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The knowledge of the largest expected earthquake magnitude in a region is one of the key issues in probabilistic seismic hazard calculations and the estimation of worst-case scenarios. Earthquake catalogues are the most informative source of information for the inference of earthquake magnitudes. We analysed the earthquake catalogue for Central Asia with respect to the largest expected magnitudes m(T) in a pre-defined time horizon T-f using a recently developed statistical methodology, extended by the explicit probabilistic consideration of magnitude errors. For this aim, we assumed broad error distributions for historical events, whereas the magnitudes of recently recorded instrumental earthquakes had smaller errors. The results indicate high probabilities for the occurrence of large events (M >= 8), even in short time intervals of a few decades. The expected magnitudes relative to the assumed maximum possible magnitude are generally higher for intermediate-depth earthquakes (51-300 km) than for shallow events (0-50 km). For long future time horizons, for example, a few hundred years, earthquakes with M >= 8.5 have to be taken into account, although, apart from the 1889 Chilik earthquake, it is probable that no such event occurred during the observation period of the catalogue.
Earthquake catalogs are probably the most informative data source about spatiotemporal seismicity evolution. The catalog quality in one of the most active seismogenic zones in the world, Japan, is excellent, although changes in quality arising, for example, from an evolving network are clearly present. Here, we seek the best estimate for the largest expected earthquake in a given future time interval from a combination of historic and instrumental earthquake catalogs. We extend the technique introduced by Zoller et al. (2013) to estimate the maximum magnitude in a time window of length T-f for earthquake catalogs with varying level of completeness. In particular, we consider the case in which two types of catalogs are available: a historic catalog and an instrumental catalog. This leads to competing interests with respect to the estimation of the two parameters from the Gutenberg-Richter law, the b-value and the event rate lambda above a given lower-magnitude threshold (the a-value). The b-value is estimated most precisely from the frequently occurring small earthquakes; however, the tendency of small events to cluster in aftershocks, swarms, etc. violates the assumption of a Poisson process that is used for the estimation of lambda. We suggest addressing conflict by estimating b solely from instrumental seismicity and using large magnitude events from historic catalogs for the earthquake rate estimation. Applying the method to Japan, there is a probability of about 20% that the maximum expected magnitude during any future time interval of length T-f = 30 years is m >= 9.0. Studies of different subregions in Japan indicates high probabilities for M 8 earthquakes along the Tohoku arc and relatively low probabilities in the Tokai, Tonankai, and Nankai region. Finally, for scenarios related to long-time horizons and high-confidence levels, the maximum expected magnitude will be around 10.
The innovative dual-purpose chicken approach aims at contributing to the transition towards sustainable poultry production by avoiding the culling of male chickens. To successfully integrate sustainability aspects into innovation, goal congruency among actors and clearly communicating the added value within the actor network and to consumers is needed. The challenge of identifying common sustainability goals calls for decision support tools. The objectives of our research were to investigate whether the tool could assist in improving communication and marketing with respect to sustainability and optimizing the value chain organization. Three actor groups participated in the tool application, in which quantitative and qualitative data were collected. The results showed that there were manifold sustainability goals within the innovation network, but only some goals overlapped, and the perception of their implementation also diverged. While easily marketable goals such as ‘animal welfare’ were perceived as being largely implemented, economic goals were prioritized less often, and the implementation was perceived as being rather low. By visualizing congruencies and differences in the goals, the tool helped identify fields of action, such as improved information flows and prompted thinking processes. We conclude that the tool is useful for managing complex decision processes with several actors involved.
Nature-based solutions (NBS) are inspired and supported by nature but designed by humans. Historically, governmental stakeholders have aimed to control nature using a top-down approach; more recently, environmental governance has shifted to collaborative planning. Polycentric governance and co-creation procedures, which include a large spectrum of stakeholders, are assumed to be more effective in the management of public goods than traditional approaches. In this context, NBS projects should benefit from strong collaborative governance models, and the European Union is facilitating and encouraging such models. While some theoretical approaches exist, setting-up the NBS co-creation process (namely co-design and co-implementation) currently relies mostly on self-organized stakeholders rather than on strategic decisions. As such, systematic methods to identify relevant stakeholders seem to be crucial to enable higher planning efficiency, reduce bottlenecks and time needed for planning, designing, and implementing NBS. In this context, this contribution is based on the analysis of 16 NBS and 359 stakeholders. Real-life constellations are compared to theoretical typologies, and a systematic stakeholder mapping method to support co-creation is presented. Rather than making one-fit-all statements about the "right" stakeholders, the contribution provides insights for those "in charge" to strategically consider who might be involved at each stage of the NBS project.
We traced diatom composition and diversity through time using diatom-derived sedimentary ancient DNA (sedaDNA) from eastern continental slope sediments off Kamchatka (North Pacific) by applying a short, diatom-specific marker on 63 samples in a DNA metabarcoding approach. The sequences were assigned to diatoms that are common in the area and characteristic of cold water. SedaDNA allowed us to observe shifts of potential lineages from species of the genus Chaetoceros that can be related to different climatic phases, suggesting that pre-adapted ecotypes might have played a role in the long-term success of species in areas of changing environmental conditions. These sedaDNA results complement our understanding of the long-term history of diatom assemblages and their general relationship to environmental conditions of the past. Sea-ice diatoms (Pauliella taeniata [Grunow] Round & Basson, Attheya septentrionalis [ostrup] R. M. Crawford and Nitzschia frigida [Grunow]) detected during the late glacial and Younger Dryas are in agreement with previous sea-ice reconstructions. A positive correlation between pennate diatom richness and the sea-ice proxy IP25 suggests that sea ice fosters pennate diatom richness, whereas a negative correlation with June insolation and temperature points to unfavorable conditions during the Holocene. A sharp increase in proportions of freshwater diatoms at similar to 11.1 cal kyr BP implies the influence of terrestrial runoff and coincides with the loss of 42% of diatom sequence variants. We assume that reduced salinity at this time stabilized vertical stratification which limited the replenishment of nutrients in the euphotic zone.
The Fram Strait is an area with a relatively low and irregular distribution of diatom microfossils in surface sediments, and thus microfossil records are scarce, rarely exceed the Holocene, and contain sparse information about past richness and taxonomic composition. These attributes make the Fram Strait an ideal study site to test the utility of sedimentary ancient DNA (sedaDNA) metabarcoding. Amplifying a short, partial rbcL marker from samples of sediment core MSM05/5-712-2 resulted in 95.7 % of our sequences being assigned to diatoms across 18 different families, with 38.6 % of them being resolved to species and 25.8 % to genus level. Independent replicates show a high similarity of PCR products, especially in the oldest samples. Diatom sedaDNA richness is highest in the Late Weichselian and lowest in Mid- and Late Holocene samples. Taxonomic composition is dominated by cold-water and sea-ice-associated diatoms and suggests several reorganisations – after the Last Glacial Maximum, after the Younger Dryas, and after the Early and after the Mid-Holocene. Different sequences assigned to, amongst others, Chaetoceros socialis indicate the detectability of intra-specific diversity using sedaDNA. We detect no clear pattern between our diatom sedaDNA record and the previously published IP25 record of this core, although proportions of pennate diatoms increase with higher IP25 concentrations and proportions of Nitzschia cf. frigida exceeding 2 % of the assemblage point towards past sea-ice presence.
The influence of land-use changes on soil hydraulic properties : implications for runoff generation
(2006)
Changes in soil hydraulic properties following ecosystem disturbances can become relevant for regional water cycles depending on the prevailing rainfall regime. In a tropical montane rainforest ecosystem in southern Ecuador, plot- scale investigations revealed that man-made disturbances were accompanied by a decrease in mean saturated hydraulic conductivity (Ks), whereas mean Ks of two different aged landslides was undistinguishable from the reference forest. Ks spatial structure weakened after disturbances in the topsoil. We used this spatial-temporal information combined with local rain intensities to assess the probability of impermeable soil layers under undisturbed, disturbed, and regenerating land-cover types. We furthermore compared the Ecuadorian man-made disturbance cycle with a similar land-use sequence in a tropical lowland rainforest region in Brazil. The studied montane rainforest is characterized by prevailing vertical flowpaths in the topsoil, whereas larger rainstorms in the study area potentially result in impermeable layers below 20 cm depth. In spite of the low frequency of such higher-intensity events, they transport a high portion of the annual runoff and may therefore significant for the regional water cycle. Hydrological flowpaths under two studied landslides are similar to the natural forest except for a somewhat higher probability of impermeable layer formation in the topsoil of the 2-year-old landslide. In contrast, human disturbances likely affect near-surface hydrology. Under a pasture and a young fallow, impermeable layers potentially develop already in the topsoil for larger rain events. A 10-year-old fallow indicates regeneration towards the original vertical flowpaths, though the land-use signal was still detectable. The consequences of land-cover change on near-surface hydrological behaviour are of similar magnitude in the tropical montane and the lowland rainforest region. This similarity can be explained by a more pronounced drop of soil permeability after pasture establishment in the montane rainforest region in spite of the prevailing much lower rain intensities.
The investigation of throughfall patterns has received considerable interest over the last decades. And yet, the geographical bias of pertinent previous studies and their methodologies and approaches to data analysis cast a doubt on the general validity of claims regarding spatial and temporal patterns of throughfall. We employed 220 collectors in a 1-ha plot of semideciduous tropical rain forest in Panama and sampled throughfall during a period of 14 months. Our analysis of spatial patterns is based on 60 data sets, whereas the temporal analysis comprises 91 events. Both data sets show skewed frequency distributions. When skewness arises from large outliers, the classical, nonrobust variogram estimator overestimates the sill variance and, in some cases, even induces spurious autocorrelation structures. In these situations, robust variogram estimation techniques offer a solution. Throughfall in our plot typically displayed no or only weak spatial autocorrelations. In contrast, temporal correlations were strong, that is, wet and dry locations persisted over consecutive wet seasons. Interestingly, seasonality and hence deciduousness had no influence on spatial and temporal patterns. We argue that if throughfall patterns are to have any explanatory power with respect to patterns of near-surface processes, data analytical artifacts must be ruled out lest spurious correlation be confounded with causality; furthermore, temporal stability over the domain of interest is essential.
Spatio-temporal patterns of throughfall and solute deposition in an open tropical rain forest
(2008)
Earthquake site responses or site effects are the modifications of surface geology to seismic waves. How well can we predict the site effects (average over many earthquakes) at individual sites so far? To address this question, we tested and compared the effectiveness of different estimation techniques in predicting the outcrop Fourier site responses separated using the general inversion technique (GIT) from recordings. Techniques being evaluated are (a) the empirical correction to the horizontal-to-vertical spectral ratio of earthquakes (c-HVSR), (b) one-dimensional ground response analysis (GRA), and (c) the square-root-impedance (SRI) method (also called the quarter-wavelength approach). Our results show that c-HVSR can capture significantly more site-specific features in site responses than both GRA and SRI in the aggregate, especially at relatively high frequencies. c-HVSR achieves a "good match" in spectral shape at similar to 80%-90% of 145 testing sites, whereas GRA and SRI fail at most sites. GRA and SRI results have a high level of parametric and/or modeling errors which can be constrained, to some extent, by collecting on-site recordings.
Increasing interests in hydrocarbon resources at depths have drawn greater attentions to the deeply-buried carbonate reservoirs in the Tarim Basin in China. In this study, the cyclic dolomite rocks of Upper Cambrian Lower Qiulitag Group from four outcrop sections in northwestern Tarim Basin were selected to investigate and evaluate the petrophysical properties in relation to depositional facies and cyclicity. The Lower Qiulitag Group includes ten lithofacies, which were deposited in intermediate to shallow subtidal, restricted shallow subtidal, intertidal, and supratidal environments on a carbonate ramp system. These lithofacies are vertically stacked into repeated shallowing-upward, meter-scale cycles which are further grouped into six third-order depositional sequences (Sq1 to Sq6). There are variable types of pore spaces in the Lower Qiulitag Group dolomite rocks, including interparticle, intraparticle, and fenestral pores of primary origin, inter crystal, and vuggy pores of late diagenetic modification. The porosity in the dolomites is generally facies-selective as that the microbially-originated thrombolites and stromatolites generally yield a relatively high porosity. In contrast, the high-energy ooidal grainstones generally have very low porosity. In this case, the microbialite-based peritidal cycles and peritidal cycle-dominated highstand (or regressive) successions have relatively high volumes of pore spaces, although highly fluctuating (or vertical inhomogeneous). Accordingly, the grainstone-based subtidal cycles and subtidal cycle-dominated transgressive successions generally yield extremely low porosity. This scenario indicates that porosity development and preservation in the thick dolomite successions are primarily controlled by depositional facies which were influenced by sea-level fluctuations of different orders and later diagenetic overprinting.
This study presents an application of an innovative sampling strategy to assess soil moisture dynamics in a headwater of the Weißeritz in the German eastern Ore Mountains. A grassland site and a forested site were instrumented with two Spatial TDR clusters (STDR) that consist of 39 and 32 coated TDR probes of 60 cm length. Distributed time series of vertically averaged soil moisture data from both sites/ensembles were analyzed by statistical and geostatistical methods. Spatial variability and the spatial mean at the forested site were larger than at the grassland site. Furthermore, clustering of TDR probes in combination with long-term monitoring allowed identification of average spatial covariance structures at the small field scale for different wetness states. The correlation length of soil water content as well as the sill to nugget ratio at the grassland site increased with increasing average wetness and but, in contrast, were constant at the forested site. As soil properties at both the forested and grassland sites are extremely variable, this suggests that the correlation structure at the forested site is dominated by the pattern of throughfall and interception. We also found a strong correlation between average soil moisture dynamics and runoff coefficients of rainfall-runoff events observed at gauge Rehefeld, which explains almost as much variability in the runoff coefficients as pre-event discharge. By combining these results with a recession analysis we derived a first conceptual model of the dominant runoff mechanisms operating in this catchment. Finally, long term simulations with a physically based hydrological model were in good/acceptable accordance with the time series of spatial average soil water content observed at the forested site and the grassland site, respectively. Both simulations used a homogeneous soil setup that closely reproduces observed average soil conditions observed at the field sites. This corroborates the proposed sampling strategy of clustering TDR probes in typical functional units is a promising technique to explore the soil moisture control on runoff generation. Long term monitoring of such sites could maybe yield valuable information for flood warning. The sampling strategy helps furthermore to unravel different types of soil moisture variability.
[1] Observations of hydrological response often exhibit considerable scatter that is difficult to interpret. In this paper, we examine runoff production of 53 sprinkling experiments on the water-repellent soils in the southern Alps of Switzerland; simulated plot scale tracer transport in the macroporous soils at the Weiherbach site, Germany; and runoff generation data from the 2.3-km(2) Tannhausen catchment, Germany, that has cracking soils. The response at the three sites is highly dependent on the initial soil moisture state as a result of the threshold dynamics of the systems. A simple statistical model of threshold behavior is proposed to help interpret the scatter in the observations. Specifically, the model portrays how the inherent macrostate uncertainty of initial soil moisture translates into the scatter of the observed system response. The statistical model is then used to explore the asymptotic pattern of predictability when increasing the number of observations, which is normally not possible in a field study. Although the physical and chemical mechanisms of the processes at the three sites are different, the predictability patterns are remarkably similar. Predictability is smallest when the system state is close to the threshold and increases as the system state moves away from it. There is inherent uncertainty in the response data that is not measurement error but is related to the observability of the initial conditions.
Stofftransport in einem Lösseinzugsgebiet: Experimentelle Evidenz und numerische Modellierung.
(2004)
[1] This paper examines the effect of uncertain initial soil moisture on hydrologic response at the plot scale (1 m(2)) and the catchment scale (3.6 km(2)) in the presence of threshold transitions between matrix and preferential flow. We adopt the concepts of microstates and macrostates from statistical mechanics. The microstates are the detailed patterns of initial soil moisture that are inherently unknown, while the macrostates are specified by the statistical distributions of initial soil moisture that can be derived from the measurements typically available in field experiments. We use a physically based model and ensure that it closely represents the processes in the Weiherbach catchment, Germany. We then use the model to generate hydrologic response to hypothetical irrigation events and rainfall events for multiple realizations of initial soil moisture microstates that are all consistent with the same macrostate. As the measures of uncertainty at the plot scale we use the coefficient of variation and the scaled range of simulated vertical bromide transport distances between realizations. At the catchment scale we use similar statistics derived from simulated flood peak discharges. The simulations indicate that at both scales the predictability depends on the average initial soil moisture state and is at a minimum around the soil moisture value where the transition from matrix to macropore flow occurs. The predictability increases with rainfall intensity. The predictability increases with scale with maximum absolute errors of 90 and 32% at the plot scale and the catchment scale, respectively. It is argued that even if we assume perfect knowledge on the processes, the level of detail with which one can measure the initial conditions along with the nonlinearity of the system will set limits to the repeatability of experiments and limits to the predictability of models at the plot and catchment scales
This paper examines the effect of spatially variable initial soil moisture and spatially variable precipitation on predictive uncertainty of simulated catchment scale runoff response in the presence of threshold processes. The underlying philosophy is to use a physically based hydrological model named CATFLOW as a virtual landscape, assuming perfect knowledge of the processes. The model, which in particular conceptualizes preferential flow as threshold process, was developed based on intensive process and parameter studies and has already been successfully applied to simulate flow and transport at different scales and catchments. Study area is the intensively investigated Weiherbach catchment. Numerous replicas of spatially variable initial soil moisture or spatially variable precipitation with the same geostatistical properties are conditioned to observed soil moisture and precipitation data and serve as initial and boundary conditions for the model during repeated simulations. The effect of spatially soil moisture on modeling catchment runoff response was found to depend strongly on average saturation of the catchment. Different realizations of initial soil moisture yielded strongly different hydrographs for intermediate initial soil moisture as well as in dry catchment conditions; in other states the effect was found to be much lower. This is clearly because of the threshold nature of preferential flow as well as the threshold nature of Hortonian production of overland flow. It was shown furthermore that the spatial pattern of a key parameter (macroporosity) that determined threshold behavior is of vast importance for the model response. The estimation of these patterns, which is mostly done based on sparse observations and expert knowledge, is a major source for predictive model uncertainty. Finally, it was shown that the usage of biased, i.e. spatially homogenized precipitation, input during parameter estimation yields a biased model structure, which gives poor results when used with highly distributed input. If spatially highly resolved precipitation was used during model parameter estimation. the predictive uncertainty of the model was clearly reduced. (c) 2005 Elsevier B.V. All rights reserved
Transverse dispersion, or tracer spreading orthogonal to the mean flow direction, which is relevant e.g, for quantifying bio-degradation of contaminant plumes or mixing of reactive solutes, has been studied in the literature less than the longitudinal one. Inferring transverse dispersion coefficients from field experiments is a difficult and error-prone task, requiring a spatial resolution of solute plumes which is not easily achievable in applications. In absence of field data, it is a questionable common practice to set transverse dispersivities as a fraction of the longitudinal one, with the ratio 1/10 being the most prevalent. We collected estimates of field-scale transverse dispersivities from existing publications and explored possible scale relationships as guidance criteria for applications. Our investigation showed that a large number of estimates available in the literature are of low reliability and should be discarded from further analysis. The remaining reliable estimates are formation-specific, span three orders of magnitude and do not show any clear scale-dependence on the plume traveled distance. The ratios with the longitudinal dispersivity are also site specific and vary widely. The reliability of transverse dispersivities depends significantly on the type of field experiment and method of data analysis. In applications where transverse dispersion plays a significant role, inference of transverse dispersivities should be part of site characterization with the transverse dispersivity estimated as an independent parameter rather than related heuristically to longitudinal dispersivity.
In this paper, an underground experiment at the Aspo Hard Rock Laboratory (HRL) is described. Main goal is optimizing geothermal heat exchange in crystalline rock mass at depth by multistage hydraulic fracturing with minimal impact on the environment, that is, seismic events. For this, three arrays with acoustic emission, microseismicity and electromagnetic sensors are installed mapping hydraulic fracture initiation and growth. Fractures are driven by three different water injection schemes (continuous, progressive and pulse pressurization). After a brief review of hydraulic fracture operations in crystalline rock mass at mine scale, the site geology and the stress conditions at Aspo HRL are described. Then, the continuous, single-flow rate and alternative, multiple-flow rate fracture breakdown tests in a horizontal borehole at depth level 410 m are described together with the monitoring networks and sensitivity. Monitoring results include the primary catalogue of acoustic emission hypocentres obtained from four hydraulic fractures with the in situ trigger and localizing network. The continuous versus alternative water injection schemes are discussed in terms of the fracture breakdown pressure, the fracture pattern from impression packer result and the monitoring at the arrays. An example of multistage hydraulic fracturing with several phases of opening and closing of fracture walls is evaluated using data from acoustic emissions, seismic broad-band recordings and electromagnetic signal response. Based on our limited amount of in situ tests (six) and evaluation of three tests in Avro granodiorite, in the multiple-flow rate test with progressively increasing target pressure, the acoustic emission activity starts at a later stage in the fracturing process compared to the conventional fracturing case with continuous water injection. In tendency, also the total number and magnitude of acoustic events are found to be smaller in the progressive treatment with frequent phases of depressurization.
A New Efficient Method to Solve the Stream Power Law Model Taking Into Account Sediment Deposition
(2019)
The stream power law model has been widely used to represent erosion by rivers but does not take into account the role played by sediment in modulating erosion and deposition rates. Davy and Lague (2009, ) provide an approach to address this issue, but it is computationally demanding because the local balance between erosion and deposition depends on sediment flux resulting from net upstream erosion. Here, we propose an efficient (i.e., O(N) and implicit) method to solve their equation. This means that, unlike other methods used to study the complete dynamics of fluvial systems (e.g., including the transition from detachment-limited to transport-limited behavior), our method is unconditionally stable even when large time steps are used. We demonstrate its applicability by performing a range of simulations based on a simple setup composed of an uplifting region adjacent to a stable foreland basin. As uplift and erosion progress, the mean elevations of the uplifting relief and the foreland increase, together with the average slope in the foreland. Sediments aggrade in the foreland and prograde to reach the base level where sediments are allowed to leave the system. We show how the topography of the uplifting relief and the stratigraphy of the foreland basin are controlled by the efficiency of river erosion and the efficiency of sediment transport by rivers. We observe the formation of a steady-state geometry in the uplifting region, and a dynamic steady state (i.e., autocyclic aggradation and incision) in the foreland, with aggradation and incision thicknesses up to tens of meters.
An exceptionally strong stationary planetary wave with Zonal Wavenumber 1 led to a sudden stratospheric warming (SSW) in the Southern Hemisphere in September 2019. Ionospheric data from European Space Agency's Swarm satellite constellation mission show prominent 6-day variations in the dayside low-latitude region at this time, which can be attributed to forcing from the middle atmosphere by the Rossby normal mode "quasi-6-day wave" (Q6DW). Geopotential height measurements by the Microwave Limb Sounder aboard National Aeronautics and Space Administration's Aura satellite reveal a burst of global Q6DW activity in the mesosphere and lower thermosphere during the SSW, which is one of the strongest in the record. The Q6DW is apparently generated in the polar stratosphere at 30-40 km, where the atmosphere is unstable due to strong vertical wind shear connected with planetary wave breaking. These results suggest that an Antarctic SSW can lead to ionospheric variability through wave forcing from the middle atmosphere.
Plain Language Summary: A sudden stratospheric warming (SSW) is an extreme wintertime polar meteorological phenomenon occurring mostly over the Arctic region. Studies have shown that Arctic SSW can influence the entire atmosphere. In September 2019, a rare SSW event occurred in the Antarctic region, providing an opportunity to investigate its broader impact on the whole atmosphere. We present observations from the middle atmosphere and ionosphere during this event, noting unusually strong wave activity throughout this region. Our results suggest that an Antarctic SSW can have a significant impact on the whole atmosphere system similar to those due to Arctic events.
Reductions in river discharge (water availability) like those from climate change or increased water withdrawal, reduce freshwater biodiversity. We combined two scenarios from the Intergovernmental Panel for Climate Change with a global hydrological model to build global scenarios of future losses in river discharge from climate change and increased water withdrawal. Applying these results to known relationships between fish species and discharge, we build scenarios of losses (at equilibrium) of riverine fish richness. In rivers with reduced discharge, up to 75% (quartile range 4-22%) of local fish biodiversity would be headed toward extinction by 2070 because of combined changes in climate and water consumption. Fish loss in the scenarios fell disproportionately on poor countries. Reductions in water consumption could prevent many of the extinctions in these scenarios
Flood risk management in Germany follows an integrative approach in which both private households and businesses can make an important contribution to reducing flood damage by implementing property-level adaptation measures. While the flood adaptation behavior of private households has already been widely researched, comparatively less attention has been paid to the adaptation strategies of businesses. However, their ability to cope with flood risk plays an important role in the social and economic development of a flood-prone region. Therefore, using quantitative survey data, this study aims to identify different strategies and adaptation drivers of 557 businesses damaged by a riverine flood in 2013 and 104 businesses damaged by pluvial or flash floods between 2014 and 2017. Our results indicate that a low perceived self-efficacy may be an important factor that can reduce the motivation of businesses to adapt to flood risk. Furthermore, property-owners tended to act more proactively than tenants. In addition, high experience with previous flood events and low perceived response costs could strengthen proactive adaptation behavior. These findings should be considered in business-tailored risk communication.
Ice-wedge polygons are widespread periglacial features and influence landscape hydrology and carbon storage. The influence of climate and topography on polygon development is not entirely clear, however, giving high uncertainties to projections of permafrost development. We studied the mid- to late Holocene development of modern ice-wedge polygon sites to explore drivers of change and reasons for long-term stability. We analyzed organic carbon, total nitrogen, stable carbon isotopes, grain size composition and plant macrofossils in six cores from three polygons. We found that ail sites developed from aquatic to wetland conditions. In the mid-Holocene, shallow lakes and partly submerged ice-wedge polygons existed at the studied sites. An erosional hiatus of ca 5000 years followed, and ice-wedge polygons re-initiated within the last millennium. Ice-wedge melt and surface drying during the last century were linked to climatic warming. The influence of climate on ice-wedge polygon development was outweighed by geomorphology during most of the late Holocene. Recent warming, however, caused ice-wedge degradation at all sites. Our study showed that where waterlogged ground was maintained, low-centered polygons persisted for millennia. Ice-wedge melt and increased drainage through geomorphic disturbance, however, triggered conversion into high-centered polygons and may lead to self-enhancing degradation under continued warming.
For bare soil conditions, the most important process driving and initiating splash and interrill erosion is the detachment of soil particles via raindrop impact. The kinetic energy of a rainfall event is controlled by the drop size and fall velocity distribution, which is often directly or indirectly implemented in erosion models. Therefore, numerous theoretical functions have been developed for the estimation of rainfall kinetic energy from available rainfall intensity measurements. The aim of this study is to assess differences inherent in a wide number of kinetic energy-rainfall intensity (KE-I) relations and their role in soil erosion modelling. Therefore, 32 KE-I relations are compared against measured rainfall energies based on optical distrometer measurements carried out at five stations of two substantially different rainfall regimes. These allow for continuous high-resolution (1-min) direct measurements of rainfall kinetic energies from a detailed spectrum of measured drop sizes and corresponding fall velocities. To quantify the effect of different KE-I relations on sediment delivery, we apply the erosion model WATEM/SEDEM in an experimental setup to four catchments of NE-Germany. The distrometer data shows substantial differences between measured and theoretical models of drop size and fall velocity distributions. For low intensities the number of small drops is overestimated by the Marshall and Palmer (1948; MP) drop size distribution, while for high intensities the proportion of large drops is overestimated by the MP distribution. The distrometer measurements show a considerable proportion of large drops falling at slower velocities than predicted by the Gunn and Kinzer (1949) terminal velocity model. For almost all rainfall events at all stations, the KE-I relations predicted higher cumulative kinetic energy sums compared to the direct measurements of the optical distrometers. The different KE-I relations show individual characteristics over the course of rainfall intensity levels. Our results indicate a high sensitivity (up to a range from 10 to 27 t ha(-1)) of the simulated sediment delivery related to different KE-I relations. Hence, the uncertainty associated with KE-I relations for soil erosion modelling is of critical importance.
German football stadiums are well known for their atmosphere. It is often described as 'electrifying,' or 'cracking.' This article focuses on this atmosphere. Using a phenomenological approach, it explores how this emotionality can be understood and how geography matters while attending a match. Atmosphere in this context is conceptualized based on work by as a mood-charged space, neither object- nor subject-centered, but rather a medium of perception which cannot not exist. Based on qualitative research done in the home stadium of Hertha BSC in the German Bundesliga, this article shows that the bodily sensations experienced by spectators during a visit to the stadium are synchronized with events on the pitch and with the more or less imposing scenery. The analysis ofin situdiaries reveals that spectators experience a comprehensive sense of collectivity. The study presents evidence that the occurrence of these bodily sensations is strongly connected with different aspects of spatiality. This includes sensations of constriction and expansion within the body, an awareness of one's location within the stadium, the influence of the immediate surroundings and cognitive here/there and inside/outside distinctions.
Indicators to assess sustainable land development often focus on either economic or ecologic aspects of landscape use. The concept of multifunctional land use helps merging those two focuses by emphasising on the rule that economic action is per se accompanied by ecological utility: commodity outputs (CO, e.g., yields) are paid for on the market, but non-commodity outputs (NCO, e.g., landscape aesthetics) so far are public goods with no markets. Agricultural production schemes often provided both outputs by joint production, but with technical progress under prevailing economic pressure, joint production increasingly vanishes by decoupling of commodity from non-commodity production. Simultaneously, by public and political awareness of these shortcomings, there appears a societal need or even demand for some non-commodity outputs of land use, which induces a market potential, and thus, shift towards the status of a commodity outputs. An approach is presented to merge both types of output by defining an indicator of social utility (SUMLU): production schemes are considered with respect to social utility of both commodity and non-commodity outputs. Social utility in this sense includes environmental and economic services as long as society expresses a demand for them. For each combination of parameters at specific frame conditions (e.g., soil and climate properties of a landscape) a production possibility curve can reflect trade-offs between commodity and non-commodity outputs. On each production possibility curve a welfare optimum can be identified expressing the highest achievable value of social utility as a trade-off between CO and NCO production. When applying more parameters, a cluster of welfare optimums is generated. Those clusters can be used for assessing production schemes with respect to sustainable land development. Examples of production possibility functions are given on easy applicable parameters (nitrogen leaching versus gross margin) and on more complex ones (biotic integrity). Social utility, thus allows to evaluate sustainability of land development in a cross-sectoral approach with respect to multifunctionality. (C) 2005 Elsevier Ltd. All rights reserved
Integrating diverging orientors : sustainable agriculture ; ecological targets and future land use
(1998)
Aerial and surface rivers
(2018)
The abundant evapotranspiration provided by the Amazon forests is an important component of the hydrological cycle, both regionally and globally. Since the last century, deforestation and expanding agricultural activities have been changing the ecosystem and its provision of moisture to the atmosphere. However, it remains uncertain how the ongoing land use change will influence rainfall, runoff, and water availability as findings from previous studies differ. Using moisture tracking experiments based on observational data, we provide a spatially detailed analysis recognizing potential teleconnection between source and sink regions of atmospheric moisture. We apply land use scenarios in upwind moisture sources and quantify the corresponding rainfall and runoff changes in downwind moisture sinks. We find spatially varying responses of water regimes to land use changes, which may explain the diverse results from previous studies. Parts of the Peruvian Amazon and western Bolivia are identified as the sink areas most sensitive to land use change in the Amazon and we highlight the current water stress by Amazonian land use change on these areas in terms of the water availability. Furthermore, we also identify the influential source areas where land use change may considerably reduce a given target sink's water reception (from our example of the Ucayali River basin outlet, rainfall by 5–12 % and runoff by 19–50 % according to scenarios). Sensitive sinks and influential sources are therefore suggested as hotspots for achieving sustainable land–water management.
Application and Acceptance of the Habitats Directive in Germany and France - Comparison of Selected Areas. Since 1992, when the Habitats Directive (92/43/EWG) came into effect, all EU member states are obligated to contribute to the establishment of a coherent ecological framework of special protection areas, called Natura 2000. The guideline states both protection objects and protection aims more precisely but its implementation is, to a large extent, left to the member states. In the neighbouring states Germany and France the organisation report strategy, and area management of the Natura 2000 areas differ significantly. Based on these conditions, in both countries two exemplary regions (mountain range and low mountain range) with 3 Natura 2000-areas were selected. In exemplary municipalities the local decision-makers and other relevant activists were interviewed regarding their acceptance of Natura 2000. The results showed altogether a higher acceptance in the 12 German municipalities than in the 12 French but at the same time an extensive insecurity regarding the new obligations on order to implement the protection system. In the French examples the lack of public participation organised by the state government contributed to a reduced acceptance during the first years of the implementation of the Habitats Guideline. Besides, crucial elements for a local acceptance of the Natura 2000 system in both states were the land owners, existing plans and development aims of the municipality, land use and a possibly existing protection status of the area. Additionally the study showed that a transparent establishment of a management plan offers the opportunity to co-ordinate different land use and protection interests. The designation of a separate area co-ordinator for each Natura 2000-area, at the same time contact for the local community like in France, can provide a valuable, confidence-building measure.
This paper introduces a novel measure to assess similarity between event hydrographs. It is based on cross recurrence plots (CRP) and recurrence quantification analysis (RQA), which have recently gained attention in a range of disciplines when dealing with complex systems. The method attempts to quantify the event runoff dynamics and is based on the time delay embedded phase space representation of discharge hydrographs. A phase space trajectory is reconstructed from the event hydrograph, and pairs of hydrographs are compared to each other based on the distance of their phase space trajectories. Time delay embedding allows considering the multidimensional relationships between different points in time within the event. Hence, the temporal succession of discharge values is taken into account, such as the impact of the initial conditions on the runoff event. We provide an introduction to cross recurrence plots and discuss their parameterization. An application example based on flood time series demonstrates how the method can be used to measure the similarity or dissimilarity of events, and how it can be used to detect events with rare runoff dynamics. It is argued that this methods provides a more comprehensive approach to quantify hydrograph similarity compared to conventional hydrological signatures.
Ocean-land thermal feedback mechanisms in the Indian Summer Monsoon (ISM) domain are an important but not well understood component of regional climate dynamics. Here we present a O-18 record analyzed in the mixed-layer dwelling planktonic foraminifer Globigerinoides ruber (sensu stricto) from the northernmost Bay of Bengal (BoB). The O-18 time series provides a spatially integrated measure of monsoonal precipitation and Himalayan meltwater runoff into the northern BoB and reveals two brief episodes of anomalously low O-18 values between 16.30.4 and 160.5 and 12.60.4 and 12.30.4 thousand years before present. The timing of these events is centered at Heinrich event 1 and the Younger Dryas, well-known phases of weak northern hemisphere monsoon systems. Numerical climate model experiments, simulating Heinrich event-like conditions, suggest a surface warming over the monsoon-dominated Himalaya and foreland in response to ISM weakening. Corroborating the simulation results, our analysis of published moraine exposure ages in the monsoon-dominated Himalaya indicates enhanced glacier retreats that, considering age model uncertainties, coincide and overlap with the episodes of anomalously low O-18 values in the northernmost BoB. Our climate proxy and simulation results provide insights into past regional climate dynamics, suggesting reduced cloud cover, increased solar radiation, and air warming of the Himalaya and foreland areas and, as a result, glacier mass losses in response to weakened ISM. Plain Language Summary Indian Summer Monsoon rainfall and Himalayan glacier/snow melts constitute the main water source for the densely populated Indian subcontinent. Better understanding of how future climate changes will affect the monsoon rainfall and Himalayan glaciers requires a long climate record. In this study, we create a 13,000-year-long climate record that allows us to better understand the response of Indian Summer Monsoon rainfall and Himalayan glaciers to past climate changes. The focus of our study is the time window between 9,000 and 22,000 years ago, an episode where the global climate experienced large and rapid changes. Our sediment record from the northern Bay of Bengal and climate change simulation indicate that during episodes of weak monsoon, the melting of the Himalayan glaciers increases substantially significantly. This is because the weakening of the monsoon results in less cloud cover and, as a result, the surface receives more sunlight and causes glacier melting.
Cosmic-Ray neutron sensors are widely used to determine soil moisture on the hectare scale. Precise measurements, especially in the case of mobile application, demand for neutron detectors with high counting rates and high signal-to-noise ratios. For a long time Cosmic Ray Neutron Sensing (CRNS) instruments have relied on He-3 as an efficient neutron converter. Its ongoing scarcity demands for technological solutions using alternative converters, which are Li-6 and B-10. Recent developments lead to a modular neutron detector consisting of several B-10-lined proportional counter tubes, which feature high counting rates via its large surface area. The modularity allows for individual shieldings of different segments within the detector featuring the capability of gaining spectral information about the detected neutrons. This opens the possibility for active signal correction, especially useful when applied to mobile measurements, where the influence of constantly changing near-field to the overall signal should be corrected. Furthermore, the signal-to-noise ratio could be increased by combining pulse height and pulse length spectra to discriminate between neutrons and other environmental radiation. This novel detector therefore combines high-selective counting electronics with large-scale instrumentation technology.
Remote sensing plays an increasingly key role in the determination of soil organic carbon (SOC) stored in agriculturally managed topsoils at the regional and field scales. Contemporary Unmanned Aerial Systems (UAS) carrying low-cost and lightweight multispectral sensors provide high spatial resolution imagery (<10 cm). These capabilities allow integrate of UAS-derived soil data and maps into digitalized workflows for sustainable agriculture. However, the common situation of scarce soil data at field scale might be an obstacle for accurate digital soil mapping. In our case study we tested a fixed-wing UAS equipped with visible and near infrared (VIS-NIR) sensors to estimate topsoil SOC distribution at two fields under the constraint of limited sampling points, which were selected by pedological knowledge. They represent all releva nt soil types along an erosion-deposition gradient; hence, the full feature space in terms of topsoils' SOC status. We included the Topographic Position Index (TPI) as a co-variate for SOC prediction. Our study was performed in a soil landscape of hummocky ground moraines, which represent a significant of global arable land. Herein, small scale soil variability is mainly driven by tillage erosion which, in turn, is strongly dependent on topography. Relationships between SOC, TPI and spectral information were tested by Multiple Linear Regression (MLR) using: (i) single field data (local approach) and (ii) data from both fields (pooled approach). The highest prediction performance determined by a leave-one-out-cross-validation (LOOCV) was obtained for the models using the reflectance at 570 nm in conjunction with the TPI as explanatory variables for the local approach (coefficient of determination (R-2) = 0.91; root mean square error (RMSE) = 0.11% and R-2 = 0.48; RMSE = 0.33, respectively). The local MLR models developed with both reflectance and TPI using values from all points showed high correlations and low prediction errors for SOC content (R-2 = 0.88, RMSE = 0.07%; R-2 = 0.79, RMSE = 0.06%, respectively). The comparison with an enlarged dataset consisting of all points from both fields (pooled approach) showed no improvement of the prediction accuracy but yielded decreased prediction errors. Lastly, the local MLR models were applied to the data of the respective other field to evaluate the cross-field prediction ability. The spatial SOC pattern generally remains unaffected on both fields; differences, however, occur concerning the predicted SOC level. Our results indicate a high potential of the combination of UAS-based remote sensing and environmental covariates, such as terrain attributes, for the prediction of topsoil SOC content at the field scale. The temporal flexibility of UAS offer the opportunity to optimize flight conditions including weather and soil surface status (plant cover or residuals, moisture and roughness) which, otherwise, might obscure the relationship between spectral data and SOC content. Pedologically targeted selection of soil samples for model development appears to be the key for an efficient and effective prediction even with a small dataset.
Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most studies are deliberately designed on the plot scale to ensure low heterogeneity in soils and plant composition, hence similar environmental conditions. Due to the immanent spatial soil variability, the transferability of results to larger areas, such as catchments, is therefore limited. However, the emergence of new technical features and increasing knowledge on details in Si cycling lead to a more complex picture at landscape and catchment scales. Dynamic and static soil properties change along the soil continuum and might influence not only the species composition of natural vegetation but also its biomass distribution and related Si stocks. Maximum likelihood (ML) classification was applied to multispectral imagery captured by an unmanned aerial system (UAS) aiming at the identification of land cover classes (LCCs). Subsequently, the normalized difference vegetation index (NDVI) and ground-based measurements of biomass were used to quantify aboveground Si stocks in two Si-accumulating plants (Calamagrostis epige-jos and Phragmites australis) in a heterogeneous catchment and related corresponding spatial patterns of these stocks to soil properties. We found aboveground Si stocks of C. epige-jos and P. australis to be surprisingly high (maxima of Si stocks reach values up to 98 g Sim(-2)), i.e. comparable to or markedly exceeding reported values for the Si storage in aboveground vegetation of various terrestrial ecosystems. We further found spatial patterns of plant aboveground Si stocks to reflect spatial heterogeneities in soil properties. From our results, we concluded that (i) aboveground biomass of plants seems to be the main factor of corresponding phytogenic Si stock quantities, and (ii) a detection of biomass heterogeneities via UAS-based remote sensing represents a promising tool for the quantification of lifelike phytogenic Si pools at landscape scales.
Transitioning German road transport partially to hydrogen energy is among the possibilities being discussed to help meet national climate targets. This study investigates impacts of a hypothetical, complete transition from conventionally-fueled to hydrogen-powered German transport through representative scenarios. Our results show that German emissions change between -179 and +95 MtCO(2)eq annually, depending on the scenario, with renewable-powered electrolysis leading to the greatest emissions reduction, while electrolysis using the fossilintense current electricity mix leads to the greatest increase. German energy emissions of regulated pollutants decrease significantly, indicating the potential for simultaneous air quality improvements. Vehicular hydrogen demand is 1000 PJ annually, requiring 446-525 TWh for electrolysis, hydrogen transport and storage, which could be supplied by future German renewable generation, supporting the potential for CO2-free hydrogen traffic and increased energy security. Thus hydrogen-powered transport could contribute significantly to climate and air quality goals, warranting further research and political discussion about this possibility.
Marine Isotope Stage 3 (MIS 3, 57-27 ka) was characterised by numerous rapid climate oscillations (i.e., Dansgaard-Oeschger (D/O-) events), which are reflected in various climate archives. So far, MIS 3 speleothem records from central Europe have mainly been restricted to caves located beneath temperate Alpine glaciers or close to the Atlantic Ocean. Thus, MIS 3 seemed to be too cold and dry to enable speleothem growth north of the Alps in central Europe. Here we present a new speleothem record from Bunker Cave, Germany, which shows two distinct growth phases from 52.0 (+0.8, -0.5) to 50.9 (+0.6, -1.3) ka and 473 (+1.0, -0.6) to 42.8 (+/- 0.9) ka, rejecting this hypothesis. These two growth phases potentially correspond to the two warmest and most humid phases in central Europe during MIS 3, which is confirmed by pollen data from the nearby Eifel. The hiatus separating the two phases is associated with Heinrich stadial 5 (HS 5), although the growth stop precedes the onset of HS 5. The first growth phase is characterised by a fast growth rate, and Mg concentrations and Sr isotope data suggest high infiltration and the presence of soil cover above the cave. The second growth phase was characterised by drier, but still favourable conditions for speleothem growth. During this phase, the delta C-13 values show a significant decrease associated with D/O-event 12. The timing of this shift is in agreement with other MIS 3 speleothem data from Europe and Greenland ice core data. (C) 2018 Elsevier Ltd. All rights reserved.
Large-scale crop yield failures are increasingly associated with food price spikes and food insecurity and are a large source of income risk for farmers. While the evidence linking extreme weather to yield failures is clear, consensus on the broader set of weather drivers and conditions responsible for recent yield failures is lacking. We investigate this for the case of four major crops in Germany over the past 20 years using a combination of machine learning and process-based modelling. Our results confirm that years associated with widespread yield failures across crops were generally associated with severe drought, such as in 2018 and to a lesser extent 2003. However, for years with more localized yield failures and large differences in spatial patterns of yield failures between crops, no single driver or combination of drivers was identified. Relatively large residuals of unexplained variation likely indicate the importance of non-weather related factors, such as management (pest, weed and nutrient management and possible interactions with weather) explaining yield failures. Models to inform adaptation planning at farm, market or policy levels are here suggested to require consideration of cumulative resource capture and use, as well as effects of extreme events, the latter largely missing in process-based models. However, increasingly novel combinations of weather events under climate change may limit the extent to which data driven methods can replace process-based models in risk assessments.
The 2020s are an essential decade for achieving the 2030 Agenda and its Sustainable Development Goals (SDGs). For this, SDG research needs to provide evidence that can be translated into concrete actions. However, studies use different SDG data, resulting in incomparable findings. Researchers primarily use SDG databases provided by the United Nations (UN), the World Bank Group (WBG), and the Bertelsmann Stiftung & Sustainable Development Solutions Network (BE-SDSN). We compile these databases into one unified SDG database and examine the effects of the data selection on our understanding of SDG interactions. Among the databases, we observed more different than similar SDG interactions. Differences in synergies and trade-offs mainly occur for SDGs that are environmentally oriented. Due to the increased data availability, the unified SDG database offers a more nuanced and reliable view of SDG interactions. Thus, the SDG data selection may lead to diverse findings, fostering actions that might neglect or exacerbate trade-offs.
To fulfill the 2030 Agenda, the complexity of sustainable development goal (SDG) interactions needs to be disentangled. However, this understanding is currently limited. We conduct a cross-sectional correlational analysis for 2016 to understand SDG interactions under the entire development spectrum. We apply several correlation methods to classify the interaction as synergy or trade-off and characterize them according to their monotony and linearity. Simultaneously, we analyze SDG interactions considering population, location, income, and regional groups. Our findings highlight that synergies always outweigh trade-offs and linear outweigh non-linear interactions. SDG 1, 5, and 6 are associated with linear synergies, SDG 3, and 7 with non-linear synergies. SDG interactions vary according to a country's income and region along with the gender, age, and location of its population. In summary, to achieve the 2030 Agenda the detected interactions and inequalities across countries need be tracked and leveraged to "leave no one behind."
Bank filtration (BF) is an established indirect water-treatment technology. The quality of water gained via BF depends on the subsurface capture zone, the mixing ratio (river water versus ambient groundwater), spatial and temporal distribution of subsurface travel times, and subsurface temperature patterns. Surface-water infiltration into the adjacent aquifer is determined by the local hydraulic gradient and riverbed permeability, which could be altered by natural clogging, scouring and artificial decolmation processes. The seasonal behaviour of a BF system in Germany, and its development during and about 6 months after decolmation (canal reconstruction), was observed with a long-term monitoring programme. To quantify the spatial and temporal variation in the BF system, a transient flow and heat transport model was implemented and two model scenarios, 'with' and 'without' canal reconstruction, were generated. Overall, the simulated water heads and temperatures matched those observed. Increased hydraulic connection between the canal and aquifer caused by the canal reconstruction led to an increase of similar to 23% in the already high share of BF water abstracted by the nearby waterworks. Subsurface travel-time distribution substantially shifted towards shorter travel times. Flow paths with travel times <200 days increased by similar to 10% and those with <300 days by 15%. Generally, the periodic temperature signal, and the summer and winter temperature extrema, increased and penetrated deeper into the aquifer. The joint hydrological and thermal effects caused by the canal reconstruction might increase the potential of biodegradable compounds to further penetrate into the aquifer, also by potentially affecting the redox zonation in the aquifer.
Understanding the physical mechanisms governing fluid-induced fault slip is important for improved mitigation of seismic risks associated with large-scale fluid injection. We conducted fluid-induced fault slip experiments in the laboratory on critically stressed saw-cut sandstone samples with high permeability using different fluid pressurization rates. Our experimental results demonstrate that fault slip behavior is governed by fluid pressurization rate rather than injection pressure. Slow stick-slip episodes (peak slip velocity < 4 mu m/s) are induced by fast fluid injection rate, whereas fault creep with slip velocity < 0.4 mu m/s mainly occurs in response to slow fluid injection rate. Fluid-induced fault slip may remain mechanically stable for loading stiffness larger than fault stiffness. Independent of fault slip mode, we observed dynamic frictional weakening of the artificial fault at elevated pore pressure. Our observations highlight that varying fluid injection rates may assist in reducing potential seismic hazards of field-scale fluid injection projects. <br /> Plain Language Summary Human-induced earthquakes from field-scale fluid injection projects including enhanced geothermal system and deep wastewater injection have been documented worldwide. Although it is clear that fluid pressure plays a crucial role in triggering fault slip, the physical mechanism behind induced seismicity still remains poorly understood. We performed laboratory tests, and here we present two fluid-induced slip experiments conducted on permeable Bentheim sandstone samples crosscut by a fault that is critically stressed. Fault slip is then triggered by pumping the water from the bottom end of the sample at different fluid injection rates. Our results show that fault slip is controlled by fluid pressure increase rate rather than by the absolute magnitude of fluid pressure. In contrast to episodes of relatively rapid but stable sliding events caused by a fast fluid injection rate, fault creep is observed during slow fluid injection. Strong weakening of the dynamic friction coefficient of the experimental fault is observed at elevated pore pressure, independent of fault slip mode. These results may provide a better understanding of the complex behavior of fluid-induced fault slip on the field scale.
In this study, a phosphorus recovery product, struvite palygorskite (S-PAL), obtained from nutrient-rich wastewater by using MgO modified palygorskite was applied for copper remediation in aqueous solution and contaminated soil to achieve waste recycling. The effects of contact time, initial pH, initial Cu(II) concentration and reaction temperature on Cu(II) adsorption in aqueous solution were intensively testified. Pseudo-second-order model was able to properly describe Cu(II) adsorption kinetics by using palygorskite (PAL) and S-PAL, and S-PAL exhibited higher adsorption amount (106.27 mg/g) than PAL (8.46 mg/g) at pH of 4. Cu(II) adsorption on PAL and S-PAL could be well fitted by Freundlich isotherm and Langmuir isotherm, respectively. The calculated thermodynamic parameters indicated that Cu(II) adsorption onto PAL and S-PAL were spontaneous and endothermic. A 28-day soil incubation experiment was conducted to evaluate the effects of PAL and S-PAL with three different rates (1%, 5% and 10% w/w) on Cu immobilization in contaminated soil. In the immobilization test, Cu extracted by 0.01 mol/L CaCl2 after seven days incubation significantly decreased with increasing rate of PAL and S-PAL. BCR sequential extraction results showed the significant decrease of acid soluble Cu and a concomitant increase of the residual fraction of Cu after S-PAL and PAL addition. XRD patterns of soil samples after treatment by PAL and S-PAL showed the formation of Cu0.6Mg1.3Si2O6 and Cu-3.04(PO4)(2)OH0.08 center dot 2H(2)O, which indicated that silanol groups and phosphate exhibited affinity for Cu in the soil.
The management of water resources in a river basin experiencing the expansion of agricultural activities requires a proper understanding of impacts on its hydrologic cycle. This study focused on the analysis of impacts of infield rainwater harvesting (IRWH) and future agricultural expansion as land and water uses change (LWUC) on the hydrologic cycle in the Wami River basin (Tanzania) using the Soil and Water Assessment Tool (SWAT). In the SWAT model, IRWH was implemented by fragmenting rainwater harvesting hydrological response units (HRUs) from cropland HRUs and assigning them as potholes for rainwater impoundment. LWUC was implemented by customizing land cover types and their corresponding model parameters in all original HRUs, and introducing projected water uses in the model. The study thus demonstrated the successful modelling of IRWH and land use change in the SWAT model using HRU fragmentation and customization approaches, respectively. The results indicated that IRWH applications in croplands led to a large increase in evapotranspiration (ET) and the soil water content, and a decrease in percolation, especially in the dry years. However, the average annual streamflow showed negligible changes when IRWH was implemented, even in 50% of current low-coverage croplands in the river basin. Thus, IRWH applications in the river basin are recommended. The results also indicated that LWUC caused huge changes in ET, the soil water content, percolation and the streamflow from the river basin. The average annual streamflow was predicted to decrease by 26% due to LWUC. However, land use change alone without projected water uses was predicted to cause a minor decrease of about 1% in the average annual streamflow. Therefore, further studies on the eco-hydrology of the river basin under various water use scenarios are recommended prior to the expansion of agricultural areas.
Inland salt meadows are particularly valuable ecosystems, because they support a variety of salt-adapted species (halophytes). They can be found throughout Europe; including the peatlands of the glacial lowlands in northeast Germany. These German ecosystems have been seriously damaged through drainage. To assess and ultimately limit the damages, temporal monitoring of soil salinity is essential, which can be conducted by geoelectrical techniques that measure the soil electrical conductivity. However, there is limited knowledge on how to interpret electrical conductivity surveys of peaty salt meadows. In this study, temporal and spatial monitoring of dissolved salts was conducted in saline peatland soils using different geoelectrical techniques at different scales (1D: conductivity probe, 2D: conductivity cross-sections). Cores and soil samples were taken to validate the geoelectrical surveys. Although the influence of peat on bulk conductivity is large, the seasonal dynamics of dissolved salts within the soil profile could be monitored by repeated geoelectrical measurements. A close correlation is observed between conductivity (similar to salinity) at different depths and temperature, precipitation and corresponding groundwater level. The conductivity distribution between top- and subsoil during the growing season reflected the leaching of dissolved salts by precipitation and the capillary rise of dissolved salts by increasing temperature (similar to evaporation). Groundwater levels below 0.38 cm resulted in very low conductivities in the topsoil, which is presumably due to limited soil moisture and thus precipitation of salts. Therefore, to prevent the disappearance of dissolved salts from the rooting zone, which are essential for the halophytes, groundwater levels should be adjusted to maintain depths of between 20 and 35 cm. Lower groundwater levels will lead to the loss of dissolved salts from the rooting zone and higher levels to increasing dilution with fresh rainwater. The easy-to-handle conductivity probe is an appropriate tool for salinity monitoring. Using this probe with regressions adjusted for sandy and organic substrates (peat and organic gyttja) additional influences on bulk conductivity (e.g. cation exchange capacity, water content) can be compensated for and the correlation between salinity and electrical conductivity is high.
In-depth understanding of the potential implications of climate change is required to guide decision- and policy-makers when developing adaptation strategies and designing infrastructure suitable for future conditions. Impact models that translate potential future climate conditions into variables of interest are needed to create the causal connection between a changing climate and its impact for different sectors. Recent surveys suggest that the primary strategy for validating such models (and hence for justifying their use) heavily relies on assessing the accuracy of model simulations by comparing them against historical observations. We argue that such a comparison is necessary and valuable, but not sufficient to achieve a comprehensive evaluation of climate change impact models. We believe that a complementary, largely observation-independent, step of model evaluation is needed to ensure more transparency of model behavior and greater robustness of scenario-based analyses. This step should address the following four questions: (1) Do modeled dominant process controls match our system perception? (2) Is my model's sensitivity to changing forcing as expected? (3) Do modeled decision levers show adequate influence? (4) Can we attribute uncertainty sources throughout the projection horizon? We believe that global sensitivity analysis, with its ability to investigate a model's response to joint variations of multiple inputs in a structured way, offers a coherent approach to address all four questions comprehensively. Such additional model evaluation would strengthen stakeholder confidence in model projections and, therefore, into the adaptation strategies derived with the help of impact models. This article is categorized under: Climate Models and Modeling > Knowledge Generation with Models Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change
Understanding the hydrologic connectivity between kettle holes and shallow groundwater, particularly in reaction to the highly variable local meteorological conditions, is of paramount importance for tracing water in a hydro(geo)logically complex landscape and thus for integrated water resource management. This article is aimed at identifying the dominant hydrological processes affecting the kettle holes' water balance and their interactions with the shallow groundwater domain in the Uckermark region, located in the north-east of Germany. For this reason, based on the stable isotopes of oxygen (delta O-18) and hydrogen (delta H-2), an isotopic mass balance model was employed to compute the evaporative loss of water from the kettle holes from February to August 2017. Results demonstrated that shallow groundwater inflow may play the pivotal role in the processes taking part in the hydrology of the kettle holes in the Uckermark region. Based on the calculated evaporation/inflow (E/I) ratios, most of the kettle holes (86.7%) were ascertained to have a partially open, flow-through-dominated system. Moreover, we identified an inverse correlation between E/I ratios and the altitudes of the kettle holes. The same holds for electrical conductivity (EC) and the altitudes of the kettle holes. In accordance with the findings obtained from this study, a conceptual model explaining the interaction between the shallow groundwater and the kettle holes of Uckermark was developed. The model exhibited that across the highest altitudes, the recharge kettle holes are dominant, where a lower ratio of E/I and a lower EC was detected. By contrast, the lowest topographical depressions represent the discharge kettle holes, where a higher ratio of E/I and EC could be identified. The kettle holes existing in between were categorized as flow-through kettle holes through which the recharge takes place from one side and discharge from the other side.
Ferruginous (Fe-rich, SO4-poor) conditions are generally restricted to freshwater sediments on Earth today, but were likely widespread during the Archean and Proterozoic Eons. Lake Towuti, Indonesia, is a large ferruginous lake that likely hosts geochemical processes analogous to those that operated in the ferruginous Archean ocean. The metabolic potential of microbial communities and related biogeochemical cycling under such conditions remain largely unknown. We combined geochemical measurements (pore water chemistry, sulfate reduction rates) with metagenomics to link metabolic potential with geochemical processes in the upper 50 cm of sediment. Microbial diversity and quantities of genes for dissimilatory sulfate reduction (dsrAB) and methanogenesis (mcrA) decrease with increasing depth, as do rates of potential sulfate reduction. The presence of taxa affiliated with known iron- and sulfate-reducers implies potential use of ferric iron and sulfate as electron acceptors. Pore-water concentrations of acetate imply active production through fermentation. Fermentation likely provides substrates for respiration with iron and sulfate as electron donors and for methanogens that were detected throughout the core. The presence of ANME-1 16S and mcrA genes suggests potential for anaerobic methane oxidation. Overall our data suggest that microbial community metabolism in anoxic ferruginous sediments support coupled Fe, S and C biogeochemical cycling.
The propagation of a seismic rupture on a fault introduces spatial variations in the seismic wave field surrounding the fault. This directivity effect results in larger shaking amplitudes in the rupture propagation direction. Its seismic radiation pattern also causes amplitude variations between the strike-normal and strike-parallel components of horizontal ground motion. We investigated the landslide response to these effects during the 2016 Kumamoto earthquake (M-w 7.1) in central Kyushu (Japan). Although the distribution of some 1500 earthquake-triggered landslides as a function of rupture distance is consistent with the observed Arias intensity, the landslides were more concentrated to the northeast of the southwest-northeast striking rupture. We examined several landslide susceptibility factors: hillslope inclination, the median amplification factor (MAF) of ground shaking, lithology, land cover, and topographic wetness. None of these factors sufficiently explains the landslide distribution or orientation (aspect), although the landslide head scarps have an elevated hillslope inclination and MAF. We propose a new physics-based ground-motion model (GMM) that accounts for the seismic rupture effects, and we demonstrate that the low-frequency seismic radiation pattern is consistent with the overall landslide distribution. Its spatial pattern is influenced by the rupture directivity effect, whereas landslide aspect is influenced by amplitude variations between the fault-normal and fault-parallel motion at frequencies < 2 Hz. This azimuth dependence implies that comparable landslide concentrations can occur at different distances from the rupture. This quantitative link between the prevalent landslide aspect and the low-frequency seismic radiation pattern can improve coseismic landslide hazard assessment.
Climate change has a major impact on arctic and boreal terrestrial ecosystems as warming leads to northward treeline shifts, inducing consequences for heterotrophic organisms associated with the plant taxa. To unravel ecological dependencies, we address how long-term climatic changes have shaped the co-occurrence of plants and fungi across selected sites in Siberia. We investigated sedimentary ancient DNA from five lakes spanning the last 47,000 years, using the ITS1 marker for fungi and the chloroplast P6 loop marker for vegetation metabarcoding. We obtained 706 unique fungal operational taxonomic units (OTUs) and 243 taxa for the plants. We show higher OTU numbers in dry forest tundra as well as boreal forests compared to wet southern tundra. The most abundant fungal taxa in our dataset are Pseudeurotiaceae, Mortierella, Sordariomyceta, Exophiala, Oidiodendron, Protoventuria, Candida vartiovaarae, Pseudeurotium, Gryganskiella fimbricystis, and Tricho-sporiella cerebriformis. The overall fungal composition is explained by the plant composition as revealed by redundancy analysis. The fungal functional groups show antagonistic relationships in their climate susceptibility. The advance of woody taxa in response to past warming led to an increase in the abun-dance of mycorrhizae, lichens, and parasites, while yeast and saprotroph distribution declined. We also show co-occurrences between Salicaceae, Larix, and Alnus and their associated pathogens and detect higher mycorrhizal fungus diversity with the presence of Pinaceae. Under future warming, we can expect feedbacks between fungus composition and plant diversity changes which will affect forest advance, species diversity, and ecosystem stability in arctic regions.
Digitale Karten in GIS
(1993)
In the era of the Internet of Things and Big Data modern cars have become mobile electronic systems or computers on wheels. Car sensors record a multitude of car and traffic related data as well as environmental parameters outside the vehicle. The data recorded are spatio-temporal by nature (floating car data) and can thus be classified as geodata. Their geospatial potential is, however, not fully exploited so far. In this paper, we present an approach to collect, process and visualize floating car data for traffic-and environment-related applications. It is demonstrated that cartographic visualization, in particular, is as effective means to make the enormous stocks of machine-recorded data available to human perception, exploration and analysis.
Quantifying the extremeness of heavy precipitation allows for the comparison of events. Conventional quantitative indices, however, typically neglect the spatial extent or the duration, while both are important to understand potential impacts. In 2014, the weather extremity index (WEI) was suggested to quantify the extremeness of an event and to identify the spatial and temporal scale at which the event was most extreme. However, the WEI does not account for the fact that one event can be extreme at various spatial and temporal scales. To better understand and detect the compound nature of precipitation events, we suggest complementing the original WEI with a “cross-scale weather extremity index” (xWEI), which integrates extremeness over relevant scales instead of determining its maximum.
Based on a set of 101 extreme precipitation events in Germany, we outline and demonstrate the computation of both WEI and xWEI. We find that the choice of the index can lead to considerable differences in the assessment of past events but that the most extreme events are ranked consistently, independently of the index. Even then, the xWEI can reveal cross-scale properties which would otherwise remain hidden. This also applies to the disastrous event from July 2021, which clearly outranks all other analyzed events with regard to both WEI and xWEI.
While demonstrating the added value of xWEI, we also identify various methodological challenges along the required computational workflow: these include the parameter estimation for the extreme value distributions, the definition of maximum spatial extent and temporal duration, and the weighting of extremeness at different scales. These challenges, however, also represent opportunities to adjust the retrieval of WEI and xWEI to specific user requirements and application scenarios.
Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.
Mediterranean ecosystems are particularly vulnerable to climate change and the associated increase in climate anomalies. This study investigates extreme ecosystem responses evoked by climatic drivers in the Mediterranean Basin for the time span 1999–2019 with a specific focus on seasonal variations as the seasonal timing of climatic anomalies is considered essential for impact and vulnerability assessment. A bivariate vulnerability analysis is performed for each month of the year to quantify which combinations of the drivers temperature (obtained from ERA5-Land) and soil moisture (obtained from ESA CCI and ERA5-Land) lead to extreme reductions in ecosystem productivity using the fraction of absorbed photosynthetically active radiation (FAPAR; obtained from the Copernicus Global Land Service) as a proxy.
The bivariate analysis clearly showed that, in many cases, it is not just one but a combination of both drivers that causes ecosystem vulnerability. The overall pattern shows that Mediterranean ecosystems are prone to three soil moisture regimes during the yearly cycle: they are vulnerable to hot and dry conditions from May to July, to cold and dry conditions from August to October, and to cold conditions from November to April, illustrating the shift from a soil-moisture-limited regime in summer to an energy-limited regime in winter. In late spring, a month with significant vulnerability to hot conditions only often precedes the next stage of vulnerability to both hot and dry conditions, suggesting that high temperatures lead to critically low soil moisture levels with a certain time lag. In the eastern Mediterranean, the period of vulnerability to hot and dry conditions within the year is much longer than in the western Mediterranean. Our results show that it is crucial to account for both spatial and temporal variability to adequately assess ecosystem vulnerability. The seasonal vulnerability approach presented in this study helps to provide detailed insights regarding the specific phenological stage of the year in which ecosystem vulnerability to a certain climatic condition occurs.
How to cite.
Vogel, J., Paton, E., and Aich, V.: Seasonal ecosystem vulnerability to climatic anomalies in the Mediterranean, Biogeosciences, 18, 5903–5927, https://doi.org/10.5194/bg-18-5903-2021, 2021.
The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly – with an annual growth rates of 3.9 (3.5) % for warm season (deseasonalised) compound events and 4.6 (4.4) % for warm spells –, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.
The life cycle of plants is largely determined by climate, which renders phenological responses to climate change a highly suitable bioindicator of climate change. Yet, it remains unclear, which are the key drivers of phenological patterns at certain life stages. Furthermore, the varying responses of species belonging to different plant functional types are not fully understood. In this study, the role of temperature and precipitation as environmental drivers of phenological changes in southern Europe is assessed. The trends of the phenophases leaf unfolding, flowering, fruiting, and senescence are quantified, and the corresponding main environmental drivers are identified. A clear trend towards an earlier onset of leaf unfolding, flowering, and fruiting is detected, while there is no clear pattern for senescence. In general, the advancement of leaf unfolding, flowering and fruiting is smaller for deciduous broadleaf trees in comparison to deciduous shrubs and crops. Many broadleaf trees are photoperiod-sensitive; therefore, their comparatively small phenological advancements are likely the effect of photoperiod counterbalancing the impact of increasing temperatures. While temperature is identified as the main driver of phenological changes, precipitation also plays a crucial role in determining the onset of leaf unfolding and flowering. Phenological phases advance under dry conditions, which can be linked to the lack of transpirational cooling leading to rising temperatures, which subsequently accelerate plant growth.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Sustained glacier melt in the Himalayas has gradually spawned more than 5,000 glacier lakes that are dammed by potentially unstable moraines. When such dams break, glacier lake outburst floods (GLOFs) can cause catastrophic societal and geomorphic impacts. We present a robust probabilistic estimate of average GLOFs return periods in the Himalayan region, drawing on 5.4 billion simulations. We find that the 100-y outburst flood has an average volume of 33.5(+3.7)/(-3.7) x 10(6) m(3) (posterior mean and 95% highest density interval [HDI]) with a peak discharge of 15,600(+2.000)/(-1,800) m(3).S-1. Our estimated GLOF hazard is tied to the rate of historic lake outbursts and the number of present lakes, which both are highest in the Eastern Himalayas. There, the estimated 100-y GLOF discharge (similar to 14,500 m(3).s(-1)) is more than 3 times that of the adjacent Nyainqentanglha Mountains, and at least an order of magnitude higher than in the Hindu Kush, Karakoram, and Western Himalayas. The GLOF hazard may increase in these regions that currently have large glaciers, but few lakes, if future projected ice loss generates more unstable moraine-dammed lakes than we recognize today. Flood peaks from GLOFs mostly attenuate within Himalayan headwaters, but can rival monsoon-fed discharges in major rivers hundreds to thousands of kilometers downstream. Projections of future hazard from meteorological floods need to account for the extreme runoffs during lake outbursts, given the increasing trends in population, infrastructure, and hydropower projects in Himalayan headwaters.
The identification of buried soil horizons in agricultural landscapes helps to quantify sediment budgets and erosion-related carbon dynamics. High-resolution mapping of buried horizons using conventional soil surveys is destructive and time consuming. Geoelectrical sensors can offer a fast and non-destructive alternative for determining horizon positions and properties. In this paper, we compare the suitability of several geoelectrical methods for measuring the depth to buried horizons (Apb, Ahb and Hab) in the hummocky ground moraine landscape of northeastern Germany. Soil profile descriptions were developed for 269 locations within a 6-ha experimental field "CarboZALF-D". A stepwise linear discriminant analysis (LDA) estimated the lateral position of the buried horizons using electromagnetic induction data and terrain attributes. To predict the depth of a buried horizon, multiple linear regression (MLR) was used for both a 120-m transect and a 0.2-ha pseudo-three-dimensional (3D) area. At these scales, apparent electrical conductivity (ECa), electrical resistivity (ER) and terrain attributes were used as independent variables. The LDA accurately predicted Apb- and Ahb-horizons (a correct classification of 93%). The LDA of the Hab-horizon had a misclassification of 24%, which was probably related to the smaller test set and the higher depth of this horizon. The MLR predicted the depth of the Apb-, Ahb- and Hab-horizons with relative root mean square errors (RMSEs) of 7, 3 and 13%, respectively, in the pseudo-3D area. MLR had a lower accuracy for the 2D transect compared to the pseudo-3D area. Overall, the use of LDA and MLR has been an efficient methodological approach for predicting buried horizon positions. Highlights The suitability of geoelectrical measurements for digital modelling of diagnostic buried soil horizons was determined. LDA and MLR were used to detect multiple horizons with geoelectrical devices and terrain attributes. Geoelectrical variables were significant predictors of the position of the target soil horizons. The use of these tested digital technologies gives an opportunity to develop high-resolution soil mapping procedures.
The precise and accurate assessment of carbon dioxide (CO2) exchange is crucial to identify terrestrial carbon (C) sources and sinks and for evaluating their role within the global C budget. The substantial uncertainty in disentangling the management and soil impact on measured CO2 fluxes are largely ignored especially in cropland. The reasons for this lies in the limitation of the widely used eddy covariance as well as manual and automatic chamber systems, which either account for short-term temporal variability or small-scale spatial heterogeneity, but barely both. To address this issue, we developed a novel robotic chamber system allowing for dozens of spatial measurement repetitions, thus enabling CO2 exchange measurements in a sufficient temporal and high small-scale spatial resolution. The system was tested from 08th July to 09th September 2019 at a heterogeneous field (100 m x 16 m), located within the hummocky ground moraine landscape of northeastern Germany (CarboZALF-D). The field is foreseen for a longer-term block trial manipulation experiment extending over three erosion induced soil types and was covered with spring barley. Measured fluxes of nighttime ecosystem respiration (R-eco) and daytime net ecosystem exchange (NEE) showed distinct temporal patterns influenced by crop phenology, weather conditions and management practices. Similarly, we found clear small-scale spatial differences in cumulated (gap-filled) R-eco, gross primary productivity (GPP) and NEE fluxes affected by the three distinct soil types. Additionally, spatial patterns induced by former management practices and characterized by differences in soil pH and nutrition status (P and K) were also revealed between plots within each of the three soil types, which allowed compensating for prior to the foreseen block trial manipulation experiment. The results underline the great potential of the novel robotic chamber system, which not only detects short-term temporal CO2 flux dynamics but also reflects the impact of small-scale spatial heterogeneity.
Climate change, along with socio-economic development, will increase the economic impacts of floods. While the factors that influence flood risk to private property have been extensively studied, the risk that natural disasters pose to public infrastructure and the resulting implications on public sector budgets, have received less attention. We address this gap by developing a two-staged model framework, which first assesses the flood risk to public infrastructure in Austria. Combining exposure and vulnerability information at the building level with inundation maps, we project an increase in riverine flood damage, which progressively burdens public budgets. Second, the risk estimates are integrated into an insurance model, which analyzes three different compensation arrangements in terms of the monetary burden they place on future governments' budgets and the respective volatility of payments. Formalized insurance compensation arrangements offer incentives for risk reduction measures, which lower the burden on public budgets by reducing the vulnerability of buildings that are exposed to flooding. They also significantly reduce the volatility of payments and thereby improve the predictability of flood damage expenditures. These features indicate that more formalized insurance arrangements are an improvement over the purely public compensation arrangement currently in place in Austria.
Stochastic modeling of precipitation for estimation of hydrological extremes is an important element of flood risk assessment and management. The spatially consistent estimation of rainfall fields and their temporal variability remains challenging and is addressed by various stochastic weather generators.
In this study, two types of weather generators are evaluated against observed data and benchmarked regarding their ability to simulate spatio-temporal precipitation fields in the Rhine catchment. A multi-site station-based weather generator uses an auto-regressive model and estimates the spatial correlation structure between stations. Another weather generator is raster-based and uses the nearest-neighbor resampling technique for reshuffling daily patterns while preserving the correlation structure between the observations.
Both weather generators perform well and are comparable at the point (station) scale with regards to daily mean and 99.9th percentile precipitation as well as concerning wet/dry frequencies and transition probabilities. The areal extreme precipitation at the sub-basin scale is however overestimated in the station-based weather generator due to an overestimation of the correlation structure between individual stations. The auto-regressive model tends to generate larger rainfall fields in space for extreme precipitation than observed, particularly in summer. The weather generator based on nearest-neighbor resampling reproduces the observed daily and multiday (5, 10 and 20) extreme events in a similar magnitude. Improvements in performance regarding wet frequencies and transition probabilities are recommended for both models.