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After a century of semi-restricted floodplain development, Southern Alberta, Canada, was struck by the devastating 2013 Flood. Aging infrastructure and limited property-level floodproofing likely contributed to the $4-6 billion (CAD) losses. Following this catastrophe, Alberta has seen a revival in flood management, largely focused on structural protections. However, concurrent with the recent structural work was a 100,000+ increase in Calgary's population in the 5 years following the flood, leading to further densification of high-hazard areas. This study implements the novel Stochastic Object-based Flood damage Dynamic Assessment (SOFDA) model framework to quantify the progression of the direct-damage flood risk in a mature urban neighborhood after the 2013 Flood. Five years of remote-sensing data, property assessment records, and inundation simulations following the flood are used to construct the model. Results show that in these 5 years, vulnerability trends (like densification) have increased flood risk by 4%; however, recent structural mitigation projects have reduced overall flood risk by 47% for this case study. These results demonstrate that the flood management revival in Southern Alberta has largely been successful at reducing flood risk; however, the gains are under threat from continued development and densification absent additional floodproofing regulations.
Phytoliths in particulate matter released by wind erosion on arable land in La Pampa, Argentina
(2022)
Silicon (Si) is considered a beneficial element in plant nutrition, but its importance on ecosystems goes far beyond that. Various forms of silicon are found in soils, of which the phytogenic pool plays a decisive role due to its good availability. This Si returns to the soil through the decomposition of plant residues, where they then participate in the further cycle as biogenic amorphous silica (bASi) or so-called phytoliths. These have a high affinity for water, so that the water holding capacity and water availability of soils can be increased even by small amounts of ASi. Agricultural land is a considerable global dust source, and dust samples from arable land have shown in cloud formation experiments a several times higher ice nucleation activity than pure mineral dust. Here, particle sizes in the particulate matter fractions (PM) are important, which can travel long distances and reach high altitudes in the atmosphere. Based on this, the research question was whether phytoliths could be detected in PM samples from wind erosion events, what are the main particle sizes of phytoliths and whether an initial quantification was possible.Measurements of PM concentrations were carried out at a wind erosion measuring field in the province La Pampa, Argentina. PM were sampled during five erosion events with Environmental Dust Monitors (EDM). After counting and classifying all particles with diameters between 0.3 and 32 mu m in the EDMs, they are collected on filters. The filters were analyzed by Scanning Electron Microscopy and Energy Dispersive X-Ray analysis (SEM-EDX) to investigate single or ensembles of particles regarding composition and possible origins.The analyses showed up to 8.3 per cent being phytoliths in the emitted dust and up to 25 per cent of organic origin. Particles of organic origin are mostly in the coarse dust fraction, whereas phytoliths are predominately transported in the finer dust fractions. Since phytoliths are both an important source of Si as a plant nutrient and are also involved in soil C fixation, their losses from arable land via dust emissions should be considered and its specific influence on atmospheric processes should be studied in detail in the future.
Urban air pollution is a substantial threat to human health. Traffic emissions remain a large contributor to air pollution in urban areas. The mobility restrictions put in place in response to the COVID-19 pandemic provided a large-scale real-world experiment that allows for the evaluation of changes in traffic emissions and the corresponding changes in air quality. Here we use observational data, as well as modelling, to analyse changes in nitrogen dioxide, ozone, and particulate matter resulting from the COVID-19 restrictions at the height of the lockdown period in Spring of 2020. Accounting for the influence of meteorology on air quality, we found that reduction of ca. 30-50 % in traffic counts, dominated by changes in passenger cars, corresponded to reductions in median observed nitrogen dioxide concentrations of ca. 40 % (traffic and urban background locations) and a ca. 22 % increase in ozone (urban background locations) during weekdays. Lesser reductions in nitrogen dioxide concentrations were observed at urban background stations at weekends, and no change in ozone was observed. The modelled reductions in median nitrogen dioxide at urban background locations were smaller than the observed reductions and the change was not significant. The model results showed no significant change in ozone on weekdays or weekends. The lack of a simulated weekday/weekend effect is consistent with previous work suggesting that NOx emissions from traffic could be significantly underestimated in European cities by models. These results indicate the potential for improvements in air quality due to policies for reducing traffic, along with the scale of reductions that would be needed to result in meaningful changes in air quality if a transition to sustainable mobility is to be seriously considered. They also confirm once more the highly relevant role of traffic for air quality in urban areas.
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.
Ranking local climate policy
(2021)
Climate mitigation and climate adaptation are crucial tasks for urban areas and can involve synergies as well as trade-offs. However, few studies have examined how mitigation and adaptation efforts relate to each other in a large number of differently sized cities, and therefore we know little about whether forerunners in mitigation are also leading in adaptation or if cities tend to focus on just one policy field. This article develops an internationally applicable approach to rank cities on climate policy that incorporates multiple indicators related to (1) local commitments on mitigation and adaptation, (2) urban mitigation and adaptation plans and (3) climate adaptation and mitigation ambitions. We apply this method to rank 104 differently sized German cities and identify six clusters: climate policy leaders, climate adaptation leaders, climate mitigation leaders, climate policy followers, climate policy latecomers and climate policy laggards. The article seeks explanations for particular cities' positions and shows that coping with climate change in a balanced way on a high level depends on structural factors, in particular city size, the pathways of local climate policies since the 1990s and funding programmes for both climate mitigation and adaptation.
Knowing the source and runout of debris flows can help in planning strategies aimed at mitigating these hazards. Our research in this paper focuses on developing a novel approach for optimizing runout models for regional susceptibility modelling, with a case study in the upper Maipo River basin in the Andes of Santiago, Chile. We propose a two-stage optimization approach for automatically selecting parameters for estimating runout path and distance. This approach optimizes the random-walk and Perla et al.'s (PCM) two-parameter friction model components of the open-source Gravitational Process Path (GPP) modelling framework. To validate model performance, we assess the spatial transferability of the optimized runout model using spatial crossvalidation, including exploring the model's sensitivity to sample size. We also present diagnostic tools for visualizing uncertainties in parameter selection and model performance. Although there was considerable variation in optimal parameters for individual events, we found our runout modelling approach performed well at regional prediction of potential runout areas. We also found that although a relatively small sample size was sufficient to achieve generally good runout modelling performance, larger samples sizes (i.e. >= 80) had higher model performance and lower uncertainties for estimating runout distances at unknown locations. We anticipate that this automated approach using the open-source R software and the System for Automated Geoscientific Analyses geographic information system (SAGA-GIS) will make process-based debris-flow models more readily accessible and thus enable researchers and spatial planners to improve regional-scale hazard assessments.
We present a chronology framework named LegacyAge 1.0 containing harmonized chronologies for 2831 pollen records (downloaded from the Neotoma Paleoecology Database and the supplementary Asian datasets) together with their age control points and metadata in machine-readable data formats.
All chronologies use the Bayesian framework implemented in Bacon version 2.5.3. Optimal parameter settings of priors (accumulation.shape, memory.strength, memory.mean, accumulation.rate, and thickness) were identified based on information in the original publication or iteratively after preliminary model inspection.
The most common control points for the chronologies are radiocarbon dates (86.1 %), calibrated by the latest calibration curves (IntCal20 and SHCal20 for the terrestrial radiocarbon dates in the Northern Hemisphere and Southern Hemisphere and Marine20 for marine materials).
The original publications were consulted when dealing with outliers and inconsistencies. Several major challenges when setting up the chronologies included the waterline issue (18.8% of records), reservoir effect (4.9 %), and sediment deposition discontinuity (4.4 %).
Finally, we numerically compare the LegacyAge 1.0 chronologies to those published in the original publications and show that the reliability of the chronologies of 95.4% of records could be improved according to our assessment.
Our chronology framework and revised chronologies provide the opportunity to make use of the ages and age uncertainties in synthesis studies of, for example, pollen-based vegetation and climate change.
The LegacyAge 1.0 dataset, including metadata, datings, harmonized chronologies, and R code used, is openaccess and available at PANGAEA (https://doi.org/10.1594/PANGAEA.933132; Li et al., 2021) and Zenodo (https://doi.org/10.5281/zenodo.5815192; Li et al., 2022), respectively.
Drought and the availability of mineable phosphorus minerals used for fertilization are two of the important issues agriculture is facing in the future. High phosphorus availability in soils is necessary to maintain high agricultural yields. Drought is one of the major threats for terrestrial ecosystem performance and crop production in future. Among the measures proposed to cope with the upcoming challenges of intensifying drought stress and to decrease the need for phosphorus fertilizer application is the fertilization with silica (Si). Here we tested the importance of soil Si fertilization on wheat phosphorus concentration as well as wheat performance during drought at the field scale. Our data clearly showed a higher soil moisture for the Si fertilized plots. This higher soil moisture contributes to a better plant performance in terms of higher photosynthetic activity and later senescence as well as faster stomata responses ensuring higher productivity during drought periods. The plant phosphorus concentration was also higher in Si fertilized compared to control plots. Overall, Si fertilization or management of the soil Si pools seem to be a promising tool to maintain crop production under predicted longer and more serve droughts in the future and reduces phosphorus fertilizer requirements.
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.
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.
The fluxes of water and solutes in the subsurface compartment of the Critical Zone are temporally dynamic and it is unclear how this impacts microbial mediated nutrient cycling in the spatially heterogeneous subsurface. To investigate this, we undertook numerical modeling, simulating the transport in a wide range of spatially heterogeneous domains, and the biogeochemical transformation of organic carbon and nitrogen compounds using a complex microbial community with four (4) distinct functional groups, in water saturated subsurface compartments. We performed a comprehensive uncertainty analysis accounting for varying residence times and spatial heterogeneity. While the aggregated removal of chemical species in the domains over the entire simulation period was approximately the same as that in steady state conditions, the sub-scale temporal variation of microbial biomass and chemical discharge from a domain depended strongly on the interplay of spatial heterogeneity and temporal dynamics of the forcing. We showed that the travel time and the Damkohler number (Da) can be used to predict the temporally varying chemical discharge from a spatially heterogeneous domain. In homogeneous domains, chemical discharge in temporally dynamic conditions could be double of that in the steady state conditions while microbial biomass varied up to 75% of that in steady state conditions. In heterogeneous domains, the interquartile range of uncertainty in chemical discharge in reaction dominated systems (log(10)Da > 0) was double of that in steady state conditions. However, high heterogeneous domains resulted in outliers where chemical discharge could be as high as 10-20 times of that in steady state conditions in high flow periods. And in transport dominated systems (log(10)Da < 0), the chemical discharge could be half of that in steady state conditions in unusually low flow conditions. In conclusion, ignoring spatio-temporal heterogeneities in a numerical modeling approach may exacerbate inaccurate estimation of nutrient export and microbial biomass. The results are relevant to long-term field monitoring studies, and for homogeneous soil column-scale experiments investigating the role of temporal dynamics on microbial redox dynamics.
Despite the amount of research focussed on the Alpine orogen, different hypotheses still exist regarding varying spatial seismicity distribution patterns throughout the region. Previous measurement-constrained regional 3D models of lithospheric density distribution and thermal field facilitate the generation of a data-based rheological model of the region.
In this study, we compute the long-term lithospheric strength and compare its spatial variation to observed seismicity patterns. We demonstrate how strength maxima within the crust (similar to 1 GPa) and upper mantle (> 2 GPa) occur at temperatures characteristic of the onset of crystal plasticity in those rocks (crust: 200-400 degrees C; mantle: similar to 600 degrees C), with almost all seismicity occurring in these regions. Correlation in the northern and southern forelands between crustal and lithospheric strengths and seismicity show different patterns of event distribution, reflecting their different tectonic settings. Seismicity in the plate boundary setting of the southern foreland corresponds to the integrated lithospheric strength, occurring mainly in the weaker domains surrounding the strong Adriatic plate. In the intraplate setting of the northern foreland, seismicity correlates to modelled crustal strength, and it mainly occurs in the weaker and warmer crust beneath the Upper Rhine Graben.
We, therefore, suggest that seismicity in the upper crust is linked to weak crustal domains, which are more prone to localise deformation promoting failure and, depending on the local properties of the fault, earthquakes at relatively lower levels of accumulated stress than their neighbouring stronger counterparts. Upper mantle seismicity at depths greater than modelled brittle conditions, can be either explained by embrittlement of the mantle due to grain-size sensitive deformation within domains of active or recent slab cooling, or by dissipative weakening mechanisms, such as thermal runaway from shear heating and/or dehydration reactions within an overly ductile mantle.
Results generated in this study are available for open access use to further discussions on the region.
Hundreds of basaltic plateau margins east of the Patagonian Cordillera are undermined by numerous giant slope failures. However, the overall extent of this widespread type of plateau collapse remains unknown and incompletely captured in local maps. To detect giant slope failures consistently throughout the region, we train two convolutional neural networks (CNNs), AlexNet and U-Net, with Sentinel-2 optical data and TanDEM-X topographic data on elevation, surface roughness, and curvature. We validated the performance of these CNNs with independent testing data and found that AlexNet performed better when learned on topographic data, and UNet when learned on optical data. AlexNet predicts a total landslide area of 12,000 km2 in a study area of 450,000 km2, and thus one of Earth's largest clusters of giant landslides. These are mostly lateral spreads and rotational failures in effusive rocks, particularly eroding the margins of basaltic plateaus; some giant landslides occurred along shores of former glacial lakes, but are least prevalent in Quaternary sedimentary rocks. Given the roughly comparable topographic, climatic, and seismic conditions in our study area, we infer that basalts topping weak sedimentary rocks may have elevated potential for large-scale slope failure. Judging from the many newly detected and previously unknown landslides, we conclude that CNNs can be a valuable tool to detect large-scale slope instability at the regional scale. However, visual inspection is still necessary to validate results and correctly outline individual landslide source and deposit areas.
Geostatistics as a subfield of statistics accounts for the spatial correlations encountered in many applications of, for example, earth sciences. Valuable information can be extracted from these correlations, also helping to address the often encountered burden of data scarcity. Despite the value of additional data, the use of geostatistics still falls short of its potential. This problem is often connected to the lack of user-friendly software hampering the use and application of geostatistics. We therefore present GSTools, a Python-based software suite for solving a wide range of geostatistical problems. We chose Python due to its unique balance between usability, flexibility, and efficiency and due to its adoption in the scientific community. GSTools provides methods for generating random fields; it can perform kriging, variogram estimation and much more. We demonstrate its abilities by virtue of a series of example applications detailing their use.
Droughts in São Paulo
(2023)
Literature has suggested that droughts and societies are mutually shaped and, therefore, both require a better understanding of their coevolution on risk reduction and water adaptation. Although the Sao Paulo Metropolitan Region drew attention because of the 2013-2015 drought, this was not the first event. This paper revisits this event and the 1985-1986 drought to compare the evolution of drought risk management aspects. Documents and hydrological records are analyzed to evaluate the hazard intensity, preparedness, exposure, vulnerability, responses, and mitigation aspects of both events. Although the hazard intensity and exposure of the latter event were larger than the former one, the policy implementation delay and the dependency of service areas in a single reservoir exposed the region to higher vulnerability. In addition to the structural and non-structural tools implemented just after the events, this work raises the possibility of rainwater reuse for reducing the stress in reservoirs.
The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.
Wind erosion of agricultural soils affects their stock of essential elements for plants, like phosphorus (P). It is known that the composition of the eroded sediments varies with height, according to the size and density of the transported substances. Aim of this study was to analyze the concentration and enrichment ratios of P forms in sediments transported by the wind. A wind-tunnel study was performed on a sandy-and a sandy loam soil in order to measure P forms concentrations in the saltating sediments. P concentrations were also measured in the particulate matter (PM) of each soil, gained with the Easy Dust Generator. In both soils, inorganic-(Pi) and organic P (Po) were preferentially transported in PM, with enrichment ratios of 1.8 and 5.5, respectively. Nevertheless, a Pi/Po of 0.9 indicated that the accumulation of the minor Po in PM was more pronounced than Pi. This agrees with P-rich light and easily erodible organic compounds, almost exclusively accumulated in PM, and in relatively heavy and less erodible minerals, like apatites, in lower height sediments. Labile P (Pl) was preferentially transported in saltating sediments of both soils. This was attributed to the selective Bray & Kurtz I's extraction of the abundant inorganic P forms of these sediments. Total P (Pt) copied the transport trends of Pi, the major form. According to the transporting trends, Pi and Po would be re-sedimented at longer distances from the source than Pl. Outcomes become useful for modeling the influence of wind erosion on P cycling.
Land degradation and water availability in semi-arid regions are interdependent challenges for management that are influenced by climatic and anthropogenic changes. Erosion and high sediment loads in rivers cause reservoir siltation and decrease storage capacity, which pose risk on water security for citizens, agriculture, and industry. In regions where resources for management are limited, identifying spatial-temporal variability of sediment sources is crucial to decrease siltation. Despite widespread availability of rigorous methods, approaches simplifying spatial and temporal variability of erosion are often inappropriately applied to very data sparse semi-arid regions. In this work, we review existing approaches for mapping erosional hotspots, and provide an example of spatial-temporal mapping approach in two case study regions. The barriers limiting data availability and their effects on erosion mapping methods, their validation, and resulting prioritization of leverage management areas are discussed.
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.
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.
Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost-vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. <br /> Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen-evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics.
Previous studies have explored the consequences of flood events for exposed households and companies by focusing on single flood events. Less is known about the consequences of experiencing repeated flood events for the resilience of households and companies. In this paper, we therefore explore how multiple floods experience affects the resilience of exposed households and companies. Resilience was made operational through individual appraisals of households and companies' ability to withstand and recover from material as well as health and psychological impacts of the 2013 flood in Germany. The paper is based on three different datasets including more than 2000 households and 300 companies that were affected by the 2013 flood. The surveys revealed that the resilience of households seems to increase, but only with regard to their subjectively appraised ability to withstand impacts on mobile goods and equipment (e.g., cars, TV, and radios). In regard to the ability of households to withstand overall financial consequences of repetitive floods, evidence for nonlinear (quadratic) trends can be found. With regard to psychological and health-related consequences, the findings are mixed but provide tentative evidence for eroding resilience among households. Companies' resilience increased with respect to material assets but appears to decrease with respect to ability to recover. We conclude by arguing that clear and operational definitions of resilience are required so that evidence-based resilience baselines can be established to assess whether resilience is eroding or improving over time.
Groundwater is the biggest single source of high-quality freshwater worldwide, which is also continuously threatened by the changing climate. In this paper, we investigate the response of the regional groundwater system to climate change under three global warming levels (1.5, 2, and 3 ∘C) in a central German basin (Nägelstedt). This investigation is conducted by deploying an integrated modeling workflow that consists of a mesoscale hydrologic model (mHM) and a fully distributed groundwater model, OpenGeoSys (OGS). mHM is forced with climate simulations of five general circulation models under three representative concentration pathways. The diffuse recharges estimated by mHM are used as boundary forcings to the OGS groundwater model to compute changes in groundwater levels and travel time distributions. Simulation results indicate that groundwater recharges and levels are expected to increase slightly under future climate scenarios. Meanwhile, the mean travel time is expected to decrease compared to the historical average. However, the ensemble simulations do not all agree on the sign of relative change. Changes in mean travel time exhibit a larger variability than those in groundwater levels. The ensemble simulations do not show a systematic relationship between the projected change (in both groundwater levels and travel times) and the warming level, but they indicate an increased variability in projected changes with adjusting the enhanced warming level from 1.5 to 3 ∘C. Correspondingly, it is highly recommended to restrain the trend of global warming.
Submerged sequences of marine terraces potentially provide crucial information of past sea-level positions. However, the distribution and characteristics of drowned marine terrace sequences are poorly known at a global scale. Using bathymetric data and novel mapping and modeling techniques, we studied a submerged sequence of marine terraces in the Bay of Biscay with the objective to identify the distribution and morphologies of submerged marine terraces and the timing and conditions that allowed their formation and preservation. To accomplish the objectives a high-resolution bathymetry (5 m) was analyzed using Geographic Information Systems and TerraceM(R). The successive submerged terraces were identified using a Surface Classification Model, which linearly combines the slope and the roughness of the surface to extract fossil sea-cliffs and fossil rocky shore platforms. For that purpose, contour and hillshaded maps were also analyzed. Then, shoreline angles, a geomorphic marker located at the intersection between the fossil sea-cliff and platform, were mapped analyzing swath profiles perpendicular to the isobaths. Most of the submerged strandlines are irregularly preserved throughout the continental shelf. In summary, 12 submerged terraces with their shoreline angles between approximately: -13 m (T1), -30 and -32 m (T2), -34 and 41 m (T3), -44 and -47 m (T4), -49 and 53 m (T5), -55 and 58 m (T6), -59 and 62 m (T7), -65 and 67 m (T8), -68 and 70 m (T9), -74 and -77 m (T10), -83 and -86 m (T11) and -89 and 92 m (T12). Nevertheless, the ones showing the best lateral continuity and preservation in the central part of the shelf are T3, T4, T5, T7, T8, and T10. The age of the terraces has been estimated using a landscape evolution model. To simulate the formation and preservation of submerged terraces three different scenarios: (i) 20-0 ka; (ii) 128-0 ka; and (iii) 128-20 ka, were compared. The best scenario for terrace generation was between 128 and 20 Ka, where T3, T5, and T7 could have been formed.
Due to the fact that silicon (Si) increases the resistance of plants against diverse abiotic and biotic stresses, Si nowadays is categorized as beneficial substance for plants. However, humans directly influence Si cycling on a global scale. Intensified agriculture and corresponding harvest-related Si exports lead to Si losses in agricultural soils. This anthropogenic desilication might be a big challenge for modern agriculture. However, there is still only little knowledge about Si cycling in agricultural systems of the temperate zone, because most studies focus on rice and sugarcane production in (sub)tropical areas. Furthermore, many studies are performed for a short term only, and thus do not provide the opportunity to analyze slow changes in soil-plant systems (e.g., desilication) over long periods. We analyzed soil and plant samples from an ongoing long-term field experiment (established 1963) in the temperate zone (NE Germany) to evaluate the effects of different nitrogen-phosphoruspotassium (NPK) fertilization rates and crop straw recycling (i.e., straw incorporation) on anthropogenic desilication in the long term. Our results clearly show that crop straw recycling not only prevents anthropogenic desilication (about 43-60% of Si exports can be saved by crop straw recycling in the long term), but also replenishes plant available Si stocks of agricultural soil-plant systems. Furthermore, we found that a reduction of N fertilization rates of about 69% is possible without considerable biomass losses. This economy of the need for N fertilizers potentially can be combined with the benefits of crop straw recycling, i.e., enhancement of carbon sequestration via straw inputs and prevention of anthropogenic desilication of agricultural soil-plant systems. Thus crop straw recycling might have the potential to act as key management practice in sustainable, low fertilization agriculture in the temperate zone in the future.
Pollen records from Siberia are mostly absent in global or Northern Hemisphere synthesis works. Here we present a taxonomically harmonized and temporally standardized pollen dataset that was synthesized using 173 palynological records from Siberia and adjacent areas (northeastern Asia, 42-75 degrees N, 50-180 degrees E). Pollen data were taxonomically harmonized, i.e. the original 437 taxa were assigned to 106 combined pollen taxa. Age-depth models for all records were revised by applying a constant Bayesian age-depth modelling routine. The pollen dataset is available as count data and percentage data in a table format (taxa vs. samples), with age information for each sample. The dataset has relatively few sites covering the last glacial period between 40 and 11.5 ka (calibrated thousands of years before 1950 CE) particularly from the central and western part of the study area. In the Holocene period, the dataset has many sites from most of the area, with the exception of the central part of Siberia. Of the 173 pollen records, 81 % of pollen counts were downloaded from open databases (GPD, EPD, PANGAEA) and 10 % were contributions by the original data gatherers, while a few were digitized from publications. Most of the pollen records originate from peatlands (48 %) and lake sediments (33 %). Most of the records (83 %) have >= 3 dates, allowing the establishment of reliable chronologies. The dataset can be used for various purposes, including pollen data mapping (example maps for Larix at selected time slices are shown) as well as quantitative climate and vegetation reconstructions. The datasets for pollen counts and pollen percentages are available at https://doi.org/10.1594/PANGAEA.898616 (Cao et al., 2019a), also including the site information, data source, original publication, dating data, and the plant functional type for each pollen taxa.
Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming
(2020)
Background: Investigating future changes in temperature-related mortality as a function of global mean temperature (GMT) rise allows for the evaluation of policy-relevant climate change targets. So far, only few studies have taken this approach, and, in particular, no such assessments exist for Germany, the most populated country of Europe.
Methods: We assess temperature-related mortality in 12 major German cities based on daily time-series of all-cause mortality and daily mean temperatures in the period 1993-2015, using distributed-lag non-linear models in a two-stage design. Resulting risk functions are applied to estimate excess mortality in terms of GMT rise relative to pre-industrial levels, assuming no change in demographics or population vulnerability.
Results: In the observational period, cold contributes stronger to temperature-related mortality than heat, with overall attributable fractions of 5.49% (95%CI: 3.82-7.19) and 0.81% (95%CI: 0.72-0.89), respectively. Future projections indicate that this pattern could be reversed under progressing global warming, with heat-related mortality starting to exceed cold-related mortality at 3 degrees C or higher GMT rise. Across cities, projected net increases in total temperature-related mortality were 0.45% (95%CI: -0.02-1.06) at 3 degrees C, 1.53% (95%CI: 0.96-2.06) at 4 degrees C, and 2.88% (95%CI: 1.60-4.10) at 5 degrees C, compared to today's warming level of 1 degrees C. By contrast, no significant difference was found between projected total temperature-related mortality at 2 degrees C versus 1 degrees C of GMT rise.
Conclusions: Our results can inform current adaptation policies aimed at buffering the health risks from increased heat exposure under climate change. They also allow for the evaluation of global mitigation efforts in terms of local health benefits in some of Germany's most populated cities.
Landscapes in high northern latitudes are assumed to be highly sensitive to future global change, but the rates and long-term trajectories of changes are rather uncertain. In the boreal zone, fires are an important factor in climate-vegetation interactions and biogeochemical cycles. Fire regimes are characterized by small, frequent, low-intensity fires within summergreen boreal forests dominated by larch, whereas evergreen boreal forests dominated by spruce and pine burn large areas less frequently but at higher intensities. Here, we explore the potential of the monosaccharide anhydrides (MA) levoglucosan, mannosan and galactosan to serve as proxies of low-intensity biomass burning in glacial-to-interglacial lake sediments from the high northern latitudes. We use sediments from Lake El'gygytgyn (cores PG 1351 and ICDP 5011-1), located in the far north-east of Russia, and study glacial and interglacial samples of the last 430 kyr (marine isotope stages 5e, 6, 7e, 8, 11c and 12) that had different climate and biome configurations. Combined with pollen and non-pollen palynomorph records from the same samples, we assess how far the modern relationships between fire, climate and vegetation persisted during the past, on orbital to centennial timescales. We find that MAs attached to particulates were well-preserved in up to 430 kyr old sediments with higher influxes from low-intensity biomass burning in interglacials compared to glacials. MA influxes significantly increase when summergreen boreal forest spreads closer to the lake, whereas they decrease when tundra-steppe environments and, especially, Sphagnum peatlands spread. This suggests that low-temperature fires are a typical characteristic of Siberian larch forests also on long timescales. The results also suggest that low-intensity fires would be reduced by vegetation shifts towards very dry environments due to reduced biomass availability, as well as by shifts towards peatlands, which limits fuel dryness. In addition, we observed very low MA ratios, which we interpret as high contributions of galactosan and mannosan from biomass sources other than those currently monitored, such as the moss-lichen mats in the understorey of the summergreen boreal forest. Overall, sedimentary MAs can provide a powerful proxy for fire regime reconstructions and extend our knowledge of long-term natural fire-climate-vegetation feedbacks in the high northern latitudes.
Recent policy changes highlight the need for citizens to take adaptive actions to reduce flood-related impacts. Here, we argue that these changes represent a wider behavioral turn in flood risk management (FRM). The behavioral turn is based on three fundamental assumptions: first, that the motivations of citizens to take adaptive actions can be well understood so that these motivations can be targeted in the practice of FRM; second, that private adaptive measures and actions are effective in reducing flood risk; and third, that individuals have the capacities to implement such measures. We assess the extent to which the assumptions can be supported by empirical evidence. We do this by engaging with three intellectual catchments. We turn to research by psychologists and other behavioral scientists which focus on the sociopsychological factors which influence individual motivations (Assumption 1). We engage with economists, engineers, and quantitative risk analysts who explore the extent to which individuals can reduce flood related impacts by quantifying the effectiveness and efficiency of household-level adaptive measures (Assumption 2). We converse with human geographers and sociologists who explore the types of capacities households require to adapt to and cope with threatening events (Assumption 3). We believe that an investigation of the behavioral turn is important because if the outlined assumptions do not hold, there is a risk of creating and strengthening inequalities in FRM. Therefore, we outline the current intellectual and empirical knowledge as well as future research needs. Generally, we argue that more collaboration across intellectual catchments is needed, that future research should be more theoretically grounded and become methodologically more rigorous and at the same time focus more explicitly on the normative underpinnings of the behavioral turn.
Aim This study investigates taxonomic and phylogenetic diversity in diatom genera to evaluate assembly rules for eukaryotic microbes across the Siberian tree line. We first analysed how phylogenetic distance relates to taxonomic richness and turnover. Second, we used relatedness indices to evaluate if environmental filtering or competition influences the assemblies in space and through time. Third, we used distance-based ordination to test which environmental variables shape diatom turnover. Location Yakutia and Taymyria, Russia: we sampled 78 surface sediments and a sediment core, extending to 7,000 years before present, to capture the forest-tundra transition in space and time respectively. Taxon Arctic freshwater diatoms. Methods We applied metabarcoding to retrieve diatom diversity from surface and core sedimentary DNA. The taxonomic assignment binned sequence types (lineages) into genera and created taxonomic (abundance of lineages within different genera) and phylogenetic datasets (phylogenetic distances of lineages within different genera). Results Contrary to our expectations, we find a unimodal relationship between phylogenetic distance and richness in diatom genera. We discern a positive relationship between phylogenetic distance and taxonomic turnover in spatially and temporally distributed diatom genera. Furthermore, we reveal positive relatedness indices in diatom genera across the spatial environmental gradient and predominantly in time slices at a single location, with very few exceptions assuming effects of competition. Distance-based ordination of taxonomic and phylogenetic turnover indicates that lake environment variables, like HCO3- and water depth, largely explain diatom turnover. Main conclusion Phylogenetic and abiotic assembly rules are important in understanding the regional assembly of diatom genera across lakes in the Siberian tree line ecotone. Using a space-time approach we are able to exclude the influence of geography and elucidate that lake environmental variables primarily shape the assemblies. We conclude that some diatom genera have greater capabilities to adapt to environmental changes, whereas others will be putatively replaced or lost due to the displacement of the Arctic tundra biome under recent global warming.
Model-derived relationships between chlorophyll a (Chl-a) and nutrients and temperature have fundamental implications for understanding complex interactions among water quality measures used for lake classification, yet accuracy comparisons of different approaches are scarce. Here, we (1) compared Chl-a model performances across linear and nonlinear statistical approaches; (2) evaluated single and combined effects of nutrients, depth, and temperature as lake surface water temperature (LSWT) or altitude on Chl-a; and (3) investigated the reliability of the best water quality model across 13 lakes from perialpine and central Balkan mountain regions. Chl-a was modelled using in situ water quality data from 157 European lakes; elevation data and LSWT in situ data were complemented by remote sensing measurements. Nonlinear approaches performed better, implying complex relationships between Chl-a and the explanatory variables. Boosted regression trees, as the best performing approach, accommodated interactions among predictor variables. Chl-a-nutrient relationships were characterized by sigmoidal curves, with total phosphorus having the largest explanatory power for our study region. In comparison with LSWT, utilization of altitude, the often-used temperature surrogate, led to different influence directions but similar predictive performances. These results support utilizing altitude in models for Chl-a predictions. Compared to Chl-a observations, Chl-a predictions of the best performing approach for mountain lakes (oligotrophic-eutrophic) led to minor differences in trophic state categorizations. Our findings suggest that both models with LSWT and altitude are appropriate for water quality predictions of lakes in mountain regions and emphasize the importance of incorporating interactions among variables when facing lake management challenges.
The Ca Mau peninsula (CMP) is a key economic region in southern Vietnam. In recent decades, the high demand for water has increased the exploitation of groundwater, thus lowering the groundwater level and leading to risks of degradation, depletion, and land subsidence, as well as salinity intrusion in the groundwater of the whole Mekong Delta region. By using a finite element groundwater model with boundary expansion to the sea, we updated the latest data on hydrogeological profiles, groundwater levels, and exploitation. The basic model setup covers seven aquifers and seven aquitards. It is determined that the inflow along the coastline to the mainland is 39% of the total inflow. The exploitation of the study area in 2019 was 567,364 m(3)/day. The most exploited aquifers are the upper-middle Pleistocene (qp(2-3)) and the middle Pliocene (n(2)(2)), accounting for 63.7% and 24.6%, respectively; the least exploited aquifers are the upper Pleistocene and the upper Miocene, accounting for 0.35% and 0.02%, respectively. In the deeper aquifers, qp(2-3) and n(2)(2), the change in storage is negative due to the high exploitation rate, leading to a decline in the reserves of these aquifers. These groundwater model results are the calculations of groundwater reserves from the coast to the mainland in the entire system of aquifers in the CMP. This makes groundwater decision managers, stakeholders, and others more efficient in sustainable water resources planning in the CMP and Mekong Delta (MKD).
Channel steepness index, k(s), is a metric derived from the stream power model that, under certain conditions, scales with relative rock uplift rate. Channel steepness index is a property of rivers, which can be relatively easily extracted from digital elevation models (DEMs). As DEM data sets are widely available for Earth and are becoming more readily available for other planetary bodies, channel steepness index represents a powerful tool for interpreting tectonic processes. However, multiple approaches to calculate channel steepness index exist. From this several important questions arise; does choice of approach change the values of channel steepness index, can values be so different that choice of approach can influence the findings of a study, and are certain approaches better than others? With the aid of a synthetic river profile and a case study from the Sierra Nevada, California, we show that values of channel steepness index vary over orders of magnitude according to the methodology used in the calculation. We explore the limitations, advantages and disadvantages of the key approaches to calculating channel steepness index, and find that choosing an appropriate approach relies on the context of a study. Given these observations, it is important that authors acknowledge the methodology used to calculate channel steepness index, to ensure that results can be contextualised and reproduced.
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.
Fires are a fundamental part of the Earth System. In the last decades, they have been altering ecosystem structure, biogeochemical cycles and atmospheric composition with unprecedented rapidity. In this study, we implement a complex networks-based methodology to track individual fires over space and time. We focus on extreme fires-the 5% most intense fires-in the tropical forests of the Brazilian Legal Amazon over the period 2002-2019. We analyse the interannual variability in the number and spatial patterns of extreme forest fires in years with diverse climatic conditions and anthropogenic pressure to examine potential synergies between climate and anthropogenic drivers. We observe that major droughts, that increase forest flammability, co-occur with high extreme fire years but also that it is fundamental to consider anthropogenic activities to understand the distribution of extreme fires. Deforestation fires, fires escaping from managed lands, and other types of forest degradation and fragmentation provide the ignition sources for fires to ignite in the forests. We find that all extreme forest fires identified are located within a 0.5-km distance from forest edges, and up to 56% of them are within a 1-km distance from roads (which increases to 73% within 5 km), showing a strong correlation that defines spatial patterns of extreme fires.
Study region:
Ca Mau Province (CMP), Mekong Delta (MD), Vietnam.
Study focus:
Groundwater from deep aquifers is the most reliable source of freshwater in the MD but extensive overexploitation in the last decades led to the drop of hydraulic heads and negative environmental impacts. Therefore, a comprehensive groundwater investigation was conducted to evaluate its composition in the context of Quaternary marine transgression and regression cycles, geochemical processes as well as groundwater extraction.
New hydrological insights for the region:
The abundance of groundwater of Na-HCO3 type and distinct ion ratios, such as Na+/Cl-, indicate extensive freshwater intrusion in an initially saline hydrogeological system, with decreasing intensity from upper Pleistocene to deeper Miocene aquifers, most likely during the last marine regression phase 60-12 ka BP. Deviations from the conservative mixing line between the two endmembers seawater and freshwater are attributed to ion-exchange processes on mineral surfaces, making ion ratios in combination with a customized water type analysis a useful tool to distinguish between salinization and freshening processes. Elevated salinity in some areas is attributed to HCO3- generation by organic matter decomposition in marine sediments rather than to seawater intrusion. Nevertheless, a few randomly distributed locations show strong evidence of recent salinization in an early stage, which may be caused by the downwards migration of saline Holocene groundwater through natural and anthropogenic pathways into deep aquifers.
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.
Controls on the deformation pattern (shortening mode and tectonic style) of orogenic forelands during lithospheric shortening remain poorly understood. Here, we use high-resolution 2D thermomechanical models to demonstrate that orogenic crustal thickness and foreland lithospheric thickness significantly control the shortening mode in the foreland. Pure-shear shortening occurs when the orogenic crust is not thicker than the foreland crust or thick, but the foreland lithosphere is thin (<70-80 km, as in the Puna foreland case). Conversely, simple-shear shortening, characterized by foreland underthrusting beneath the orogen, arises when the orogenic crust is much thicker. This thickened crust results in high gravitational potential energy in the orogen, which triggers the migration of deformation to the foreland under further shortening. Our models present fully thick-skinned, fully thin-skinned, and intermediate tectonic styles in the foreland. The first tectonics forms in a pure-shear shortening mode whereas the others require a simple-shear mode and the presence of thick (>similar to 4 km) sediments that are mechanically weak (friction coefficient <similar to 0.05) or weakened rapidly during deformation. The formation of fully thin-skinned tectonics in thick and weak foreland sediments, as in the Subandean Ranges, requires the strength of the orogenic upper lithosphere to be less than one-third as strong as that of the foreland upper lithosphere. Our models successfully reproduce foreland deformation patterns in the Central and Southern Andes and the Laramide province.
Silicon (Si) speciation and availability in soils is highly important for ecosystem functioning, because Si is a beneficial element for plant growth. Si chemistry is highly complex compared to other elements in soils, because Si reaction rates are relatively slow and dependent on Si species. Consequently, we review the occurrence of different Si species in soil solution and their changes by polymerization, depolymerization, and condensation in relation to important soil processes. We show that an argumentation based on thermodynamic endmembers of Si dependent processes, as currently done, is often difficult, because some reactions such as mineral crystallization require months to years (sometimes even centuries or millennia). Furthermore, we give an overview of Si reactions in soil solution and the predominance of certain solid compounds, which is a neglected but important parameter controlling the availability, reactivity, and function of Si in soils. We further discuss the drivers of soil Si cycling and how humans interfere with these processes. The soil Si cycle is of major importance for ecosystem functioning; therefore, a deeper understanding of drivers of Si cycling (e.g., predominant speciation), human disturbances and the implication for important soil properties (water storage, nutrient availability, and micro aggregate stability) is of fundamental relevance.
Building and changing a microbiome at will and maintaining it over hundreds of generations has so far proven challenging. Despite best efforts, complex microbiomes appear to be susceptible to large stochastic fluctuations. Current capabilities to assemble and control stable complex microbiomes are limited. Here, we propose a looped mass transfer design that stabilizes microbiomes over long periods of time. Five local microbiomes were continuously grown in parallel for over 114 generations and connected by a loop to a regional pool. Mass transfer rates were altered and microbiome dynamics were monitored using quantitative high-throughput flow cytometry and taxonomic sequencing of whole communities and sorted subcommunities. Increased mass transfer rates reduced local and temporal variation in microbiome assembly, did not affect functions, and overcame stochasticity, with all microbiomes exhibiting high constancy and increasing resistance. Mass transfer synchronized the structures of the five local microbiomes and nestedness of certain cell types was eminent. Mass transfer increased cell number and thus decreased net growth rates mu'. Subsets of cells that did not show net growth mu'SCx were rescued by the regional pool R and thus remained part of the microbiome. The loop in mass transfer ensured the survival of cells that would otherwise go extinct, even if they did not grow in all local microbiomes or grew more slowly than the actual dilution rate D would allow. The rescue effect, known from metacommunity theory, was the main stabilizing mechanism leading to synchrony and survival of subcommunities, despite differences in cell physiological properties, including growth rates.
Provisioning a sufficient stable source of food requires sound knowledge about current and upcoming threats to agricultural production. To that end machine learning approaches were used to identify the prevailing climatic and soil hydrological drivers of spatial and temporal yield variability of four crops, comprising 40 years yield data each from 351 counties in Germany. Effects of progress in agricultural management and breeding were subtracted from the data prior the machine learning modelling by fitting smooth non-linear trends to the 95th percentiles of observed yield data. An extensive feature selection approach was followed then to identify the most relevant predictors out of a large set of candidate predictors, comprising various soil and meteorological data. Particular emphasis was placed on studying the uniqueness of identified key predictors. Random Forest and Support Vector Machine models yielded similar although not identical results, capturing between 50% and 70% of the spatial and temporal variance of silage maize, winter barley, winter rapeseed and winter wheat yield. Equally good performance could be achieved with different sets of predictors. Thus identification of the most reliable models could not be based on the outcome of the model study only but required expert's judgement. Relationships between drivers and response often exhibited optimum curves, especially for summer air temperature and precipitation. In contrast, soil moisture clearly proved less relevant compared to meteorological drivers. In view of the expected climate change both excess precipitation and the excess heat effect deserve more attention in breeding as well as in crop modelling.
Climate change and increasing water demand in urban environments necessitate planning water utility companies' finances. Traditionally, methods to estimate the direct water utility business interruption costs (WUBIC) caused by droughts have not been clearly established. We propose a multi-driver assessment method. We project the water yield using a hydrological model driven by regional climate models under radiative forcing scenarios. We project water demand under stationary and non-stationary conditions to estimate drought severity and duration, which are linked with pricing policies recently adopted by the Sao Paulo Water Utility Company. The results showed water insecurity. The non-stationary trend imposed larger differences in the drought resilience financial gap, suggesting that the uncertainties of WUBIC derived from demand and climate models are greater than those associated with radiative forcing scenarios. As populations increase, proactively controlling demand is recommended to avoid or minimize reactive policy changes during future drought events, repeating recent financial impacts.
The detection of auto-fluorescence in phytogenic, hydrated amorphous silica depositions (phytoliths) has been found to be a promising approach to verify if phytoliths were burnt or not, especially in archaeological contexts. However, it is unknown so far at what temperature and how auto-fluorescence is induced in phytoliths. We used fluorescence microscopy, scanning electron microscope-energy dispersive X-ray spectroscopy (SEM-EDX), and Fourier transform infrared spectroscopy to analyze auto-fluorescence in modern phytoliths extracted from plant samples or in intact leaves of winter wheat. Leaves and extracted phytoliths were heated at different temperatures up to 600 degrees C. The aims of our experiments were i) to find out what temperature is needed to induce auto-fluorescence in phytoliths, ii) to detect temperature-dependent changes in the molecular structure of phytoliths related to auto-fluorescence, and iii) to derive a mechanistic understanding of auto-fluorescence in phytoliths. We found organic compounds associated with phytoliths to cause auto-fluorescence in phytoliths treated at temperatures below approx. 400 degrees C. In phytoliths treated at higher temperatures, i.e., 450 and 600 degrees C, phytolith auto-fluorescence was mainly caused by molecular changes of phytolith silica. Based on our results we propose that auto-fluorescence in phytoliths is caused by clusterization-triggered emissions, which are caused by overlapping electron clouds forming non-conventional chromophores. In phytoliths heated at temperatures above about 400 degrees C dihydroxylation and the formation of siloxanes result in oxygen clusters that serve as non-conventional chromophores in fluorescence events. Furthermore, SEM-EDX analyses revealed that extractable phytoliths were dominated by lumen phytoliths (62%) compared to cell wall phytoliths (38%). Our findings might be not only relevant in archaeological phytolith-based examinations, but also for studies on the temperature-dependent release of silicon from phytoliths and the potential of long-term carbon sequestration in phytoliths.
Management of agricultural soil quality requires fast and cost-efficient methods to identify multiple stressors that can affect soil organisms and associated ecological processes. Here, we propose to use soil protists which have a great yet poorly explored potential for bioindication. They are ubiquitous, highly diverse, and respond to various stresses to agricultural soils caused by frequent management or environmental changes. We test an approach that combines metabarcoding data and machine learning algorithms to identify potential stressors of soil protist community composition and diversity. We measured 17 key variables that reflect various potential stresses on soil protists across 132 plots in 28 Swiss vineyards over 2 years. We identified the taxa showing strong responses to the selected soil variables (potential bioindicator taxa) and tested for their predictive power. Changes in protist taxa occurrence and, to a lesser extent, diversity metrics exhibited great predictive power for the considered soil variables. Soil copper concentration, moisture, pH, and basal respiration were the best predicted soil variables, suggesting that protists are particularly responsive to stresses caused by these variables. The most responsive taxa were found within the clades Rhizaria and Alveolata. Our results also reveal that a majority of the potential bioindicators identified in this study can be used across years, in different regions and across different grape varieties. Altogether, soil protist metabarcoding data combined with machine learning can help identifying specific abiotic stresses on microbial communities caused by agricultural management. Such an approach provides complementary information to existing soil monitoring tools that can help manage the impact of agricultural practices on soil biodiversity and quality.
Compound inland flood events
(2022)
Several severe flood events hit Germany in recent years, with events in 2013 and 2016 being the most destructive ones, although dynamics and flood processes were very different. While the 2013 event was a slowly rising widespread fluvial flood accompanied by some severe dike breaches, the events in 2016 were fast-onset pluvial floods, which resulted in surface water flooding in some places due to limited capacities of the drainage systems and in destructive flash floods with high sediment loads and clogging in others, particularly in small steep catchments. Hence, different pathways, i.e. different routes that the water takes to reach (and potentially damage) receptors, in our case private households, can be identified in both events. They can thus be regarded as spatially compound flood events or compound inland floods. This paper analyses how differently affected residents coped with these different flood types (fluvial and pluvial) and their impacts while accounting for the different pathways (river flood, dike breach, surface water flooding and flash flood) within the compound events. The analyses are based on two data sets with 1652 (for the 2013 flood) and 601 (for the 2016 flood) affected residents who were surveyed around 9 months after each flood, revealing little socio-economic differences - except for income - between the two samples. The four pathways showed significant differences with regard to their hydraulic and financial impacts, recovery, warning processes, and coping and adaptive behaviour. There are just small differences with regard to perceived self-efficacy and responsibility, offering entry points for tailored risk communication and support to improve property-level adaptation.
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.
Forest structure and individual tree inventories of northeastern Siberia along climatic gradients
(2022)
We compile a data set of forest surveys from expeditions to the northeast of the Russian Federation, in Krasnoyarsk Krai, the Republic of Sakha (Yakutia), and the Chukotka Autonomous Okrug (59-73 degrees N, 97-169 degrees E), performed between the years 2011 and 2021. The region is characterized by permafrost soils and forests dominated by larch (Larix gmelinii Rupr. and Larix cajanderi Mayr).
Our data set consists of a plot database describing 226 georeferenced vegetation survey plots and a tree database with information about all the trees on these plots. The tree database, consisting of two tables with the same column names, contains information on the height, species, and vitality of 40 289 trees. A subset of the trees was subject to a more detailed inventory, which recorded the stem diameter at base and at breast height, crown diameter, and height of the beginning of the crown.
We recorded heights up to 28.5 m (median 2.5 m) and stand densities up to 120 000 trees per hectare (median 1197 ha(-1)), with both values tending to be higher in the more southerly areas. Observed taxa include Larix Mill., Pinus L., Picea A. Dietr., Abies Mill., Salix L., Betula L., Populus L., Alnus Mill., and Ulmus L.
In this study, we present the forest inventory data aggregated per plot. Additionally, we connect the data with different remote sensing data products to find out how accurately forest structure can be predicted from such products. Allometries were calculated to obtain the diameter from height measurements for every species group. For Larix, the most frequent of 10 species groups, allometries depended also on the stand density, as denser stands are characterized by thinner trees, relative to height. The remote sensing products used to compare against the inventory data include climate, forest biomass, canopy height, and forest loss or disturbance. We find that the forest metrics measured in the field can only be reconstructed from the remote sensing data to a limited extent, as they depend on local properties. This illustrates the need for ground inventories like those data we present here.
The data can be used for studying the forest structure of northeastern Siberia and for the calibration and validation of remotely sensed data.
We propose a novel way to measure and analyze networks of drainage divides from digital elevation models. We developed an algorithm that extracts drainage divides based on the drainage basin boundaries defined by a stream network. In contrast to streams, there is no straightforward approach to order and classify divides, although it is intuitive that some divides are more important than others. A meaningful way of ordering divides is the average distance one would have to travel down on either side of a divide to reach a common stream location. However, because measuring these distances is computationally expensive and prone to edge effects, we instead sort divide segments based on their tree-like network structure, starting from endpoints at river confluences. The sorted nature of the network allows for assigning distances to points along the divides, which can be shown to scale with the average distance downslope to the common stream location. Furthermore, because divide segments tend to have characteristic lengths, an ordering scheme in which divide orders increase by 1 at junctions mimics these distances. We applied our new algorithm to the Big Tujunga catchment in the San Gabriel Mountains of southern California and studied the morphology of the drainage divide network. Our results show that topographic metrics, like the downstream flow distance to a stream and hillslope relief, attain characteristic values that depend on the drainage area threshold used to derive the stream network. Portions along the divide network that have lower than average relief or are closer than average to streams are often distinctly asymmetric in shape, suggesting that these divides are unstable. Our new and automated approach thus helps to objectively extract and analyze divide networks from digital elevation models.
Detailed organic geochemical and carbon isotopic (delta C-13 and Delta C-14) analyses are performed on permafrost deposits affected by coastal erosion (Herschel Island, Canadian Beaufort Sea) and adjacent marine sediments (Herschel Basin) to understand the fate of organic carbon in Arctic nearshore environments. We use an end-member model based on the carbon isotopic composition of bulk organic matter to identify sources of organic carbon. Monte Carlo simulations are applied to quantify the contribution of coastal permafrost erosion to the sedimentary carbon budget. The models suggest that similar to 40% of all carbon released by local coastal permafrost erosion is efficiently trapped and sequestered in the nearshore zone. This highlights the importance of sedimentary traps in environments such as basins, lagoons, troughs, and canyons for the carbon sequestration in previously poorly investigated, nearshore areas.
Plain Language Summary Increasing air and sea surface temperatures at high latitudes leads to accelerated thaw, destabilization, and erosion of perennially frozen soils (i.e., permafrost), which are often rich in organic carbon. Coastal erosion leads to an increased mobilization of organic carbon into the Arctic Ocean, which there can be converted into greenhouse gases and may therefore contribute to further warming. Carbon decomposition can be limited if organic matter is efficiently deposited on the seafloor, buried in marine sediments, and thus removed from the short-term carbon cycle. Basins, canyons, and troughs near the coastline can serve as sediment traps and potentially accommodate large quantities of organic carbon along the Arctic coast. Here we use biomarkers (source-specific molecules), stable carbon isotopes, and radiocarbon to identify the sources of organic carbon in the nearshore zone of the southern Canadian Beaufort Sea near Herschel Island. We quantify the contribution of coastal permafrost erosion to the sedimentary carbon budget of the area and estimate that more than a third of all carbon released by local permafrost erosion is efficiently trapped in marine sediments. This highlights the importance of regional sediment traps for carbon sequestration.
Rising temperatures in the Arctic affect soil microorganisms, herbivores, and peatland vegetation, thus directly and indirectly influencing microbial CH4 production. It is not currently known how methanotrophs in Arctic peat respond to combined changes in temperature, CH4 concentration, and vegetation. We studied methanotroph responses to temperature and CH4 concentration in peat exposed to herbivory and protected by exclosures. The methanotroph activity was assessed by CH4 oxidation rate measurements using peat soil microcosms and a pure culture of Methylobacter tundripaludum SV96, qPCR, and sequencing of pmoA transcripts. Elevated CH4 concentrations led to higher CH4 oxidation rates both in grazed and exclosed peat soils, but the strongest response was observed in grazed peat soils. Furthermore, the relative transcriptional activities of different methanotroph community members were affected by the CH4 concentrations. While transcriptional responses to low CH4 concentrations were more prevalent in grazed peat soils, responses to high CH4 concentrations were more prevalent in exclosed peat soils. We observed no significant methanotroph responses to increasing temperatures. We conclude that methanotroph communities in these peat soils respond to changes in the CH4 concentration depending on their previous exposure to grazing. This "conditioning " influences which strains will thrive and, therefore, determines the function of the methanotroph community.
Extreme weather events like heavy rainfall and heat waves will likely increase in intensity and frequency due to climate change. As the impacts of these extremes are particularly prominent in urban agglomerations, cities face an urgent need to develop adaptation strategies. Ecosystem-based Adaptation (EbA) provides helpful strategies that harness ecological processes in addition to technical interventions. EbA has been addressed in informal adaptation planning. Formal municipality planning, namely landscape planning, is supposed to include traditionally some EbA measures, although adaptation has not been their explicit focus. Our research aims to investigate how landscape plans incorporate climate-related extremes and EbA as well as to discuss the potential to enhance EbA uptake in formal planning. We conducted a document analysis of informal planning documents from 85 German cities and the analysis of formal landscape plans of 61 of these cities. The results suggest that city size does affect the extent of informal planning instruments and the comprehensiveness of formal landscape plans. Climate-related extremes and EbA measures have traditionally been part of landscape planning. Almost all landscape plans address heat stress, while climate change and heavy rain have been addressed less often, though more frequently since 2008. Greening of walls and roofs, on-site infiltration and water retention reveal significant potential for better integration in landscape plans. Landscape planning offers an entry point for effective climate adaptation through EbA in cities. Informal and formal planning instruments should be closely combined for robust, spatially explicit, legally binding implementation of EbA measures in the future.
Atmospheric dynamics of extreme discharge events from 1979 to 2016 in the southern Central Andes
(2020)
During the South-American Monsoon season, deep convective systems occur at the eastern flank of the Central Andes leading to heavy rainfall and flooding. We investigate the large- and meso-scale atmospheric dynamics associated with extreme discharge events (> 99.9th percentile) observed in two major river catchments meridionally stretching from humid to semi-arid conditions in the southern Central Andes. Based on daily gauge time series and ERA-Interim reanalysis, we made the following three key observations: (1) for the period 1940-2016 daily discharge exhibits more pronounced variability in the southern, semi-arid than in the northern, humid catchments. This is due to a smaller ratio of discharge magnitudes between intermediate (0.2 year return period) and rare events (20 year return period) in the semi-arid compared to the humid areas; (2) The climatological composites of the 40 largest discharge events showed characteristic atmospheric features of cold surges based on 5-day time-lagged sequences of geopotential height at different levels in the troposphere; (3) A subjective classification revealed that 80% of the 40 largest discharge events are mainly associated with the north-northeastward migration of frontal systems and 2/3 of these are cold fronts, i.e. cold surges. This work highlights the importance of cold surges and their related atmospheric processes for the generation of heavy rainfall events and floods in the southern Central Andes.
Alpine ecosystems on the Tibetan Plateau are being threatened by ongoing climate warming and intensified human activities. Ecological time-series obtained from sedimentary ancient DNA (sedaDNA) are essential for understanding past ecosystem and biodiversity dynamics on the Tibetan Plateau and their responses to climate change at a high taxonomic resolution. Hitherto only few but promising studies have been published on this topic. The potential and limitations of using sedaDNA on the Tibetan Plateau are not fully understood. Here, we (i) provide updated knowledge of and a brief introduction to the suitable archives, region-specific taphonomy, state-of-the-art methodologies, and research questions of sedaDNA on the Tibetan Plateau; (ii) review published and ongoing sedaDNA studies from the Tibetan Plateau; and (iii) give some recommendations for future sedaDNA study designs. Based on the current knowledge of taphonomy, we infer that deep glacial lakes with freshwater and high clay sediment input, such as those from the southern and southeastern Tibetan Plateau, may have a high potential for sedaDNA studies. Metabarcoding (for microorganisms and plants), metagenomics (for ecosystems), and hybridization capture (for prehistoric humans) are three primary sedaDNA approaches which have been successfully applied on the Tibetan Plateau, but their power is still limited by several technical issues, such as PCR bias and incompleteness of taxonomic reference databases. Setting up high-quality and open-access regional taxonomic reference databases for the Tibetan Plateau should be given priority in the future. To conclude, the archival, taphonomic, and methodological conditions of the Tibetan Plateau are favorable for performing sedaDNA studies. More research should be encouraged to address questions about long-term ecological dynamics at ecosystem scale and to bring the paleoecology of the Tibetan Plateau into a new era.
In the following article, the focus is on the transformative potentials created by so-called persistence avant-gardes and prevention innovators. The text extends Bluhdorn's guiding concept of narratives of hope (Bluhdorn 2017; Bluhdorn and Butzlaff 2019) by considering those groups that are marginalized within debates on socio-ecological transformation. With a closer look at the narratives of prevention and blockade that these actors engage, the ambiguous nature of postgrowth avant-gardes is carved out. Their discursive, argumentative, and effective inhibition of transitory policies is interpreted as a pro-active potential, rather than a mere obstacle to socio-ecological transformation. Adding a geographical perspective, the paper pleads for a more precise theoretical penetration of the ambivalent figure of avantgardes when analyzing processes of local and regional postgrowth.
Many researchers and politicians believe that the COVID-19 crisis may have opened a "window of opportunity " to spur sustainability transformations. Still, evidence for such a dynamic is currently lacking. Here, we propose the linkage of "big data " and "thick data " methods for monitoring debates on transformation processes by following the COVID-19 discourse on ecological sustainability in Germany. We analysed variations in the topics discussed by applying text mining techniques to a corpus with 84,500 newspaper articles published during the first COVID-19 wave. This allowed us to attain a unique and previously inaccessible "bird's eye view " of how these topics evolved. To deepen our understanding of prominent frames, a qualitative content analysis was undertaken. Furthermore, we investigated public awareness by analysing online search behaviour. The findings show an underrepresentation of sustainability topics in the German news during the early stages of the crisis. Similarly, public awareness regarding climate change was found to be reduced. Nevertheless, by examining the newspaper data in detail, we found that the pandemic is often seen as a chance for sustainability transformations-but not without a set of challenges. Our mixed-methods approach enabled us to bridge knowledge gaps between qualitative and quantitative research by "thickening " and providing context to data-driven analyses. By monitoring whether or not the current crisis is seen as a chance for sustainability transformations, we provide insights for environmental policy in times of crisis.
The mechanical behavior of the sandy facies of Opalinus Clay (OPA) was investigated in 42 triaxial tests performed on dry samples at unconsolidated, undrained conditions at confining pressures (p(c)) of 50-100 MPa, temperatures (T) between 25 and 200 degrees C and strain rates (epsilon) (over dot ) of 1 x-10(-3)-5 x-10(-6) -s(-1). Using a Paterson-type deformation apparatus, samples oriented at 0 degrees, 45 degrees and 90 degrees to bedding were deformed up to about 15% axial strain. Additionally, the influence of water content, drainage condition and pre-consolidation was investigated at fixed p(c)-T conditions, using dry and re-saturated samples. Deformed samples display brittle to semi-brittle deformation behavior, characterized by cataclastic flow in quartz-rich sandy layers and granular flow in phyllosilicate-rich layers. Samples loaded parallel to bedding are less compliant compared to the other loading directions. With the exception of samples deformed 45 degrees and 90 degrees to bedding at p(c) = 100 MPa, strain is localized in discrete shear zones. Compressive strength (sigma(max)) increases with increasing pc, resulting in an internal friction coefficient of approximate to 0.31 for samples deformed at 45 degrees and 90 degrees to bedding, and approximate to 0.44 for samples deformed parallel to bedding. In contrast, pre-consolidation, drainage condition, T and epsilon(over dot )do not significantly affect deformation behavior of dried samples. However, sigma(max) and Young's modulus (E) decrease substantially with increasing water saturation. Compared to the clay-rich shaly facies of OPA, sandy facies specimens display higher strength sigma(max) and Young's modulus E at similar deformation conditions. Strength and Young's modulus of samples deformed 90 degrees and 45 degrees to bedding are close to the iso-stress Reuss bound, suggesting a strong influence of weak clay-rich layers on the deformation behavior.
Trends in streamflow, rainfall and potential evapotranspiration (PET) time series, from 1970 to 2017, were assessed for five important hydrological basins in Southeastern Brazil. The concept of elasticity was also used to assess the streamflow sensitivity to changes in climate variables, for annual data and 5-, 10- and 20-year moving averages. Significant negative trends in streamflow and rainfall and significant increasing trend in PET were detected. For annual analysis, elasticity revealed that 1% decrease in rainfall resulted in 1.21-2.19% decrease in streamflow, while 1% increase in PET induced different reductions percentages in streamflow, ranging from 2.45% to 9.67%. When both PET and rainfall were computed to calculate the elasticity, results were positive for some basins. Elasticity analysis considering 20-year moving averages revealed that impacts on the streamflow were cumulative: 1% decrease in rainfall resulted in 1.83-4.75% decrease in streamflow, while 1% increase in PET induced 3.47-28.3% decrease in streamflow. This different temporal response may be associated with the hydrological memory of the basins. Streamflow appears to be more sensitive in less rainy basins. This study provides useful information to support strategic government decisions, especially when the security of water resources and drought mitigation are considered in face of climate change.
Distributed environmental models such as land surface models (LSMs) require model parameters in each spatial modeling unit (e.g., grid cell), thereby leading to a high-dimensional parameter space. One approach to decrease the dimensionality of the parameter space in these models is to use regularization techniques. One such highly efficient technique is the multiscale parameter regionalization (MPR) framework that translates high-resolution predictor variables (e.g., soil textural properties) into model parameters (e.g., porosity) via transfer functions (TFs) and upscaling operators that are suitable for every modeled process. This framework yields seamless model parameters at multiple scales and locations in an effective manner. However, integration of MPR into existing modeling workflows has been hindered thus far by hard-coded configurations and non-modular software designs. For these reasons, we redesigned MPR as a model-agnostic, stand-alone tool. It is a useful software for creating graphs of NetCDF variables, wherein each node is a variable and the links consist of TFs and/or upscaling operators. In this study, we present and verify our tool against a previous version, which was implemented in the mesoscale hydrologic model (mHM; https://www.ufz.de/mhm, last access: 16 January 2022). By using this tool for the generation of continental-scale soil hydraulic parameters applicable to different models (Noah-MP and HTESSEL), we showcase its general functionality and flexibility. Further, using model parameters estimated by the MPR tool leads to significant changes in long-term estimates of evapotranspiration, as compared to their default parameterizations. For example, a change of up to 25 % in long-term evapotranspiration flux is observed in Noah-MP and HTESSEL in the Mississippi River basin. We postulate that use of the stand-alone MPR tool will considerably increase the transparency and reproducibility of the parameter estimation process in distributed (environmental) models. It will also allow a rigorous uncertainty estimation related to the errors of the predictors (e.g., soil texture fields), transfer function and its parameters, and remapping (or upscaling) algorithms.
Dominant processes in a watershed are those that most strongly control hydrologic function and response. Estimating dominant processes enables hydrologists to design physically realistic streamflow generation models, design management interventions, and understand how climate and landscape features control hydrologic function. A recent approach to estimating dominant processes is through their link to hydrologic signatures, which are metrics that characterize the streamflow timeseries. Previous authors have used results from experimental watersheds to link signature values to underlying processes, but these links have not been tested on large scales. This paper fills that gap by testing signatures in large sample data sets from the U.S., Great Britain, Australia, and Brazil, and in Critical Zone Observatory (CZO) watersheds. We found that most inter-signature correlations are consistent with process interpretations, that is, signatures that are supposed to represent the same process are correlated, and most signature values are consistent with process knowledge in CZO watersheds. Some exceptions occurred, such as infiltration and saturation excess processes that were often misidentified by signatures. Signature distributions vary by country, emphasizing the importance of regional context in understanding signature-process links and in classifying signature values as "high" or "low." Not all signatures were easily transferable from single, small watersheds to large sample studies, showing that visual or process-based assessment of signatures is important before large-scale use. We provide a summary table with information on the reliability of each signature for process identification. Overall, our results provide a reference for future studies that seek to use signatures to identify hydrological processes.
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.
Aim: The continental-scale distribution of plant functional types, such as evergreen and summergreen needle-leaf forest, is assumed to be determined by contemporary climate. However, the distribution of summergreen needle-leaf forest of larch (Larix Mill.) differs markedly between the continents, despite relatively similar climatic conditions. The reasons for these differences are little understood. Our aim is to identify potential triggers and drivers of the current distribution patterns by comparing species' bioclimatic niches, glacial refugia and postglacial recolonization patterns.
Location: Northern hemisphere.
Taxon: Species of the genus Larix (Mill.).
Methods: We compare species distribution and dominance using species ranges and sites of dominance, as well as their occurrence on modelled permafrost extent, and active layer thickness (ALT). We compare the bioclimatic niches and calculate the niche overlap between species, using the same data in addition to modern climate data. We synthesize pollen, macrofossil and ancient DNA palaeo-evidence of past Larix occurrences of the last 60,000 years and track differences in distribution patterns through time.
Results: Bioclimatic niches show large overlaps between Asian larch species and American Larix laricina. The distribution across various degrees of permafrost extent is distinctly different for Asian L. gmelinii and L. cajanderi compared to the other species, whereas the distribution on different depths of ALT is more similar among Asian and American species. Northern glacial refugia for Larix are only present in eastern Asia and Alaska.
Main Conclusion: The dominance of summergreen larches in Asia, where evergreen conifers dominate most of the rest of the boreal forests, is dependent on the interaction of several factors which allows Asian L. gmelinii and L. cajanderi to dominate where these factors coincide. These factors include the early postglacial spread out of northern glacial refugia in the absence of competitors as well as a positive feedback mechanism between frozen ground and forest.
From gustiness to dustiness
(2022)
This study delivers the first empirical data-driven analysis of the impact of turbulence induced gustiness on the fine dust emissions from a measuring field. For quantification of the gust impact, a new measure, the Gust uptake Efficiency (GuE) is introduced. GuE provides a percentage of over- or under-proportional dust uptake due to gust activity during a wind event. For the three analyzed wind events, GuE values of up to 150% could be found, yet they significantly differed per particle size class with a tendency for lower values for smaller particles. In addition, a high-resolution correlation analysis among 31 particle size classes and wind speed was conducted; it revealed strong negative correlation coefficients for very small particles and positive correlations for bigger particles, where 5 mu m appears to be an empirical threshold dividing both directions. We conclude with a number of suggestions for further investigations: an optimized field experiment setup, a new particle size ratio (PM1/PM0.5 in addition to PM10/PM2.5), as well as a comprehensive data-driven search for an optimal wind gust definition in terms of soil erosivity.
Resolving the grand challenges and wicked problems of the Anthropocene will require skillfully combining a broad range of knowledge and understandings-both scientific and non-scientific-of Earth systems and human societies. One approach to this is transdisciplinary research, which has gained considerable interest over the last few decades, resulting in an extensive body of literature about transdisciplinarity. However, this has in turn led to the challenge that developing a good understanding of transdisciplinary research can require extensive effort. Here we provide a focused overview and perspective for disciplinary and interdisciplinary researchers who are interested in efficiently obtaining a solid understanding of transdisciplinarity. We describe definitions, characteristics, schools of thought, and an exemplary three-phase model of transdisciplinary research. We also discuss three key challenges that transdisciplinary research faces in the context of addressing the broader challenges of the Anthropocene, and we consider approaches to dealing with these specific challenges, based especially on our experiences with building up transdisciplinary research projects at the Institute for Advanced Sustainability Studies.
The curse of the past
(2021)
One challenge for modern agricultural management schemes is the reduction of harmful effects on the envi-ronment, e.g. in terms of the emission of nutrients. Sampling the effluent of tile drains is a very efficient way to sample seepage water from larger areas directly underneath the main rooting zone. Time series of solute con-centration in tile drains can be linked to agricultural management data and thus indicate the efficacy of individual management measures. To that end, the weekly runoff and solute concentration were determined in long-term measurement campaigns at 25 outlets of artificial tile drains at 19 various arable fields in the German federal state of Mecklenburg-Vorpommern. The study sites were distributed within a 23,000 km(2) region and were deemed representative of intense arable land use. In addition, comprehensive meteorological and man-agement data were provided. To disentangle the different effects, monitoring data were subjected to a principal component analysis. Loadings on the prevailing principal components and spatial and temporal patterns of the component scores were considered indicative of different processes. Principal component scores were then related to meteorological and management data via random forest modelling. Hydrological conditions and weather were identified as primary driving forces for the nutrient discharge behaviour of the drain plots, as well as the nitrogen balance. In contrast, direct effects of recent agricultural management could hardly be identified. Instead, we found clear evidence of the long-term and indirect effects of agriculture on nearly all solutes. We conclude that tile drain effluent quality primarily reflected the soil-internal mobilisation or de-mobilisation of nutrients and related solutes rather than allowing inferences to be drawn about recent individual agricultural management measures. On the other hand, principal component analysis revealed a variety of indirect and long-term effects of fertilisation on solutes other than nitrogen or phosphorus that are still widely overlooked in nutrient turnover studies.
Sudden glacier advances in the Cachapoal Valley, Southern Central Andes of Chile (34 degrees S)
(2021)
Throughout the Andes Mountains of South America, a general trend of glacier shrinkage has taken place in modern times. However, a few glaciers have undergone considerable temporally advances or even surged during the mid-19th to 20th century CE. These valley glaciers are mainly located in the Central Andes of Chile and Argentina. The research presented here focuses on the changes of the Cachapoal Glacier in the Southern Central Andes of Chile. Spectacular glacier advances occurred at least three times in historical times, which lead to river blockages and successive lake outburst floods. The glacier advances were reconstructed with a multi-method approach including geomorphological mapping, Be-10 cosmogenic exposure dating of moraines, multi-temporal comparison of historical and recent photographs and paintings as well as the interpretation of aerial photographs and satellite images and the analysis of early travel reports. The article highlights the diversity of environmental conditions for the formation of glaciers in terms of the topographical and climatic setting and the resulting distinct glacier behavior along the Andes Mountains. It is argued for the Cachapoal Glacier that the glacier advances are intrinsic to the glacier type and may not be necessarily climate-dependent. This is characteristic for avalanche-fed glaciers of which the glacier dynamic is strongly controlled by the topographic setting and sudden inputs of ice and rock avalanches as well as by the specific debris transfer system and hydrological drainage pattern. At the regional level, the fluctuations of the Cachapoal Glacier are compared with glaciers of neighboring mountain ranges in the Southern Central Andes and at the global scale with those of the Karakoram Mountains in High Asia with a similar dynamic glacier behavior.
Throughfall, that is, the fraction of rainfall that passes through the forest canopy, is strongly influenced by rainfall and forest stand characteristics which are in turn both subject to seasonal dynamics. Disentangling the complex interplay of these controls is challenging, and only possible with long-term monitoring and a large number of throughfall events measured in parallel at different forest stands. We therefore based our analysis on 346 rainfall events across six different forest stands at the long-term terrestrial environmental observatory TERENO Northeast Germany. These forest stands included pure stands of beech, pine and young pine, and mixed stands of oak-beech, pine-beech and pine-oak-beech. Throughfall was overall relatively low, with 54-68% of incident rainfall in summer. Based on the large number of events it was possible to not only investigate mean or cumulative throughfall but also its statistical distribution. The distributions of throughfall fractions show distinct differences between the three types of forest stands (deciduous, mixed and pine). The distributions of the deciduous stands have a pronounced peak at low throughfall fractions and a secondary peak at high fractions in summer, as well as a pronounced peak at higher throughfall fractions in winter. Interestingly, the mixed stands behave like deciduous stands in summer and like pine stands in winter: their summer distributions are similar to the deciduous stands but the winter peak at high throughfall fractions is much less pronounced. The seasonal comparison further revealed that the wooden components and the leaves behaved differently in their throughfall response to incident rainfall, especially at higher rainfall intensities. These results are of interest for estimating forest water budgets and in the context of hydrological and land surface modelling where poor simulation of throughfall would adversely impact estimates of evaporative recycling and water availability for vegetation and runoff.
The biodiversity of tundra areas in northern high latitudes is threatened by invasion of forests under global warming. However, poorly understood nonlinear responses of the treeline ecotone mean the timing and extent of tundra losses are unclear, but policymakers need such information to optimize conservation efforts. Our individual-based model LAVESI, developed for the Siberian tundra-taiga ecotone, can help improve our understanding. Consequently, we simulated treeline migration trajectories until the end of the millennium, causing a loss of tundra area when advancing north. Our simulations reveal that the treeline follows climate warming with a severe, century-long time lag, which is overcompensated by infilling of stands in the long run even when temperatures cool again. Our simulations reveal that only under ambitious mitigation strategies (relative concentration pathway 2.6) will ~30% of original tundra areas remain in the north but separated into two disjunct refugia.
A reliable estimation of flood impacts enables meaningful flood risk management and rapid assessments of flood impacts shortly after a flood. The flood in 2021 in Central Europe and the analysis of its impacts revealed that these estimations are still inadequate. Therefore, we investigate the influence of different data sets and methods aiming to improve flood impact estimates. We estimated economic flood impacts to private households and companies for a flood event in 2013 in Germany using (a) two different flood maps, (b) two approaches to map exposed objects based on OpenStreetMap and the Basic European Asset Map, (c) two different approaches to estimate asset values, and (d) tree-based models and Stage-Damage-Functions to describe the vulnerability. At the macro scale, water masks lead to reasonable impact estimations. At the micro and meso-scale, the identification of affected objects by means of water masks is insufficient leading to unreliable estimations. The choice of exposure data sets is most influential on the estimations. We find that reliable impact estimations are feasible with reported numbers of flood-affected objects from the municipalities. We conclude that more effort should be put in the investigation of different exposure data sets and the estimation of asset values. Furthermore, we recommend the establishment of a reporting system in the municipalities for a fast identification of flood-affected objects shortly after an event.
Agriculture in India accounts for 18% of greenhouse gas (GHG) emissions and uses significant land and water. Various socioeconomic factors and food subsidies influence diets in India. Indian food systems face the challenge of sustainably nourishing the 1.3 billion population. However, existing studies focus on a few food system components, and holistic analysis is still missing. We identify Indian food systems covering six food system components: food consumption, production, processing, policy, environmental footprints, and socioeconomic factors from the latest Indian household consumer expenditure survey. We identify 10 Indian food systems using k-means cluster analysis on 15 food system indicators belonging to the six components. Based on the major source of calorie intake, we classify the ten food systems into production-based (3), subsidy-based (3), and market-based (4) food systems. Home-produced and subsidized food contribute up to 2000 kcal/consumer unit (CU)/day and 1651 kcal/CU/day, respectively, in these food systems. The calorie intake of 2158 to 3530 kcal/CU/day in the food systems reveals issues of malnutrition in India. Environmental footprints are commensurate with calorie intake in the food systems. Embodied GHG, land footprint, and water footprint estimates range from 1.30 to 2.19 kg CO(2)eq/CU/day, 3.89 to 6.04 m(2)/CU/day, and 2.02 to 3.16 m(3)/CU/day, respectively. Our study provides a holistic understanding of Indian food systems for targeted nutritional interventions on household malnutrition in India while also protecting planetary health.
Geopolitical shifts and the changing significance of borders in the EU's neighbourhood are usually understood as a matter of international power politics. Factors that accompany geopolitical impact on borders, such as media coverage of geopolitical change, often appear as secondary or irrelevant. However the recent Ukraine conflict revealed the contrary as pro-EU attitudes were strongly supported by 'western' media. Therefore this paper seeks to clarify the role of news media in creating perspectives and attitudes on geopolitical shifts and the significance of European borders. Empirical evidence on the coverage of the evolving Ukraine crisis by German news sources portrays the media as promoters of biased framings and imaginaries which suggest that the EU be a potential conflict party in the newly evolving geostrategic confrontation in its eastern neighbourhood. The findings indicate that during critical periods of the Ukraine crisis media reports combined rising euphoria about Europe and 'the West', as defenders of the 'good cause', with excessive moral polarising and the discursive normalisation of a rhetoric of escalation. Imaginaries of a bipolar world (The West against Russia) and a new Cold War prepared the ground for a new understanding of European borders and neighbourhood relations as being manipulable at will.
Aerosol emissions from human activities are extensive and changing rapidly over Asia. Model simulations and satellite observations indicate a dipole pattern in aerosol emissions and loading between South Asia and East Asia, two of the most heavily polluted regions of the world. We examine the previously unexplored diverging trends in the existing dipole pattern of aerosols between East and South Asia using the high quality, two-decade long ground-based time series of observations of aerosol properties from the Aerosol Robotic Network (AERONET), from satellites (Moderate Resolution Imaging Spectroradiometer (MODIS) and Ozone Monitoring Instrument (OMI)), and from model simulations (Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The data cover the period since 2001 for Kanpur (South Asia) and Beijing (East Asia), two locations taken as being broadly representative of the respective regions. Since 2010 a dipole in aerosol optical depth (AOD) is maintained, but the trend is reversed-the decrease in AOD over Beijing (East Asia) is rapid since 2010, being 17% less in current decade compared to first decade of twenty-first century, while the AOD over South Asia increased by 12% during the same period. Furthermore, we find that the aerosol composition is also changing over time. The single scattering albedo (SSA), a measure of aerosol's absorption capacity and related to aerosol composition, is slightly higher over Beijing than Kanpur, and has increased from 0.91 in 2002 to 0.93 in 2017 over Beijing and from 0.89 to 0.92 during the same period over Kanpur, confirming that aerosols in this region have on an average become more scattering in nature. These changes have led to a notable decrease in aerosol-induced atmospheric heating rate (HR) over both regions between the two decades, decreasing considerably more over East Asia (- 31%) than over South Asia (- 9%). The annual mean HR is lower now, it is still large (>= 0.6 K per day), which has significant climate implications. The seasonal trends in AOD, SSA and HR are more pronounced than their respective annual trends over both regions. The seasonal trends are caused mainly by the increase/decrease in anthropogenic aerosol emissions (sulfate, black carbon and organic carbon) while the natural aerosols (dust and sea salt) did not change significantly over South and East Asia during the last two decades. The MERRA-2 model is able to simulate the observed trends in AODs well but not the magnitude, while it also did not simulate the SSA values or trends well. These robust findings based on observations of key aerosol parameters and previously unrecognized diverging trends over South and East Asia need to be accounted for in current state-of-the-art climate models to ensure accurate quantification of the complex and evolving impact of aerosols on the regional climate over Asia.
Rivers play a relevant role in the nutrient turnover during the transport from land to ocean. Here, highly dynamic planktonic processes are more important compared to streams making it necessary to link the dynamics of nutrient turnover to control mechanisms of phytoplankton. We investigated the basic conditions leading to high phytoplankton biomass and corresponding nutrient dynamics in eutrophic, 8th order River Elbe (Germany). In a first step, we performed six Lagrangian sampling campaigns in the lower river section at different hydrological conditions. While nutrient concentrations remained high at low algal densities in autumn and at moderate discharge in summer, high algal concentrations occurred at low discharge in summer. Under these conditions, concentrations of silica and nitrate decreased and rates of nitrate assimilation were high. Soluble reactive phosphorus was depleted and particulate phosphorus increased inversely. Rising molar C:P ratios of seston indicated a phosphorus limitation of phytoplankton, so far rarely observed in eutrophic large rivers. Global radiation combined with mixing depth had a strong predictive power to explain maximum chlorophyll concentration. In a second step, we estimated nutrient turnover exemplarily for N during the campaign with the lowest discharge based on mass balances and metabolism-based process measurements. Mass balance calculations revealed a total nitrate uptake of 423 mg N m(-2)d(-1). Increasing phytoplankton density dominantly explained whole river gross primary production and related assimilatory nutrient uptake. In conclusion, riverine nutrient uptake strongly depends on the growth conditions for phytoplankton, which are favored at high irradiation and low discharge.
There is a movement towards the concepts of integrated flood risk management and governance. In these concepts, each stakeholder prone to flooding is tasked with actively limiting flood impacts. Currently, relatively more research has focused upon the adaptation of private households and not on private businesses operating in flood-prone areas. This paper offers an extension of this literature on business-level flood adaptation by exploring the potential presence of moral hazard. The analyses are based on survey data collected in the aftermath of six floods across Germany between 2002 and 2013 to provide a first indication of the presence of moral hazard in private businesses. Moral hazard is where increased insurance coverage results in policyholders preparing less, increasing the risk they face, a counterproductive outcome. We present an initial study of moral hazard occurring through three channels: the performance of emergency measures during a flood, changes in precautionary behavior employed before a given flood occurred, and changes in the intention to employ additional precautionary measures after a flood. We find, much like for private households, no strong indication that moral hazard is present regarding past adaptation. However, there is a potential avenue after 2005 for insurance coverage to lower businesses' intentions to employ more adaptation measures after a flood. This has significant policy relevance such as opportunities for strengthening the link between insurance and risk reduction measures and boosting insurance coverage against flooding in general.
Climate change threatens to undermine efforts to eradicate extreme poverty. However, climate policies could impose a financial burden on the global poor through increased energy and food prices. Here, we project poverty rates until 2050 and assess how they are influenced by mitigation policies consistent with the 1.5 degrees C target. A continuation of historical trends will leave 350 million people globally in extreme poverty by 2030. Without progressive redistribution, climate policies would push an additional 50 million people into poverty. However, redistributing the national carbon pricing revenues domestically as an equal-per-capita climate dividend compensates this policy side effect, even leading to a small net reduction of the global poverty headcount (-6 million). An additional international climate finance scheme enables a substantial poverty reduction globally and also in Sub-Saharan Africa. Combining national redistribution with international climate finance thus provides an important entry point to climate policy in developing countries. Ambitious climate policies can negatively impact the global poor by affecting income, food and energy prices. Here, the authors quantify this effect, and show that it can be compensated by national redistribution of the carbon pricing revenues in combination with international climate finance.
Future precipitation levels remain uncertain because climate models have struggled to reproduce observed variations in temperature-precipitation correlations. Our analyses of Holocene proxy-based temperature-precipitation correlations and hydrological sensitivities from 2,237 Northern Hemisphere extratropical pollen records reveal a significant latitudinal dependence and temporal variations among the early, middle, and late Holocene. These proxy-based variations are largely consistent with patterns obtained from transient climate simulations (TraCE21k). While high latitudes and subtropical monsoon areas show mainly stable positive correlations throughout the Holocene, the mid-latitude pattern is temporally and spatially more variable. In particular, we identified a reversal from positive to negative temperature-precipitation correlations in the eastern North American and European mid-latitudes from the early to mid-Holocene that mainly related to slowed down westerlies and a switch to moisture-limited convection under a warm climate. Our palaeoevidence of past temperature-precipitation correlation shifts identifies those regions where simulating past and future precipitation levels might be particularly challenging.
Inventory of dams in Germany
(2021)
Dams are an important element of water resources management. Data about dams are crucial for practitioners, scientists, and policymakers for various purposes, such as seasonal forecasting of water availability or flood mitigation. However, detailed information on dams on the national level for Germany is so far not freely available. We present the most comprehensive open-access dam inventory for Germany (DIG) to date. We have collected and combined information on dams using books, state agency reports, engineering reports, and internet pages. We have applied a priority rule that ensures the highest level of reliability for the dam information. Our dam inventory comprises 530 dams in Germany with information on name, location, river, start year of construction and operation, crest length, dam height, lake area, lake volume, purpose, dam structure, and building characteristics. We have used a global, satellite-based water surface raster to evaluate the location of the dams. A significant proportion (63 %) of dams were built between 1950-2013. Our inventory shows that dams in Germany are mostly single-purpose (52 %), 53% can be used for flood control, and 25% are involved in energy production. The inventory is freely available through GFZ (GeoForschungsZentrum) Data Services (https://doi.org/10.5880/GFZ.4.4.2020.005)
The efficiency of sediment routing from land to the ocean depends on the position of submarine canyon heads with regard to terrestrial sediment sources. We aim to identify the main controls on whether a submarine canyon head remains connected to terrestrial sediment input during Holocene sea-level rise. Globally, we identified 798 canyon heads that are currently located at the 120m-depth contour (the Last Glacial Maximum shoreline) and 183 canyon heads that are connected to the shore (within a distance of 6 km) during the present-day highstand. Regional hotspots of shore-connected canyons are the Mediterranean active margin and the Pacific coast of Central and South America. We used 34 terrestrial and marine predictor variables to predict shore-connected canyon occurrence using Bayesian regression. Our analysis shows that steep and narrow shelves facilitate canyon-head connectivity to the shore. Moreover, shore-connected canyons occur preferentially along active margins characterized by resistant bedrock and high river-water discharge.
How fast the Northern Hemisphere (NH) forest biome tracks strongly warming climates is largely unknown. Regional studies reveal lags between decades and millennia. Here we report a conundrum: Deglacial forest expansion in the NH extra-tropics occurs approximately 4000 years earlier in a transient MPI-ESM1.2 simulation than shown by pollen-based biome reconstructions. Shortcomings in the model and the reconstructions could both contribute to this mismatch, leaving the underlying causes unresolved. The simulated vegetation responds within decades to simulated climate changes, which agree with pollen-independent reconstructions. Thus, we can exclude climate biases as main driver for differences. Instead, the mismatch points at a multi-millennial disequilibrium of the NH forest biome to the climate signal. Therefore, the evaluation of time-slice simulations in strongly changing climates with pollen records should be critically reassessed. Our results imply that NH forests may be responding much slower to ongoing climate changes than Earth System Models predict. <br /> Deglacial forest expansion in the Northern Hemisphere poses a conundrum: Model results agree with the climate signal but are several millennia ahead of reconstructed forest dynamics. The underlying causes remain unsolved.
Developing countries are increasingly impacted by floods, especially in Asia. Traditional flood risk man-agement, using structural measures such as levees, can have negative impacts on the livelihoods of social groups that are more vulnerable. Ecosystem-based adaptation (EbA) provides a complementary approach that is potentially more inclusive of groups that are commonly described as more vulnerable, such as the poor and women. However, there is a lack of disaggregated and quantitative information on the potential of EbA to support vulnerable groups of society. This paper provides a quantitative analysis of the differ-ences in vulnerability to flooding as well as preferences for EbA benefits across income groups and gen -der. We use data collected through a survey of households in urban and rural Central Vietnam which included a discrete choice experiment on preferences for ecosystem services. A total of 1,010 households was surveyed during 2017 through a random sampling approach. Preferences are measured in monetary and non-monetary terms to avoid issues that may arise from financial constraints faced by respondents and especially the more vulnerable groups. Our results reveal that lower income households and women are overall more vulnerable than their counterparts and have stronger preferences for the majority of the EbA benefits, including flood protection, seafood abundance, tourism, and recreation suitability. These findings strongly indicate that EbA is indeed a promising tool to support groups of society that are espe-cially vulnerable to floods. These results provide crucial insights for future implementation of EbA pro-jects and for the integration of EbA with goals targeted at complying with the Sendai Framework and Sustainable Development Goals. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Air pollution is a pressing issue that is associated with adverse effects on human health, ecosystems, and climate. Despite many years of effort to improve air quality, nitrogen dioxide (NO2) limit values are still regularly exceeded in Europe, particularly in cities and along streets. This study explores how concentrations of nitrogen oxides (NOx = NO + NO2) in European urban areas have changed over the last decades and how this relates to changes in emissions. To do so, the incremental approach was used, comparing urban increments (i.e. urban background minus rural concentrations) to total emissions, and roadside increments (i.e. urban roadside concentrations minus urban background concentrations) to traffic emissions. In total, nine European cities were assessed. The study revealed that potentially confounding factors like the impact of urban pollution at rural monitoring sites through atmospheric transport are generally negligible for NOx. The approach proves therefore particularly useful for this pollutant. The estimated urban increments all showed downward trends, and for the majority of the cities the trends aligned well with the total emissions. However, it was found that factors like a very densely populated surrounding or local emission sources in the rural area such as shipping traffic on inland waterways restrict the application of the approach for some cities. The roadside increments showed an overall very diverse picture in their absolute values and trends and also in their relation to traffic emissions. This variability and the discrepancies between roadside increments and emissions could be attributed to a combination of local influencing factors at the street level and different aspects introducing inaccuracies to the trends of the emis-sion inventories used, including deficient emission factors. Applying the incremental approach was evaluated as useful for long-term pan-European studies, but at the same time it was found to be restricted to certain regions and cities due to data availability issues. The results also highlight that using emission inventories for the prediction of future health impacts and compliance with limit values needs to consider the distinct variability in the concentrations not only across but also within cities.
Global flood models (GFMs) are increasingly being used to estimate global-scale societal and economic risks of river flooding. Recent validation studies have highlighted substantial differences in performance between GFMs and between validation sites. However, it has not been systematically quantified to what extent the choice of the underlying climate forcing and global hydrological model (GHM) influence flood model performance. Here, we investigate this sensitivity by comparing simulated flood extent to satellite imagery of past flood events, for an ensemble of three climate reanalyses and 11 GHMs. We study eight historical flood events spread over four continents and various climate zones. For most regions, the simulated inundation extent is relatively insensitive to the choice of GHM. For some events, however, individual GHMs lead to much lower agreement with observations than the others, mostly resulting from an overestimation of inundated areas. Two of the climate forcings show very similar results, while with the third, differences between GHMs become more pronounced. We further show that when flood protection standards are accounted for, many models underestimate flood extent, pointing to deficiencies in their flood frequency distribution. Our study guides future applications of these models, and highlights regions and models where targeted improvements might yield the largest performance gains.
The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. An annual temperature increase of 1 degrees C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 degrees C (3.5 degrees C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021-2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071-2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced.
Purpose Microplastics have become a ubiquitous pollutant in marine, terrestrial and freshwater systems that seriously affects aquatic and terrestrial ecosystems. Common methods for analysing microplastic abundance in soil or sediments are based on destructive sampling or involve destructive sample processing. Thus, substantial information about local distribution of microplastics is inevitably lost. Methods Tomographic methods have been explored in our study as they can help to overcome this limitation because they allow the analysis of the sample structure while maintaining its integrity. However, this capability has not yet been exploited for detection of environmental microplastics. We present a bimodal 3D imaging approach capable to detect microplastics in soil or sediment cores non-destructively. Results In a first pilot study, we demonstrate the unique potential of neutrons to sense and localize microplastic particles in sandy sediment. The complementary application of X-rays allows mineral grains to be discriminated from microplastic particles. Additionally, it yields detailed information on the 3D surroundings of each microplastic particle, which supports its size and shape determination. Conclusion The procedure we developed is able to identify microplastic particles with diameters of approximately 1 mm in a sandy soil. It also allows characterisation of the shape of the microplastic particles as well as the microstructure of the soil and sediment sample as depositional background information. Transferring this approach to environmental samples presents the opportunity to gain insights of the exact distribution of microplastics as well as their past deposition, deterioration and translocation processes.
Increasing arctic coastal erosion rates imply a greater release of sediments and organic matter into the coastal zone. With 213 sediment samples taken around Herschel Island-Qikiqtaruk, Canadian Beaufort Sea, we aimed to gain new insights on sediment dynamics and geochemical properties of a shallow arctic nearshore zone. Spatial characteristics of nearshore sediment texture (moderately to poorly sorted silt) are dictated by hydrodynamic processes, but ice-related processes also play a role. We determined organic matter (OM) distribution and inferred the origin and quality of organic carbon by C/N ratios and stable carbon isotopes delta C-13. The carbon content was higher offshore and in sheltered areas (mean: 1.0 wt.%., S.D.: 0.9) and the C/N ratios also showed a similar spatial pattern (mean: 11.1, S.D.: 3.1), while the delta C-13 (mean: -26.4 parts per thousand VPDB, S.D.: 0.4) distribution was more complex. We compared the geochemical parameters of our study with terrestrial and marine samples from other studies using a bootstrap approach. Sediments of the current study contained 6.5 times and 1.8 times less total organic carbon than undisturbed and disturbed terrestrial sediments, respectively. Therefore, degradation of OM and separation of carbon pools take place on land and continue in the nearshore zone, where OM is leached, mineralized, or transported beyond the study area.
Large-scale flood risk assessments are crucial for decision making, especially with respect to new flood defense schemes, adaptation planning and estimating insurance premiums. We apply the process-based Regional Flood Model (RFM) to simulate a 5000-year flood event catalog for all major catchments in Germany and derive risk curves based on the losses per economic sector. The RFM uses a continuous process simulation including a multisite, multivariate weather generator, a hydrological model considering heterogeneous catchment processes, a coupled 1D-2D hydrodynamic model considering dike overtopping and hinterland storage, spatially explicit sector-wise exposure data and empirical multi-variable loss models calibrated for Germany. For all components, uncertainties in the data and models are estimated. We estimate the median Expected Annual Damage (EAD) and Value at Risk at 99.5% confidence for Germany to be euro0.529 bn and euro8.865 bn, respectively. The commercial sector dominates by making about 60% of the total risk, followed by the residential sector. The agriculture sector gets affected by small return period floods and only contributes to less than 3% to the total risk. The overall EAD is comparable to other large-scale estimates. However, the estimation of losses for specific return periods is substantially improved. The spatial consistency of the risk estimates avoids the large overestimation of losses for rare events that is common in other large-scale assessments with homogeneous return periods. Thus, the process-based, spatially consistent flood risk assessment by RFM is an important step forward and will serve as a benchmark for future German-wide flood risk assessments.
Hydrogeological information about an aquifer is difficult and costly to obtain, yet essential for the efficient management of groundwater resources. Transferring information from sampled sites to a specific site of interest can provide information when site-specific data is lacking. Central to this approach is the notion of site similarity, which is necessary for determining relevant sites to include in the data transfer process. In this paper, we present a data-driven method for defining site similarity. We apply this method to selecting groups of similar sites from which to derive prior distributions for the Bayesian estimation of hydraulic conductivity measurements at sites of interest. We conclude that there is now a unique opportunity to combine hydrogeological expertise with data-driven methods to improve the predictive ability of stochastic hydrogeological models.
Detecting whether and how river discharge responds to strong earthquake shaking can be time-consuming and prone to operator bias when checking hydrographs from hundreds of gauging stations. We use Bayesian piecewise regression models to show that up to a fifth of all gauging stations across Chile had their largest change in daily streamflow trend on the day of the M-w 8.8 Maule earthquake in 2010. These stations cluster distinctly in the near field though the number of detected streamflow changes varies with model complexity and length of time window considered. Credible seismic streamflow changes at several stations were the highest detectable in eight months, with an increased variance of discharge surpassing the variance of discharge following rainstorms. We conclude that Bayesian piecewise regression sheds new and unbiased insights on the duration, trend, and variance of streamflow response to strong earthquakes, and on how this response compares to that following rainstorms.
The Flood Damage Database HOWAS 21 contains object-specific flood damage data resulting from fluvial, pluvial and groundwater flooding. The datasets incorporate various variables of flood hazard, exposure, vulnerability and direct tangible damage at properties from several economic sectors. The main purpose of development of HOWAS 21 was to support forensic flood analysis and the derivation of flood damage models. HOWAS 21 was first developed for Germany and currently almost exclusively contains datasets from Germany. However, its scope has recently been enlarged with the aim to serve as an international flood damage database; e.g. its web application is now available in German and English. This paper presents the recent advancements of HOWAS 21 and highlights exemplary analyses to demonstrate the use of HOWAS 21 flood damage data. The data applications indicate a large potential of the database for fostering a better understanding and estimation of the consequences of flooding.
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.
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.
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.
High-performance numerical codes are an indispensable tool for hydrogeologists when modeling subsurface flow and transport systems. But as they are written in compiled languages, like C/C++ or Fortran, established software packages are rarely user-friendly, limiting a wider adoption of such tools. OpenGeoSys (OGS), an open-source, finite-element solver for thermo-hydro-mechanical-chemical processes in porous and fractured media, is no exception. Graphical user interfaces may increase usability, but do so at a dramatic reduction of flexibility and are difficult or impossible to integrate into a larger workflow. Python offers an optimal trade-off between these goals by providing a highly flexible, yet comparatively user-friendly environment for software applications. Hence, we introduceogs5py, a Python-API for the OpenGeoSys 5 scientific modeling package. It provides a fully Python-based representation of an OGS project, a large array of convenience functions for users to interact with OGS and connects OGS to the scientific and computational environment of Python.
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.
Knickpoints in longitudinal river profiles are proxies for the climatic and tectonic history of active mountains. The analysis of river profiles commonly relies on the assumption that drainage network configurations are stable. Here, we show that this assumption must be made cautiously if changes in contributing area are fast relative to knickpoint migration rates. We studied the Parachute Creek basin in the Roan Plateau, Colorado, United States, where knickpoint retreat occurs in horizontally uniform lithology so that drainage area is the sole governing variable. In this basin, we identified an anomalous catchment in the degree to which a stream power-based model predicted knickpoint locations. The catchment is experiencing area loss as the plateau edge is eroded by cliff migration in proximity to the Colorado River. Model predictions improve if the plateau edge is assumed to have migrated over the time scale of knickpoint retreat. Finally, a Lagrangian model of knickpoint migration enabled us to study the kinematic links between drainage area loss and knickpoint migration and offered constraints on the temporal aspects of area loss. Modeled onset and amount of area loss are consistent with cliff retreat rates along the margin of the Roan Plateau inferred from the incisional history of the upper Colorado River.
Elevation-dependent compensation effects in snowmelt in the Rhine River Basin upstream gauge Basel
(2021)
In snow-dominated river basins, floods often occur during early summer, when snowmelt-induced runoff superimposes with rainfall-induced runoff. An earlier onset of seasonal snowmelt as a consequence of a warming climate is often expected to shift snowmelt contribution to river runoff and potential flooding to an earlier date. Against this background, we assess the impact of rising temperatures on seasonal snowpacks and quantify changes in timing, magnitude and elevation of snowmelt. We analyse in situ snow measurements, conduct snow simulations and examine changes in river runoff at key gauging stations. With regard to snowmelt, we detect a threefold effect of rising temperatures: snowmelt becomes weaker, occurs earlier and forms at higher elevations. Due to the wide range of elevations in the catchment, snowmelt does not occur simultaneously at all elevations. Results indicate that elevation bands melt together in blocks. We hypothesise that in a warmer world with similar sequences of weather conditions, snowmelt is moved upward to higher elevation. The movement upward the elevation range makes snowmelt in individual elevation bands occur earlier, although the timing of the snowmelt-induced runoff stays the same. Meltwater from higher elevations, at least partly, replaces meltwater from elevations below.
The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021-2050) and far-term period (2071-2100) with reference to 1976-2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021-2050 and between +131 and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture.
When inferring on the magnitude of future heat-related mortality due to climate change, human adaptation to heat should be accounted for. We model long-term changes in minimum mortality temperatures (MMT), a well-established metric denoting the lowest risk of heat-related mortality, as a function of climate change and socio-economic progress across 3820 cities. Depending on the combination of climate trajectories and socio-economic pathways evaluated, by 2100 the risk to human health is expected to decline in 60% to 80% of the cities against contemporary conditions. This is caused by an average global increase in MMTs driven by long-term human acclimatisation to future climatic conditions and economic development of countries. While our adaptation model suggests that negative effects on health from global warming can broadly be kept in check, the trade-offs are highly contingent to the scenario path and location-specific. For high-forcing climate scenarios (e.g. RCP8.5) the maintenance of uninterrupted high economic growth by 2100 is a hard requirement to increase MMTs and level-off the negative health effects from additional scenario-driven heat exposure. Choosing a 2 degrees C-compatible climate trajectory alleviates the dependence on fast growth, leaving room for a sustainable economy, and leads to higher reductions of mortality risk.