Open Access
Refine
Year of publication
Document Type
- Article (189)
- Postprint (53)
- Doctoral Thesis (3)
- Other (2)
- Preprint (2)
- Review (2)
- Monograph/Edited Volume (1)
Language
- English (252)
Keywords
- Uncertainties (4)
- climate change (4)
- River (3)
- deep biosphere (3)
- events (3)
- permafrost (3)
- streamflow (3)
- time-series (3)
- uncertainty (3)
- Accuracy Asseessment (2)
Institute
- Institut für Geowissenschaften (252) (remove)
Empirical evidence of the relationship between social support and post-disaster mental health provides support for a general beneficial effect of social support (main-effect model; Wheaton, 1985). From a theoretical perspective, a buffering effect of social support on the negative relationship between disaster-related stress and mental health also seems plausible (stress-buffering model; Wheaton, 1985). Previous studies, however, (a) have paid less attention to the buffering effect of social support and (b) have mainly relied on interpersonal support (but not collective-level support such as community resilience) when investigating this issue. This previous work might have underestimated the effect of support on post-disaster mental health. Building on a sample of residents in Germany recently affected by flooding (N = 118), we show that community resilience to flooding (but not general interpersonal social support) buffered against the negative effects of flooding on post-disaster mental health. The results support the stress-buffering model and call for a more detailed look at the relationship between support and resilience and post-disaster adjustment, including collective-level variables.
Abstract. The Sea of Marmara, in northwestern Turkey, is a transition zone where the dextral North Anatolian Fault zone (NAFZ) propagates westward from the Anatolian Plate to the Aegean Sea Plate. The area is of interest in the context of seismic hazard of Istanbul, a metropolitan area with about 15 million inhabitants. Geophysical observations indicate that the crust is heterogeneous beneath the Marmara basin, but a detailed characterization of the crustal heterogeneities is still missing. To assess if and how crustal heterogeneities are related to the NAFZ segmentation below the Sea of Marmara, we develop new crustal-scale 3-D density models which integrate geological and seismological data and that are additionally constrained by 3-D gravity modeling. For the latter, we use two different gravity datasets including global satellite data and local marine gravity observation. Considering the two different datasets and the general non-uniqueness in potential field modeling, we suggest three possible “end-member” solutions that are all consistent with the observed gravity field and illustrate the spectrum of possible solutions. These models indicate that the observed gravitational anomalies originate from significant density heterogeneities within the crust. Two layers of sediments, one syn-kinematic and one pre-kinematic with respect to the Sea of Marmara formation are underlain by a heterogeneous crystalline crust. A felsic upper crystalline crust (average density of 2720 kgm⁻³) and an intermediate to mafic lower crystalline crust (average density of 2890 kgm⁻³) appear to be cross-cut by two large, dome-shaped mafic highdensity bodies (density of 2890 to 3150 kgm⁻³) of considerable thickness above a rather uniform lithospheric mantle (3300 kgm⁻³). The spatial correlation between two major bends of the main Marmara fault and the location of the highdensity bodies suggests that the distribution of lithological heterogeneities within the crust controls the rheological behavior along the NAFZ and, consequently, maybe influences fault segmentation and thus the seismic hazard assessment in the region.
Abstract. The Sea of Marmara, in northwestern Turkey, is a transition zone where the dextral North Anatolian Fault zone (NAFZ) propagates westward from the Anatolian Plate to the Aegean Sea Plate. The area is of interest in the context of seismic hazard of Istanbul, a metropolitan area with about 15 million inhabitants. Geophysical observations indicate that the crust is heterogeneous beneath the Marmara basin, but a detailed characterization of the crustal heterogeneities is still missing. To assess if and how crustal heterogeneities are related to the NAFZ segmentation below the Sea of Marmara, we develop new crustal-scale 3-D density models which integrate geological and seismological data and that are additionally constrained by 3-D gravity modeling. For the latter, we use two different gravity datasets including global satellite data and local marine gravity observation. Considering the two different datasets and the general non-uniqueness in potential field modeling, we suggest three possible “end-member” solutions that are all consistent with the observed gravity field and illustrate the spectrum of possible solutions. These models indicate that the observed gravitational anomalies originate from significant density heterogeneities within the crust. Two layers of sediments, one syn-kinematic and one pre-kinematic with respect to the Sea of Marmara formation are underlain by a heterogeneous crystalline crust. A felsic upper crystalline crust (average density of 2720 kgm⁻³) and an intermediate to mafic lower crystalline crust (average density of 2890 kgm⁻³) appear to be cross-cut by two large, dome-shaped mafic highdensity bodies (density of 2890 to 3150 kgm⁻³) of considerable thickness above a rather uniform lithospheric mantle (3300 kgm⁻³). The spatial correlation between two major bends of the main Marmara fault and the location of the highdensity bodies suggests that the distribution of lithological heterogeneities within the crust controls the rheological behavior along the NAFZ and, consequently, maybe influences fault segmentation and thus the seismic hazard assessment in the region.
In the context of examining the potential usage of safe and sustainable geothermal energy in the Alberta Basin, whether in deep sediments or crystalline rock, the understanding of the in situ stress state is crucial. It is a key challenge to estimate the 3-D stress state at an arbitrarily chosen point in the crust, based on sparsely distributed in situ stress data.
To address this challenge, we present a large-scale 3-D geomechanical-numerical model (700 km x 1200 km x 80 km) from a large portion of the Alberta Basin, to provide a 3-D continuous quantification of the contemporary stress orientations and stress magnitudes. To calibrate the model, we use a large database of in situ stress orientation (321 S-Hmax) as well as stress magnitude data (981 S-V, 1720 S-hmin and 2 (+11) S-Hmax) from the Alberta Basin. To find the best-fit model, we vary the material properties and primarily the displacement boundary conditions of the model. This study focusses in detail on the statistical calibration procedure, because of the large amount of available data, the diversity of data types, and the importance of the order of data tests.
The best-fit model provides the total 3-D stress tensor for nearly the whole Alberta Basin, and allows estimation of stress orientation and stress magnitudes in advance of any well. First-order implications for the well design and configuration of enhanced geothermal systems are revealed. Systematic deviations of the modelled stress from the in situ data are found for stress orientations in the Peace River and the Bow Island Arch as well as for leak-off test magnitudes.
Hydrocarbons can be found in many different habitats and represent an important carbon source for microbes. As fossil fuels, they are also an important economical resource and through natural seepage or accidental release they can be major pollutants. DNA-specific stains and molecular probes bind to hydrocarbons, causing massive background fluorescence, thereby hampering cell enumeration. The cell extraction procedure of Kallmeyer et al. (2008) separates the cells from the sediment matrix. In principle, this technique can also be used to separate cells from oily sediments, but it was not originally optimized for this application. Here we present a modified extraction method in which the hydrocarbons are removed prior to cell extraction. Due to the reduced background fluorescence the microscopic image becomes clearer, making cell identification, and enumeration much easier. Consequently, the resulting cell counts from oily samples treated according to our new protocol are significantly higher than those treated according to Kallmeyer et al. (2008). We tested different amounts of a variety of solvents for their ability to remove hydrocarbons and found that n-hexane and in samples containing more mature oils methanol, delivered the best results. However, as solvents also tend to lyse cells, it was important to find the optimum solvent to sample ratio, at which hydrocarbon extraction is maximized and cell lysis minimized. A volumetric ratio of 1:2-1:5 between a formalin-fixed sediment slurry and solvent delivered highest cell counts. Extraction efficiency was around 30-50% and was checked on both oily samples spiked with known amounts of E. coli cells and oil-free samples amended with fresh and biodegraded oil. The method provided reproducible results on samples containing very different kinds of oils with regard to their degree of biodegradation. For strongly biodegraded oil MeOH turned out to be the most appropriate solvent, whereas for less biodegraded samples n-hexane delivered best results.
In this paper, we analyse the effectiveness of flood management measures based on the concept known as "retaining water in the landscape". The investigated measures include afforestation, micro-ponds and small-reservoirs. A comparative and model-based methodological approach has been developed and applied for three meso-scale catchments located in different European hydro-climatological regions: Poyo (184 km(2)) in the Spanish Mediterranean, Upper Iller (954 km(2)) in the German Alps and Kamp (621 km(2)) in Northeast-Austria representing the Continental hydro-climate. This comparative analysis has found general similarities in spite of the particular differences among studied areas. In general terms, the flood reduction through the concept of "retaining water in the landscape" depends on the following factors: the storage capacity increase in the catchment resulting from such measures, the characteristics of the rainfall event, the antecedent soil moisture condition and the spatial distribution of such flood management measures in the catchment. In general, our study has shown that, this concept is effective for small and medium events, but almost negligible for the largest and less frequent floods: this holds true for all different hydro-climatic regions, and with different land-use, soils and morphological settings.
Monsoon systems around the world are governed by the so-called moisture-advection feedback. Here we show that, in a minimal conceptual model, this feedback implies a critical threshold with respect to the atmospheric specific humidity q(o) over the ocean adjacent to the monsoon region. If q(o) falls short of this critical value q(o)(c), monsoon rainfall over land cannot be sustained. Such a case could occur if evaporation from the ocean was reduced, e.g. due to low sea surface temperatures. Within the restrictions of the conceptual model, we estimate q(o)(c) from present-day reanalysis data for four major monsoon systems, and demonstrate how this concept can help understand abrupt variations in monsoon strength on orbital timescales as found in proxy records.
Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour.
We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981-2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate).
Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case.
At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model- based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.
Extreme weather events are likely to occur more often under climate change and the resulting effects on ecosystems could lead to a further acceleration of climate change. But not all extreme weather events lead to extreme ecosystem response. Here, we focus on hazardous ecosystem behaviour and identify coinciding weather conditions. We use a simple probabilistic risk assessment based on time series of ecosystem behaviour and climate conditions. Given the risk assessment terminology, vulnerability and risk for the previously defined hazard are estimated on the basis of observed hazardous ecosystem behaviour.
We apply this approach to extreme responses of terrestrial ecosystems to drought, defining the hazard as a negative net biome productivity over a 12-month period. We show an application for two selected sites using data for 1981-2010 and then apply the method to the pan-European scale for the same period, based on numerical modelling results (LPJmL for ecosystem behaviour; ERA-Interim data for climate).
Our site-specific results demonstrate the applicability of the proposed method, using the SPEI to describe the climate condition. The site in Spain provides an example of vulnerability to drought because the expected value of the SPEI is 0.4 lower for hazardous than for non-hazardous ecosystem behaviour. In northern Germany, on the contrary, the site is not vulnerable to drought because the SPEI expectation values imply wetter conditions in the hazard case than in the non-hazard case.
At the pan-European scale, ecosystem vulnerability to drought is calculated in the Mediterranean and temperate region, whereas Scandinavian ecosystems are vulnerable under conditions without water shortages. These first model- based applications indicate the conceptual advantages of the proposed method by focusing on the identification of critical weather conditions for which we observe hazardous ecosystem behaviour in the analysed data set. Application of the method to empirical time series and to future climate would be important next steps to test the approach.
The computation of such synthetic GFs is computationally and operationally demanding. As a consequence, the onthe-fly recalculation of synthetic GFs in each iteration of an optimisation is time-consuming and impractical. Therefore, the pre-calculation and efficient storage of synthetic GFs on a dense grid of source to receiver combinations enables the efficient lookup and utilisation of GFs in time-critical scenarios. We present a Python-based framework and toolkit - Pyrocko-GF - that enables the pre-calculation of synthetic GF stores, which are independent of their numerical calculation method and GF transfer function. The framework aids in the creation of such GF stores by interfacing a suite of established numerical forward modelling codes in seismology (computational back ends). So far, interfaces to back ends for layered Earth model cases have been provided; however, the architecture of Pyrocko-GF is designed to cover back ends for other geometries (e.g. full 3-D heterogeneous media) and other physical quantities (e.g. gravity, pressure, tilt). Therefore, Pyrocko-GF defines an extensible GF storage format suitable for a wide range of GF types, especially handling elasticity and wave propagation problems. The framework assists with visualisations, quality control, and the exchange of GF stores, which is supported through an online platform that provides many pre-calculated GF stores for local, regional, and global studies. The Pyrocko-GF toolkit comes with a well-documented application programming interface (API) for the Python programming language to efficiently facilitate forward modelling of geophysical processes, e.g. synthetic waveforms or static displacements for a wide range of source models.
Investigation of transient soil moisture profiles yields valuable information of near- surface processes. A recently developed reconstruction algorithm based on the telegraph equation allows the inverse estimation of soil moisture profiles along coated, three rod TDR probes. Laboratory experiments were carried out to prove the results of the inversion and to understand the influence of probe rod deformation and solid objects close to the probe in heterogeneous media. Differences in rod geometry can lead to serious misinterpretations in the soil moisture profile, but have small influence on the average soil moisture along the probe. Solids in the integration volume have almost no effect on average soil moisture, but result in locally slightly decreased moisture values. Inverted profiles obtained in a loamy soil with a clay content of about 16% were in good agreement with independent measurements.
We propose a RAndom Interacting Network (RAIN) model to study the interactions between a pair of complex networks. The model involves two major steps: (i) the selection of a pair of nodes, one from each network, based on intra-network node-based characteristics, and (ii) the placement of a link between selected nodes based on the similarity of their relative importance in their respective networks. Node selection is based on a selection fitness function and node linkage is based on a linkage probability defined on the linkage scores of nodes. The model allows us to relate within-network characteristics to between-network structure. We apply the model to the interaction between the USA and Schengen airline transportation networks (ATNs). Our results indicate that two mechanisms: degree-based preferential node selection and degree-assortative link placement are necessary to replicate the observed inter-network degree distributions as well as the observed inter-network assortativity. The RAIN model offers the possibility to test multiple hypotheses regarding the mechanisms underlying network interactions. It can also incorporate complex interaction topologies. Furthermore, the framework of the RAIN model is general and can be potentially adapted to various real-world complex systems.
The Seismic Hazard Inferred from Tectonics based on the Global Strain Rate Map (SHIFT_GSRM) earthquake forecast was designed to provide high-resolution estimates of global shallow seismicity to be used in seismic hazard assessment. This model combines geodetic strain rates with global earthquake parameters to characterize long-term rates of seismic moment and earthquake activity. Although SHIFT_GSRM properly computes seismicity rates in seismically active continental regions, it underestimates earthquake rates in subduction zones by an average factor of approximately 3. We present a complementary method to SHIFT_GSRM to more accurately forecast earthquake rates in 37 subduction segments, based on the conservation of moment principle and the use of regional interface seismicity parameters, such as subduction dip angles, corner magnitudes, and coupled seismogenic thicknesses. In seven progressive steps, we find that SHIFT_GSRM earthquake-rate underpredictions are mainly due to the utilization of a global probability function of seismic moment release that poorly captures the great variability among subduction megathrust interfaces. Retrospective test results show that the forecast is consistent with the observations during the 1 January 1977 to 31 December 2014 period. Moreover, successful pseudoprospective evaluations for the 1 January 2015 to 31 December 2018 period demonstrate the power of the regionalized earthquake model to properly estimate subduction-zone seismicity.
High-pressure is a key feature of deep subsurface environments. High partial pressure of dissolved gasses plays an important role in microbial metabolism, because thermodynamic feasibility of many reactions depends on the concentration of reactants. For gases, this is controlled by their partial pressure, which can exceed 1 MPa at in situ conditions. Therefore, high hydrostatic pressure alone is not sufficient to recreate true deep subsurface in situ conditions, but the partial pressure of dissolved gasses has to be controlled as well. We developed an incubation system that allows for incubations at hydrostatic pressure up to 60 MPa, temperatures up to 120 degrees C, and at high gas partial pressure. The composition and partial pressure of gasses can be manipulated during the experiment. To keep costs low, the system is mainly made from off-the-shelf components with only very few custommade parts. A flexible and inert PVDF (polyvinylidene fluoride) incubator sleeve, which is almost impermeable for gases, holds the sample and separates it from the pressure fluid. The flexibility of the incubator sleeve allows for sub-sampling of the medium without loss of pressure. Experiments can be run in both static and flow-through mode. The incubation system described here is usable for versatile purposes, not only the incubation of microorganisms and determination of growth rates, but also for chemical degradation or extraction experiments under high gas saturation, e.g., fluid-gas-rock-interactions in relation to carbon dioxide sequestration. As an application of the system we extracted organic compounds from sub-bituminous coal using H2O as well as a H2O-CO2 mixture at elevated temperature (90 degrees C) and pressure (5 MPa). Subsamples were taken at different time points during the incubation and analyzed by ion chromatography. Furthermore we demonstrated the applicability of the system for studies of microbial activity, using samples from the Isis mud volcano. We could detect an increase in sulfate reduction rate upon the addition of methane to the sample.
After the flood in 2002, the level of private precautions taken increased considerably. One contributing factor is the fact that, in general, a larger proportion of people knew that they were at risk of flooding. The best level of precaution was found before the flood events in 2006 and 2011. The main reason for this might be that residents had more experience with flooding than residents affected in 2005 or 2010. Yet, overall, flood experience and knowledge did not necessarily result in building retrofitting or flood-proofing measures, which are considered as mitigating damages most effectively. Hence, investments still need to be stimulated in order to reduce future damage more efficiently.
This study focuses on evaluating the potential of ALOS/PALSAR time-series data to analyze the activation of deep-seated landslides in the foothill zone of the high mountain Alai range in the southern Tien Shan (Kyrgyzstan). Most previous field-based landslide investigations have revealed that many landslides have indicators for ongoing slow movements in the form of migrating and newly developing cracks. L-band ALOS/PALSAR data for the period between 2007 and 2010 are available for the 484 km(2) area in this study. We analyzed these data using the Small Baseline Subset (SBAS) time-series technique to assess the surface deformation related to the activation of landslides. We observed up to +/- 17 mm/year of LOS velocity deformation rates, which were projected along the local steepest slope and resulted in velocity rates of up to -63 mm/year. The obtained rates indicate very slow movement of the deep-seated landslides during the observation time. We also compared these movements with precipitation and earthquake records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with an earthquake event. Overall, the results of this study indicated the great potential of L-band InSAR time series analysis for efficient spatiotemporal identification and monitoring of slope activations in this region of high landslide activity in Southern Kyrgyzstan.
This study focuses on evaluating the potential of ALOS/PALSAR time-series data to analyze the activation of deep-seated landslides in the foothill zone of the high mountain Alai range in the southern Tien Shan (Kyrgyzstan). Most previous field-based landslide investigations have revealed that many landslides have indicators for ongoing slow movements in the form of migrating and newly developing cracks. L-band ALOS/PALSAR data for the period between 2007 and 2010 are available for the 484 km2 area in this study. We analyzed these data using the Small Baseline Subset (SBAS) time-series technique to assess the surface deformation related to the activation of landslides. We observed up to ±17 mm/year of LOS velocity deformation rates, which were projected along the local steepest slope and resulted in velocity rates of up to −63 mm/year. The obtained rates indicate very slow movement of the deep-seated landslides during the observation time. We also compared these movements with precipitation and earthquake records. The results suggest that the deformation peaks correlate with rainfall in the 3 preceding months and with an earthquake event. Overall, the results of this study indicated the great potential of L-band InSAR time series analysis for efficient spatiotemporal identification and monitoring of slope activations in this region of high landslide activity in Southern Kyrgyzstan.
Inventories of individually delineated landslides are a key to understanding landslide physics and mitigating their impact. They permit assessment of area-frequency distributions and landslide volumes, and testing of statistical correlations between landslides and physical parameters such as topographic gradient or seismic strong motion. Amalgamation, i.e. the mapping of several adjacent landslides as a single polygon, can lead to potentially severe distortion of the statistics of these inventories. This problem can be especially severe in data sets produced by automated mapping. We present five inventories of earthquake-induced landslides mapped with different materials and techniques and affected by varying degrees of amalgamation. Errors on the total landslide volume and power-law exponent of the area-frequency distribution, resulting from amalgamation, may be up to 200 and 50 %, respectively. We present an algorithm based on image and digital elevation model (DEM) analysis, for automatic identification of amalgamated polygons. On a set of about 2000 polygons larger than 1000 m(2), tracing landslides triggered by the 1994 Northridge earthquake, the algorithm performs well, with only 2.7-3.6% incorrectly amalgamated landslides missed and 3.9-4.8% correct polygons incorrectly identified as amalgams. This algorithm can be used broadly to check landslide inventories and allow faster correction by automating the identification of amalgamation.
Anisotropic material properties are usually neglected during inversions for source parameters of earthquakes. In general anisotropic media, however, moment tensors for pure-shear sources can exhibit significant non-double-couple components. Such effects may be erroneously interpreted as an indication for volumetric changes at the source. Here we investigate effects of anisotropy on seismic moment tensors and radiation patterns for pure-shear and tensile-type sources. Anisotropy can significantly influence the interpretation of the source mechanisms. For example, the orientation of the slip within the fault plane may affect the total seismic moment. Also, moment tensors due to pure- shear and tensile faulting can have similar characteristics depending on the orientation of the elastic tensor. Furthermore, the tensile nature of an earthquake can be obscured by near-source anisotropic properties. As an application, we consider effects of inhomogeneous anisotropic properties on the seismic moment tensor and the radiation patterns of a selected type of micro-earthquakes observed in W-Bohemia. The combined effects of near-source and along- path anisotropy cause characteristic amplitude distortions of the P, S1 and S2 waves. However, the modeling suggests that neither homogeneous nor inhomogeneous anisotropic properties alone can explain the observed large non-double-couple components. The results also indicate that a correct analysis of the source mechanism, in principle, is achievable by application of anisotropic moment tensor inversion
In this paper a change-point detection method is proposed by extending the singular spectrum transformation (SST) developed as one of the capabilities of singular spectrum analysis (SSA). The method uncovers change points related with trends and periodicities. The potential of the proposed method is demonstrated by analysing simple model time series including linear functions and sine functions as well as real world data (precipitation data in Kenya). A statistical test of the results is proposed based on a Monte Carlo simulation with surrogate methods. As a result, the successful estimation of change points as inherent properties in the representative time series of both trend and harmonics is shown. With regards to the application, we find change points in the precipitation data of Kenyan towns (Nakuru, Naivasha, Narok, and Kisumu) which coincide with the variability of the Indian Ocean Dipole (IOD) suggesting its impact of extreme climate in East Africa.
In a recent BAMS article, it is argued that community-based Open Source Software (OSS) could foster scientific progress in weather radar research, and make weather radar software more affordable, flexible, transparent, sustainable, and interoperable.
Nevertheless, it can be challenging for potential developers and users to realize these benefits: tools are often cumbersome to install; different operating systems may have particular issues, or may not be supported at all; and many tools have steep learning curves.
To overcome some of these barriers, we present an open, community-based virtual machine (VM). This VM can be run on any operating system, and guarantees reproducibility of results across platforms. It contains a suite of independent OSS weather radar tools (BALTRAD, Py-ART, wradlib, RSL, and Radx), and a scientific Python stack. Furthermore, it features a suite of recipes that work out of the box and provide guidance on how to use the different OSS tools alone and together. The code to build the VM from source is hosted on GitHub, which allows the VM to grow with its community.
We argue that the VM presents another step toward Open (Weather Radar) Science. It can be used as a quick way to get started, for teaching, or for benchmarking and combining different tools. It can foster the idea of reproducible research in scientific publishing. Being scalable and extendable, it might even allow for real-time data processing.
We expect the VM to catalyze progress toward interoperability, and to lower the barrier for new users and developers, thus extending the weather radar community and user base.
In a recent BAMS article, it is argued that community-based Open Source Software (OSS) could foster scientific progress in weather radar research, and make weather radar software more affordable, flexible, transparent, sustainable, and interoperable.
Nevertheless, it can be challenging for potential developers and users to realize these benefits: tools are often cumbersome to install; different operating systems may have particular issues, or may not be supported at all; and many tools have steep learning curves.
To overcome some of these barriers, we present an open, community-based virtual machine (VM). This VM can be run on any operating system, and guarantees reproducibility of results across platforms. It contains a suite of independent OSS weather radar tools (BALTRAD, Py-ART, wradlib, RSL, and Radx), and a scientific Python stack. Furthermore, it features a suite of recipes that work out of the box and provide guidance on how to use the different OSS tools alone and together. The code to build the VM from source is hosted on GitHub, which allows the VM to grow with its community.
We argue that the VM presents another step toward Open (Weather Radar) Science. It can be used as a quick way to get started, for teaching, or for benchmarking and combining different tools. It can foster the idea of reproducible research in scientific publishing. Being scalable and extendable, it might even allow for real-time data processing.
We expect the VM to catalyze progress toward interoperability, and to lower the barrier for new users and developers, thus extending the weather radar community and user base.
We investigate the inclusions hosted in peritectic garnet from metapelitic migmatites of the Kinzigite Formation (Ivrea Zone, NW Italy) to evaluate the starting composition of the anatectic melt and fluid regime during anatexis throughout the upper amphibolite facies, transition, and granulite facies zones. Inclusions have negative crystal shapes, sizes from 2 to 10 mu m and are regularly distributed in the core of the garnet. Microstructural and micro-Raman investigations indicate the presence of two types of inclusions: crystallized silicate melt inclusions (i.e., nanogranitoids, NI), and fluid inclusions (FI). Microstructural evidence suggests that FI and NI coexist in the same cluster and are primary (i.e., were trapped simultaneously during garnet growth). FI have similar compositions in the three zones and comprise variable proportions of CO2, CH4, and N-2, commonly with siderite, pyrophyllite, and kaolinite, suggesting a COHN composition of the trapped fluid. The mineral assemblage in the NI contains K-feldspar, plagioclase, quartz, biotite, muscovite, chlorite, graphite and, rarely, calcite. Polymorphs such as kumdykolite, cristobalite, tridymite, and less commonly kokchetavite, were also found. Rehomogenized NI from the different zones show that all the melts are leucogranitic but have slightly different compositions. In samples from the upper amphibolite facies, melts are less mafic (FeO + MgO = 2.0-3.4 wt%), contain 860-1700 ppm CO2 and reach the highest H2O contents (6.5-10 wt%). In the transition zone melts have intermediate H2O (4.8-8.5 wt%), CO2 (457-1534 ppm) and maficity (FeO + MgO = 2.3-3.9 wt%). In contrast, melts at granulite facies reach highest CaO, FeO + MgO (3.2-4.7 wt%), and CO2 (up to 2,400 ppm), with H2O contents comparable (5.4-8.3 wt%) to the other two zones. Our results represent the first clear evidence for carbonic fluid-present melting in the Ivrea Zone. Anatexis of metapelites occurred through muscovite and biotite breakdown melting in the presence of a COH fluid, in a situation of fluid-melt immiscibility. The fluid is assumed to have been internally derived, produced initially by devolatilization of hydrous silicates in the graphitic protolith, then as a result of oxidation of carbon by consumption of Fe3+-bearing biotite during melting. Variations in the compositions of the melts are interpreted to result from higher T of melting. The H2O contents of the melts throughout the three zones are higher than usually assumed for initial H2O contents of anatectic melts. The CO2 contents are highest at granulite facies, and show that carbon-contents of crustal magmas are not negligible at high T. The activity of H2O of the fluid dissolved in granitic melts decreases with increasing metamorphic grade. Carbonic fluid-present melting of the deep continental crust represents, together with hydrate-breakdown melting reactions, an important process in the origin of crustal anatectic granitoids.
The information about climate change impact on river discharge is vitally important for planning adaptation measures. The future changes can affect different water-related sectors. The main goal of this study was to investigate the potential water resource changes in Ukraine, focusing on three mesoscale river catchments (Teteriv, UpperWestern Bug, and Samara) characteristic for different geographical zones. The catchment scale watershed model—Soil and Water Integrated Model (SWIM)—was setup, calibrated, and validated for the three catchments under consideration. A set of seven GCM-RCM (General Circulation Model-Regional Climate Model) coupled climate scenarios corresponding to RCPs (Representative Concentration Pathways) 4.5 and 8.5 were used to drive the hydrological catchment model. The climate projections, used in the study, were considered as three combinations of low, intermediate, and high end scenarios. Our results indicate the shifts in the seasonal distribution of runoff in all three catchments. The spring high flow occurs earlier as a result of temperature increases and earlier snowmelt. The fairly robust trend is an increase in river discharge in the winter season, and most of the scenarios show a potential decrease in river discharge in the spring.
The information about climate change impact on river discharge is vitally important for planning adaptation measures. The future changes can affect different water-related sectors. The main goal of this study was to investigate the potential water resource changes in Ukraine, focusing on three mesoscale river catchments (Teteriv, UpperWestern Bug, and Samara) characteristic for different geographical zones. The catchment scale watershed model—Soil and Water Integrated Model (SWIM)—was setup, calibrated, and validated for the three catchments under consideration. A set of seven GCM-RCM (General Circulation Model-Regional Climate Model) coupled climate scenarios corresponding to RCPs (Representative Concentration Pathways) 4.5 and 8.5 were used to drive the hydrological catchment model. The climate projections, used in the study, were considered as three combinations of low, intermediate, and high end scenarios. Our results indicate the shifts in the seasonal distribution of runoff in all three catchments. The spring high flow occurs earlier as a result of temperature increases and earlier snowmelt. The fairly robust trend is an increase in river discharge in the winter season, and most of the scenarios show a potential decrease in river discharge in the spring.
The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At midaltitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.
The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At midaltitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.
The results of streamflow trend studies are often characterized by mostly insignificant trends and inexplicable spatial patterns. In our study region, Western Austria, this applies especially for trends of annually averaged runoff. However, analysing the altitudinal aspect, we found that there is a trend gradient from higher-altitude to lower-altitude stations, i.e. a pattern of mostly positive annual trends at higher stations and negative ones at lower stations. At mid-altitudes, the trends are mostly insignificant. Here we hypothesize that the streamflow trends are caused by the following two main processes: on the one hand, melting glaciers produce excess runoff at higher-altitude watersheds. On the other hand, rising temperatures potentially alter hydrological conditions in terms of less snowfall, higher infiltration, enhanced evapotranspiration, etc., which in turn results in decreasing streamflow trends at lower-altitude watersheds. However, these patterns are masked at mid-altitudes because the resulting positive and negative trends balance each other. To support these hypotheses, we attempted to attribute the detected trends to specific causes. For this purpose, we analysed trends of filtered daily streamflow data, as the causes for these changes might be restricted to a smaller temporal scale than the annual one. This allowed for the explicit determination of the exact days of year (DOYs) when certain streamflow trends emerge, which were then linked with the corresponding DOYs of the trends and characteristic dates of other observed variables, e.g. the average DOY when temperature crosses the freezing point in spring. Based on these analyses, an empirical statistical model was derived that was able to simulate daily streamflow trends sufficiently well. Analyses of subdaily streamflow changes provided additional insights. Finally, the present study supports many modelling approaches in the literature which found out that the main drivers of alpine streamflow changes are increased glacial melt, earlier snowmelt and lower snow accumulation in wintertime.
The aim of this paper is to estimate the Hurst parameter of Fractional Gaussian Noise (FGN) using Bayesian inference. We propose an estimation technique that takes into account the full correlation structure of this process. Instead of using the integrated time series and then applying an estimator for its Hurst exponent, we propose to use the noise signal directly. As an application we analyze the time series of the Nile River, where we find a posterior distribution which is compatible with previous findings. In addition, our technique provides natural error bars for the Hurst exponent.
Modern natural hazards research requires dealing with several uncertainties that arise from limited process knowledge, measurement errors, censored and incomplete observations, and the intrinsic randomness of the governing processes. Nevertheless, deterministic analyses are still widely used in quantitative hazard assessments despite the pitfall of misestimating the hazard and any ensuing risks.
In this paper we show that Bayesian networks offer a flexible framework for capturing and expressing a broad range of uncertainties encountered in natural hazard assessments. Although Bayesian networks are well studied in theory, their application to real-world data is far from straightforward, and requires specific tailoring and adaptation of existing algorithms. We offer suggestions as how to tackle frequently arising problems in this context and mainly concentrate on the handling of continuous variables, incomplete data sets, and the interaction of both. By way of three case studies from earthquake, flood, and landslide research, we demonstrate the method of data-driven Bayesian network learning, and showcase the flexibility, applicability, and benefits of this approach.
Our results offer fresh and partly counterintuitive insights into well-studied multivariate problems of earthquake-induced ground motion prediction, accurate flood damage quantification, and spatially explicit landslide prediction at the regional scale. In particular, we highlight how Bayesian networks help to express information flow and independence assumptions between candidate predictors. Such knowledge is pivotal in providing scientists and decision makers with well-informed strategies for selecting adequate predictor variables for quantitative natural hazard assessments.
Low biostratigraphic resolution and lack of chronostratigraphic calibration hinder precise correlations between platform carbonates and coeval deep-water successions. These are the main obstacle when studying the record of Mesozoic oceanic anoxic events in carbonate platforms. In this paper carbon and strontium isotope stratigraphy are used to produce the first chronostratigraphic calibration of the Barremian-Aptian biostratigraphy of the Apenninic carbonate platform of southern Italy. According to this calibration, the segment of decreasing delta C-13 values, leading to the negative peak that is generally taken as the onset of the Selli event, starts a few metres above the last occurrence of Palorbitolina lenticularis and Voloshinoides murgensis. The following rise of delta C-13 values, corresponding to the interval of enhanced accumulation of organic matter in deep-water sections, ends just below the first acme of Salpingoporella dinarica, which roughly corresponds to the segment of peak delta C-13 values. The whole carbon isotope excursion associated with the oceanic anoxic event 1a is bracketed in the Apenninic carbonate platform between the last occurrence of Voloshinoides murgensis and the "Orbitolina level", characterized by the association of Mesorbitolina parva and Mesorbitolina texana. Since these bioevents have been widely recognized beyond the Apenninic platform, the calibration presented in this paper can be used to pinpoint the interval corresponding to the Early Aptian oceanic anoxic event in other carbonate platforms of central and southern Tethys. This calibration will be particularly useful to interpret the record of the Selli event in carbonate platform sections for which a reliable carbon isotope stratigraphy is not available.
In light of possible future restrictions on the use of fossil fuel, due to climate change obligations and continuous depletion of global fossil fuel reserves, the search for alternative renewable energy sources is expected to be an issue of great concern for policy stakeholders. This study assessed the feasibility of bioenergy production under relatively low-intensity conservative, eco-agricultural settings (as opposed to those produced under high-intensity, fossil fuel based industrialized agriculture). Estimates of the net energy gain (NEG) and the energy return on energy invested (EROEI) obtained from a life cycle inventory of the energy inputs and outputs involved reveal that the energy efficiency of bioenergy produced in low-intensity eco-agricultural systems could be as much as much as 448.5–488.3 GJ·ha−1 of NEG and an EROEI of 5.4–5.9 for maize ethanol production systems, and as much as 155.0–283.9 GJ·ha−1 of NEG and an EROEI of 14.7–22.4 for maize biogas production systems. This is substantially higher than for industrialized agriculture with a NEG of 2.8–52.5 GJ·ha−1 and an EROEI of 1.2–1.7 for maize ethanol production systems, as well as a NEG of 59.3–188.7 GJ·ha−1 and an EROEI of 2.2–10.2 for maize biogas production systems. Bioenergy produced in low-intensity eco-agricultural systems could therefore be an important source of energy with immense net benefits for local and regional end-users, provided a more efficient use of the co-products is ensured.
Accelerating climate change and increased economic and environmental interests in permafrost-affected regions have resulted in an acute need for more directed permafrost research. In June 2014, 88 early career researchers convened to identify future priorities for permafrost research. This multidisciplinary forum concluded that five research topics deserve greatest attention: permafrost landscape dynamics, permafrost thermal modeling, integration of traditional knowledge, spatial distribution of ground ice, and engineering issues. These topics underline the need for integrated research across a spectrum of permafrost-related domains and constitute a contribution to the Third International Conference on Arctic Research Planning (ICARP III).
Convergence between the Indian and Asian plates has reshaped large parts of Asia, changing regional climate and biodiversity, yet geodynamic models fundamentally diverge on how convergence was accommodated since the India-Asia collision. Here we report palaeomagnetic data from the Burma Terrane, which is at the eastern edge of the collision zone and is famous for its Cretaceous amber biota, to better determine the evolution of the India-Asia collision. The Burma Terrane was part of a Trans-Tethyan island arc and stood at a near-equatorial southern latitude at similar to 95 Ma, suggesting island endemism for the Burmese amber biota. The Burma Terrane underwent significant clockwise rotation between similar to 80 and 50 Ma, causing its subduction margin to become hyper-oblique. Subsequently, it was translated northward on the Indian Plate by an exceptional distance of at least 2,000 km along a dextral strike-slip fault system in the east. Our reconstructions are only compatible with geodynamic models involving an initial collision of India with a near-equatorial Trans-Tethyan subduction system at similar to 60 Ma, followed by a later collision with the Asian margin.
Water infiltration in soil is not only affected by the inherent heterogeneities of soil, but even more by the interaction with plant roots and their water uptake. Neutron tomography is a unique non-invasive 3D tool to visualize plant root systems together with the soil water distribution in situ. So far, acquisition times in the range of hours have been the major limitation for imaging 3D water dynamics. Implementing an alternative acquisition procedure we boosted the speed of acquisition capturing an entire tomogram within 10 s. This allows, for the first time, tracking of a water front ascending in a rooted soil column upon infiltration of deuterated water time-resolved in 3D. Image quality and resolution could be sustained to a level allowing for capturing the root system in high detail. Good signal-to-noise ratio and contrast were the key to visualize dynamic changes in water content and to localize the root uptake. We demonstrated the ability of ultra-fast tomography to quantitatively image quick changes of water content in the rhizosphere and outlined the value of such imaging data for 3D water uptake modelling. The presented method paves the way for time-resolved studies of various 3D flow and transport phenomena in porous systems
Water infiltration in soil is not only affected by the inherent heterogeneities of soil, but even more by the interaction with plant roots and their water uptake. Neutron tomography is a unique non-invasive 3D tool to visualize plant root systems together with the soil water distribution in situ. So far, acquisition times in the range of hours have been the major limitation for imaging 3D water dynamics. Implementing an alternative acquisition procedure we boosted the speed of acquisition capturing an entire tomogram within 10 s. This allows, for the first time, tracking of a water front ascending in a rooted soil column upon infiltration of deuterated water time-resolved in 3D. Image quality and resolution could be sustained to a level allowing for capturing the root system in high detail. Good signal-to-noise ratio and contrast were the key to visualize dynamic changes in water content and to localize the root uptake. We demonstrated the ability of ultra-fast tomography to quantitatively image quick changes of water content in the rhizosphere and outlined the value of such imaging data for 3D water uptake modelling. The presented method paves the way for time-resolved studies of various 3D flow and transport phenomena in porous systems.
Ice-rich yedoma-dominated landscapes store considerable amounts of organic carbon (C) and nitrogen (N) and are vulnerable to degradation under climate warming. We investigate the C and N pools in two thermokarst-affected yedoma landscapes - on Sobo-Sise Island and on Bykovsky Peninsula in the north of eastern Siberia. Soil cores up to 3m depth were collected along geomorphic gradients and analysed for organic C and N contents. A high vertical sampling density in the profiles allowed the calculation of C and N stocks for short soil column intervals and enhanced understanding of within-core parameter variability. Profile-level C and N stocks were scaled to the landscape level based on landform classifications from 5 m resolution, multispectral RapidEye satellite imagery. Mean landscape C and N storage in the first metre of soil for Sobo-Sise Island is estimated to be 20.2 kg C m(-2) and 1.8 kg N m(-2) and for Bykovsky Peninsula 25.9 kg C m(-2) and 2.2 kg N m(-2). Radiocarbon dating demonstrates the Holocene age of thermokarst basin deposits but also suggests the presence of thick Holoceneage cover layers which can reach up to 2 m on top of intact yedoma landforms. Reconstructed sedimentation rates of 0.10-0.57 mm yr(-1) suggest sustained mineral soil accumulation across all investigated landforms. Both yedoma and thermokarst landforms are characterized by limited accumulation of organic soil layers (peat). We further estimate that an active layer deepening of about 100 cm will increase organic C availability in a seasonally thawed state in the two study areas by similar to 5.8 Tg (13.2 kg C m(-2)). Our study demonstrates the importance of increasing the number of C and N storage inventories in ice-rich yedoma and thermokarst environments in order to account for high variability of permafrost and thermokarst environments in pan-permafrost soil C and N pool estimates.
Changes in rainfall interception along a secondary forest succession gradient in lowland Panama
(2013)
Secondary forests are rapidly expanding in tropical regions. Yet, despite the importance of understanding the hydrological consequences of land-cover dynamics, the relationship between forest succession and canopy interception is poorly understood. This lack of knowledge is unfortunate because rainfall interception plays an important role in regional water cycles and needs to be quantified for many modeling purposes. To help close this knowledge gap, we designed a throughfall monitoring study along a secondary succession gradient in a tropical forest region of Panama. The investigated gradient comprised 20 forest patches 3 to 130 yr old. We sampled each patch with a minimum of 20 funnel-type throughfall collectors over a continuous 2month period that had nearly 900 mm of rain. During the same period, we acquired forest inventory data and derived several forest structural attributes. We then applied simple and multiple regression models (Bayesian model averaging, BMA) and identified those vegetation parameters that had the strongest influence on the variation of canopy interception. Our analyses yielded three main findings. First, canopy interception changed rapidly during forest succession. After only a decade, throughfall volumes approached levels that are typical for mature forests. Second, a parsimonious (simple linear regression) model based on the ratio of the basal area of small stems to the total basal area outperformed more complex multivariate models (BMA approach). Third, based on complementary forest inventory data, we show that the influence of young secondary forests on interception in realworld fragmented landscapes might be detectable only in regions with a substantial fraction of young forests. Our re-sults suggest that where entire catchments undergo forest regrowth, initial stages of succession may be associated with a substantial decrease of streamflow generation. Our results further highlight the need to study hydrological processes in all forest succession stages, including early ones.
The Baringo-Tugen-Barsemoi 2013 drillcore (BTB13), acquired as part of the Hominin Sites and Paleolakes Drilling Project, recovered 228 m of fluviolacustrine sedimentary rocks and tuffs spanning a similar to 3.29-2.56 Ma interval of the highly fossiliferous and hominin-bearing Chemeron Formation, Tugen Hills, Kenya. Here we present a Bayesian stratigraphic age model for the core employing chronostratigraphic control points derived from Ar-40/Ar-39 dating of tuffs from core and outcrop, Ar-40/Ar-39 age calibration of related outcrop diatomaceous units, and core magnetostratigraphy. The age model reveals three main intervals with distinct sediment accumulation rates: an early rapid phase from 3.2 to 2.9 Ma; a relatively slow phase from 2.9 to 2.7 Ma; and the highest rate of accumulation from 2.7 to 2.6 Ma. The intervals of rapid accumulation correspond to periods of high Earth orbital eccentricity, whereas the slow accumulation interval corresponds to low eccentricity at 2.9-2.7 Ma, suggesting that astronomically mediated climate processes may be responsible for the observed changes in sediment accumulation rate. Lacustrine transgression-regression events, as delineated using sequence stratigraphy, dominantly operate on precession scale, particularly within the high eccentricity periods. A set of erosively based fluvial conglomerates correspond to the 2.9-2.7 Ma interval, which could be related to either the depositional response to low eccentricity or to the development of unconformities due to local tectonic activity. Age calibration of core magnetic susceptibility and gamma density logs indicates a close temporal correspondence between a shift from high- to low-frequency signal variability at similar to 3 Ma, approximately coincident the end of the mid-Piacenzian Warm Period, and the beginning of the cooling of world climate leading to the initiation of Northern Hemispheric glaciation c. 2.7 Ma. BTB13 and the Baringo Basin records may thus provide evidence of a connection between high-latitude glaciation and equatorial terrestrial climate toward the end of the Pliocene.
The Chew Bahir Drilling Project (CBDP) aims to test possible linkages between climate and evolution in Africa through the analysis of sediment cores that have recorded environmental changes in the Chew Bahir basin. In this statistical project we consider the Chew Bahir palaeolake to be a dynamical system consisting of interactions between its different components, such as the waterbody, the sediment beneath lake, and the organisms living within and around the lake. Recurrence is a common feature of such dynamical systems, with recurring patterns in the state of the system reflecting typical influences. Identifying and defining these influences contributes significantly to our understanding of the dynamics of the system. Different recurring changes in precipitation, evaporation, and wind speed in the Chew Bahir basin could result in similar (but not identical) conditions in the lake (e.g., depth and area of the lake, alkalinity and salinity of the lake water, species assemblages in the water body, and diagenesis in the sediments). Recurrence plots (RPs) are graphic displays of such recurring states within a system. Measures of complexity were subsequently introduced to complement the visual inspection of recurrence plots, and provide quantitative descriptions for use in recurrence quantification analysis (RQA). We present and discuss herein results from an RQA on the environmental record from six short (< 17 m) sediment cores collected during the CBDP, spanning the last 45 kyrs. The different types of variability and transitions in these records were classified to improve our understanding of the response of the biosphere to climate change, and especially the response of humans in the area.
Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961–1990) and a future (2071–2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.
Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961–1990) and a future (2071–2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate
projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.
Climate impacts on human livelihoods: where uncertainty matters in projections of water availability
(2014)
Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models, as well as greenhouse gas scenarios, are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure what is referred to here as AHEAD (Adequate Human livelihood conditions for wEll-being And Development). Based on a trans-disciplinary sample of concepts addressing human well-being and livelihoods, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows for the uncertainty of climate and impact model projections to be identified and differentiated. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions - and where it is not. The results indicate that livelihood conditions are compromised by water scarcity in 34 countries. However, more often, AHEAD fulfilment is limited through other elements. The analysis shows that the water-specific uncertainty ranges of the model output are outside relevant thresholds for AHEAD for 65 out of 111 countries, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. In 46 of the countries in the analysis, water-specific uncertainty is relevant to AHEAD. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy decisions.
Climate or land use?
(2017)
This study intends to contribute to the ongoing discussion on whether land use and land cover changes (LULC) or climate trends have the major influence on the observed increase of flood magnitudes in the Sahel. A simulation-based approach is used for attributing the observed trends to the postulated drivers. For this purpose, the ecohydrological model SWIM (Soil and Water Integrated Model) with a new, dynamic LULC module was set up for the Sahelian part of the Niger River until Niamey, including the main tributaries Sirba and Goroul. The model was driven with observed, reanalyzed climate and LULC data for the years 1950–2009. In order to quantify the shares of influence, one simulation was carried out with constant land cover as of 1950, and one including LULC. As quantitative measure, the gradients of the simulated trends were compared to the observed trend. The modeling studies showed that for the Sirba River only the simulation which included LULC was able to reproduce the observed trend. The simulation without LULC showed a positive trend for flood magnitudes, but underestimated the trend significantly. For the Goroul River and the local flood of the Niger River at Niamey, the simulations were only partly able to reproduce the observed trend. In conclusion, the new LULC module enabled some first quantitative insights into the relative influence of LULC and climatic changes. For the Sirba catchment, the results imply that LULC and climatic changes contribute in roughly equal shares to the observed increase in flooding. For the other parts of the subcatchment, the results are less clear but show, that climatic changes and LULC are drivers for the flood increase; however their shares cannot be quantified. Based on these modeling results, we argue for a two-pillar adaptation strategy to reduce current and future flood risk: Flood mitigation for reducing LULC-induced flood increase, and flood adaptation for a general reduction of flood vulnerability.
Climate or Land Use?
(2015)
This study intends to contribute to the ongoing discussion on whether land use and land cover changes (LULC) or climate trends have the major influence on the observed increase of flood magnitudes in the Sahel. A simulation-based approach is used for attributing the observed trends to the postulated drivers. For this purpose, the ecohydrological model SWIM (Soil and Water Integrated Model) with a new, dynamic LULC module was set up for the Sahelian part of the Niger River until Niamey, including the main tributaries Sirba and Goroul. The model was driven with observed, reanalyzed climate and LULC data for the years 1950-2009. In order to quantify the shares of influence, one simulation was carried out with constant land cover as of 1950, and one including LULC. As quantitative measure, the gradients of the simulated trends were compared to the observed trend. The modeling studies showed that for the Sirba River only the simulation which included LULC was able to reproduce the observed trend. The simulation without LULC showed a positive trend for flood magnitudes, but underestimated the trend significantly. For the Goroul River and the local flood of the Niger River at Niamey, the simulations were only partly able to reproduce the observed trend. In conclusion, the new LULC module enabled some first quantitative insights into the relative influence of LULC and climatic changes. For the Sirba catchment, the results imply that LULC and climatic changes contribute in roughly equal shares to the observed increase in flooding. For the other parts of the subcatchment, the results are less clear but show, that climatic changes and LULC are drivers for the flood increase; however their shares cannot be quantified. Based on these modeling results, we argue for a two-pillar adaptation strategy to reduce current and future flood risk: Flood mitigation for reducing LULC-induced flood increase, and flood adaptation for a general reduction of flood vulnerability.
Many agriculture-based economies are increasingly under stress from climate change and socio-economic pressures. The excessive exploitation of natural resources still represents the standard procedure to achieve socio-economic development. In the area of the Moulouya river basin, Morocco, natural water availability represents a key resource for all economic activities. Agriculture represents the most important sector, and frequently occurring water deficits are aggravated by climate change. On the basis of historical trends taken from CRU TS 2.1, this paper analyses the impact of climate change on the per capita water availability under inclusion of population trends. The Climatic Water Balance (CWB) shows a significant decrease for the winter period, causing adverse effects for the main agricultural season. Further, moisture losses due to increasing evapotranspiration rates indicate problems for the annual water budget and groundwater recharge. The per capita blue water availability falls below a minimum threshold of 500 m(3) per year, denoting a high regional vulnerability to increasing water scarcity assuming a no-response scenario. Regional development focusing on the water-intense sectors of agriculture and tourism appears to be at risk. Institutional capacities and policies need to address the problem, and the prompt implementation of innovative water production and efficiency measures is recommended.
The sediment flux through Himalayan rivers directly impacts water quality and is important for sustaining agriculture as well as maintaining drinking-water and hydropower generation. Despite the recent increase in demand for these resources, little is known about the triggers and sources of extreme sediment flux events, which lower water quality and account for extensive hydropower reservoir filling and turbine abrasion. Here, we present a comprehensive analysis of the spatiotemporal trends in suspended sediment flux based on daily data during the past decade (2001-2009) from four sites along the Sutlej River and from four of its main tributaries. In conjunction with satellite data depicting rainfall and snow cover, air temperature and earthquake records, and field observations, we infer climatic and geologic controls of peak suspended sediment concentration (SSC) events. Our study identifies three key findings: First, peak SSC events (a parts per thousand yen 99th SSC percentile) coincide frequently (57-80%) with heavy rainstorms and account for about 30% of the suspended sediment flux in the semi-arid to arid interior of the orogen. Second, we observe an increase of suspended sediment flux from the Tibetan Plateau to the Himalayan Front at mean annual timescales. This sediment-flux gradient suggests that averaged, modern erosion in the western Himalaya is most pronounced at frontal regions, which are characterized by high monsoonal rainfall and thick soil cover. Third, in seven of eight catchments, we find an anticlockwise hysteresis loop of annual sediment flux variations with respect to river discharge, which appears to be related to enhanced glacial sediment evacuation during late summer. Our analysis emphasizes the importance of unconsolidated sediments in the high-elevation sector that can easily be mobilized by hydrometeorological events and higher glacial-meltwater contributions. In future climate change scenarios, including continuous glacial retreat and more frequent monsoonal rainstorms across the Himalaya, we expect an increase in peak SSC events, which will decrease the water quality and impact hydropower generation.