bluuebunny/crossref_metadata_2025 huggingface dataset:
Multiple-tool approach of combining microbial markers with artificial and natural tracers to specify the origin of fecal contamination in a karst groundwater catchment
Authors: Sinreich Michael
Published: March 2020

Diverse tools do exist to study the pathway from the source of a contamination to groundwater and related springs. The backward approach, i.e. sampling spring water to determine the origin of contamination, is more complex and requires multiple information. Microbial source tracking using host-specific markers is one of the tools, which however has shown to be insufficient as a stand-alone method, particularly in karst groundwater catchments.    

A karst spring in the Swiss Jura Mountains was studied with respect to the occurrence and correlation of a set of fecal indicators, including classical parameters as well as a number of bacteroidale markers. Sporadic monitoring proved the impact on spring water quality, mainly during high water stages. Additional event-focused sampling over varying recharge intensities evidenced a more detailed and divergent pattern of individual indicators. In particular, the results arose the question how to interpret peaks of human fecal markers in the rural-dominated catchment.

A multiple-tool approach, complementing fecal indicator monitoring with artificial tracer experiments and natural tracers measurements, assessed the input, storage and transfer of potential contaminants in order to specify the origin of both ruminant and human fecal contaminations. Natural tracers allowed for distinguishing between water components from the saturated zone, from the soil/epikarst storage, or from freshly infiltrated rainwater. Furthermore, the breakthrough of injected dye tracers, and their remobilization during subsequent recharge events, respectively, were correlated to the occurrence of fecal markers. System’s residence time distribution over discharge, deduced from numerous former dye tracing tests, also allowed for attributing maximum travel distances to their arrival.

The findings of the approach hypothesize the origin of human fecal contamination at the spring being in relationship with septic tanks undergoing concentrated overflow already at moderate rainfall intensities. Those intensities are, however, not sufficient to transport diffuse ruminant contamination through the vadose zone. Linkage with vulnerability assessment and land-use information can finally better locate the potential source points. Such toolbox provides not only useful basics for groundwater protection and catchment management, but also insight into general processes governing fate and transport of fecal contaminants in a karst groundwater environment.
Impacts of global re-/afforestation and deforestation on large scale atmospheric circulation
Authors: Manola Iris , Coumou Dim , Alessandri Andrea , Davin Edouard , Guo Suqi , Havermann Felix , De Hertog Steven , Lejeune Quentin , Menke Inga , Pongratz Julia , Schleussner Carl , Seneviratne Sonia , Thiery Wim
Published: March 2020

Land cover and land management (LCLM) changes have a high potential to influence the biogeophysical and biogeochemical earth system processes. The interaction of soil and vegetation with the atmosphere alternates the water, energy and momentum balance, in turn affecting the climate locally, as well as the climate of distant regions through teleconnection pathways. This, among others, might benefit or oppose risks to local and global breadbasket regions, impacting the crop yields.

In this study, we conduct model experiments to assess the local and remote impact of LCLM changes, in particular global re-/afforestation and deforestation, with a focus on the large-scale boreal summer atmospheric circulation. We hypothesize that due to the dominant role of land-atmosphere feedbacks in this season, robust dynamical transformations take place due to the LCLM changes. The idealized model experiments consist of three fully coupled Earth System Models (EC-EARTH, MPI-ESM and CESM) that run under constant 2015 greenhouse forcing for 150 years. Globally the LCLM changes go through a sequence of unchanged grid boxes in a checkerboard approach as recent studies have done, in order to accurately separate the local from the non-local effects.
Adaptive Social Protection - an innovative approach to build resilience in a multi-hazard environment
Authors: Sett Dominic , Sandholz Simone
Published: March 2020

Many countries face high risk to multiple natural hazards - such as earthquakes, floods, storms or extreme heat - which jeopardize human security around the globe. At the same time, a significant part of the world’s population is still living in poverty, often facing an increased vulnerability to hazards. On top it is often the most poor and vulnerable living in high-risk places. Hence, they are often disproportionally affected by disasters, facing significant development set-backs after disastrous events.

In response, many risk management and poverty reduction strategies have been applied in accordance with global agendas - such as the Sendai Framework for Disaster Risk Reduction – to strengthen disaster resilience. These range from early warning systems to the deployment financial mechanisms, and several specific disaster risk management (DRM), climate change adaptation (CCA), as well as livelihood support and other social protection (SP) programmes. Thus, many different streams have evolved, which, however, work towards similar goals and objectives. Those efforts are therefore often scattered and lacking cooperation and integration, hence preventing or hampering effective, well-coordinated risk management.

To overcome this deficit, Adaptive Social Protection has recently emerged as a promising approach to integrate SP, CCA and DRM with the goal to effectively build resilience to climate-related and other natural hazards. Best practices from several countries underline that this integrative approach provides a meaningful risk management option for the most vulnerable. However, ASP is still not well researched and lacks consideration on international level and in most countries’ approaches to build resilience.

This presentation will outline results from an extensive systematic literature review and highlight recent ASP developments and best practices from around the globe, as well as accenting protection gaps and entry points for ASP implementation. Drawing on this review and an ongoing study on the country of Indonesia, steps towards an effective ASP approach in will be discussed that will help building resilience in a multi-hazard environment.
Debris flow events in Austria - regional strategies for mitigation and adaptation in the light of climate change
Authors: Moser Markus , Mehlhorn Susanne
Published: March 2020

Recent years have repeatedly witnessed natural disasters throughout Austria, e.g. the catastrophic debris flows of 2012, 2013, 2016, 2017 and 2019 which caused enormous damage and losses in some areas. The impacts of climate change on these events is rather unclear in many cases, it must be assumed that the intensity and frequency of extreme events and natural hazards is likely to increase in future.

Management of bedload/debris flow processes to ensure the protective function is a major challenge. Observing the historical development shows the constant change of design types and constructions in the course of time. Hand in hand with technical progress, lessons learned from events in the light of climate change as well as a higher process understanding the constructions were constantly improved. Other reasons for the development of fitted systems with an integrative catchment-view down to the receiving stream are the high and still rising maintenance and clearance costs. On the basis of these findings and results, recommendations were derived to improve the function fulfilment of the technical protection measures. Furthermore, integrative concepts focus on the adaptation of the alpine forests to climate change. Under the principle, “fit for the future” the recommendations are summarized and presented in this contribution.
Supporting European coastal sectors to adapt to changes in extreme sea levels with climate change
Authors: Muis Sanne , Irazoqui Apecechea Maialen , Dullaart Job , de Lima Rego Joao , Madsen Kristine S. , Su Jian , Yan Kun , Verlaan Martin
Published: March 2020

Climate change will lead to increases in the flood risk in low-lying coastal areas. Understanding the magnitude and impact of such changes is vital to design adaptive strategies and create awareness. In  the  context  of  the  CoDEC  project  (Coastal  Dataset  for  Evaluation  of  Climate  impact),  we  developed a consistent European dataset of extreme sea levels, including climatic changes from 1979 to 2100. To simulate extreme sea levels, we apply the Global Tide and Surge Model v3.0 (GTSMv3.0), a 2D hydrodynamic model with global coverage. GTSM has a coastal resolution of 2.5 km globally and 1.25 km in Europe, and incorporates dynamic interactions between sea-level  rise,  tides  and  storm surges. Validation of the dataset shows a good performance with a mean bias of 0-.04 m for the 1 in 10-year water levels. When analyzing changes in extreme sea levels for the future climate scenarios, it is projected that by the end of the century the 1 in 10-year water levels are likely to increase up to 0.5 m. This change is largely driven by the increase in mean sea levels, although locally changes in storms surge and interaction with tides can amplify the impacts of sea-level rise with changes up to 0.2 m in the 1 in 10-year water level.

The CoDEC dataset will be made accessible through a web portal on Copernicus Climate Data Store (C3S). The dataset includes a set of Climate Impact Indicators (CII’s) and new tools designed to evaluate the impacts of climate change on different sectors and industries. This data service will support European coastal sectors to adapt to changes in sea levels associated with climate change. In this presentation we will also demonstrate how the C3S coastal service can be used to enhance the understanding of local climate impacts.
Postprocessing heavy precipitation forecasts for India with Quantile Mapping
Authors: Widmann Martin , Angus Michael , Orr Andrew , Leckebusch Gregor
Published: March 2020

It is estimated that around 10% of India’s population (or 130 million people) are acutely exposed to flooding resulting from intense rainfall, particularly during the main monsoon season (June to September). Such severe weather and accompanying flooding can result in considerable disruption to human communities and individuals by causing loss of life, damage to property, loss of livestock, destruction of crops and agricultural land, and deterioration of health conditions owing to waterborne diseases. To provide early warning of these heavy rainfall events, reliable impact-focused forecasting from operational weather forecasting centres such as NCMRWF (National Centre for Medium Range Weather Forecasting) and IMD (Indian Meteorological Department) is crucial.

Yet, despite the advances in numerical weather predictions and the state-of-the-art models used in India, accurately forecasting extreme weather at these scales is still difficult, and the intensity and spatial structure of predicted precipitation can both exhibit large errors. These errors are mainly caused by the limited resolution of weather forecasting models, and the resulting lack of adequate representation of small-scale processes. Some of them can be substantially reduced by statistical postprocessing of the forecasts taking into account past observations. However, currently no postprocessing methods for precipitation are applied to the weather forecasts over India.

Here, we present first results of postprocessing precipitation ensemble forecasts for India with local Quantile Mapping. Given our focus on heavy precipitation and the associated problem of a low number of cases and high sampling variability for the simulated and observed empirical Probability Density Functions (PDFs), we employ both standard, non-parametric PDFs but also parametric PDFs based on the Gamma and Generalised Extreme Value distributions.

This work is part of the ‘Weather and Climate Science for Service Partnership India’ (WCSSP-India) project ‘Heavy Precipitation forecast Postprocessing over India (HEPPI)’. Quantile Mapping is a member-by-member postprocessing method that essentially retains the spatial structure of the raw simulation. Within HEPPI we will also test ensemble-based methods and methods that adjust the spatial structure. This work provides the basis for further integration of meteorological and hydrological predictions.
Overview of observed seismic signals on Mars
Authors: Ceylan Savas , Clinton John F. , Giardini Domenico , Böse Maren , van Driel Martin , Euchner Fabian , Horleston Anna , Kawamura Taichi , Khan Amir , Orhand-Mainsant Guénolé , Scholz John-Robert , Stähler Simon , Charalambous Constantinos , Banerdt W. Bruce , Garcia Raphaël F. , Kedar Sharon , Lognonné Philippe , Panning Mark , Pike Tom , Smrekar Suzanne E.
Published: March 2020

InSight landed on Mars in late November 2018, and the SEIS package, which consists of one short period and one very broadband sensor, was deployed on the surface shortly after. The data returned by the InSight is monitored in a timely manner by the Marsquake Service (MQS), a ground segment support group of InSight that has been set up to establish and maintain the seismicity catalogue. The MQS has at least one member on duty who routinely checks the data for any type of seismic signals. All suspicious signals are then communicated to the InSight team after evaluation.

To date, MQS has identified more than 365 events which are classified into two general families as high and low frequency, with each family having unique features in terms of their energy content. The most distinct quakes detected so far belong to the low frequency family that occurred on Sol 173 and 235, and have clear P and S-wave arrivals that reveal a distance around 30 degrees east of the lander, pointing the region in the vicinity of Cerberus Fossae. In addition to the signals of seismic origin, the SEIS data contain features that originate from other sources such as atmospheric effects or electronics. Part of these non-seismic observations may resemble quakes which may lead to wrong interpretations, and therefore require careful analysis.

Here, we show examples of signals of both seismic and non-seismic origins. We describe the characteristics of these observations in time and frequency domains in order to give an overview of martian data content.
Disentangling the Control of Canopy Structure and Plant Physiology on the Diurnal Dynamics of SIF and Photosynthesis
Authors: Chang Christine , Wen Jiaming , Zhou Ruiqing , Sun Ying
Published: March 2020

Solar-induced chlorophyll fluorescence (SIF) offers a promising tool to remotely monitor photosynthesis from the canopy to regional scale. However, in order to interpret instantaneous satellite SIF measurements in a biological context, there needs to be a better understanding of the diurnal dynamics of SIF and photosynthesis. Using two maize sites with contrasting row orientations, we acquired canopy scale SIF and hyperspectral reflectance using a tower and UAV, in conjunction with concurrent leaf-level measurements of photosynthesis and chlorophyll fluorescence. We show that SIF dynamics are impacted by a combination of canopy structure and plant physiology, which can lead to a divergent SIF-photosynthesis relationship, particularly at certain times of day. These findings have significant implications for upscaling and interpreting satellite SIF retrievals, which rely on daily mean integrals.
Segmentation of coronal features to understand the solar EIV and UV irradiance variability
Authors: Zender Joe , van der Zwaart Rens , Kariyappa Rangaiah , Damé Luc , Giono Gabriel
Published: March 2020

The study of solar irradiance variability is of great importance in heliophysics, the Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of features in the solar magnetosphere, chromosphere, and corona.  We studied the variability of solar irradiance for a period of 10 years (May 2010–January 2020) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, the Atmospheric Imaging Assembly (AIA), and the Helioseismic and Magnetic Imager (HMI) of on board the Solar Dynamics Observatory (SDO), and applied a linear model between the identified features and the measured solar irradiance by LYRA.

We used the spatial possibilistic clustering algorithm (SPoCA) to identify coronal holes, and a morphological feature detection algorithm to identify active regions (AR), coronal bright points (BPS), and the quite sun (QS) and segment coronal features from the EUV observations of AIA. The AIA segmentation maps were then applied on SWAP images, images of all AIA wavelengths, HMI line-of-sight (LOS) magnetograms, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/BPs/QS features were computed and compared with LYRA irradiance measurements as a proxy for ultraviolet irradiation incident to the Earth atmosphere.

We modelled the relation between the solar disk features (ARs, CHs, BPs, and QS) applied to magnetrogram and EUV images against the solar irradiance as measured by LYRA and the F10.7 radio flux. To avoid correlation between different the segmented features, a principal component analysis (PCM) was done. Using the independent component, a straightforward linear model was used and corresponding coefficients computed using the Bayesian framework. The model selected is stable and coefficients converge well.

The application of the model to data from 2010 to 2020 indicates that both at solar cycle timeframes as well as shorter timeframes, the active region influence the EUV irradiance as measured at Earth. Our model replicates the LYRA measured irradiance well.
Analyzing German transformation pathways‘ alignment with national and global climate and sustainability goals in the FABLE framework
Authors: Schneider Uwe A. , Steinhauser Jan
Published: March 2020

Successful implementation of the Paris climate agreement and the 2015 UN sustainability goals requires large-scale transformations in all relevant areas, with land-use and land-management among the most critical ones. On a global scale, a variety of transformation pathways has been discussed. However, these pathways often assume a uniform global transformation from which each country’s transformation pathway follows in a top-down manner. This approach faces implementation difficulties due to inconsistencies between resulting country pathways and the respective country’s political reality. Hence, a bottom-up approach may create less ambitious, but more realistic transformation pathways, both on a regional and global scale.
As part of an international effort to create national and global transformation pathways in line with the Paris climate agreement and the 2015 UN sustainability goals, this project aims to model impacts from current and projected German environmental policies and societal developments and to embed them into a broader international context. We analyze current data, trends and developmental goals for key aspects of German society and policies affecting environmental factors, utilizing the FABLE calculator.
By implementing these national results as well as data from analogous projects focusing on other countries into a global framework, we can compare the global impacts of projected national transformation pathways as well as needs for adjustment in regards to climate and sustainability goals. This approach will allow for partial corrections in each national model, more in line with each country’s respective economic and political circumstances.
Converting scientific research into a practical tool co-designed with the stakeholders in R Shiny: a web-based application for managing the main reservoir of the drinking water supply system in the Romagna region, Italy
Authors: Pugliese Alessio , Neri Mattia , Brath Armando , Toth Elena
Published: March 2020

Complex water optimisation problems represent one of the biggest challenges of the near future due to human and climate impacts. On the one hand, stakeholders in the water supply sector require high-level knowledge of the whole water cycle process at different scales, with the aim to either assess the risk for uncertain future water availability or rely on more analytic approaches for decision making. On the other hand, scientific research produces high quality models, algorithms and schemes capable of solving the water problems, but scientists often struggle when it comes to deploy tools that deliver their research outcomes to stakeholders and decision makers that ultimately will use them. The principal goal of this project is to fill the gap between the development of innovative research methodologies and their practical usability in the real world. We present “RApp”, a web-based application written purely in R within the Shiny framework and developed in collaboration with the water supply company Romagna Acque SpA. RApp simulates and visualizes the behavior of the reservoir that sustains the drinking water supply system of the Romagna region, Italy, in order to support its optimal management. Reservoir simulations are obtained connecting, through a unique and site-specific modelling chain, the inflows from the upstream catchments, the functioning of the reservoir, the potential of the treatment plant and the water demand. The optimized monthly-based management rules were obtained off-line, through a multi-objective optimization algorithm by maximizing the water yields and, at the same time, minimizing the occurrence of water outages during drought periods. The RApp user can produce quick reports of the past and expected reservoir yields and stored volumes, in terms of either graphical or table outputs, as a function of different initial and boundary conditions provided by the users, such as the initial stored volume, the expected inflows, the adoption of optimized or user-defined management rules, the occurrence of an abrupt change in the water demand, thus, allowing stakeholders to explore the impact of different scenarios and management options. For developing the tool, a very close interaction between the research group and the stakeholders was required, and is still ongoing, in order to define and then expand the functionalities of the software that are most needed for its practical use.
Quantifying snowfall from orographic cloud seeding
Authors: Friedrich Katja , Ikeda Kyoko , Tessendorf Sarah , French Jeffrey , Rauber Robert , Geerts Bart , Xue Lulin , Rasmussen Roy , Blestrud Derek , Kunkel Melvin , Dawson Nick , Parkinson Shaun
Published: March 2020

Cloud seeding has been used as one water management strategy to overcome the increasing demand for water despite decades of inconclusive results on the efficacy of cloud seeding. In this study snowfall accumulation from glaciogenic cloud seeding is quantified based on snow gauge and radar observations from three days in January 2017, when orographic clouds in the absent of natural precipitation were seeded with silver iodide (AgI) in the Payette basin of Idaho during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE). On each day, a seeding aircraft equipped with AgI flares flew back and forth on a straight-line flight track producing a zig-zag pattern representing two to eight lines of clouds visible through enhancements in radar reflectivity. As these seeding lines started to form precipitation, they passed over several snow gauges and through the radar observational domain. For the three cases presented here, precipitation gauges measured increases between 0.05-0.3 mm as precipitation generated by cloud seeding pass over the instruments. A variety of relationships between radar reflectivity factor and liquid equivalent snowfall rate were used to quantify snowfall within the radar observation domain. For the three cases, snowfall occurred within the radar observational domain between 25 -160 min producing a total amount of water generated by cloud seeding ranging from 123,220 to 339,540 m3 using the best-match Ze-S relationship. Uncertainties in radar reflectivity estimated snowfall are provided by considering not only the best-match Ze-S relationship but also an ensemble of Ze-S relationships based on the range of coefficients published from previous studies and then examining the percentile of snowfall estimates based on all of the Ze-S relationships within the ensemble. Considering the interquartile range and 5th/95th percentiles, uncertainties in total amount of water generated by cloud seeding can range between 20-45% compared to the best-math estimates. These results provide new insights towards understanding how cloud seeding impacts precipitation and its distribution across a region.
The origin of elevated plateaus along passive continental margins
Authors: Bonow Johan M. , Japsen Peter , Green Paul F. , Chalmers James A.
Published: March 2020

Many passive continental margins around the world are characterised by elevated plateaus at 1 to 2 km or more above sea level cut by deeply incised valleys and commonly separated from an adjacent coastal plain by one or more escarpments. Mesozoic–Cenozoic rift systems parallel to the coast are commonly present offshore with a transition from continental to oceanic crust further offshore. These landscapes occur in arctic, temperate and tropical climate and in different geological settings independent of the time span since break-up (e.g. along the Atlantic from south to north).

The plateaux are typically more than 100 km wide, much larger in some cases, and extend hundreds of kilometres along the margin, cutting across bedrock of different ages and resistances. The key to understanding the formation of regional, low-relief erosion surfaces is the base-level, as this is the level to which fluvial systems grade the landscape. The most likely base level is sea level, particularly for locations along continental margins during the post-rift development of passive margins.

It is commonly assumed that the characteristic, large-scale morphology of elevated, passive continental margins with  high-level plateaux and deeply incised valleys persisted since rifting and crustal separation Further, it is assumed that the absence of post-rift sediments is evidence of non-deposition, despite continental-stretching theory predicting deposition of a thick post-rift sequence overlying both the rift and its margins.

However, our studies of the passive continental margins of West and East Greenland, Norway, NE Brazil and southern Africa provide evidence of km-scale, post-rift subsidence and that the plateau surfaces were graded to sea level long after break-up and subsequently lifted to their present elevations. In some of these cases, the presence of post-rift marine sediments at high elevation provide direct proof of this interpretation. Since elevated plateaux cut by deeply incised valleys are a characteristic feature of these and other margins, this similarity suggests that such topography elsewhere in the world may also be unrelated to the processes of rifting and continental separation. We present a wide range of evidence from passive margins around the world in support of this hypothesis,

 

Bonow et al. 2014: High-level landscapes along the margin of East Greenland – a record of tectonic uplift and incision after breakup in the NE Atlantic. Global and Planetary Change.

Green et al. 2018: Post-breakup burial and exhumation of passive continental margins: Seven propositions to inform geodynamic models. Gondwana Research.

Japsen et al. 2019: Elevated passive continental margins: Numerical modeling vs observations. A comment on Braun (2018). Gondwana Research.
Analysis of potential flood damage on crops at global scale
Authors: Annis Antonio , Chiarelli Davide Danilo , Nardi Fernando , Rulli Maria Cristina
Published: March 2020

Most of the food production connected to crops is located in fluvial corridors because of their suitable morphology and fertile soils. The knowledge and large scale quantification of the agricultural resources at flood risk has a crucial importance for improving urban and regional planning. Recent advances in satellite derived products related to land use, digital terrain and hydrologic variables can give a strong support on extensive analyses on cropland areas in floodplains and their interactions with natural ecosystems and human activities. In this work, we present a global assessment of cropland at flood risk in terms of extension, productivity and the related calories adopting the Global Cropland Area Database (GCAD), the Global Floodplain Dataset (GFPLAIN250m), the Global flood hazard maps (GFHM) in conjunction with continental remotely-sensed data representing free flowing (versus artificially regulated) rivers and urban density maps. Spatially distributed and aggregated results of the research allow to identify the most critical areas in terms of food security and floods, thus allowing to support intervention strategies for food security management at large scale and for different socio-economic contexts.
Historical Relationship between Snow Depth and Damaged Area in South Korea
Authors: Chung Gunhui , Park Heeseong
Published: March 2020

Recently, snow disasters have been increased in South Korea due to the unexpected heavy snow in a region where winter gives little snow. For instance, 10 people were dead by the collapsed roof due to the unusual heavy snow. Many local governments do not have enough snow removal equipment because of little snow in winter season. Therefore, it has been important to estimate the amount of snow damage to prepare heavy snow disaster. There are not many researches to estimate damage of snow disaster in South Korea. In this study, historical snow damage data from 1994~2018 recorded in National Disaster Report were used to predict the future snow disaster damage using a statistical equation. However, it was not easy to predict the amount of snow damage when the heavy snow is happened in the area where no snow during the winter in history. Therefore, the relationship between the snow depth and damaged area were analyzed using the historical damage data. Principal multiple regression method was applied to develop the snow damage estimation function using the damaged area. The developed model could be applied to plan the budget for the snow removal equipment or snow damage reduction.

 

Acknowledgement:

This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Intelligent Management Program for Urban Water Resources Project, funded by Korea Ministry of Environment(MOE) (2019002950002).

 
Combining tree ring analysis and remote sensing to assess the 2017 black pine dieback in Vinschgau/Val Venosta (Italy)
Authors: Obojes Nikolaus , Klemm Jennifer , Sonnenschein Ruth , Giammarchi Francesco , Tonon Giustino , Tappeiner Ulrike , Zebisch Marc
Published: March 2020

To prevent further erosion of pastures along the south slopes of the Vinschgau/Val Venosta (South Tyrol/Italy) about 900 ha of non-native black pine (Pinus nigra) have been afforested there between 1900 and the 1960s. This drought-tolerant Mediterranean species was supposed to be able to cope with the dry climate at degraded soils in the inner-alpine dry valley. Nevertheless, black pine in the Vinschgau has been affected by reoccurring tree vitality decline and diebacks in the last 20 years linked to repeated droughts and heat waves. Observing growth trends via tree ring analysis is usually restricted to single stands. On the other hand, remote sensing data to track tree vitality was not available in sufficient spatial and temporal resolution to be applied to complex mountain terrain until recently. This has changed with the launch of the Sentinel-2 A and B satellites in 2015 and 2017 with a spatial resolution of 10 to 20 m and a revisiting period of 5 days. To analyse the accordance of remote sensing-based vegetation indices to tree-ring based growth data, we compared twelve sites across the Vinschgau/Val Venosta with a differing degree of vitality loss in 2017 for a four-year period from 2015 to 2018. In general, less vital sites were located at lower elevation and on steeper slopes. Radial tree growth was positively correlated to spring precipitation and strongly decreased during earlier hot and dry years such as 1995 and 2003. We found high and statistically significant correlations between site-average basal area increment as well as tree ring width indices and multiple vegetation indices (Normalized Difference Vegetation Index NDVI, Green Normalized Difference Vegetation Index GNDVI, Normalized Difference Infrared Index NDII, Moisture Stress Index MSI) especially for the dry 2017 growing season and the 2018 recovery year, which had large gradients in tree vitality between sites. Overall, these results show that remote sensing-based vegetation indices can be used to scale up stand level growth data also in complex mountain terrain.
Evaluating Freshwater Lens Vulnerability in a Multi-layered, Island Aquifer System in the Tropics
Authors: Banks Eddie W. , Noorduijn Saskia , Batelaan Okke , Post Vincent , Werner Adrian , Munday Tim , Soerensen Camilla , Cahill Kevin , Jolly Phillip , Ellis Joanna
Published: March 2020

Groundwater is the primary source of freshwater supply on remote small islands, where it exists as a freshwater lens. It is extremely vulnerable to over-extraction, pollution and seawater intrusion. Ensuring long-term sustainable management of the groundwater resource is of the utmost importance when there are growing water demands, sea-level rise and/or recharge decline. This study used a three-dimensional, variable-density numerical groundwater flow and solute transport model to investigate vulnerability of a freshwater lens in a multi-layered aquifer system on Milingimbi Island, a small tropical island in northern Australia. The model was used to explore the impacts and possibility of increased groundwater demand on the freshwater lens, its volume, geometry as well as the thickness of the transition zone. The risks of saltwater intrusion, both laterally from the ocean and by localised up-coning from the deeper, more saline aquifers beneath the freshwater lens, were also assessed. Model calibration used observed hydraulic heads and salinity observations from pumping and observation wells. Subsurface bulk conductivity values, which were calculated from inverted airborne electromagnetic (AEM) and near-surface geophysical data, were also used in the calibration process. The results showed that the hydraulic heads and observed salinity achieved the ‘best fit’ in the calibration process, whereas the addition of the geophysical data assisted in constraining the lens geometry in the steady state model and integrated the data poor areas based on traditional hydrogeological datasets. The models’ calibration sensitivity to the range of measured salinities could be enhanced by improving the conversion factor between the AEM-derived conductivity values and the observed salinity data. This would best be accomplished by targeted monitoring wells at discrete depths and locations across the lens and improvements in the sampling/restoration of existing ones. The numerical model provided a framework to evaluate the key underlying hydrogeological processes on the island, as well as an important decision-making tool to ensure a sustainable and reliable water supply for the island community.
Social tipping as a response to anticipated sea level rise
Authors: Wiedermann Marc , Smith E Keith , Donges Jonathan F , Heitzig Jobst , Winkelmann Ricarda
Published: March 2020

Social tipping, where minorities trigger large populations to engage in collective action, has been suggested as a key component to address contemporary global challenges, such as climate change or biodiversity loss. At the same time, certain climate tipping elements, such as the West Antarctic Ice Sheet, are already at risk of transgressing their critical thresholds, even within the aspired goals of the Paris Agreement to limit global temperature rise to 1.5° to 2°C. Consequently, recent studies suggest rapid societal transformations, i.e, wanted tipping, may be required to prevent the crossing of dangerous tipping points or critical thresholds in the climate system.

Here, we explore likelihoods for such social tipping in climate action as a response to anticipated climate impacts, particularly sea-level rise. We first propose a low-dimensional model for social tipping as a refined version of Granovetter's famous and well-established threshold model. This model assumes individuals to become active, e.g., to mitigate climate change, through social influence if a sufficient number of instigators in one’s social network initiate a considered action. We estimate the number of instigators as shares of per-country populations that will likely be impacted by sea-level rise within a given time-window of anticipation. Specifically, we consider sea-level contributions from thermal expansion, mountain glaciers, Greenland as well as Antarctica under different concentration pathways. Additionally, we use nationally aggregated social science survey data of climate change attitudes to estimate the proportion of the population that has the potential to be mobilized for climate action, thereby accounting for heterogeneities across countries as well.

Our model shows that social tipping, i.e., the majority of a population acting against climate change, becomes likely if the individuals' anticipation time horizon of climate impacts lies in the order of a century. This observation aligns well with ethical time horizons that are often assumed in the context of climate tipping points as they represent the expected lifetime of our children and grandchildren. We thus show that, even though sea-level rise is generally a very slow process, a small dedicated minority of anticipatory individuals – usually 10–20 percent of the population – has the potential to tip collective climate action and with it a whole ensemble of attitudes, behaviours and ultimately policies.
Data assimilation in lake Geneva using the SPUX framework
Authors: Safin Artur , Bouffard Damien , Runnalls James , Georgatos Fotis , Bouillet Eric , Ozdemir Firat , Perez Cruz Fernando , Šukys Jonas
Published: March 2020

Lakes form an integral component of ecosystems and our communities. Aside from being a source of drinking water, lakes provide additional benefits such as recreation, heat management and fishing. At the same time, human activity can significantly disrupt the natural state of the aquatic ecology. In the past, limited understanding of the hydrological and biochemical processes in aquatic systems has led to significant eutrophication in certain cases. To mitigate further risk, monitoring programs have been implemented. Recently new instrumentation, such as in situ observation platforms, remote sensing and computational resources enable comprehensive monitoring of the temporal evolution of the environment’s spatial heterogeneity.

A major focus of the DATALAKES project is to use the multiple sources of observational measurements for data assimilation and forecasting purposes. The aim is to infer the entire state of the lake as accurately as possible using high-resolution three-dimensional hydrodynamic models. Uncertainty quantification using Bayesian inference and modern Markov Chain Monte Carlo methods is implemented using the SPUX package, with the stochasticity provided by an ensemble of weather forecasts. To obtain predictions in a reasonable time, we parallelize both the particle filtering and the hydrodynamic model on the CSCS cluster. The data assimilation component will combine multiple in-situ sources with remote sensing measurements of lake water surface temperature and incorporate the respective uncertainties in measurement into the error model. To enable the use of multi-level variance reduction schemes, we perform calibration of essential hydrodynamic model parameters for a hierarchy of discretisations. The results show that the framework is capable of inferring the state of lake Geneva from observational measurements.
Variational Bayesian Independent Component Analysis for InSAR displacement time series with application to California
Authors: Gualandi Adriano , Liu Zhen
Published: March 2020

The exploitation of ever increasing Interferometric Synthetic Aperture Radar (InSAR) datasets to monitor the Earth surface deformation is an important goal of today’s geodesy. Surface geodetic deformation observations are often the result of the combination of a multitude of sources (either volcano-tectonic deformation associated with seismic events, post-seismic relaxation, aseismic transients, long-term creep loading, magma intrusions or non-tectonic deformation associated with hydrological loads, poroelastic rebound, anthropic activity and various sources of noise). In this regard, we are facing a so-called Blind Source Separation (BSS) problem. Natural approaches to tackle BSS problems are those multivariate statistical techniques which attempt to decompose the dataset into a limited number of statistically independent sources, under the assumption that the different physical mechanisms underlying the observations have independent footprints either in space or time. Multiple algorithms have been proposed to separate the various independent sources, and here we show the capabilities of a variational Bayesian Independent Component Analysis (vbICA) algorithm. In particular, we show through synthetic test cases its superiority with respect to other commonly used multivariate statistical techniques like the Principal Component Analysis (PCA) and the FastICA algorithm. Application of vbICA to InSAR time series from European Space Agency (ESA) Sentinel-1 satellite in the Central Valley and on the Central San Andreas Fault segment, California, spanning the time range 2015-2019, shows that the algorithm provides a viable way to separate elastic and inelastic deformation in response to the aquifer charge/discharge as well as creeping signal from seasonal loading.
Comparison of the main sea ice parameters received from satellite measurements and based on numerical simulation for the Baltic Sea region
Authors: Jakacki Jaromir , Muzyka Maciej , Konik Marta , Przyborska Anna , Andrzejewski Jan
Published: March 2020

During the last decades remote sensing observations as well as modelling tools has been developed and become key elements of oceanographic research. One of the main advantages of both tools is a possibility of measuring large-scale areas.

The remote sensing measurements deliver only snapshots of the ice situation with no information about backgroundconditions. Moreover, providing picture of the whole area requires sometimes combining various datasets that increases uncertainties.  Modelling simulations provide full history of external conditions, but they also introduce errors that are the result of parameterizations. Also, an inaccuracy provided by forcing fields at the top and bottom boundaries are accumulated in the model.

In this work sea ice parameters such as sea ice concentration, thickness and volume obtained from both – satellite measurements and modelling has been compared. Numerical simulations were performed using standalone Community Ice Code (CICE) model (v. 6.0). It is a descendant of the basin scale dynamic-thermodynamic and thickness distribution sea ice model. The model is well known by scientific community and was widely used in a global as well as regional research, even operationally. The satellite derived ice thickness products were based on the C band HH-polarized SAR measurements originating from the satellites Sentinel-1 and RADARSAT-2. The sea ice concentration maps contain also visual and infrared information from MODIS and NOAA.

The ice extent, thickness and volume were compared in several regions within the Baltic Sea.  Seasonal changes were analyzed with a particular attention to ice formation and melting time. The sea ice extent datasets were compatible. Inconsistencies were observed for the sea ice thickness delivered by satellite measurements, especially during the ice melt. The work presents direction for ignoring satellite data with an error related to ice melting that allows for excluding erroneous satellite maps and obtain reliable intercalibration.

 

This work was partly funded by Polish National Science Centre, project number 2017/25/B/ST10/00159
Modelling water-related processes in rock wall permafrost
Authors: Magnin Florence , Josnin Jean-Yves , Ravanel Ludovic , Deline Philip
Published: March 2020

Rock wall permafrost has been increasingly regarded since the early 2000s in reason of the growing frequency and magnitude of bedrock failures from mountain permafrost areas. One of the main current challenges to better assess its degradation and the failure mechanisms is the understanding of hydraulic processes, i.e. water infiltration and circulation in the fractures. Indeed, recent thermal and mechanical models have considered a homogeneous and ice-saturated rock medium, overlooking water-related processes which may act along fractures when water percolates. But observations of water stains alongside ice bodies in several rock fall scars point out the need to gain knowledge about such processes.

Recent development in numerical codes allow to fully couple thermal and hydraulic processes, and have so far mostly been used to investigate polar permafrost terrains. In this communication, we will present a first attempt to couple thermal and hydraulic processes in a numerical model of high-alpine bedrock permafrost. This entails designing a new modelling approach accounting for heterogeneous (fractured) and non-saturated areas in the rock medium, as well as water outlets and fracture intersections to permit water circulation. We implement Richards equations in the Finite Element simulation system Feflow (DHI-WASY) to model variably saturated flow and advective-conductive heat transports combined with phase change processes. We simulate heat and mass transports in a 2D geometry (vertical cross-section) reflecting the Aiguille du Midi settings (3842 m a.s.l., Mont Blanc massif, European Alps). The model is forced with climate time series partially constructed out of measured air temperature and assumptions about previous climate period. Steady freezing occurring between 1550 and 1850 AD (Little Ice Age) points out the role of fractures in the freezing rate, as fractures favor infiltration of cold water from the surface, acting as freezing corridors. Under thawing, water movements are enabled in the unfrozen upper parts of the model geometry through a partially saturated domain, whereas the lower part remains saturated. In the thawed zones, fractures that are not completely filled by ice can accelerate water circulation and create thawing corridors.

In this communication, we will present the modelling approach and the preliminary results. We will show that our numerical investigations bear strong potential to address thermal and mechanical effects of water infiltration (from snow melting and rain) and circulation in the frozen bedrock.

 