bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing a water distribution network design on water age. Comparison between implicit and explicit approaches
Authors: Mitrovic Djordje , van Laarhoven Karel , Hillebrand Bram
Published: February 2023

A common practice in Dutch and Flemish water utilities is to make masterplans for their network revisions and revise them on a regular basis, approximately every five years. The masterplans represent the ideal redesigns of their networks in terms of company specific objectives and constraints related to existing network infrastructure. The masterplans are used as a guideline when rehabilitating the networks. Among others, one of the objectives is to minimize the residence time, i.e., water age. However, the recurring assessment of water age with traditional methods, within an optimization procedure could take years for convergence for a large network of several thousand nodes. Consequently, the modellers often try to improve the residence time implicitly by minimizing network’s volume via layout optimization and diameter minimization, thus leading to increased velocities in pipes. Recently a graph theory model for estimating water age with satisfying accuracy has been proposed in the literature. The proposed model is estimated to be more than a hundred thousand times faster than the assessment of water age using Epanet, thus enabling the assessment of water age within optimization procedures. This research proposes a novel optimization methodology for simultaneous layout and pipe sizing optimization, employing the proposed graph-based model to explicitly assess the water age objective. To secure the reliability of the optimal solutions the methodology introduces a penalty to limit the size of the branched sections by setting a maximum to the number of customers connected to branched sections. The proposed methodology is applied to a real-world Dutch network. The aim of the research is to compare the optimal designs obtained using implicit (minimizing network’s volume) and new explicit (minimizing maximum water age) approaches.
Long-term Ozone Trends in Different Urban Developments
Authors: Nelson Beth , Lee James , Lu Keding
Published: February 2023

High emissions of NOx and anthropogenic VOCs from urban areas are a major source of tropospheric ozone production. Tropospheric ozone is a secondary air pollutant that is harmful to human health as well as crop and ecosystem productivity, and an important greenhouse gas. It is formed from the chemical processing of NOx and VOCs in a non-linear cycle, making ozone reduction strategies challenging. Urban centres across the world are developing at different rates and emitting different combinations and concentrations of chemical species, resulting in location specific drivers of urban ozone concentrations. Alongside this, different countries and cities have implemented a wide range of location specific air quality and climate change measures to reduce air pollution and greenhouse gas emissions. The diversity of these policies over the past few decades has further led to different outcomes for secondary pollutant formation across the globe.As part of TOAR-II, the Urban Ozone Working Group explores the long-term trends in urban ozone concentrations over the past 20 years on a global scale. Using ground based data from global Air Quality networks, trends in ozone concentrations of > 12 cities across different continents are presented, and temporal changes in ozone trends are identified. This study utilises the TOAR database, accessed via the TOAR Data Portal, which collects hourly data of long-term surface air quality measurements from over 10,000 stations globally. Where sufficient long-term NOx and VOC data are available, ozone concentration trends are compared to trends in its precursor species. Trends in ozone concentrations are then related to the state of development of the city using factors such as GDP and the UN City Development Index, and an assessment of how cities in different phases of development are contributing to tropospheric ozone across the world is discussed. Trends in ozone will also be compared to country and city specific changes in air quality and net zero policy interventions.
Advantages and issues of applying Machine learning based denosing on inversions of the DPRK nuclear tests
Authors: Steinberg Andreas , Gaebler Peter , Pilger Christoph
Published: February 2023

We apply a current state-of-the-art machine learning based denoising algorithm on the seismological and hydroacoustic waveform records of the selected DPRK nuclear tests. We use the DeepDenoiser algorithm to reduce the noise present in the waveform records of the larger DPRK nuclear tests. The denosing of waveform records using machine learning has obvious advantages on the picking of phases and signal detection but the question is if the currently available techniques can be used beyond that. We investigate the impact the denoising has on the source mechanism inferences by comparing the seismic moment tensor inversion results of original and denoised data. Because of the good signal to noise ratio and as the source type is well known we can in this cases establish if the so denoised waveforms can be used for further source analysis. We find that care needs to be taken using the modified waveform data but also find promising results hinting at possible further use the technique in the future for standard analyses. We further investigate if the application of the chosen denoising algorithm allows for the better resolution of the seismic moment tensor of the smaller DPRK nuclear tests.
A traffic prediction framework under extreme weather combined disaster knowledge and deep learning
Authors: Tang Jiting , Yang Saini
Published: February 2023

Studying the spatiotemporal patterns of urban road traffic under extreme weather is a key step to building a climate-resilient city. Although existing researches model and simulate traffic states from different perspectives, the traffic forecasting of the urban road networks under extreme weather is seldom addressed. In this paper, a novel Knowledge-driven Attribute-augmented Attention Spatiotemporal Graph Convolutional Network framework is proposed to predict urban road traffic under wind and rain especially in tropical cyclone disasters. Considering the disaster conditions, we model the external dynamic hazard attributes and static environment attributes, and designed an attribute-augmented unit to encode and integrate these factors into the deep learning model. The model is combined with the graph convolutional network (GCN), the gated recurrent unit (GRU), and the attention mechanism. Experiments demonstrate that the predictability of traffic speed can be greatly increased by supplementing the disaster-related factors, the prediction accuracy reaches 0.79. The proposed approach outperforms baselines by 12.16%-31.67% on real-world Shenzhen’s traffic datasets. The model also performs robustly on different road vulnerabilities and hazard intensities. The model errors are mainly occurred in the early peak with extreme wind and rain and the coastal area in the southeast of Shenzhen because of the greater uncertainty. The framework and findings provide a valuable reference for the decision-making of traffic management and control prior to a disaster to alleviate traffic congestion and reduce the negative impact of disasters.
Attributing human health impacts to climate change
Authors: Lo Eunice , Mitchell Dann , Vicedo-Cabrera Ana M. , Perkins-Kirkpatrick Sarah
Published: February 2023

Attributing extreme weather events to human-induced climate change has been a topic of interest for decades. In recent years where unprecedented and high-impact events have occurred all over the world, it is all the more important to not just understand how human influence on the climate system has changed the probability or magnitude of the weather events, but also how it has changed the impacts of these events on human life. In this talk, I will review the climate-epidemiology literature on attributing adverse human health impacts to climate change, with a focus on heat-related mortality, as it is well-established that high temperatures are associated with increased mortality risks. I will include notable heat-mortality events in history such as the 1995 Chicago heatwave, 2006 UK summer, and the 2003 European heatwave. I will also discuss the use of large ensembles of future climate projections to ‘attribute’ heat-related mortality that could occur if global mean warming reached certain levels, keeping other factors unchanged. Finally, I will discuss the use of climate-health attribution information in engaging with the media and communicating with policymakers.
Model development for climate optimized aircraft design
Authors: Deck Kathrin , Yin Feijia , Grewe Volker , Radhakrishnan Kaushik , Lührs Benjamin , Linke Florian , Niklaß Malte
Published: February 2023

Aviation as an important transport sector contributes to anthropogenic climate change via CO2 effects and non-CO2 effects. Non-CO2 effects include e.g., effects from NOx emissions, H2O emissions and the formation of contrails. Mitigation options include optimization of aircraft operations, e.g., re-routing, and optimization of the aircraft design, while this work focuses on the second option via providing a model for aircraft design optimization. Furthermore, we take CO2 and non-CO2 effects into account.Previous research (e.g. Grewe et al., 2014) investigated the optimization of aircraft operations with the use of climate cost functions. With these functions, the climate impact per unit non-CO2 emission/flown distance is described depending on the type of emission, the emission location and corresponding time. An equivalent model for aircraft design purposes is currently missing. It has to cover a suitable route network with emission locations and altitudes to be able to optimize regarding the climate impact of CO2 and non-CO2 effects. Within the EU Clean Sky 2 project GLOWOPT, this concept is applied for aircraft design features, presented as climate functions for aircraft design (CFAD).Here, we present the development routine for the CFAD. As input, emission inventories based on a long-range aircraft (A350 as baseline in this study) are used. The emission inventories cover a set of climb angles and final cruise altitudes to combine both the aircraft design parameter and geographical information of emissions. The climate impact is calculated with the climate-chemistry response model AirClim (Grewe and Stenke, 2008; Dahlmann et al., 2016) to create a response surface. The climate metric Average Temperature Response with a time horizon of 100 years is used as a measure for the climate impact. The created response surface, the CFAD, can be integrated in the aircraft design process to optimize the aircraft design. The CFAD are to be verified with additional emission inventories to evaluate the accuracy.Grewe, V., Frömming, C., Matthes, S., Brinkop, S., Ponater, M., Dietmüller, S., Jöckel, P., Garny, H., Tsati, E., Dahlmann, K., Søvde, O. A., Fuglestvedt, J., Berntsen, T. K., Shine, K. P., Irvine, E. A., Champougny, T., and Hullah, P.: Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0), Geoscientific Model Development, 7, 175–201, https://doi.org/10.5194/gmd-7-175-2014, 2014.Grewe, V. and Stenke, A.: AirClim: an efficient tool for climate evaluation of aircraft technology, Atmospheric Chemistry and Physics, 8, 4621–4639, https://doi.org/10.5194/acp-8-4621-2008, 2008.Dahlmann, K., Grewe, V., Frömming, C., and Burkhardt, U.: Can we reliably assess climate mitigation options for air traffic scenarios despite large uncertainties in atmospheric processes?, Transportation Research Part D, 46, 40-55, https://doi.org/10.1016/j.trd.2016.03.006, 2016.
Innovative real-time iFLUX sensors reveal rapidly changing groundwater – surface water dynamics in peatlands of the Upper Biebrza Basin (Poland)
Authors: Van Putte Niels , Joris Marjan , De Kleyn Timothy , Cools Joris , Grodzka-Łukaszewska Maria , Verreydt Goedele
Published: February 2023

Interactions between groundwater and surface water are of crucial importance for the ecological functioning of wetland systems since they control groundwater levels in the wetlands, water temperature in the river and exchange of solutes. Anthropogenic impacts such as the construction of drainage systems in the vicinity of wetlands can completely change the magnitude and direction of groundwater – surface water exchange, often negatively affecting the ecological functioning of the wetlands.Management practices aiming to conserve the ecological status strongly depend on estimates of groundwater – surface water exchange. However, currently established methods to estimate groundwater flow (i) rely on point measurements, missing the effect of crucial short term events (e.g. precipitation), (ii) rely on differences in physical characteristics between the groundwater and surface water (e.g. temperature and/or conductivity), which are not always present or (iii) require extensive modelling.In this presentation, we present a newly developed sensor, the iFLUX sensor. Two versions of this sensor exist, for measuring horizontal and vertical flow, respectively. The sensor probe for horizontal flow consists of two bidirectional flow sensors that are superimposed and is installed in a monitoring well with dedicated pre-pack filter, allowing for measurement of both groundwater flux magnitude and direction. The probe measuring vertical flow can be installed directly in the soil, in the riverbed or in a monitoring well. With a broad measuring range of groundwater fluxes from 0.5 cm/day to 2000 cm/day and measurements every second, this setup can map rapidly changing flow conditions.Here, we show a selection of results from a case study in North-East Poland. In the Biebrza National Park, high groundwater levels resulting from subsurface runoff from the uplands protect the highly valuable peatland system. During most of the year, the river is gaining, with a sharp increase in upward groundwater flux in the hyporheic zone during summer months. In the valley surrounding the river, groundwater flows towards the river, as expected. However, the data show a remarkable diurnal pattern of both flow magnitude and direction, with the highest flow velocity occurring in the late afternoon, suggesting a relation with evapotranspiration. After large precipitation events, the flow direction reverses, suggesting infiltration of surface water into the aquifer.Since these events occur on a small temporal scale, they were never measured before in the area with traditional methods. As such, our sensors provide new insights in groundwater – surface water interactions and will become an invaluable tool in ecohydrological studies worldwide, ultimately leading to more integrated management strategies to protect our remaining wetlands.
Development of a non-invasive modular electromagnetic induction (EMI) system with spatial high resolution for agricultural applications
Authors: Dick Markus , Zimmermann Egon , Huisman Johan Alexander , Mester Achim , Tchantcho Amin Tazifor Martial , Wüstner Peter , Ramm Michael , van Waasen Stefan
Published: February 2023

The acquisition of high-resolution soil information is essential for more environmentally friendly and efficient management of agricultural areas in the context of precision farming. The electrical conductivity (EC) of the soil can be measured quickly and without direct contact using electromagnetic induction (EMI) systems. The EC can be related to soil properties such as soil water content, pore water electrical conductivity, nutrition, clay content and salinity. EMI devices provide an apparent conductivity value that averages electrical conductivity variations with depth. To reconstruct the depth-dependent conductivity from measured data, EMI devices with different coil separations between transmitter and receiver or coil orientations are required. For the measurement with different coil separations, measurements with several commercial devices are commonly combined. However, mutual interference between devices is problematic here, so that measurements with the individual devices must be carried out either one after the other or with sufficient spatial separation, which complicates data acquisition substantially. To simplify EMI data acquisition and to improve depth resolution, an EMI device is required that provides simultaneous measurements with a larger number of freely selectable coil distances. To achieve this, a modular scalable multi-coil system (SELMA) with one transmitter and 12 receiver coils was developed. In the first test configuration, the receiver coils are arranged in a coplanar configuration and equally distributed from 0.3 to 3.6 m in a straight line. The system currently operates at a transmission frequency of 20 kHz and is designed for a measurement range from 2 mS/m to 100 mS/m. The noise of the measured apparent electrical conductivity is below 1 mS/m at a measurement rate of 10 Hz. To achieve modularity, decentralised System-on-Chip modules are used for the data acquisition, which are connected to the control unit (PC) via Ethernet. In addition to the apparent conductivity values, temperatures, pressure, and acceleration are recorded. The reliability of the EMI measurements was checked by repeatedly measuring a transect using a custom-made sled.
Additional horizontal displacement across the transportation infrastructures induced by land subsidence revealed by SAR interferometry
Authors: Hu Jyr-Ching , Chiu Chun-Ying
Published: February 2023

Groundwater has been over-pumped and excessive use during the past decades due to the lack of sufficient surface water caused by rapid economic developments and growing population, especially in the central part of Taiwan. The alluvial fan of the Cho-Shui River in Western Taiwan suffers the most serious land subsidence hazard with a maximum subsidence rate in excess of 3 cm/yr which is affecting the transportation infrastructures across the land subsidence area. The long-term spatial land subsidence variation from 1995 to 2020 reveals that the center of land subsidence area changed significantly with time from the coastal area to inland area. The decreasing of land subsidence could obviously be detected by the velocity profile along the Taiwan High Speed Rail during different time periods from geodetic measurements. Not only the vertical displacement increases the risk on potential damage on transportation infrastructures across the land subsidence bowls but also the induced additional horizontal displacement owing to the vertical subsidence could result in the unexpected risk for the infrastructure. In this study, we used the technique of multi-temporal InSAR to calculate the vertical deformation and the east-west deformation combined with the velocity field of the ascending and descending orbits. Three large-scale subsidence bowls are detected and accompanied by maximum additional horizontal deformation of ~8 mm/yr than that predicted by tectonic movement outside of the subsidence bowl. This additional E-W displacement is the major risk concerns of the N-S trending Taiwan High Speed Rail.
Post-earthquake geoenvironmental changes in landslide-affected watersheds in Atsuma, Hokkaido (Japan)
Authors: Hayakawa Yuichi S. , Lo Tennyson , Zulhilmi Azim , Yu Xinyue , Wang Xiaoxiao
Published: February 2023

Following drastic changes in geoenvironmental components by coseismic landslides in mountainous watersheds, more gradual changes can be observed in the elements, including bare-land surface conditions, sediment connectivity, and vegetation recovery on sloping terrains. Such geoenvironmental changes may continue for years to decades, with complex interrelationships among various geomorphological and ecological factors. Their assessments are also crucial for local to regional environmental management. After the occurrence of numerous coseismic landslides triggered by the 2018 Hokkaido Eastern Iburi Earthquake in northern Japan, geomorphological and geoecological changes were explored using optical and laser sensors on uncrewed aerial systems. Morphological characteristics of the landslide-affected slopes in the watersheds were assessed with structure-from-motion multi-view stereo photogrammetry and light detection and ranging topographic datasets, while vegetation recovery on the slopes was examined with visible-light and near-infrared images. Although spatial relationships among morphological developments, sediment mobility, and vegetation recovery were not clearly observed, their general temporal trends may be correspondent. Dominant processes affecting the morphological developments are supposed to be frost heave in the cold climate and non-frequent high-intensity rainfalls, and these can be conditioning vegetation growth. Such local changes will be further examined on a wider, regional scale. 
Computationally inexpensive robust design of run-of-river hydropower plants
Authors: Yildiz Veysel , Brown Solomon , Rougé Charles
Published: February 2023

Run of River hydropower plants (RoR) are characterised by a negligible storage capacity and by generation almost completely dependent on the quantity and variability of river flows. RoRs designed today will be deployed in a world characterised by a changing climate and uncertain economic conditions (electricity prices, interest rates, cost overruns). Investments need to be financially robust to these perturbations, but both design optimisation and robustness analyses traditionally incur large computing times and resources to explore a large range of potential futures. This hinders widespread uptake of these methods, and the emissions associated with large computing costs mitigate the environmental benefits of an otherwise renewable energy source.Here we demonstrate a computationally inexpensive method for the optimisation (including multi-objective optimisation) and robustness analysis of run-of-river plants. It is based on the remark that the daily flow duration curve (FDC) can be approximated by a limited number of points, supporting a much faster evaluation of performance for a given FDC. Our method carries out the following steps:  (1) we approximate the daily FDC with N regularly spaced points, (2) we couple a multi-objective evolutionary algorithm with our state-of-the-art toolbox to optimise technical and financial indicators of performance, (energy production and economic profit) and generate design alternatives, (3) we sample uncertain factors to generate an ensemble of plausible future states of the World (SOWs), (4) we approximate the future FDC of each ensemble member with N points, (5) we quantify the robustness of selected alternative designs across the entire ensemble of SOWs.We test our method with N=25, 50, 100, 250 and 500 points. We compare these results with traditional analysis (TA) done without approximating the FDC, and evaluated the trade-off between quality of results and required computational resources. Computational time required for performing optimisation with historical record (27 years of daily discharge) using 100,000 function evaluations is reduced by 98% and 92% for N = 25 and 500 respectively. The resulting Pareto optimal set has a good diversity and hypervolume performance for N ≥ 50 points is close (> 95%) to that of the set found by using 1,000 years of synthetic data for the optimisation. Likewise, the time required for analysing robustness across S = 500 SOWs is 98% less than TA in which we use an HPC platform and take 1,000 (synthetic stream flow) years into account. The performance evaluation of alternatives across the entire ensemble of SOWs is very similar to the robustness values based on TA. These preliminary results suggest that optimisation and robustness analysis can be performed with the proposed methodology for RoRs by using far less computational resources.
Paleoecology/paleoclimate of the Levant and its impact on the spread of modern humans from Africa to Europe
Authors: Litt Thomas
Published: February 2023

Which routes did Homo sapiens take when spreading from Africa to Eurasia? The climatic conditions changed and with them the living conditions. Over the past twelve years, a research team has deciphered the complex interplay of cultural innovations, mobility and environmental changes funded by the German Research Foundation (Collaborative Research Center 806 "Our Way to Europe"). Our working group in Bonn specifically investigated when and where migration corridors or barriers existed  from a paleoecological and paleoclimatological point of view. It turned out that the Levant, as the only permanent land bridge between Africa and Eurasia during the Quaternary, was the key region as a migration corridor for modern humans. Cores from the Dead Sea Deep Drilling Project (ICDP) were investigated, in which the environmental and climate history of the last 200 ka is excellently preserved and documented. In particular, pollen analysis allows changes in vegetation cover to be identified and environmental and climatic conditions to be reconstructed. These data illustrate that the Levant could only have served as a corridor when, under more favorable conditions, for example, neither deserts nor dense forests impeded the spread of modern humans.
Rapid source characterization of the Maule earthquake using Prompt Elasto-Gravity Signals
Authors: Arias Gabriela , Bletery Quentin , Licciardi Andrea , Juhel Kevin , Ampuero Jean-Paul , Rouet-Leduc Bertrand
Published: February 2023

The recently identified Prompt Elasto-Gravity Signals (PEGS), generated by large earthquakes, propagate at the speed of light and are sensitive to the earthquake magnitude and focal mechanism. These characteristics make PEGS potentially more accurate than P-wave based early warning algorithms (which produce saturated magnitude estimations) and faster than Global Navigation Satellite Systems (GNSS)-based systems. We use a deep learning model called PEGSNet, originally developed for application in Japan, to track the temporal evolution of the magnitude of the 2010 Mw 8.8 Maule earthquake. The model is a Convolutional Neural Network (CNN), trained on a database of synthetic PEGS -- simulated for an exhaustive set of possible earthquakes distributed along the Chilean subduction zone -- augmented with empirical noise. The approach is multi-station and leverages the information recorded on all the available stations to estimate as fast as possible the magnitude and location of an on-going earthquake. Our results indicate that PEGSNet could have estimated an  Mw > 8.7 earthquake after 100 seconds in the Maule case. Our synthetic tests using real data and noise recordings further support the instantaneous tracking of the source time function of the earthquake.
Infiltrating flood waves into aquifers: Column experiments on the suitability of filter materials
Authors: Augustin Lea , Baumann Thomas
Published: February 2023

With global warming, a rising amount of people will be affected by water scarcity and droughts. At the same time, precipitation intensities and thus flood risks are projected to increase. Since these extremes often occur in the same location, co-management strategies of floods and droughts may offer a promising solution. The project Smart-SWS, funded by the BMBF as part of the initiative WaX – Hydrological Extreme Events, links drought prevention and flood protection with a concept for infiltrating flood waves into riverine aquifers as decentralized, technically supported underground storage. The two main challenges of the project are ensuring water quality with respect to health and environmental risks and controlling clogging of the system. The temporal asymmetry between very rapid infiltration of a flood wave and long-term storage in the aquifer, coupled with relatively long periods of no infiltration, results in stringent requirements for infiltration system design and materials.The goal of the infiltration process is to improve retention of undesirable materials while maintaining high infiltration rates. As part of this work, potential materials will be evaluated for their suitability for infiltration of flood waters into the aquifer. For this purpose, river water quality needs to be seasonally monitored. Parameterization and characterization of clogging can be performed in column experiments using different potential materials, at different hydrodynamic and hydrochemical conditions, and with defined infiltration and dry phases. Established concepts for the transport of (bio)colloids as well as the substitution of contaminants by fluorescent tracers with similar sorption properties can be used to demonstrate the efficiency of retention and the local formation of clogging in time and space.To test potential materials for the infiltration ditches and their contaminant retention behavior during wetting and drying cycles, a transparent column setup with temperature, pressure, electrical conductivity, redox potential, pH, and turbidity probes, as well as visual monitoring was established. This allows to record spatially resolved breakthrough curves, depositions, and reactions. We expect an increase of contaminant retention with an increase of filtered fines from the infiltrated water. Both, inorganic and organic colloids, are tested for this purpose and supplemented by experimental data from field sites. The shear forces in the porous materials are matched to the expected shear forces in the infiltration ditch. The hydrochemical stress due to a reduction in ionic strength during infiltration is also simulated in the experiments.With this work, the behavior of contaminants and particles in infiltration systems can be predicted and optimized in order to fulfil environmental and legal requirements for the water quality.
Extraction of diving body waves from a dense network of seismometers at kilometric offsets: a case study from the Paris Basin
Authors: Riahi Ali , Kazantsev Alexandre , Metaxian Jean-Philippe , Stutzmann Eleonore , Schimmel Martin , Montagner Jean-Paul
Published: February 2023

We reconstruct the body and surface waves from the seismic ambient wave field, recorded by a dense seismic array deployment in the Paris Basin, France, with a final objective of performing a 3D seismic tomography by inversion of the retrieved P-phase arrivals. The array was installed in November 2010 and consists of around 100 stations. The stations were shifted to different locations every day, yielding around 580 recording locations with an interstation distance of about 400 m. Each station has continuously recorded around 3-4 days of the seismic ambient wavefield. We calculate the cross-coherency between each station couple in the frequency band of 1.0-4.5 Hz and estimate the empirical Green’s functions. We use the polarization properties of the cross-correlation tensors to separate the P- and Rayleigh wavefields. The results show the reconstruction of the fundamental and higher modes of Rayleigh and Love waves, as well as of diving P- waves. We observe the apparent group velocity of the fundamental and first higher mode of the Rayleigh wave around 0.5 and 1.5 km/s, respectively, and the apparent group velocity of around 0.8 km/s for the fundamental mode of the Love wave. The extraction of the P waves is challenging because of a high amplitude coherent artefact that can cause misinterpretation of the P- wave moveout. We propose a new approach to filter out the extracted P- wave in presence of this artifact and reconstruct the P-wave with a correct apparent velocity of around 2-3 km/s, validated against available active seismic data. This approach is based on template-matching and can be regarded as the most crucial step in P-wave retrieval from our dataset. Future steps will consist of using the extracted P-wave arrival time for a 3D tomography of the anticline structure located beneath the array.
Incorporating Weather Forecasts into Short-Term Water Demand Prediction using Probabilistic Deep Learning with Long Short-Term Memory Networks
Authors: Johnen Gregor , Kley-Holsteg Jens , Ziel Florian
Published: February 2023

As could be seen in recent years, ensuring the water supply-demand balance is a topic of increasing concern to supply companies facing the threat of increased demand scenarios resulting from long-term effects due to climate change. Especially demand peaks of multiple hours during the day or persisting demand peaks of several days caused by prolongued dry periods and more heat days throughout the summer force water suppliers to more efficiently control and manage their resources. Being able to take proactive and informed decisions through reliable short-term probabilistic forecasts is therefore crucial in this context.This research proposes two probabilistic deep learning architectures based on long short-term memory (LSTM) networks to forecast hourly water demand up to 10 days in advance. Both models processes different temporal sequences of data, including past observations of water demand and regressors as well as future regressors with different time lengths. The models encode long-term historic information of the water demand and features, including historic meteorological information, and simultaneously incorporate short-term future information on calender- and weather features using statistically optimized point forecasts (DWD MOSMIX) of the latter. Through implementing the models in an autoregressive manner, the output is fed back into itself at each step and predictions are made conditioned on the previous one to account for correct path dependency between consecutive hours. This way the model produces multi-step-ahead forecasts of variable length by using future information together with the historic context.In a case study of central Germany, the performance of the proposed deep learning models was compared to a Lasso estimated high-dimensional time series model and a conventional AR(p) model. Results indicate the potential of the proposed approach of using weather forecasts in short-term water demand prediction especially for lead times larger than 24 hours.
A Novel Workflow for Streamflow Prediction in the Presence of Missing Gauge Observations
Authors: Mbuvha Rendani , Adounkpe Peniel Julien Yise , Houngnibo Mandela Coovi Mahuwetin , Newlands Nathaniel
Published: February 2023

Streamflow predictions are a vital tool for detecting flood and drought events. Such predictions are even more critical to Sub-Saraharan African regions that are vulnerable to the increasing frequency and intensity of such events. These regions are sparsely gauged, with few available gauging stations that are often plagued with missing data due to various causes, such as harsh environmental conditions and constrained operational resources. This work presents a novel workflow for predicting streamflow in the presence of missing gauge observations. We leverage bias correction of the GEOGloWS ECMWF streamflow service (GESS) forecasts for missing data imputation and predict future streamflow using the state-of-the-art Temporal Fusion transformers at ten river gauging stations in the Benin Republic.We show by simulating missingness in a testing period that GESS forecasts have a significant bias that results in poor imputation performance over the ten Beninese stations. Our findings suggest that overall bias correction by Elastic Net and Gaussian Process regression achieves superior performance relative to traditional imputation by established methods such as Random Forest, k-Nearest Neighbour, and GESS lookup. We also show that the Temporal Fusion Transformer yields high predictive skill and further provides explanations for predictions through the weights of its attention mechanism. The findings of this work provide a basis for integrating Global streamflow prediction model data and state-of-the-art machine learning models into operational early-warning decision-making systems (e.g., flood/ drought alerts) in resource-constrained countries vulnerable to drought and flooding due to extreme weather events.
Increased belowground tree carbon allocation in a mature mixed forest in a dry vs. a wet year
Authors: Rog Ido , Hilman Boaz , Fox Hagar , Avital Shifra , Klein Tamir
Published: February 2023

Climate change is expected to increase the frequency and severity of droughts in Mediterranean forests. Tree survival and storage of atmospheric CO2 in these forests depend on how individual tree species allocate their carbon (C). Here, we measured a complete set of above- and belowground C pools and fluxes in five coniferous and broadleaf species co-existing in a mature evergreen forest. Our study period included a drought year, followed by an above-average wet year, and the seasonal long dry period characterizes Mediterranean climate. To quantify the exact timing and spatial distribution of belowground C allocation, we additionally applied 13CO2 pulse labelling of one of the tree species (Quercus calliprinos). We found that during the dry versus wet year, photosynthetic C uptake decreased, C use in the C sinks remained unchanged and C allocation to belowground sinks increased. Among the five major C sinks, respiration was the main flux (~64%), while smaller fluxes like exudation (~9%) and reproduction (~1%) were those which increased the most in the dry year. To cope with seasonal drought, most trees relied on starch to maintain the C supply, but between years we found no significant differences in starch and sugars in aboveground tissues. Relative to the C storage dynamics, higher water use efficiency was found in conifers, while species-specific differences between dry and wet years were found among the broadleaves. Interestingly, in the wet season, after pulse labelling, C was allocated from the labeled leaves to the roots in two main time-lags: first after 3-5 days and second after 15-20 days. Labeled C reached fine roots at a distance of 0-6 m from the labeled tree. These detailed tree-level observations expose inter-annual and interspecific differences in C allocation among fluxes and tissues, specifically in response to varying water availability.
Evidence of water transport in the Earth’s mantle from an Undetected Seismic Phase in Waveforms from Southern Tyrrhenian (Italy) intermediate-depth and Deep Earthquakes
Authors: Ninivaggi Teresa , Selvaggi Giulio , Mazza Salvatore , Filippucci Marilena , Tursi Fabrizio , Czuba Wojciech
Published: February 2023

We found a previously unreported later seismic phase from intermediate-depth and deep earthquakes of the Southern Tyrrhenian subduction zone recorded by European seismic stations. Later phases are useful to constrain local-scale discontinuities, especially in subduction zones, but their observation is infrequent, since it depends on seismic stations distribution and slab geometry. Their detection, therefore, is a great opportunity to improve our knowledge of subduction systems and Earth’s interior. They also represent a powerful mean to retrieve the chemical composition of such deep structures. 

We analysed thousands of waveforms of the strongest earthquakes occurred in the Southern Tyrrhenian subduction system and recorded by European seismic stations from 1990 to 2020. 

The unknown seismic phase is visible at stations from 6 to 9 degrees from the epicentre, towards the north. Only earthquakes located in a well-defined region of the slab, in the depth range of 215–320 km, generate this secondary phase. We built a direct 2D P-velocity model of the Tyrrhenian slab to reproduce observed travel times and ray paths of direct and later phases. We interpret the later phase as a compressional (P) wave that propagates downward in a narrow, high P-wave velocity layer within the deepest part of the subducting slab. We proprose that the high P-wave velocity layer in the subducting slab could be related to the presence of the dense hydrous magnesium silicate phase A, which is probably the main (meta) stable hydrous phase in the upper-mantle deep slab. Our findings provide further insights on the Southern Tyrrhenian slab structure and have also relevant implications on water transport in the Earth’s mantle and slab petrology.
Reducing the operator effect in LSPIV image-based discharge measurements
Authors: Bodart Guillaume , Le Coz Jérôme , Jodeau Magali , Hauet Alexandre
Published: February 2023

The operator effect is a prominent error source in image-based velocimetry methods. The LSPIV method is known to be sensitive to the parameters and choices of the user, as shown in the literature and emphasized by the results of a video gauging intercomparison, the Video Globe Challenge 2020 (VGC2020) (Le Coz et al., 2021). The intercomparison was carried out during the COVID-19 lockdown of spring 2020 and involved 15 to 23 participants using the LSPIV method among other techniques on 8 videos representative of the diversity of river gauging conditions and imaging viewpoints. Each video came with a discharge reference and associated uncertainty. An in depth investigation of the intercomparison results has been carried out to identify the most sensitive parameter(s) for each video and also to review the common setting mistakes (cf. Bodart et al., 2022). The investigation highlighted the strong impact of the image temporal sampling (extraction framerate) and of the velocity filtering on the discharge errors. The ortho-rectification and the surface coefficient were also found to be impacting in given cases. Based on these observations, several assistance tools and automated filters are proposed to reduce the operator effect. They are evaluated on the intercomparison dataset. The assistance tools use available information (e.g. transect data) or basic user inputs (e.g. manual spotting of some velocities) to determine the optimal extraction framerate, grid points and searching area (SA) for LSPIV computation. The sequence of automated filters is built for the specific context of discharge measurement: spatial coherency of the velocities in a local neighborhood and temporal coherency of the velocities computed at a point. These velocity filters are systematic and do not require any input from the user. The application of the assistance tools and automated filters to the intercomparison dataset leads to a significant improvement of the results. On the eight videos, the mean interquartile range of the percent error initially at 17% is reduced to 2% and the mean median of the percent error initially at -9% is reduced to 0.6% with the assistance tools and filters. The results are encouraging and can be implemented in software tools for the operational deployment of the LSPIV method for discharge measurement.Le Coz, J., Hauet, A., and Despax, A. (2021). The Video Globe Challenge 2020, a video streamgauging race during the Covid-19 lockdown, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2116, https://doi.org/10.5194/egusphere-egu21-2116, 2021Bodart, G., Le Coz, J., Jodeau, M., and Hauet, A.: Quantifying the operator effect in LSPIV image-based velocity and discharge measurements, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4457, https://doi.org/10.5194/egusphere-egu22-4457, 2022.
Acceleration of Antarctic Circumpolar Current at the Drake Passage during the GRACE era
Authors: Yang Chengcheng , Cheng Xuhua , Huang Duotian , Qin Jianhuang , Zhou Guidi , Chen Jiajia
Published: February 2023

Previous studies have identified intense climatic change in the Southern Ocean. However, the response of ACC transport to climate change is not fully understood. In this study, by using in-situ ocean bottom pressure (OBP) records and five GRACE products, long-term variations of ACC transport are studied. Our results confirm the reliability of GRACE CSR mascon product in ACC transport estimation at the Drake Passage. Superimposed on interannual variability, ACC transport exhibits an obvious increasing trend (1.32±0.07Sv year-1) during the GRACE era. Based on results of a mass-conservation ocean model simulation, we suggest that the acceleration of ACC is associated with intensified westerly winds and loss of land ice in Antarctica.
The Bouvet triple junction: a model of Gondwana fragmentation in Jurassic and Early Cretaceous times
Authors: Reeves Colin
Published: February 2023

The mid-ocean ridges of the Atlantic and Indian oceans remain essentially fixed with respect to a constellation of mantle plumes throughout Gondwana dispersal.  The Bouvet plume is central to the dispersal process.  A model for the complex early Bouvet (Africa-Antarctica-South America) triple junction provides a link between the relatively simple tectonic histories of the South Atlantic and Indian oceans.  The model is based on interpretation of ocean-floor topography and repeated, meticulous and iterative animation in ‘Atlas’ plate-modelling software.East and West Gondwana started to separate at   ̴184 Ma (Toarcian) with a 2000-km-long dextral transtensional rift between Africa and Antarctica.  The earliest triple junction was initiated south of Africa as the Malvinas plateau started to move west along the Agulhas fault at   ̴165 Ma (Callovian).  Limpopia, a micro-fragment, at first remained attached to Antarctica while the Maurice Ewing Bank (MEB) retained its attachment to Africa.  New dynamism initiated rifting in the South Atlantic Ocean and between India and Antarctica-Australia early in the Cretaceous.  Complex reorganisation of micro-fragments near the Bouvet plume head led, by   ̴129 Ma (Hauterivian), to a triple junction configuration with the present outline of South America intact (including the MEB fixed off the Malvinas plateau) and with Limpopia, the continental core of the Mozambique Ridge (supplemented by copious Cretaceous volcanism) fixed to Africa.  This configuration was to prove long-lived.It is interesting to speculate whether the large Morokweng meteorite impact in southern Africa (J/K boundary) could have triggered tectonic acceleration.The model is illustrated in animation at https://www.reeves.nl/gondwana/aac-anim-
Optimisation of an ERT acquisition for soil-plant interaction in presence of biochar
Authors: Vasconez-Maza Marco D. , Thiesson Julien , Guerin Roger , Delarue Frederic , Mendieta Aida , Jougnot Damien
Published: February 2023

In the mitigating strategies of human impact on environments, the biochar addition to shallow soil horizon represents a promising way among the existing Carbon Dioxide Removal technique. This study is part of a project that aims at evaluating the impact of the presence of biochar in soils on the growth of roots. Geophysical techniques are a good candidate for non-invasive investigation and field monitoring. Among the existing techniques, Electrical Resistivity Tomography (ERT) has already shown great potential for detecting the presence and growth of roots in agricultural soils.In this study, our goal is to test whether ERT is able to track changes in root growth in a technosol. The field experiment takes place on a setup consisting of 20 plots of 2 meters by 3 meters where the first 0.3 meters were disturbed and for half of them biochar has been incorporated (ca. 2% wt.). As we are expecting 3D effect on this specific field (effects of the limits of the plot, effects of the roots), we design a numerical study to determine the best experimental setup for a 2D ERT profile using pyGIMLi, an open-source software library for geophysical inversion.We conducted several numerical simulations to determine the optimal dimensions of a meshed body, which was considered as a semi-infinite space, to simulate profiles of 48 and 96 electrodes separated by 0.1 meters. Field measurements on plots with and without biochar showed electric resistivity values of 45 ohm m and 56 ohm m, respectively, suggesting that ERT might be able to detect the biochar presence. Using this information, we focus our numerical simulations on a suitable configuration to assess the effect of biochar onto root growth.