bluuebunny/crossref_metadata_2025 huggingface dataset:
A versatile exploration method for simulated data based on Self Organizing Maps
Authors: Innocenti Maria Elena , Köhne Sophia , Hornisch Simon , Grauer Rainer , Amaya Jorge , Raeder Jimmy , Ferdousi Banafsheh , Edmond James "Andy" , Lapenta Giovanni
Published: March 2022

The large amount of data produced by measurements and simulations of space plasmas has made it fertile ground for the application of classification methods, that can support the scientist in preliminary data analysis. Among the different classification methods available, Self Organizing Maps, SOMs [Kohonen, 1982] offer the distinct advantage of producing an ordered, lower-dimensional representation of the input data that preserves their topographical relations. The 2D map obtained after training can then be explored to gather knowledge on the data it represents. The distance between nodes reflects the distance between the input data: one can then further cluster the map nodes to identify large scale regions in the data where plasma properties are expected to be similar.

In this work, we train SOMs using data from different simulations of different aspects of the heliospheric environment: a global magnetospheric simulation done with the OpenGGCM-CTIM-RCM code, a Particle In Cell simulation of plasmoid instability done with the semi-implicit code ECSIM, a fully kinetic simulation of single X point reconnection done with the Vlasov code implemented in MuPhy2.

We examine the SOM feature maps, unified distance matrix and SOM node weights to unlock information on the input data. We then classify the nodes of the different SOMs into a lower and automatically selected number of clusters, and we obtain, in all three cases, clusters that map well to our a priori knowledge on the three systems. Results for the magnetospheric simulations are described in Innocenti et al, 2021. 

This classification strategy then emerges as a useful, relatively cheap and versatile technique for the analysis of simulation, and possibly observational, plasma physics data.

Innocenti, M. E., Amaya, J., Raeder, J., Dupuis, R., Ferdousi, B., & Lapenta, G. (2021). Unsupervised classification of simulated magnetospheric regions. Annales Geophysicae Discussions, 1-28. 

https://angeo.copernicus.org/articles/39/861/2021/angeo-39-861-2021.pdf
Assessing Potential Atmospheric CO2 Monitoring Sites for Improved  Estimation of Southern Ocean CO2 Uptake
Authors: Suntharalingam Parvadha , Chen Zhaohui , Jones Anna , Buchanan David
Published: March 2022

The Southern Ocean plays a fundamental role in in the global carbon cycle and is estimated to absorb  ~40% of anthropogenic carbon-dioxide (CO2) emissions. Recent studies have highlighted  the potentially large  decadal variability of this uptake, and the uncertainties associated with estimates derived from different  ocean carbon measurement technologies. The majority of these estimates of Southern Ocean CO2 uptake are commonly derived from ‘bottom-up’ analyses of oceanic carbon measurements. An independent means of estimating air-sea CO2 fluxes is provided by ‘top-down’ analyses, which employ inverse methods or data assimilation techniques  combining atmospheric CO2 measurements with numerical transport model analyses. Robust regional flux estimates from such top-down methods require an atmospheric observational network with sufficient spatial coverage. At present, however, long-term measurements of atmospheric CO2 are only available at a limited number of sites in the Southern Ocean region. Given this sparse atmospheric sampling there is an urgent need for expansion of the current Southern Ocean atmospheric CO2 measurement network.

The British Antarctic Survey has identified a number of locations (including the sub-Antarctic and South Atlantic Islands of Tristan da Cunha, South Georgia and the Falklands) where new systems for long-term observations of CO2 could be established. In this analysis we present results from a set of Observing System Sampling Experiments (OSSEs) using the GEOS-Chem atmospheric transport model, in combination with the Local Ensemble Transform Kalman Filter method (Chen et al. 2021) to identify the effectiveness of these locations towards providing improved constraints on Southern Ocean air-sea fluxes.  Our assessment of potential sampling sites is derived from metrics quantifying the uncertainty reduction of regional oceanic CO2 flux estimates.

References

Chen et al.  (2021) Variability of North Atlantic CO2 fluxes for the 2000–2017 period estimated from atmospheric inverse analyses. Biogeosciences, 18 (15). pp. 4549-4570. ISSN 1726-4189.
Numerical modelling of lithospheric deformations with frictional plasticity
Authors: Duretz Thibault , de Borst René , Räss Ludovic , Yamato Phillippe , Hageman Tim , Le Pourhiet Laetitia
Published: March 2022

Strain localisation is a key process that allows for the emergence of tectonic plates and controls their long-term deformation. Upper crustal levels are relatively cold and their rheology is thus governed by frictional plasticity. In order to predict the formation of tectonic plates and quantify the deformation of the Earth's upper shell, geodynamic modelling simulation tools must reliably account for deformation in the frictional plastic realm. 

Nevertheless, the simulation of frictional plastic strain localisation poses severe issues. Commonly employed implementations (visco-plastic and visco-elasto-plastic) often fail to accurately satisfy force balance and suffer from a lack of convergence upon mesh refinement. These problems are intimately linked to the fact that commonly employed models do not encompass any characteristic spatial or temporal scales of localisation. Various regularisation techniques can thus be used as a remedy. Here we investigate three popular regularisation techniques, namely viscoplasticity, gradient plasticity and the use of a Cosserat medium, and discuss their potential application for geodynamic modelling.  
Decadal variability southern North Sea pH: ocean acidification in reverse?
Authors: Humphreys Matthew , Hilgen Cecile , Ourradi Yasmina , Schilder Jos , Reichart Gert-Jan
Published: March 2022

The global ocean absorbs about a quarter of the anthropogenic carbon dioxide (CO2) emitted annually. A well-known consequence is a decline in seawater pH termed ocean acidification, which varies in magnitude but is on average about 0.002 a−1 and is thought to be ubiquitous in the surface ocean. However, time-series observations from Rijkswaterstaat (RWS; part of the Dutch government) and the Royal Netherlands Institute for Sea Research (NIOZ) of southern North Sea surface pH reveal decadal variability and indicate that pH has been increasing by about 0.02 a−1 since 2010. An earlier phase of pH increase was observed in the 1980s and has been explained by changing riverine nutrient inputs to the ocean. However, nutrient concentrations have remained relatively stable since 2010, so this cannot be the driver of the current transient. From a CO2-chemistry perspective, the decadal pH variability cannot be explained using only the RWS time-series data because no additional marine carbonate system variables (e.g. total alkalinity (TA), dissolved inorganic carbon (DIC) or CO2 fugacity(fCO2)) were measured before 2018. In this study, we aim to better understand the decadal pH variability by determining the equivalent changes in the other carbonate system variables and their possible drivers. We combined datasets from SOCAT (fCO2), GLODAP and other recent North Sea cruises (TA and DIC), and the RWS time series (pH) for the period from 2000 to 2021. We corrected DIC and TA for spatial bias by salinity normalisation and further corrected DIC for seasonal sampling bias. This showed that TA gradually increased from 2000 to 2021, but without evidence for a change in slope around 2010. However, DIC increased from 2000 to 2010, but decreased thereafter. The changes in pH predicted from corrected TA and DIC agree with the RWS time-series data in direction (decreasing before 2010, increasing thereafter) but are an order of magnitude smaller. This discrepancy may result from unknown contributors to total alkalinity (e.g. from dissolved organic matter) and/or may be associated with uncertainties due to the relatively sparse TA and DIC datasets and the spatial/seasonal bias corrections that we applied. Irrespective of the underlying mechanisms involved the air-sea fCO2 difference (ΔfCO2)decreased by about 0.6 µatm a−1, indicating that the southern North Sea became a stronger sink (or weaker source) of CO2 from 2000 to 2021.
Palaeoclimate and sea-level inferences from Ringgåsvatnet, Nordaustlandet, Svalbard Archipelago.
Authors: Buckby Joseph , Furze Mark , Bakke Jostein , Linge Henriette
Published: March 2022

The overarching aim of the project is to contextualise glacier activity across a transect of the Svalbard Archipelago to reconstruct and infer the past climatic and atmosphere-ocean interaction during the Late Quaternary, thus enabling the determination of temperature and precipitation gradients across the archipelago as well as identifying shifts in the positioning and coalescing of the polar air and ocean masses. Palaeoclimates will be reconstructed along a highly sensitive transect across the Svalbard Archipelago ranging from the east at northern Nordaustlandet, northern Spitsbergen and Erdmannflya in southwest central Spitsbergen. This will be elucidated by the investigation of Quaternary geomorphology, sea-level histories, proxies, and geochrononologies from lacustrine sediment records and terrestrial surface exposure dating. The lake Ringgåsvatnet is situated above 80ºN on Nordaustlandet, northeast Svalbard Archipelago. Sediment cores were retrieved in 2017 and have undergone of analysis and interpretation of the glacial, sea-level and palaeoclimate story contained within. Ringgåsvatnet forms part of transect of cores that seek to elucidate the evolution of palaeoclimatic gradients across Svalbard during the Holocene. Ahlmannfonna resides within the main catchment of Ringgåsvatnet, and likely receiving meltwater from the northwest margin of Austfonna ice cap during deglaciation. The cores record the post-glacial emergence of Ringgåsvatnet and the surrounding terrain, with initial isolation of the basin dated to the Early Holocene based on AMS 14C radiocarbon dates on terrestrial macrofossils and foraminifera supported by other chronological approaches (210Pb, PSV). Marine and lacustrine sedimentation in Ringgåsvatnet and its post-glacial emergence denote a clear shift in the climate during the Holocene. The core record contains a basal marine unit which transitions to a distinct phase of the Ringgåsvatnet basin becoming isolated rather abruptly over a short period. This then gives way to a lacustrine environment dominated by minerogenic input primarily of a glaciogenic origin with several phases / oscillations of glaciogenic sediment variability interpreted as glacial activity. There are multiple oxidized horizons throughout the lacustrine phase of the indicating periods of short but higher biogenic / organic productivity. There appears to be no distinct / extensive period of no glaciogenic input into Ringgåsvatnet during the Holocene, suggesting that Ahlmannfonna remained throughout and did not disappear, although it may have remained in a heavily reduced state during the Holocene Climatic Optimum / mid-Holocene.
Assessing the surface reactivity of volcanic ashes in view of their potential respiratory hazard: the Pomici di Avellino eruption (3.9 ka BP)
Authors: Fernandez Giada , Giaccio Biagio , Pacella Alessandro , Sottili Gianluca , Tomatis Maura , Turci Francesco
Published: March 2022

Volcanic ashes from the Pomici di Avellino (PdA) eruption, an Early Bronze Age (ca. 3.9 ka BP) Plinian event from Somma-Vesuvius, had a wide dispersal area including most of the Central-South regions of Italy. The finest fraction of volcanic ashes can impact the human respiratory apparatus and induce severe respiratory difficulties and pathologies. Particle size, shape and composition, as well as surface reactivity are the key properties that define health hazard of volcanic ashes. Recent studies evidenced that volcanic ashes could generate significant amounts of free radicals. The particle-derived free radicals can contribute, together with the reactive species (ROS) produced by the cells, to the onset of oxidative stress. To evaluate the potential health impact of volcanic ashes both in proximal and distal areas we examined some physical and chemical characteristics of PdA ashes that may play a role in the onset of adverse health effects. Specifically, the particle size distribution (PSD) and surface properties (the specific surface area (SSA), the mobilization of bio-accessible iron ions and the ability to generate hydroxyl radicals) of PdA ashes have been measured.    

PSD was obtained by automated image analysis coupled with electron microscopy. Bio-available iron was quantified using specific iron chelator and colorimetric reactions. The physisorption of N2 at 77 K (N2 BET method) was used to measure the specific surface area. Electron Paramagnetic Resonance (EPR) coupled with spin trapping technique was used to quantify the ·OH radical generation.  

The results show a high surface area value, the presence of an amount of removable iron, and a reactivity in the formation of hydroxyl radicals. Furthermore, the ·OH radical generation is continuous in time. In particular, PdA volcanic ashes reactivity is probably related to the presence of surface bio-accessible iron, which is able to generate free radicals. Thus, free radical generation could make Mt. Vesuvius ashes potentially toxic and threaten people’s health causing respiratory problems. Overall, the physico-chemical characteristics of ash particles from Somma-Vesuvius might pose a significant health hazard even in distal areas, where the transport and the inhalation of fine-grained ashes from explosive eruptions might cause respiratory diseases. In light of these new data, further investigation (e.g. crystalline silica amount) to assess Somma-Vesuvius ashes toxicity is required.
A Study on Heavy Rainfall and Flash Floods Using Different Climate Toolboxes
Authors: Khomenko Inna , Tootoonchi Roshanak
Published: March 2022

Under the climate change, extreme precipitation responsible for flash floods, which can cause significant economic losses and human casualties, become more frequent and severe. These escalations are expected to become higher due to global warming which leads to increased water vapor in the atmosphere and thus, intensified precipitation events. Recent reports show that most flood events in Italy constitute flash floods, therefore it is projected for the region of Italy to be increasingly affected by flood events caused by heavy precipitation.

In this study, trends in extreme precipitation for present day and future projections up to 2100 under the worst-case scenario of warming, namely the Representative Concentration Pathway (RCP) 8.5 scenario are investigated using Copernicus and KNMI Climate Explorer databases.

On the basis of extremely easy-to-use KNMI Climate Explorer database anomalies of RX1day (1981-2010 reference period) for historical period and up to 2100 are retrieved for 7 Italian cities highly affected by flash floods (Venice, Rome, Naples, Genoa, Cagliari, Catanzaro, Palermo).For the mentioned regions the strong positive trends are calculated and the highest positive anomalies up to 50-80 mm/day are observed in the half of the XXI century.

The Copernicus toolbox editor was used to retrieve the RX1day index and 95th percentile from present day simulation (2011–2020) and future projection (2021–2100) of global precipitation from a total of 18 bias adjusted Global Climate Models from CMIP5 and precipitation time series for 7 Italian cities were extracted in order to obtain the trends. RX1day index doesn’t show significant increasing trend. Moreover, for the 95th percentile negative trends are obtained for most of the Italian cities in question.

Since heavy rainfalls are usually caused by convective precipitation, near surface convective precipitation trends for the period of 1991 to 2020 are derived from ERA5 monthly averaged reanalysis for the Mediterranean region and Italy, for the months in which the flash floods are often observed. The most significant increases in convective precipitation are obtained in July for Northern Italy, and in September for Southern Italy, and in November for the west coast zone.

It can therefore be said that for the historical data the positive trends in precipitation are dominated. However, for different projections and climate models from different database different results, sometimes even opposite results, are obtained.
Assessment of global burned area satellite products in the African savannah
Authors: Arbelo Manuel , García-Lázaro Jose Rafael , Moreno-Ruiz Jose Andres
Published: March 2022

Africa is the continent with the highest annual burned area, with the African savanna being the most affected ecosystem. This paper presents an assessment of the spatio-temporal accuracy of three of the main global-scale burned area products derived from images from polar-orbiting satellite-borne sensors: 1) Fire_CCI 5. 1, of 250 m spatial resolution, developed by the European Space Agency (ESA) and led by the University of Alcalá de Henares; 2) MCD64A1 C6, of 500 m spatial resolution, developed by the University of Maryland; and 3) GABAM (Global Annual Burned Area Map), of 30 m spatial resolution, developed through the Google Earth Engine (GEE) platform by researchers from the Aerospace Information Research Institute of China. The first two products are based on daily images from the MODIS (Moderate-Resolution Imaging Spectroradiometer) sensor onboard NASA's Terra and Aqua satellites, and the third is based on Landsat images available on GEE. The almost total absence of reference burned area data from official sources has made it difficult to assess the spatio-temporal accuracy of these burned area products in Africa. However, the recent creation of the Burned Area Reference Database (BARD), which includes reference datasets from different international projects, opens the possibility for a more detailed assessment. The study focused on a region covering an area of approximately 29.5 million ha located in the southern hemisphere between 10oS and 15oS and bounded longitudinally by the 35oE and 40oE meridians. The results show that the Fire_CCI 5.1, MCD64A1 C6 and GABAM products present an annual distribution of burned area with an irregular pattern in the interval between 7 and 10 million ha per year (around 30% of the whole study area), but there is hardly any correlation between their time series, with correlation coefficients lower than 0.3 for the period 2000-2019. The spatio-temporal accuracy analysis was performed for 2005, 2010 and 2016, the only years for which BARD has reference perimeters. The results are highly variable, with values between 1 and 20 million ha per year depending on the product, the year and the reference set used, which does not allow definitive conclusions to be drawn on the accuracy of the burned area estimates. These results indicate that uncertainties persist both in the burned area estimates derived from remote sensing products in these regions and in the reference sets used for their evaluation, which require further research effort.
Performance comparison of induced seismicity forecasting models with existing datasets
Authors: Clasen Repolles Victor , Rinaldi Antonio Pio , Ciardo Federico , Passarelli Luigi
Published: March 2022

Within the workflow of Adaptive Traffic Light System, it is important to evaluate the performance of different induced seismicity forecasting models in order to properly weight the forecasts during seismic hazard calculation. In this respect, we propose a standardize test bench approach capable of comparing outputs’ models (in terms of seismicity rate) and their uncertainties in real time. We test this approach using different models that are trained using existing datasets from geothermal exploration campaigns. Notably, we use two statistical models that link injection volumetric rate to seismicity rate with the difference that a Bayesian approach (EM1_BH) additionally adds epistemic uncertainty to the aleatoric uncertainty introduced in a purely frequentist approach (EM1_MLE), one pressure-based seismicity model (HM0_CAPS) based on 1D analytical solution for linear pore-fluid diffusion and finally one hybrid 1D model that includes a physic-based module for linear and non-linear pore-fluid diffusion linked to a stochastic model for seismicity generation using a seed approach (HM0_SEED and HM1_SEED). By using these different models and their uncertainties in our numerical investigations, we show the robustness of the proposed testbench approach.
A complex network perspective on catchment water quality dynamics: characteristics, pattern, and drivers
Authors: Wen Qingzhi , Jiang Jiping , Sivakumar Bellie
Published: March 2022

Understanding the connections in the dynamics of water quality at different locations in a catchment is important for catchment studies and watershed management. Complex network science provides effective ways to uncover connections and patterns in catchment water quality dynamics. This study  investigates the spatial connections in each of five water quality indexes (Chloride, Dissolved oxygen, pH, Total nitrogen, and Total organic carbon) and flow rate in the Chesapeake Bay basin, USA.High-resolution data (five minutes) from 120 water quality monitoring stations are analyzed. 1) The clustering coefficient (CC) and degree distribution methods are employed to examine the connections and identify the type of the water quality networks. The results indicate that the networks of water quality parameters are  scale-free. The power-law (γ) values of for the networks of Chl, DO, flow rate, pH, TN, TOC are 0.74, 0.67, 0.37, 2.0, 0.57 and 1.2, respectively. 2) Monte Carlo simulation of degree distributions and clustering coefficients (CC) shown that all water quality parameters present a decrease in the CC along with the turn down of the threshold of correlation coefficient (R), but the R threshold for DO and flow rate was 0.9. Other water quality parameters showed a sharp decline in the range of correlation coefficient (R) of 0.3-0.6, show a gentle decrease, and then decrease sharply, with an inverse s-curve. 3) All the WQ parameters show stable patterns of CC versus R, for different sizes of networks, arrived by randomly reducing the number of nodes (i.e. stations) of the networks. This seems to indicate that the pattern is an internal systemically feature of the networks, regardless of the node selected for analysis. The variations of CC values for the different stations in the networks  with different R values also help identify the “heat area” of the whole catchment, which  has some nodes with stable large CC. For the different water quality parameters, the heat area is basically the same, except for pH and TN for which the area is much smaller. The present findings on the characteristics, patterns, and drivers of water quality dynamics in catchments have important implications for water quality studies, especially in large networks of monitoring stations.
Groundwater discharge as a driver of methane emissions from Arctic lakes
Authors: Olid Carolina , Rodellas Valentí , Rocher-Ros Gerard , Garcia-Orellana Jordi , Diego-Feliu Marc , Alorda-Kleinglass Aaron , Bastviken David , Karlsson Jan
Published: March 2022

Methane (CH4) emissions from Arctic lakes are significant and highly sensitive to global warming. Groundwater inputs to lakes could be substantial and constitute a link between CH4 from melting permafrost to emissions via lakes. Yet, groundwater CH4 inputs and associated drivers are hitherto poorly understood. In this study, we disclose temporal and spatial patterns of groundwater CH4 inputs to Arctic lakes in the discontinuous permafrost zone in northern Sweden. Results show that groundwater discharge is a major source of CH4 to the lakes. Spatial patterns across lakes suggest that groundwater inflow rates are primarily related to lake morphology and land cover. Groundwater CH4 inputs and atmospheric CH4 emissions from lakes were higher in summer than in autumn, reflecting changes in hydrological and biological drivers. This study reveals the large role and the drivers of groundwater discharge in lake CH4 cycling, which may be further exacerbated with the ongoing climate change, as rising temperatures, increasing precipitation, and permafrost thawing are likely to increase groundwater CH4 inputs to lakes.
Prediction of the North Atlantic Oscillation index for the winter months December-January-February via nonlinear methods
Authors: Hauke Clara , Ahrens Bodo , Dalelane Clementine
Published: March 2022

Recently, an increase in forecast skill of the seasonal climate forecast for winter in Europe has been achieved through an ensemble subsampling approach by way of predicting the mean winter North Atlantic Oscillation (NAO) index through linear regression (based on the autumn state of the four predictors sea surface temperature, Arctic sea ice volume, Eurasian snow depth and stratospheric temperature) and the sampling of the ensemble members which are able to reproduce this NAO state. This thesis shows that the statistical prediction of the NAO index can be further improved via nonlinear methods using the same predictor variables as in the linear approach. This likely also leads to an increase in seasonal climate forecast skill. The data used for the calculations stems from the global reanalysis by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5. The available time span for use in this thesis covered only 40 years from 1980 till 2020, hence it was important to use a method that still yields statistically significant and meaningful results under those circumstances. The nonlinear method chosen was k-nearest neighbor, which is a simple, yet powerful algorithm when there is not a lot of data available. Compared to other methods like neural networks it is easy to interpret. The resulting method has been developed and tested in a double cross-validation setting. While sea ice in the Barents-Kara sea in September-October shows the most predictive capability for the NAO index in the subsequent winter as a single predictor, the highest forecast skill is achieved through a combination of different predictor variables.
Multiple reservoirs impact on flood frequency curves: a new global and physically-based index
Authors: Cipollini Stefano , Fiori Aldo , Volpi Elena
Published: March 2022

The influence of the human activity (e.g. land use changes, alterations of the river system, hydraulic structures realization) on the flood frequency curves, represents a notable information to understand hydrologic changes identifying some of its drivers. In this work we provide a simple yet physically-based global index to assess the effect of multiple reservoirs, located in series along the main channel, on peak flood quantile at the catchment scale. The index formulation is based on an Instantaneous Unit Hydrograph (IUH) method, and it takes into account the main parameters of the system, such as the relative location and relative storage coefficient of the reservoirs, their number, and a climatic parameter. An analytical formulas of the index is provided, and it is independent of the return period. Numerical experiments and a comparison with the literature indices confirm the efficiency of the proposed index and allow to disentangle the role of the parameters on the flood peak reduction. Finally, we also present and discuss results of the index application for a real case study, that is the reservoirs system of the Tiber River (Central Italy).    
A complete rockfall inventory across twelve orders of magnitude.
Authors: Jacobs Benjamin , Huber Florian , Krautblatter Michael
Published: March 2022

Understanding the magnitude-frequency relationship of rock falls is one of the most important issues for both geomorphologists assessing sediment budgets as well as public stakeholders evaluating rock fall hazards. Multi-temporal Terrestrial Laser Scanning (TLS) surveys, or more general LiDAR, is often applied to produce rock fall inventories of event magnitudes and their frequency. However, LiDAR-based rock fall inventories systematically miss or underestimate both ends of the magnitude bandwidth.

Here we present the first attempt of a complete rock fall inventory including the full spectrum of magnitudes, ranging from fragmental rock falls (cm³) to Bergsturz-sized events (106 m³). We combine rock fall inventories derived from multi-temporal TLS campaigns over six years, rock fall collectors and the historic record in a previously intensely investigated study area (Reintal, German Alps). We investigate which factors – such as structural geology, systematic sampling limitations or different rock fall processes – can lead to possible misinterpretation of rock fall inventories regarding geomorphic systems.

The study shows that (i) LiDAR-based rock fall inventories do not cover the full spectrum of rock fall magnitudes due to their limitations in temporal and spatial resolution, (ii) structural geological features control the magnitude/frequency relation beyond the roll-over of these inventories and (iii) taking fragmentation as well as a clear distinction between rock fall processes into account when analysing rock fall inventories is crucial.
Holocene climate in Northern Urals (Komi Republic, Russia): a multi-proxy approach based on pollen and brGDGTs
Authors: Barhoumi Chéïma , Joannin Sébastien , Ali Adam A. , Ménot Guillemette , Golubeva Yulia , Subetto Dmitri , Kryshen Alexander , Drobyshev Igor , Peyron Odile
Published: March 2022

The functioning of the boreal forests of Russia is still little documented and little understood. It is governed by complex mechanisms that link climate, vegetation and disturbances, such as fires or human impact.In this presentation, we aim to provide robust reconstructions of the Holocene climate (temperatures and precipitation) of the Vychegda River basin in the Republic of Komi region, based on two different proxies: pollen assemblages and GDGTs (Glycerol Dialkyl Glycerol Tetraethers). This first study of GDGTs in this area corresponds to a preliminary step for the calibration of this proxy in peats. Higher temperatures and precipitation are recorded between 7000 and 4000 cal. yr BP (mean annual temperatures around 3°C and precipitation between 600 and 700 mm per year). This climatic optimum is in agreement with previous pollen-based climate reconstructions, and climate patterns in the neighboring Russian and Fennoscandia (Komi Republic - previous study-, Arctic Russia, Siberia and Northern Europe, Andreev and Klimanov, 2000; Golubeva, 2008; Seppä et al., 2009a). These results, in conjunction with the reconstruction of fire activity and vegetation dynamics in this region, led to a better understanding of the crossed influences of these factors. In particular, vegetation is mainly controlled by climate during the first part of the Holocene, while a threshold is reached on in fire frequency after 3500 cal. yr BP and this parameter has a greater impact on vegetation than climate. Over the past 600 years, the intensification of human activities led to overexploitation of the forest and an increase in its fire activity.
Extreme weather effects on land ownership in Uganda
Authors: Murken Lisa , Krähnert Kati , Gornott Christoph
Published: March 2022

This study examines the effects of (extreme) weather conditions on the willingness to purchase and on actual purchase of land ownership rights in Uganda. We use three waves of the Uganda National Panel Survey in combination with high-resolution gridded precipitation and temperature data, with which we calculate a drought index as weather shock measure, the Standardized Precipitation Evapotranspiration Index (SPEI). Using a household fixed-effects approach, we exploit spatial and temporal variation in SPEI values to causally identify the effect of extreme weather events on the willingness to acquire ownership to land and actual changes in the land ownership structure of households over time. Results show that dry conditions dampen households’ intentions to purchase land ownership rights, while wet conditions positively affect such intentions. In addition, wet conditions substantially increase the price households are willing to pay to purchase land ownership. The effects are robust to different specifications, persistent over time and translate into actual changes of land ownership ratios with a two-year time lag. The findings suggest that more favourable climatic conditions for agriculture increase interest in land ownership, which has implications for land formalisation programmes and climate change adaptation efforts.
Experimental Validation of Numerical Simulation of Tidal Power Plants (Deep Green) using ADCP Measurements
Authors: Saravana Prabahar Nimal Sudhan , Fredriksson Sam , Broström Göran , Bergqvist Björn
Published: March 2022

Tidal turbines harnessing power from tidal currents, have the prospective to become an important source for renewable energy production. The tidal power plant studied here, the Deep Green, rather than being fixed like conventional horizontally mounted axial tidal turbines, uses a ‘flying’ kite with a turbine attached to it. The kite, which is tethered to the bottom, converses in a lemniscate trajectory (Ꝏ) perpendicular to the direction of the tidal current. In the trajectory, the apparent flow velocity experienced by the turbine is several times the tidal flow, thereby allowing utilization of sites with lower tidal current velocities than most traditional tidal power plants. To study the operation of single power plants and for designing efficient arrays of tidal power plants Computational Fluid Dynamics (CFD) are used.

Through previous studies, the Deep Green is modelled using Large Eddy Simulations (LES) and the Actuator Line Model (ALM). While using ALM, the Deep Green wing and its turbine are represented as a momentum source that moves in a prescribed trajectory (lemniscate). Using the numerical simulations, the impact of the Deep Green on the tidal flow is studied by analysing the changed velocity field and turbulence characteristics downstream of the power plant. Before conducting large-scale numerical studies on the design of arrays, the numerical model needs to be validated against observations.

The measurements used for this study were performed by Minesto AB in the site Holyhead deep using a vessel mounted ADCP (Acoustic Doppler Current Profiler) downstream of the kite. A domain and boundary conditions similar to the measurements are set up in the numerical simulation. The velocity downstream of the power plant is compared with the measured velocity data, and the preliminary study shows good agreement between ADCP observations and output from the CFD model. The results of the validation will be helpful to strengthen the methods used in numerical modelling in order to conduct sound tidal power array analysis.
Sources and transformation of dissolved inorganic carbon in a Himalayan river system
Authors: Sarkar Siddhartha , Shah Rayees Ahmed , Kumar Sanjeev
Published: March 2022

Inland waters play a vital role in the global carbon cycling. Mountainous rivers act as active pipelines for the transportation of sediments and elements from the mountains through the plains to be ultimately processed and buried along the coasts. During this transit, various in situ biogeochemical processes govern the alterations of the suspended and dissolved matter (and associated organic and inorganic components) and in the process exchange major GHGs (CH4, CO2 and N2O) with the atmosphere. Due to changing climate and the associated shifts in the flow regime of the world rivers, it is essential to revisit the mechanisms by which carbon is being transported along the river continuum and further constrain the effects of regional climate and lithology on the rates of transport and processing. The rivers originating from the Tibetan plateau and the Himalayan region play a dominant role in continental weathering, and represent some of the highest rates among the large river systems across the globe.

            In the present study, an attempt has been made to estimate the concentrations and fluxes of dissolved inorganic carbon (DIC) in the Jhelum River (a tributary of the Indus River) along with its major tributaries (Sindh, Liddar, Vishav, and Rambiara) situated in the Kashmir valley of the western Himalaya. The Jhelum River drains a distinct terrain of recent alluvium to a thick loess deposit, which is assumed to have a significant contribution to the inorganic carbon loading into the river. Furthermore, the flow velocity of the river and turbidity varies along its continuum resulting in a strong coupling of respiration and primary production. We used the miller-tans plots (a graphical mixing model) to identify the sources of inorganic carbon in different reaches along the continuum. Preliminary results from ~ 50 sites and three major seasons in the valley indicate DIC source with isotopically enriched signature (d13CDIC ~ – 2.1 to –3.7 ‰) in the Sind and Lidder catchments whereas a depleted source in the mainstem of the river (d13CDIC ~ –7.1 ‰).
Turbulent transfer and concentration statistics in a street canyon with tree planting
Authors: Fellini Sofia , Del Ponte Annika Vittoria , Barulli Marilina , Ridolfi Luca , Soulhac Lionel , Marro Massimo , Salizzoni Pietro
Published: March 2022

The exacerbation of the urban heat island due to global warming poses a serious risk to the health of citizens. Furthermore, the alteration of the urban microclimate affects air quality with an expected increase in the concentrations of harmful pollutants. Greening cities is an effective tool to mitigate these effects. However, the effect of tree planting in urban street canyons is still a debated topic. Despite their positive effect on temperature and their filtering action, trees can hinder air circulation thus limiting pollutant removal processes. In this context, it is essential to understand and model the effect of trees on the ventilation of street pollutants, heat and moisture . To this end, we present in this work the results of an experimental campaign conducted in a wind tunnel. An urban geometry with a street canyon perpendicular to the wind direction was reproduced. A linear source of passive scalar simulated the emission of pollutants from vehicular traffic. Reduced scale trees have been conceived to mimic a realistic aerodynamic behaviour. We investigated four different configurations of vegetation density: a street with no trees, two trees in the middle of the street, two rows of scattered trees and two dense rows of trees. Concentration and velocity measurements were performed in order to characterize the transfer processes of pollutants inside the street and to estimate a bulk vertical exchange rate. Results show that the presence of trees alters the concentration field in the street with a progressive shift from a nearly two-dimensional to a three-dimensional field. Despite the significant spatial variation in concentration, the presence of trees does not alter the overall efficiency of the ventilation as the vertical bulk exchange velocity remains almost constant in the different configurations. The statistical analysis of the turbulent concentration signal gives other insights in the transfer processes. The turbulent signal measured in different positions of the cavity and for different tree density follows a Gamma distribution with constant fluctuation intensity suggesting an almost universal behaviour within the canyon and providing a powerful modelling tool. Finally, combined measurements of concentration and velocity allows to measure the turbulent mass fluxes at the roof height and investigate their spectrum therefore enlightening the effect of trees on typical scales of motion.
Comprehensive risk assessment of July 2021 European flooding including associated uncertainties
Authors: Bhola Punit , Doucet Margot , Alarcon Stefanie , Reinhardt Bernhard
Published: March 2022

In July 2021, low-pressure system “Bernd” parked itself over central Europe in July 2021 and caused significant flooding in western Germany and neighbouring countries. The devastating flooding led to more than 180 causalities in Germany and caused catastrophic losses by disrupting infrastructure.

As the flood event unfolded, we at Verisk Extreme Event Solutions, re-modelled the event using state-of-the-art flood models by simulating river flows in our hydrological and flood inundation patterns in hydraulic model from observed precipitation fields derived from NASA’s Global Precipitation Measurement (GPM). Using the remodelled hazard and our Industry Exposure Database (IED), we provided a range of insured loss estimates for the insurance and reinsurance market. We will discuss the event with respect to hazard and uncertainties associated with risks, such as demand surge, cost inflation and infrastructure damage.
Revealing underwater plastics: Detection of suspended macroplastics using acoustic backscatter
Authors: Boon Anouk , Buschman Frans
Published: March 2022

Plastic pollution has become a threat to both nature and humans. A substantial amount of plastic is transported in rivers towards the sea. Insight in the sources and transport in rivers, and how this is changing with conditions like discharge, is needed to plan effective mitigation strategies. Current measurement techniques mostly target floating items, recent studies however suggest that suspended plastics form a significant part of the total riverine plastic transport. Despite being successful, recently applied sampling techniques using several nets in the vertical are too invasive, expensive and labour intensive to apply on large spatial and temporal scale. A non-invasive and continuous measurement technique of suspended plastics, applicable on a large scale, is needed.

 

Sonar has shown potential for plastic detection. During measurements, a high-frequency acoustic signal is transmitted. This signal is scattered by water and suspended particles. Using an Acoustic Doppler Current Profiler (ADCP), the chosen sonar device, flow velocity can be obtained using the frequency shift of the signal. Aside from the frequency shift, also the strength of the returned acoustic signal can be measured. This backscatter strength depends on the size, form and material of the sampled object. It is nowadays used to estimate suspended sediment concentrations, but also relatively large objects like fish, organic matter and macro-plastics can be recognised by high backscatter intensity. As ADCPs have been broadly used for decades, current and historical data from a large network of measuring devices are available for analysis of plastic transport and its fluctuations. We propose steps for a method to quantify the macroplastic concentration from ADCP data.

 

During the study, a RDI StreamPro ADCP is horizontally mounted in a basin. Macroplastics differing in shape, size and polymer type are sampled 5 times within a period of 10 seconds, on three different distances (around 1, 3 and 5 meter) from the transducer. Almost all plastic items show a significantly higher backscatter intensity than the background signal, on all measurement distances. In contrast to net-based measurements, rotation is found to be an important aspect in the identification of items during ADCP measurements. To further develop the detection method, analysis of ADCP field data containing the usual background noise, combined with net measurements for validation, is needed. Expectation is that net measurements, used to make an estimate of the fraction organic material and plastic, are only needed periodically to make a good continuous estimate of macroplastic transport using ADCP data.
Value of ground information in regions with limited landslide inventory for trigger threshold development — Application in Nilgiris, Tamil Nadu State, India
Authors: Nedumpallile Vasu Nikhil , Banks Vanessa , Mathiyalaghan Rajkumar , Kumar Sumit , Karmarkar Rabisankar , Singh Gargi , Kumar Mishra Akshaya , Rossi Mauro , Arnhardt Christian , Dashwood Claire , Ghosh Saibal , Bee Emma
Published: March 2022

Forecasting rainfall-induced landslides, whilst challenging, is increasingly important due to the impact these hazards can have on society. The difficulty in forecasting arises from the inherent variability of geo-environmental factors and the scale at which underlying processes operate. The availability of data required to develop and validate thresholds for operational purposes is often limited. In regions where data (e.g. meteorological, or geotechnical) is sparse or incomprehensive, it is important to have a framework to systematically fuse the incomplete datasets to aid the development of a threshold model or to supplement an existing preliminary trigger threshold model.

For this study, a bespoke conceptual hydrological model called the ‘BGS water balance model’ is used in Nilgiris (Tamil Nadu state, India) to integrate the ground and meteorological information for informed decision making on the landscape saturation condition. This simple conceptual model with applicability over a large area provides an approximation of the degree of saturation value that can be used to map the potential antecedent wetness pathway leading to the initiation of landslides.

In this session, the BGS water balance model features along with the study area geological characteristics, landslide controls, input datasets and sensitivity analysis will be discussed. Further, we will show the results of the back-analysed landslides and explore the value of this approach in the context of landslide forecasting.