bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of small hydropower plants under uncertainty: from the hydrological cycle to energy conversion
Authors: Pagotelis Panagiotis , Tsilipiras Konstantinos , Lyras Antonis , Koutsovitis Anastasios , Sakki Georgia-Konstantina , Efstratiadis Andreas
Published: February 2023

We investigate the design of small hydropower plants under multiple sources of uncertainty and contrast it with the conventional deterministic practice that leads to a unique solution. In particular, we emphasize three sources of uncertainty, referring to: (a) the rainfall process, (b) the rainfall-runoff transformation, and (c) the flow-energy conversion. The first is due to the natural (i.e., hydroclimatic) variability, and is represented through stochastic approaches. Regarding the rainfall-runoff uncertainty, this arises from inherent structural shortcomings and poor parameter identifiability across the calibration procedure. In fact, hydrological model parameterizations using only historical data are often insufficient for accurately predicting catchment behavior over the long term, as they may not capture the full range of hydroclimatic conditions that the catchment may be subjected to. To address this issue, we use synthetic time series as drivers to parameterize the model and validate it against observed data. This approach preserves the probabilistic properties and dependence structure of the observed data while also providing a much wider range of hydroclimatic conditions for model training. In addition, it allows for assessing and quantifying the total model uncertainty. The final source of uncertainty is depicted by means of probabilistic efficiency curves. This Monte Carlo simulation-optimization framework is formalized as a modular procedure, where the different sources of uncertainty, as well as the full context, is tested through the design of a small hydropower plant in Epirus, Western Greece.
Sparse image domain wavefield tomography for low-cost CCS monitoring in repurposed hydrocarbon fields
Authors: de Ridder Sjoerd , Mohammadzaheri Afsaneh , Calvert Alexander , Lüthje Mikael
Published: February 2023

Seismic time-lapse (4D) imaging has been considered as a key solution to monitor CO2 reservoirs. However, traditionally this technology requires dense data acquisition to produce high-resolution images. It is anticipated that monitoring will be required for more than 50 years after CCS operations cease and the monitoring phase is profit-negative. Developing cheaper 4D seismic imaging techniques is necessary. Historical knowledge of the subsurface structure in and near abandoned hydrocarbon fields, could reduce the dense data requirement of 4D imaging.Here we present preliminary results of 4D seismic (image-domain) wavefield tomography (IDWT) using pre-stack gathers from a sparse monitoring acquisition. IDWT uses short-offset data to exploit primarily kinematic changes rather than amplitude changes. IDWT minimises the shift between baseline and monitor migrations by optimising the monitor velocity model. Pre-stack IDWT, unlike post-stack methods, can use individual shot gathers to calculate the migration images. This property is beneficial when using sparse data acquisition permitting reliable measurement of shifts between monitor and baseline. Knowing the structure of the subsurface, we can design sparse acquisition surveys for seismic deployment, to minimize uncertainty in target areas. We create synthetic models based on Tyra gas field, a prospective future repository of CO2 in the Danish sector of North Sea and simulate CCS and subsequent leakage scenarios. The presence of CO2 in the reservoir, as well as the effect of reservoir pressure on the overburden stress-state, changes the seismic velocity structure of the reservoir and the overburden. These velocity changes cause an apparent depth (or time) shift when migrating the data.
Glacial retreat driving enhanced methane emissions in the high Arctic
Authors: Kleber Gabrielle , Hodson Andrew , Magerl Leonard , Schytt Mannerfelt Erik , Bradbury Harold , Zhu Yizhu , Trimmer Mark , Turchyn Alexandra
Published: February 2023

Permafrost and glaciers in the high Arctic form an impermeable ‘cryospheric cap’ that traps a large reservoir of sub-surface methane and hinders it from reaching the atmosphere. The vulnerability of the cryosphere to climate warming is making releases of this methane possible, but uncertainty in the magnitude and timing makes future predictions of Arctic greenhouse gas emissions difficult. In Svalbard, where air temperatures are rising more than twice as fast as the average for the Arctic, glaciers are retreating and leaving behind an exposed forefield that enables rapid methane escape.We undertook a field survey of unprecedented spatial coverage across central Svalbard to identify methane emission hotspots in glacial forefields, a previously unknown emission source. Here we document how methane-rich groundwater springs that have formed in recently revealed forefields of 78 land-terminating glaciers are bringing deep-seated methane gas to the surface. Waters collected from these springs are supersaturated with methane up to 600,000-times greater than atmospheric equilibration, with strong isotopic evidence of a thermogenic source. We estimate annual emissions of methane degassing from such groundwater springs to be up to 2.31 kt across the Svalbard archipelago. Our findings reveal that climate-driven glacial retreat is facilitating widespread release of methane, a positive feedback loop that is likely to be prevalent across other regions of the rapidly warming Arctic.
Hydrogeological, hydrodynamic and anthropogenic factors affecting the spread of pharmaceuticals and pesticides in water resources of the Granada plain (Southern Spain)
Authors: Llamas Marta Inés , Jiménez-Gavilán Pablo , Luque-Espinar Juan Antonio , Benavente-Herrera José , Candela Lucila , Sanmiguel-Martí Mónica , Rambla-Nebot Javier , Aranda-Mares José Luis , Vadillo-Pérez Iñaki
Published: February 2023

The anthropogenic organic contaminants contemplated in the environmental legislation, as well as those of emerging concern, threaten the quality of water resources to a degree that remains largely unknown. Contaminant exposure in the aquatic environment is a crucial element if a full understanding of the risk is pursued. There are still many uncertainties about the occurrence of organic contaminants and their behavior in the hydro(geo)logical media in large scale areas. The case study of the unconfined aquifer of the Granada Plain (approximately 200 km2) is presented here. Two groundwater and surface water monitoring campaigns were conducted (March 2017 and June 2018). Water samples were analysed for (i) 171 organic contaminants (e.g., pesticides, pharmaceuticals, drugs of abuse, PAHs); (ii) major and minor ions (Ca2+, Mg2+, Na+, K+, Cl-, SO42-, HCO3-, NO3-) and (iii) isotopes of the water molecule (δ18O, δ2H) and δ13C from the dissolved inorganic carbon. Additionally, in situ measurements of physico-chemical parameters (pH, temperature, electrical conductivity, redox potential and dissolved oxygen) were carried out. In total, 41 organic pollutants were detected, at least once: 17 pharmaceuticals or drugs of abuse, 21 pesticides or their metabolites and three PAHs. Statistical tests confirmed the significance of seasonal changes for some of these parameters (e.g., EC, Cl-, F-, δ18O, δ13C), revealing the influence from snowmelt water input on streams and the intensification of irrigation. In March 2017, the group of pesticides (largely represented by triazines) predominated, whereas the frequency of detection of pharmaceuticals increased substantially in June 2018. Based on the obtained results, a qualitative evaluation has been made to suggest four main factors affecting the spatial and seasonal variation of organic pollutants in the aquifer: (i) the variation of the unsaturated zone thickness; (ii) the river-groundwater hydraulic connection; (iii) the hydraulic gradient; and (iv) the anthropogenic factor determining the period of contaminant release throughout the year and wastewater management practices. The river-groundwater hydraulic connection can be especially important in the case of those contaminants whose main path of entry into the aquatic environment occurs through wastewater discharge into streams (i.e., pharmaceuticals).
Modeling water flow dynamics in an agricultural field in Cyprus using image spectral data
Authors: Varvaris Ioannis , Pittaki Zampela , Neophytides Stelios , Leventis Georgios , Eliades Marinos , Papoutsa Christiana , Tzouvaras Marios , Stathopoulos Nikolaos , Neocleous Kyriacos , Themistocleous Kyriacos , Michaelides Silas , Kontoes Charalampos , Hadjimitsis Diofantos
Published: February 2023

Soil degradation implies a long-term decline in soil productivity and quality. Therefore, soil health restoration constitutes an urgent priority to achieve sustainable ecosystem services that are vital to life on Earth. That requires the development of targeted agricultural policy maps. To generate them on a national scale, a large number of hydrogeological models should be built for selected representative agricultural fields. However, the parameterization of the effective properties as input in hydrogeological models for simulating water flow and solute transport is a time-consuming and costly process characterized by high uncertainty because of the spatial variability of soil physical and hydraulic properties. In the long-term, the usage of Earth Observation (EO) data in parameterizing effective soil properties, meteorological conditions, and vegetation indexes have a clear advantage over other methods based on ground-only measured data since using EO data allows repeated monitoring of land degradation dynamics over larger spatial scales and multiple climatic/biogeographical regions at lower costs and less time-consuming. In this study, integrating EO models and global pedotransfer functions, a concept is proposed for covering the absence of data and estimating the effective parameters as input in a single porosity model for simulating the water flow dynamics in a selected agricultural field in Cyprus. For the calibration and validation of the models, groundwater level data from two different periods were utilized. The performance statistics of the developed water flow model for the entire simulation were characterized fairly well, setting the suggested concept as a valuable tool for parameterizing the effective hydraulic parameters.Acknowledgement“The authors acknowledge the ‘EXCELSIOR’: ERATOSTHENES: EΧcellence Research Centre for Earth Surveillance and Space-Based Monitoring of the Environment H2020 Widespread Teaming project (www.excelsior2020.eu). The ‘EXCELSIOR’ project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 857510, from the Government of the Republic of Cyprus through the Directorate General for the European Programmes, Coordination and Development and the Cyprus University of Technology.”
A surrogate model to investigate the geothermal potential with variable groundwater flow velocity
Authors: Previati Alberto , Silvestri Valerio , Presta Asciutto Alberto , Frattini Paolo , Crosta Giovanni
Published: February 2023

Many cities worldwide extend upon alluvial aquifers which have a great potential for low temperature geothermal installations. Typically, the geothermal potential describes the ability to exchange heat with the subsurface and the relative sustainability.To estimate the geothermal potential of shallow aquifers many techniques have been adopted such as analytical solutions and numerical methods considering aquifer thermal parameters (e.g. porosity, thermal diffusivity) and the system configuration (e.g. diameter of pipes, borehole thermal resistance). Analytical methods are typically fast and easy to implement in a GIS environment but commonly neglect the effects of groundwater advection on heat transfer mechanisms. On the other hand, physically based numerical methods can handle conductive and advective transport and complex 3D geometries but have the limitation of domain size/resolution that makes modeling unfeasible at scales greater than city districts or cities.Hence, a new solution based on a surrogate model is presented to estimate the geothermal potential of aquifers at large scale covering a great variability of Darcy flow velocity. The model is based on the response of a synthetic transient-state 3D FEM model reproducing the infinite line source (ILS) configuration. The simulated thermal perturbation over a representative volume at different time stages was then used to calculate the thermal resistance of the aquifer and the corresponding (energy replenishment) potential combining the most relevant variables that affect the heat transport in porous media: thermal conductivity, specific heat capacity, saturation, porosity and flow velocity.Then, a machine learning regression-based surrogate model was generated by fitting the calculated response (thermal potential) for all possible combinations of input variables. The proposed model well replicates the ASHRAE analytical solution which is based on the ILS method for no groundwater flow, and goes beyond including the effects of thermal transport by groundwater.Finally, the model response was implemented in a GIS to obtain large scale geothermal potential maps in areas with highly variable groundwater flow velocity (between 10-5 to 10 m/d) highlighting an expected increase of the geothermal potential due to the advective transport. Field experiments are necessary to verify the numerical findings aiming to reconsider the commonly adopted temperature delta thresholds in areas where the energy replenishment potential is high due to groundwater advection.
Effect of distance of crop canopy temperature observations on Crop Water Stress Index
Authors: Yadav Aditi , Upreti Hitesh , Singhal Gopal
Published: February 2023

The need for water management in the agriculture sector, which is a 70% consumer of global water resources, is imperative. For the same, a plant-based index called crop water stress index (CWSI) is widely being adopted for irrigation scheduling. An empirically derived CWSI is dependent on three parameters of canopy temperature (Tc), air temperature (Ta), and relative humidity (RH).This study was conducted by performing controlled crop experiments in the arid region of Uttar Pradesh state of India, which aims to evaluate the significance of height of Tc observations, taken from March to April 2022, on CWSI calculations for the wheat crop.This has been done by observing theTc by aiming the wheat crop from the top of the crown at two distances of 10 cm and 100 cm, respectively. Handheld remote sensingdevice known as infrared thermometeris used for the observation of canopy temperature. Variation in the height from 10 cm to 100 cm leads to a variation in the field of view from 51.28 sq. cm to 5128 sq. cm. The effect of enhanced area and the involvement of extra soiland vegetation pixels can be understood by this work. Five different irrigation regimes have been provided to study the effect of change in height for Tc observations. The regimes consist of five plots 1,2,3,4, and 5 with soil moisture depletion by the following percentage respectively: 50% in drip irrigation, 25% in drip irrigation, unregulated flood irrigation, 50% in flood irrigation, and no irrigation plot.Plot 2 has been used to formulatea lower baselinefor CWSI calculations. A lower baseline represents a non-water-stressed condition of the crop where the crop is provided with sufficient irrigation treatment leading towards negligible stress conditions. The lower baseline equations used for CWSI assessment for 10 cm and 100 cm height are -1.287(VPD) -2.19 and -1.214(VPD)-1.738, respectively. VPD represents vapor pressure deficit which is a function of Ta and RH. Upon increasing the height from 10 cm to 100 cm, Tc increased by 2.1%, 2.7%, 0.6%, 0.9%, and 1.3% for plots 1,2,3,4, and 5, respectively. This change in temperature led to a decrease in CWSI by 21.8%,36.4 %,9.2%, and 12.2% in plots 1, 2, 3, and 4 respectively. An increase in CWSI by 5.8% for a rise of 1.3% in Tc for plot 5 was also noted. Further coefficient of determination R2 was observed between CWSI at 10 cm height and CWSI at 100 cm height for all plots. It was observed to be 0.65, 0.50, 0.93, 0.93, and 0.87 for plots 1, 2, 3, 4, and 5, respectively. This study shows the effect of observation distance of crop canopy temperature on CWSI that can lead to the development of sampling procedures meant for CWSI studies.
The airborne greenhouse gas observation systems MAMAP2D-Light and MAMAP2D – Characterization and performance assessment
Authors: Borchardt Jakob , Gerilowski Konstantin , Huhs Oke , Krautwurst Sven , Bovensmann Heinrich , Bösch Hartmut , Burrows John P.
Published: February 2023

Remote sensing measurements of greenhouse gases from aircraft to detect and quantify greenhouse gas emissions began about 15 years ago. These measurements have been exploited to detect and quantify predominantly anthropogenic emissions. However, with new satellite systems targeting especially methane (CH4) emissions on different scales, high-precision airborne measurements are needed to validate these satellite systems and detect and quantify emissions too small to be detected from space-based sensors.For this, the MAMAP2D family of airborne passive imaging remote sensing instruments has been and is being built at the Institute of Environmental Physics of the University of Bremen. MAMAP2D-Light, the first of this family, is a lightweight, compact spectrometer measuring carbon dioxide (CO2) and CH4 enhancements in a short-wave infrared band around 1.6 µm with a spectral resolution of ~1.1 nm. It was flown successfully on a Diamond HK36 TTC-ECO motor glider aircraft of the Jade University of Applied Sciences in Wilhelmshaven and the High Altitude Long Range operations (HALO) aircraft of DLR during the COMET 2.0 Arctic campaign in Canada. The MAMAP2D instrument, the next biggest in the MAMAP2D family, covers the SWIR band with a higher spectral resolution and additionally contains a near-infrared channel covering O2 absorption around 760 µm for path-length correction and is currently assembled in the laboratory.In this poster, we will present the spectral characterization of the MAMAP2D-Light instrument as flown during the COMET 2.0 Arctic campaign and assess its performance for detecting local CH4 and CO2 gradients. Additionally, initial laboratory characterizations of the MAMAP2D breadboarding activity will be presented.
Large-ensemble forecast-based extreme event attribution
Authors: Aengenheyster Matthias , Leach Nicholas , Sparrow Sarah , Allen Myles
Published: February 2023

The science of extreme event attribution has rapidly grown in recent years. However, when attributing an observed event using climate models there are constant questions about the ability of the model to represent the relevant physical processes, and about different synoptic situations giving rise to the same threshold exceedance on a chosen metric.

For this reason, there has been growing interest into forecast-based attribution: operational forecast models that successfully predicted the event in question are initialized at different lead times to the event while removing an estimate of anthropogenic contribution to atmospheric composition and ocean temperatures. These much higher-resolved models increase confidence in process representation and synoptic situation, but their high cost presents barriers to true large-ensemble studies.

In this work we represent the whole range between the two approaches by using an N144 slab ocean-atmosphere model to run a perfect model forecast attribution study, forecasting one of its own realizations. A 500-member ensemble is initialized at lead times from days to four months, with and without an estimate of human influence to CO2 concentrations and ocean temperatures.

We can thus perform a traditional extreme event attribution study, investigating how extreme an event was in the model’s own climatology, and a forecast-based attribution. For several events, we quantify the decrease in forecast skill and increase in anthropogenic impact, showing different behaviours depending on world region and event class, and the approach to the limit of traditional attribution once predictability is lost.

By bridging the gap, we hope to increase confidence in the forecast-based attribution methodology and present a new way to conduct attribution using large ensembles of relatively low-resolution models.
Is climate the main driver of Mid-Holocene settlement dynamics on the Varamin plain?
Authors: Kirsten Fabian , Dallmeyer Anne , Busch Robert , Böhmer Thomas , Bernbeck Reinhard , Pollock Susan , Schütt Brigitta
Published: February 2023

For different areas throughout West Asia and the Middle East, settlement discontinuities and periods of cultural decline in the Mid-Holocene have been attested. Whether these phenomena were caused mainly by climatic factors, especially periods of drought, has been an ongoing scientific debate of the last decade(s).  One of these regions, the Varamin plain, is located few kilometers east of Teheran on an alluvial fan along the southern slopes of the Elburs-mountain-range (Northern Iranian Highlands). A recent archaeological survey on the Varamin plain revealed a striking absence of archaeological finds for the end of the Proto-Elamite period (Early Bronze Age) between approximately 5000 and 4100 BP that has been interpreted as a (temporal) abandonment of the plain. This crisis presumably lasted until the beginning of the Iron Age around 3500 BP.Since paleoenvironmental and paleoclimatic information for this region are scarce, this study makes use of 3 different approaches to unravel the Holocene climate variability in West Asia in general and the Northern Iranian plateau specifically: a) analysis of climate reconstructions, b) a high-resolution snapshot simulation performed in ICON-NWP for the mid-Holocene time-slice (7000 BP) and c) a transient simulation performed with the Max Planck Institute Earth System Model (MPI-ESM) spanning the period from 8000 BP to pre-industrial (PI, 100 BP).The comparison of the regional proxy-based climate reconstructions reveals a considerable degree of hetegorenity, impeding any straightforward inferences regarding possible paleoclimatic forcings for settlement dynamics. In particular, no specific drought period can be identified that coincides with the settlement crisis.The model results show that there is a general aridification trend between 7000 BP and PI in West Asia. While absolute annual mean precipitation changes are small, the model data reveal a shift in seasonality of precipitation with drier autumns and winters but substantially wetter conditions during spring during mid-Holocene times. In combination with longer and colder winters during the Mid-Holocene, this may have enhanced water availability and therefore favored agricultural production.  Superimposed on this minor aridification trend, the model shows pronounced climatic variability with distinct multi-decadal wet and dry periods with variations of up to +/-12% in precipitation. Therefore, we cannot exclude that climatic events and variability including their geomorphological responses may have played a role in settlement discontinuties, but we can not clearly identify climate changes as the main driver.
Physics-guided machine learning for laboratory earthquake prediction
Authors: Shokouhi Parisa , Borate Prabhav , Riviere Jacques , Mali Ankur , Kifer Dan
Published: February 2023

Recent laboratory studies of fault friction have shown that deep learning can accurately predict the magnitude and timing of stick-slip sliding events, the laboratory equivalent of earthquakes, from the preceding acoustic emissions (AE) events or time-lapse active-source ultrasonic signals. While there are observations that provide insight into the physics of these predictions, the underlying precursory mechanisms are not fully understood. Furthermore, these purely data-driven models require a large amount of training data and may not generalize well outside their training domain. Here, we present a physics-guided machine learning approach - by incorporating the relevant physics directly in the prediction model architecture - with the objectives of enhancing model predictions and generalizability as well as reducing the amount of required training data. We use data from well-controlled double-direct shear laboratory friction experiments on Westerly granite blocks exhibiting numerous regular and irregular stick-slip cycles. Simultaneously, AEs are recorded while the faults are also regularly probed by ultrasonic waves transmitted through the fault zone to monitor the evolution of the contact stiffness during shearing. Our physics-guided ML models take features extracted from AE time series or time-lapse active source ultrasonic signals and predict the shear stress history, which gives both the timing and size of the laboratory earthquakes. The models are constrained by friction laws as well as simplified physical laws governing ultrasonic transmission and AE generation. Our findings indicate that physics-guided ML models outperform purely data-driven models in important ways; they provide accurate predictions even with little training data and transfer learning is greatly enhanced when physics constraints are incorporated. These findings have important implications for earthquake predictions in the field, where training data are scarce.  
Investigating Seasonal Variations in Mars' Hydrogen Escape Flux derived by model fitting Lyman Alpha observations from Emirates Mars Ultraviolet Spectrometer (EMUS) onboard the Emirates Mars Mission (EMM).
Authors: Marwan Mohammad , Yousuf Maryam , Mohammad Badriya , AlHammadi Huda
Published: February 2023

The Martian atmosphere has undergone significant decay over time, with several factors contributing to this process. It is believed that thermal (Jeans) escape is a significant contributor to hydrogen loss on Mars (Chaufray, 2021). In this research, the role of thermal (Jeans) escape in the uplifting of hydrogen molecules to the exosphere, driven by solar wind forcing, is investigated on seasonal bases. Studying hydrogen escape seasonally can provide insights into the role of solar forcing in atmospheric processes. This research utilizes observations from the Emirates Mars Ultraviolet Spectrometer (EMUS) onboard the Emirates Mars Mission (EMM) To study the atmospheric Hydrogen Lyman Alpha emission on seasonal timescales. The data for this study focuses on the perihelion (greater than Ls 225) and aphelion (between 60-90 Ls)  periods, during which variations in the escape flux due to exobase temperature changes are expected. Level 2b/2a data is specifically chosen because it includes calibrated brightness and added geometric data, a combination of different EMUS observation modes is used in the study. The Lyman Alpha brightness measurements are used to derive the density profile of hydrogen in the Martian atmosphere using the same approach described in (Chaufray, 2008). The atmospheric model is divided into two parts, below the exobase the hydrogen density is described by a diffusive model, while above it uses Chamberlain’s model without satellite particles (Chamberlain, 1963). Deriving atmospheric hydrogen density profile is done by assuming the exobase temperature and solving radiative transfer equations to compute theoretical intensities which are then fitted with observational data to determine exobase temperature and density, a reasonable fit of observations is done assuming the parameters are in ranges that are in line with photochemical models (Krasnopolsky, 2002). This approach has been used to analyze the Mariner 6, 7 exospheric Lyman-α data during the late 1960s (Anderson and Hord, 1971), and the same approach has been used to analyze SPICAM Lyman-α data on Mrs express (Chaufray, 2008), this research attempts to use the same approach to analyze EMUS Lyman-α observations. It is expected that the (Jeans) escape flux of Hydrogen will vary on seasonal timescales, with higher escape fluxes observed around the perihelion period when the exobase temperature is the highest. This is due to the fact that the (Jeans) escape mechanism is driven by the temperature of the exobase, with higher temperatures resulting in higher escape rates. On the other hand, it is expected that lower escape fluxes will be observed during the aphelion period when the exobase temperature is lower.
Surface attached vortices as a proxy for gas transfer in free-surface turbulent flow
Authors: Babiker Omer , Bjerkebæk Ivar , Xuan Anqing , Shen Lian , Ellingsen Simen A
Published: February 2023

Gas transfer between ocean and atmosphere is largely governed by the turbulence in the topmost centimetres beneath the free surface. It has been frequently observed that areas of strong positive divergence of the surface-tangential velocity field correspond to efficient surface renewal and consequently increased transfer of gas across the interface. Patches of strong positive surface divergence occur in the form of intermittent upwelling events visible as ``boils'' on the surface.It has been qualitatively observed that surface-attached ``bathtub'' vortices tend to appear at the edges of upwelling boils, hence a correlation between the density of these long-lived vortices and average surface divergence might be expected. Surface-attached vortices leave imprints on the surface which are particularly simple to detect: they live for a long time compared to turbulence turn-over, and their imprints are in the form of nearly circular dimples.From direct numerical simulations, we show that a very high correlation exists between the time-dependent number of surface-attached vortices and the mean square of the surface divergence. A correlation coefficient of over 0.9 is found, where peaks in the number of vortices occur a little time after the peak in surface divergence, approximately half of the integral timescale of the bulk turbulence.We use a newly developed method whereby the surface-attached vortices are identified with high precision and accuracy from their surface imprint only. Thus, observation of surface dimples can act as a proxy for surface divergence, with the prospect of remote sensing of gas transfer rate.
Forest management strategies to improve water-related ecosystem services in central Italy
Authors: Lompi Marco , Pacetti Tommaso , Pasini Giovanni , Santolini Riccardo
Published: February 2023

Forest management can represent a powerful tool to optimise ecosystem services related to water, as water availability is deeply connected with forests and their management. The objective of this study is to improve the understanding of the forest–water connection, developing a methodology that can explain which forest types and management strategies can increase water availability and flood protection in Casentino Forest National Park (Parco Nazionale delle Foreste Casentinesi). The different forest management types for every species considered in the study are abandoned or unmanaged forest, coppice, coetaneous and non-coetaneous high forest. The Casentino Forest National Park in Central Italy on the Apennine Mountains covers a set of 25 small river basins, which have been chosen as a case study to test a methodology based on hydrological modelling and machine learning tool. First, the Soil Water Assessment Tool (SWAT) has been calibrated and used to model the baseline scenario, evaluating the ecosystem services the forest park provides. The baseline scenario has been built in the SWAT model, characterising the forest-related parameters, such as the leaf area index, the leaf-to-biomass fraction, the biomass of the forest or the canopy storage among others. This information has been retrieved with land use data, such as the Corine Land Cover, available forest technical map and MODIS satellite images. The following step has been the analysis of multiple land use scenarios to understand the potential effect of different forest management on water-related ecosystem services. Nevertheless, the SWAT model is hugely time-consuming in modelling several land use scenarios, as each forest management strategy needs to be described with a new set of parameters and model runs. For this reason, a Support Vector Machine (SVM) learning model has been trained to reproduce the hydrological behaviour of the Park using the  SWAT model outputs for the baseline scenario as a training dataset. The SVM has been validated with a Jack-Knife cross-validation to test its reliability in determining the average annual water yield, runoff, evapotranspiration and percolation in the river basins using the different forest management types as input. Then, the SVM has been used to model a set of 4200 different land use scenarios to understand the type of forest with the higher water yield content or lower surface runoff. The results show that the oldest forests, especially with a prevalence of oaks, have great potential in regulating services, while the coppices contribute more to the provisioning services.
A decision-support framework to construct climate impact storylines using downward counterfactuals
Authors: Ciullo Alessio
Published: February 2023

Managing extreme weather events of unprecedented magnitude is one of the main challenges facing climate risk management and climate adaptation. Because of the unprecedented nature of these events, some authors have questioned the use of probabilistic approaches in this context. As an alternative, they introduced the so-called climate storylines approach. Climate storylines do not aim at predicting system states; rather, their focus is on revealing plausible chains of events whose impact might undermine the performance of the system.Conceptually, climate storylines relate to - but are separate from – downward counterfactual histories. Downward counterfactual histories are plausible alternative realizations of historical events that could have turned to the worse. By constructing downward counterfactual histories in a disaster risk reduction context, some authors showed that many disasters that took societies by surprise could have in fact been anticipated.This talk will introduce a decision-support framework to build climate storylines based on downward counterfactual histories. The framework is event-oriented, it focuses on impact and it is designed to be applied in a participatory fashion. By following the framework, the user first constructs climate storylines based on an iterative analysis of what (combinations of) counterfactuals are deemed critical (i.e., downward). Then, the user analyzes the future impact of the constructed storylines under climatic and socio-economic scenarios. Finally, the user explores the effects on the estimated impacts of the value-laden choices involved in the construction of the storylines.The framework is applied to study the impact of tropical cyclones hitting the European Union’s outermost regions on the stability of the European Union Solidarity Fund (EUSF), a public fund that provides financial relief to Member States affected by large disasters. Contrary to what historic evidence would suggest, it is found that extreme - yet plausible - tropical cyclones might deplete the EUSF capital if they happen concurrently with large events in mainland Europe, and that a substantial recapitalization of the fund might be required to cope with future climatic and socio-economic changes.
Experimental investigation of environmentally affected cracking during indentation testing of Anroechter sandstone
Authors: Korkolis Evangelos , Renner Joerg
Published: February 2023

Environmental effects on cracking have important implications in geoengineering applications, such as mechanized tunnel construction. The time required and the cost of excavation could be reduced by employing techniques such as special cutting fluids that lower the strength of the rock.At first contact, the cutting tool acts as an indenter, penetrating the rock surface and causing distributed brittle damage and subsequently localized deformation. We performed indentation tests using blunt indenters, mimicking a section of a standard cutting disk, on unconfined cylindrical Anroechter sandstone specimens using a servo-hydraulic press. The loading rate was varied over two orders of magnitude. A first set of experiments was performed at room temperature and humidity; in a second, specimens had their top surface wetted with water during indentation. Preliminary results show that in the presence of water, the peak indentation force is reduced by approximately 13%. The short duration of the tests (a few minutes) and the relatively low porosity of the sample material (approximately 10%) suggest a fast-acting weakening mechanism. Currently, we are focusing our efforts on understanding the effect of wetting fluid chemistry on peak indentation pressure and exploring the interplay with loading rate.
The Global Runoff Data Centre: A building block in the chain of reproducible hydrology
Authors: Recknagel Thomas , Färber Claudia , Plessow Henning , Looser Uli
Published: February 2023

The Global Runoff Data Centre (GRDC) operates under the auspices of the World Meteorological Organization (WMO) at the German Federal Institute of Hydrology (BfG). It serves an important function for the scientific community as an archive for global runoff data. In 2022, the GRDC was referenced as a data source in over 100 peer-reviewed publications. Awareness of the need for reproducibility in hydrologic science has grown considerably in recent years. Thus, data archives also have the responsibility to improve their infrastructure to meet these requirements. Essential measures include making data and programs available in public repositories, containerization of computational environments and the provision of application programming interfaces (APIs).To achieve these goals, the GRDC uses web portals for data provision, develops APIs for script-based data access, and provides program libraries in R or Python, e.g. for data analysis, as open source on repositories such as Github. We show the implementation status of these measures as well as positive effects that have resulted from the implementation, but also highlight obstacles and challenges in achieving a fully open and unrestricted data world.
Numerical simulation of a sedimentation tank applied to an open loop Ground Heat Exchanger system
Authors: Hernandez Dorian , Pasquier Philippe , Guibault François
Published: February 2023

Ground Heat Exchanger (GHE) used with heat pumps have the potential to lower energy consumption and greenhouse gas emissions. In particular, Standing Column Well (SCW), which is a category of GHE that uses groundwater has the heat transfer medium, is more compact and less expensive than conventional closed-loop GHEs. SCWs are usually coupled with an injection well to enhance the advection process and the overall efficiency during peak power period. Due to the sediment load present in groundwater, water reinjection tends to clog the aquifer, making it less permeable, and in the worst case, leading to undesirable overflows. To avoid this problem, the use of a sedimentation tank placed before the injection well is investigated. To assess the feasibility of this solution, a fully coupled numerical model has been developed based on standard SCW conditions and on laboratory analysis performed on sediments. The fluid dynamics and settling processes have been coupled and simulated with the Mixture model at a constant temperature. Results show that a conventional sedimentation tank can reduce the sediment concentration in the groundwater returned to the aquifer for different flow rate conditions. As the temperature has a major impact on the sedimentation process, a coupled Heat transfer Mixture model simulation was developed to analyse the response of the tank efficiency for a range of typical SCW operating conditions.
Using Bayesian network to build a participatory framework for sustainable agriculture water management in Yunlin, Taiwan
Authors: Lee Shih-Yao , Yu Hwa-Lung
Published: February 2023

Agricultural water use comprises the major part of the total water consumption in many countries, and Taiwan is no exception. However, urbanization and industrialization have triggered the competition for water among different sectors. Water is transferred to satisfy the daily need and industrial need, especially the need of high-tech industries, from the agricultural sector. Groundwater hence becomes an alternative water resource for agriculture, but the over-exploitation of groundwater resources also leads to some problems such as environmental degradation and land subsidence, and climate change has worsened the situation in the recent years.In Taiwan, groundwater is one of the vital water resources for irrigation, especially when the first crop rice begins being cultivated in the late dry season in central Taiwan. Yunlin County located in central Taiwan is chosen as the study area, which is now facing severe issues about groundwater over-exploitation and suffering from land subsidence threatening the safety of Taiwan High Speed Rail. Because of the high water consumption, groundwater extraction from agriculture is deemed to be the major cause of the land subsidence and should be well monitored and reduced. However, farmers’ pumping behaviors are highly related to the national water allocation policy, food policy and the socioeconomic factors in the rural area. The top-down agricultural water management might not be sufficient and sustainable. Hence, in this study, we propose a participatory framework for agricultural water management using a Bayesian network. The framework tries to incorporate the main factors that affect decision making among different stakeholders, including the Water Resources Agency, Irrigation Agency, Agriculture and Food Agency, farmers, etc., and represent the causal relationship among factors through Bayes’ theorem, or the conditional probability tables (CPTs). The CPTs are constructed based on data, literature reviews and interviews with stakeholders. The key issues concerning different stakeholders are considered in the framework as well, such as surface water shortage for agriculture, land subsidence, and sustainability of agriculture in Yunlin. The network can be used to hold discussions with stakeholders and show the interactions of their decisions among others. The aim of this framework is to facilitate the discussions and formulate the strategies for sustainable agricultural water management with the aid of the intuitive and transparent structure of the Bayesian network.
Mixing Processes in the Dotson Ice Shelf Outflow
Authors: Dotto Tiago , Hall Rob , Sheehan Peter , Damerell Gillian , Zheng Yixi , Boehme Lars , Stammerjohn Sharon , Heywood Karen
Published: February 2023

The Dotson Ice Shelf (DIS) shows high rates of basal melting in recent decades. Relatively warm ocean currents access the sub-ice shelf cavity and interact with the base of the ice shelf providing heat for its melting. The water mass transformation associated with the mixture of warm water and meltwater creates buoyant plumes that shallow as they flow out from the cavity. Here, we show that high turbulent kinetic energy (TKE) dissipation rates (up to order 10−7 W kg−1) and diapycnal eddy diffusivities (up to order 10−2 m2 s−1) are associated with the outflow current from DIS. Four high-resolution Vertical Microstructure Profile (VMP) and ship-based Acoustic Doppler Current Profiler (SADCP) sections were conducted in January and February 2022 at the western side of DIS spanning the outflow as it hugs the steep topographic slope. Near-bed TKE dissipations rates are elevated by up to 3 orders of magnitude and elevated mixing rates are also observed mid-water column around the edges of the outflow. These elevated TKE are associated with friction near the bed and current shear at the outflow boundary. In this presentation, we explore the consequences for dissipation of physical and biogeochemical properties.
The future Pan-European Atlas for Sustainable Geo-Energy Capacities. The #GSEU project.
Authors: Herms Ignasi , Canteli Paula , Ramalho Elsa , Arnó Georgina , Garcia-Crespo Jesús , Carvalho Joao , Colomer Montse , Garcia de la Noceda Celestino , Caldeira Rita , Marzán Ignacio , de Santiago Cristina , Glotzl Gregor , Hladik Vit , Nador Annamaria , Steiner Cornelia , Jirman Petr , Koevoets Maayke
Published: February 2023

Through a five-year Coordination and Support Action, the new #GSEU (Geological Service for Europe) project, EuroGeoSurveys, and 48 partner organizations from 36 European countries (including both national and regional Geological Survey Organisations - GSO, and associated partners) will deliver a plan for a sustainable Geological Service for Europe to be implemented beyond the 2027 project end. The project will directly support the vision of European Green Deal, focusing on our Earth and what lies within its subsurface, i.e. water, energy, raw materials, and all areas that require subsurface data and expertise. The GSEU’s key objective is to develop and make permanently available pan-European geological data on the already existing European Geological Data Infrastructure (EGDI) and related information services for the sustainable and safe use of our subsurface and its resources. The project is structured in 9 Working Packages (WP). Its ‘WP3 Geothermal energy & underground storage inventory’ will deliver the named online GIS ‘Pan-European Atlas for Sustainable Geo-Energy Capacities (SGEC)’, a future harmonized and generalized distribution of maps and databases of already known assessed capacity and resource potential, mainly from previous European projects, and supported with additional national and regional information from GSOs, including standardized qualitative and quantitative attributes. This will consider information on geothermal energy resources and subsurface storage capacities for sustainable energy carriers (hydrogen, heat and cold) and sequestration of CO2. This contribution will present the main objectives, methods and expected results with the publication of the future atlas.
Revealing cloud-precipitation processes from Spaceborne Doppler Cloud Radar
Authors: Sato Kaori , Okamoto Hajime
Published: February 2023

The Earth Clouds Aerosol and Radiation Explorer (JAXA/ESA) will be observing clouds, aerosols and vertical air motions with a high-sensitivity W-band Doppler Cloud Profiling Radar (CPR) and a 355 nm high spectral resolution Atmospheric Lidar (ATLID). The standard and research algorithms for cloud- precipitation and validation methodologies using ground observations have been developed and improved to make the most of the new observation capabilities of the satellite. This paper presents an overview of the active sensor-based algorithms prepared for the EarthCARE satellite mission, and the applications of the methodologies to understand the physical processes associated with clouds, precipitation and air-motion.