self-sustaining subduction initiation, in which subduction becomes self-sustaining; b) frozen subduction initiation, in which subduction stops at shallow depths; c) slab break-off, in which the subducting circular slab breaks off soon after formation; and d) plume underplating, in which the plume does not pass through the lithosphere and instead spreads beneath it (i.e., failed subduction initiation). These regimes depend on several parameters, such as the size, composition, and temperature of the plume, the brittle/plastic strength and age of the oceanic lithosphere, and the presence/absence of lithospheric heterogeneities. The results show that subduction initiates and becomes self-sustaining when the lithosphere is older than 10 Myr and the non dimensional ratio of the plume buoyancy force and lithospheric strength above the plume is higher than approximately 2. The outcomes of our numerical experiments are applicable for subduction initiation in the modern and Precambrian Earth and for the origin of plume-related corona structures on Venus. (C) 2016 Elsevier B.V. All rights reserved.
The Earth’s shallow subsurface with sedimentary cover acts as a waveguide to any incoming wavefield. Within the framework of my thesis, I focused on the characterization of this shallow subsurface within tens to few hundreds of meters of sediment cover. I imaged the seismic 1D shear wave velocity (and possibly the 1D compressional wave velocity). This information is not only required for any seismic risk assessment, geotechnical engineering or microzonation activities, but also for exploration and global seismology where site effects are often neglected in seismic waveform modeling.
First, the conventional frequency-wavenumber (f - k) technique is used to derive the dispersion characteristic of the propagating surface waves recorded using distinct arrays of seismometers in 1D and 2D configurations. Further, the cross-correlation technique is applied to seismic array data to estimate the Green’s function between receivers pairs combination assuming one is the source and the other the receiver. With the consideration of a 1D media, the estimated cross-correlation Green’s functions are sorted with interstation distance in a virtual 1D active seismic experiment. The f - k technique is then used to estimate the dispersion curves. This integrated analysis is important for the interpretation of a large bandwidth of the phase velocity dispersion curves and therefore improving the resolution of the estimated 1D Vs profile.
Second, the new theoretical approach based on the Diffuse Field Assumption (DFA) is used for the interpretation of the observed microtremors H/V spectral ratio. The theory is further extended in this research work to include not only the interpretation of the H/V measured at the surface, but also the H/V measured at depths and in marine environments. A modeling and inversion of synthetic H/V spectral ratio curves on simple predefined geological structures shows an almost perfect recovery of the model parameters (mainly Vs and to a lesser extent Vp). These results are obtained after information from a receiver at depth has been considered in the inversion.
Finally, the Rayleigh wave phase velocity information, estimated from array data, and the H/V(z, f) spectral ratio, estimated from a single station data, are combined and inverted for the velocity profile information. Obtained results indicate an improved depth resolution in comparison to estimations using the phase velocity dispersion curves only. The overall estimated sediment thickness is comparable to estimations obtained by inverting the full micortremor H/V spectral ratio.
We present an algorithm that performs sequentially one-dimensional inversion of subsurface magnetic permeability and electrical conductivity by using multi-configuration electromagnetic induction sensor data. The presented method is based on the conversion of the in-phase and out-of-phase data into effective magnetic permeability and electrical conductivity of the equivalent homogeneous half-space. In the case of small-offset systems, such as portable electromagnetic induction sensors, for which in-phase and out-of-phase data are moderately coupled, the effective half-space magnetic permeability and electrical conductivity can be inverted sequentially within an iterative scheme. We test and evaluate the proposed inversion strategy using synthetic and field examples. First, we apply it to synthetic data for some highly magnetic environments. Then, the method is tested on real field data acquired in a basaltic environment to image a formation of archaeological interest. These examples demonstrate that a joint interpretation of in-phase and out-of-phase data leads to a better characterisation of the subsurface in magnetic environments such as volcanic areas.