HAL-BRGM, les publications scientifiques en libre accès du BRGM
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A model for the concomitant early formation of dolomite and fibrous clays in coastal bay systems: Evidence from the Eocene (Paris Basin, France)
No full textInternational audienceDetailed analysis of Lutetian-Bartonian deposits in the Paris Basin ('Marnes et Caillasses' Formation) provides new evidence of concomitant magnesian fibrous clays (palygorskite and sepiolite) and early microcrystalline dolomite. Although relatively uncommon in sedimentary archives, palygorskite and sepiolite are found in a wide range of environments, from deep-marine to terrestrial. In coastal bay environments, these clay minerals can be formed under arid conditions, either by direct precipitation or by transformation from a precursor, often in association with carbonate. The concomitant formation of fibrous clays and dolomite remains poorly understood until now. Most models consider that fibrous clays form alongside calcite. More recently, it has been suggested that dolomite dissolution can facilitate fibrous clay formation during diagenesis. A new integrative model for concomitant dolomite and fibrous clay formation in coastal marine bay systems is proposed here, based on X-ray diffraction, organic carbon isotopes, electron microscopy, cathodoluminescence, and epifluorescence. In such systems, highly fluctuating hydro-biogeochemical conditions alternately favour the early formation of dolomite or fibrous clays. This study highlights, for the first time, the concomitant presence of three striking processes: (i) microbially influenced microcrystalline dolomite formation; (ii) detrital Al-Fesmectite transformation into palygorskite; (iii) dolomite dissolution, facilitating magnesium availability. These processes are favoured by the warm climate conditions of the Middle Eocene and a progressively restricted coastal bay environment related to regional regression. Based on geochemical and biostratigraphic data, this study also provides the first evidence of the Late Lutetian Thermal Maximum (LLTM) in coastal environments. During the LLTM, increased aridity punctuated by episodic floods linked to intensified run-off further exacerbated the already highly fluctuating hydrobiogeochemical conditions, thus favouring the early formation of dolomite and fibrous clays. These climate conditions, combined with basin confinement linked to Pyrenean deformation, may have facilitated the onset of a significant Eocene fibrous clay episode in NW Europ
Guidelines for the FAIRt publication of Terrestrial Laser Scanner Data in Geomorphic Research
No full textThe increasing dissemination of data from Terrestrial or Permanent Laser Scanning (TLS/PLS) topographic surveys in geomorphology requires the establishment of clear recommendations for their publication. The work presented here proposes a framework to ensure that published datasets comply with the FAIRt (Findable, Accessible, Interoperable, Reusable, trustworthy) principles, with a particular attention on the documentation of the processing steps. This facilitates the evaluation of the relevance of published point clouds and their reuse. Central to this proposal is a set of structured metadata that is essential to document acquisition conditions, methodological choices and processing parameters in order to understand how the published cloud was obtained and what it can be used for. The framework presented in this article is organised into three distinct parts: the essential perimeter of publication, without which the cloud cannot be exploited, pre-processing and processing. These recommendations are accompanied by concrete examples of datasets to illustrate their implementation. To ensure the long-term interoperability of distribution, it is recommended that the LAS format be used as the standard for TLS clouds, associated with a GeoJSON file of metadata. This approach constitutes a component of a long-term preservation process, which is based on the use of open sharing and storage platforms. This standard is therefore intended to be a support tool for researchers, structuring publication practices while remaining open to adapt to future technological and scientific developments. Designed for TLS acquisitions, it could be extended to photogrammetric point clouds if specific photogrammetric processing information is provided
Investigating the effects of high-temperature thermal energy storage on aquifer biogeochemistry
No full textInternational audienceHigh-temperature aquifer thermal storage energy (HT-ATES) is a key technology for reducing greenhouse gas emissions related to space heating and cooling by storing seasonal energy in the subsurface. However, such process could significantly affect aquifers geochemistry and microbial communities. Elevated temperatures influence geochemical equilibria, changing mineral solubility, potentially leading to clogging, organic matter or trace elements mobilization, while simultaneously affecting microbial community structures and functions. Biogeochemical processes in HT-ATES remain poorly understood, making dedicated laboratory experiments crucial to assess their operational and environmental impacts. As part of the Horizon Europe PUSH-IT project (https://www.push-it-thermalstorage.eu/), this study investigates how repetitive heating and cooling cycles induced by HT-ATES affect biogeochemical processes in the subsurface. To simulate HT-ATES conditions, a pressurized flow through experiment is conducted where groundwater from a monitoring HT-ATES well at TUDelft (Netherlands) is injected through aquifer sediments at varying temperatures.Preliminary analysis of aquifer sediments and water composition provide initial insights. Sediments are quartz rich with detectable amounts of carbonates and clay minerals. The groundwater is brackish Na-Cl type (~6 g/L salinity) under reducing conditions. Dissolved gases such as CH4 and CO2 are present, along with Fe, Mn, NH4 and elevated organic carbon concentrations. Initial microbial analysis showed a cell concentration of ~106 cell/mL and revealed a dominance of bacteria (89%) with key genus Nitrospina, a nitrite-oxidizing bacteria, suggesting a role in nitrogen cycling, alongside other taxa (six major phyla identified) potentially involved in metal and sulphate reduction and organic matter degradation.Throughout the experiments, geochemical parameters (pH, redox potential, conductivity, key redox-sensitive compounds) and microbial community composition (qPCR, 16S rRNA Illumina sequencing) are monitored in both circulating water and sediments. These results help understand the impacts of HT-ATES on biogeochemical evolution of storage aquifers and assess the long-term stability of these systems and implications on groundwater quality.Acknowledgements: Funded by the European Union under grant agreement 1011096566 (PUSH-IT project). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor CINEA can be held responsible for them
A methodology to bridge urban shade guidelines with climate metrics
No full textInternational audienceUrban overheating poses significant challenges to public comfort and health, particularly in pedestrian areas. While urban climate studies offer detailed maps of thermal discomfort and heat stress, urban planning often relies on simplified guidelines, creating a gap between research and practice. This study introduces a methodology to bridge this gap by developing a spatially aggregated dissatisfaction indicator, PPD*^, based on the Universal Thermal Climate Index (UTCI) and incorporating a minimum spatial requirement for shade derived from existing cities' shading policies. The novel indicator separately accounts for thermal discomfort in both shaded and sunlit pedestrian areas. A simulated case study in a neighborhood in La Rochelle, France, evaluates six tree planting scenarios, with canopy cover ranging from 0% to 80%. Results indicate that a 20% canopy cover is a practical threshold for mitigating discomfort in moderate and warm climates. This methodology can also be extended to assess additional cooling strategies, such as evaporative systems, and provides valuable insights for optimizing cost-effective and sustainable urban adaptation measures
A First Look at River Discharge Estimation From SWOT Satellite Observations
No full textInternational audienceThe Surface Water and Ocean Topography (SWOT) satellite has the potential to transform global hydrologic science by offering simultaneous and synoptic estimates of river discharge and other hydraulic variables. Discharge is estimated from SWOT observations of water surface elevation, width, and slope. A first assessment using just the highest quality SWOT measurements, over the first 15 months (March 2023–July 2024) of the mission evaluated at 65 gauged reaches shows results consistent with pre‐launch expectations. SWOT estimates track discharge dynamics without relying on any gauge information: median correlation is 0.73, with a correlation interquartile range of 0.51–0.89. SWOT estimates capture discharge magnitude correctly in some cases but are biased (median bias is 50%) in others. There are already a total of 11,274 ungauged global locations with highest quality SWOT measurements where SWOT discharge is expected to accurately track discharge variations: this value will increase as SWOT data record length grows, algorithms are refined and SWOT measurements are reprocessed. This first look indicates that SWOT discharge is performing as expected for SWOT data that achieve performance requirements, providing observed information on discharge variations in ungauged basins globally
Features Leverage in Graph Models for Mineral Prospectivity Mapping
No full textInternational audienceMineral Prospectivity Mapping (MPM), the process of identifying areas with high potential for mineral deposits, can be divided into two main categories: knowledge-driven and data-driven. Knowledgedriven techniques rely on expert opinion on geological data, while data-driven techniques employ ML models to predict the probabilities of mineral occurrences based on known geological datasets. Recently, with the advancement of machine learning (ML) methods, data-driven MPM has gained significant improvements. Notably, graph-based approaches overcome the disadvantages of previously used approaches (pixel-based, image-based) and have demonstrated better performances. However, the graph construction in current methods is based solely on spatial distances between pixels, regardless of their geological attributes. In this paper, we introduce a novel graph construction approach that combines spatial distances with other distances obtained from feature mining. Our experiments show that this combination outperforms existing graphs, and can be considered as a promising approach to integrate feature mining into data-driven models in MPM
The effect of spatial distribution of small farm reservoirs on their cumulative hydrological impacts in a small agricultural catchment: a modeling exploration
No full textInternational audienceAgriculture has always had to face up climate variability, especially rainfall variability, as water stress can damage crops. In many regions of the world, infrastructures to store runoff and stream water such as small reservoirs are seen as a solution to secure food production. The presence of multiple reservoirs in one catchment leads to cumulative impacts which are not necessarily the sum of the individual impacts. In the literature, their impacts are generally studied through modeling. However, the large size of the studied catchments and the aggregated representation of reservoirs in models do not allow to precisely study their cumulative impacts (Habets et al.,2018, https://doi.org/10.1016/j.scitotenv.2018.06.188).In this work, the effect of small reservoir spatial distribution on their hydrological impacts in a small catchment is investigated by a modeling approach using the distributed agro-hydrological model MHYDAS-small-reservoir (Lebon et al., 2022, https://doi.org/10.1016/j.envsoft.2022.105409). This model features physically-based modeling of surface hydrological processes coupled with a soil-crop model, a reservoir model, a groundwater model, and a decision model for agricultural practices. Space discretization is done following parcel shapes and topography. The specificity of the model is thus the spatially explicit representation of reservoirs and associated processes such as irrigation. We constructed eightteen situations with contrasted spatial distribution of reservoirs along the stream network, namely i) upstream, ii) balanced, and iii) downstream, and with varying values of reservoir densities and cumulated reservoir volume.The Gélon catchment (20km², France), for which MHYDAS-small-reservoir had been previously tested and validated, was used as basis for the numerical experiment. We performed the simulations on 20 years at a hourly time step, with multiple repetitions for each situation. We considered a reference situation without any reservoir, and with the spatial crop distribution of the year 2015. For each situation, reservoirs were randomly positioned along the stream network, with different probability distributions for the upstream, balanced, and downstream modalities. Nearby crops were modified compared to reference and connected to the reservoirs to reach a total irrigated area of 1 km² in all tested situations. The impact of reservoirs is thus due to the infrastructure itself and the associated nearby modifications of cultivated species and practices. Impacts are quantified relatively to the reference situation, and based on stream discharges and crop yields at different time horizons.The first analysis of the results revealed that the mean interannual outlet discharge decreased in all the simulations, with high interannual and seasonal variability. Higher reservoir number, higher total stored volume, and downstream distributions generally led to higher hydrological impacts, with interactive effects of these factors. The main driver for these impacts was found to be the water withdrawals in reservoirs, which depends on irrigation needs and water availability. The spatial distribution of reservoirs thus appears as an important factor to consider in models to evaluate their impacts
Pre-Alpine structuration of the Briançonnais basement: lithostratigraphy, geochronology and tectono-metamorphic reconstruction of three Alpine massifs.
No full textInternational audiencePaleozoic European crust – i.e., crust formed or reworked before the Permian and the onset of the Alpine orogenic cycle, is exposed in several massifs in the Briançonnais domain of the Western Alps. These Briançonnais crustal rocks (or 'basement', hereafter) show many similarities with other basement rocks accross Europe, particularly those affected by the Variscan orogeny. While the successive Variscan tectono-metamorphic events have been studied in many European basement massifs to unravel the orogenic and paleogreographic organization of Europe during the Paleozoic, not much has been done in comparison on the Briançonnais basement rocks.Though partly transposed and re-equilibrated during the Meso-Cenozoic Alpine cycle, older fabrics and mineral remnants enable reconstructing part of their pre-Permian history. Our study is focused on three basement massifs of the Briançonnais domain, namely the Ambin, Vanoise and Ruitor massifs. These massifs are largely made of Cambrian to pre-Cambrian metasedimentary units cut by intrusives with variable chemical affinities, interpreted as related to the Cambro-Ordovician bimodal volcanism event. We herein present preliminary results on the (1) lithostratigraphy of this basement in the three different areas, (2) zircon U/Pb geochronology of key formations (e.g., metasediments and intrusives) and (3) the structuration of this basement crust despite the strong Alpine imprint
ADVANCED GAUSSIAN PROCESSES FOR THE SURROGATE MODELLING OF ENERGY SYSTEMS
No full textInternational audienceSurrogate models are efficient and accurate approximations of computationally expensive numerical models, derived from the statistical analysis of a limited number of model evaluations. Their primary purpose is to mitigate the computational burden. Surrogates are used for a wide variety of tasks such as sensitivity analysis (identifying the most influential parameters or parameter combinations), model calibration, uncertainty propagation and system optimization. Among other techniques, Gaussian Processes (GP) are especially appealing since they lie on sound theoretical foundations, are known to be flexible, rather accurate and, to some extent, they can be interpreted. This paper investigates to which extent advanced variants of GPs can improved the prediction when an exponentially increasing number of parameter combinations that must be explored. Multi-start strategy for the GP training, alternative objectives for GP training and linear embedding (i.e. considering a linear transformation of the variables) are investigated. Throughout this study, a dataset of 4589 time-dependent simulations of a geothermal absorption cooling system with 17 sizing variables is used. It turns out that none of these strategies can improve the Cross-Validation Root Mean Square Error when compared to standard GP training with Log Marginal Likelihood maximization, GP training with a single deterministic starting point, and no linear embedding. Applying standard GP algorithms and approaches seems sufficient for the surrogate modelling of energy systems, at least for the considered dataset
Agricultural dynamics in the semi-arid Northeast region of Brazil: issues for natural resources management and territorial governance
No full textInternational audienceCeará State (Northeast Brazil) was recently affected by a severe multi-year drought (2012-2018) that had drastic societal consequences. The agricultural sector was particularly impacted and agricultural trajectories have evolved accordingly. The dairy sector has been strongly consolidated among family farmers, as seeming to offer greater resilience to drought than irrigated crops. However, the consequences of these important agricultural dynamics on natural resource management, and particularly water, have not been adequately studied. This study aimed to explore how agricultural trajectories have been transformed and how this has affected the sustainability of water, land, and forest resource management. It then suggests a territorial governance organization to discuss related issues and collectively try to solve them. This study emphasizes two main agricultural transformations: (i) the increase in mechanized permanent cropping systems substituting the traditional shifting agriculture system with forest fallow rotation, and (ii) increased fodder production through 'passive irrigation' in lowlands and infiltration areas around dams. These processes support a strong dynamic of individual small dam building. The main issues of these transformations in terms of natural resource management concern soil health in a regional context of high vulnerability to desertification, and the strong mobilization of water in lowlands and small individual dams. Since these dams are located upstream of the State's strategic dams, they weaken its water security and open the challenge of finding trade-offs between upstream-downstream regions, macro-micro water infrastructures and agricultural development-water supply. To contribute to meeting this challenge, three participatory governance platforms articulated from the State to the local territories are being tested in an attempt to negotiate collective trade-offs on the use of natural resources, decompartmentalize public action targeting rural territories, and promote a bottom-up approach to territorial development