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geoscientificInformation

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    The Ploemeur-Guidel observatory (Britanny, France) is focusing on surface-depth relationships in a fractured crystalline geological context and oceanic climate. It is built on 2 sub-sites, one highly anthropized, the other in natural state. In Ploemeur, groundwater has been pumped since 1991, supplying more than 1 million m3 of clean drinking water annual at a sustainable rate. Such high productivity is explained the specific fractured network in granite and micaschists, draining deep geological layers (~400 m). Extracted water quality is very good, with limited nitrate concentration, in a region that has been strongly affected by widespread pollution. Guidel site is in a similar, but natural context. Deep iron-rich groundwater is upflowing, creating surface and deep groundwater-dependent ecosystems, and feeding a classified coastal wetland. Both sites have a very dense equipment to study rapid to long-term surface-depth exchanges: a flux tower, unsaturated zone monitoring, a network of ~50 shallow (<10m) and deep boreholes (>80m), hydrochemical, temperature and deformation. An well-characterized fractured experimental site offers the possibility to conduct experiments to test innovative instruments and develop new methodologies

  • Meteorological observations from weather stations interpolated on a 25x25 km grid, on a daily basis from 1979 to the last calendar year completed, for France. Meteorological observations are freely accessible via OGC SensorThings Standard service : https://frost.geosas.fr/agri4cast/v1.0/ Observed properties : - maximum air temperature (°C), - minimum air temperature (°C), - mean air temperature (°C), - mean daily wind speed at 10m (m/s), - vapour pressure (hPa), - sum of precipitation (mm/day), - potential evapotranspiration from a crop canopy (mm/day), - total global radiation (KJ/m2/day), More informations on Agri4cast Resources Portal : https://agri4cast.jrc.ec.europa.eu/DataPortal/Index.aspx

  • Hyperspectral data were obtained during an acquisition campaign led on Toulouse (France) urban area on July 2015 using Hyspex instrument which provides 408 spectral bands spread over 0.4 – 2.5 μ. Flight altitude lead to 2 m spatial resolution images. Supervised SVN classification results for 600 urban trees according to a 3 level nomenclature: leaf type (5 classes), family (12 and 19 classes) and species (14 and 27 classes). The number of classes differ for the two latter as they depend on the minimum number of individuals considered (4 and 10 individuals per class respectively). Trees positions have been acquired using differential GPS and are given with centimetric to decimetric precision. A randomly selected subset of these trees has been used to train machine SVM and Random Forest classification algorithms. Those algorithms were applied to hyperspectral images using a number of classes for family (12 and 19 classes) and species (14 and 27 classes) levels defined according to the minimum number of individuals considered during training/validation process (4 and 10 individuals per class, respectively). Global classification precision for several training subsets is given by Brabant et al, 2019 (https://www.mdpi.com/470202) in terms of averaged overall accuracy (AOA) and averaged kappa index of agreement (AKIA).

  • Hyperspectral ENVI standard simulated images. Spatial and spectral configurations generated correspond to ESA SENTINEL-2 instrument that was lunched on 2015, and HYPXIM sensor which was under study at that time.

  • Full hyperspectral VNIR-SWIR ENVI standard image obtained from the coregistration of both VNIR and SWIR ones through a signal aggregation process that allowed to obtain a synthetic VNIR 1.6 m spatial resolution image, with pixels exactly corresponding to natif SWIR image ones. First, a spatially resampled 1.6 m VNIR image was built, where output pixel values were calculated as the average of the VNIR 0.8 m pixel values that spatially contribute to it. Then, ground control points (GCP) were selected over both images and SWIR one was tied to the VNIR 1.6 m image using a bilinear resampling method using ENVI tool. This lead to a 1.6 m spatial resolution full VNIR-SWIR image.

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    This data set contains the temperature values at the position of 557 Pardosa saltans spiders, measured each minute during 90 minutes in a laboratory thermal gradient. Additionnal information on sex, development stage and morphology is provided for each individual. For details see Cabon et al 2023 in Journal of Thermal Biology: https://www-sciencedirect-com.passerelle.univ-rennes1.fr/science/article/pii/S0306456523002474 https://doi.org/10.1016/j.jtherbio.2023.103706 Link to the dataset: https://doi.org/10.48579/PRO/AF5COX

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    Fractured aquifers are known to be very heterogeneous with complex flow path geometries. Their characterization and monitoring remain challenging despite the importance to better understand their behavior at all spatial and temporal scales. Heat and correspondingly temperature data have gained much interest in recent years and are often used as a tracer for characterizing groundwater flows. In the current work,a fast computer code is developed using Ramey and Hassan and Kabir analytical solutions which converts the temperature profile to the flow rate profile along the borehole. The method developed is validated through numerical simulations. A global sensitivity study recognizes the media thermal properties as the most influential parameters. For testing the method in the field,fiber-optic distributed temperature sensing (FO-DTS) data were used to monitor the dynamic behavior of fractured aquifers at the borehole scale at the Ploemeur-Guidel field site in Brittany,France. DTS data are used to infer the flow rates in the different sections of a fractured wellbore (flow profile) and calculate the contribution of each fracture to the total flow. DTS data were acquired for about three days in three different hydraulic conditions corresponding to two different ambient flow conditions and one pumping condition. Flow profiling using distributed temperature data matches satisfactorily with results from heat-pulse flow metering performed in parallel for cross-checking. Moreover,flow profiling reveals the daily variations of ambient flow in this fractured borehole. Furthermore,it shows that during ambient flowing conditions,shallow and deep fractures contribute roughly equally to the total flow while during the pumping condition,the deepest fractures contribute more to the total flow,suggesting a possible reorganization of flow and hydraulic heads depending on the hydraulic conditions. Thus,although the proposed method (DTS data and proposed framework) may be costlier and is based on indirect characterization through temperature measurements,it provides real-time monitoring of complex fracture interactions and recharge processes in fractured media. Thus,this method allows for a full analysis of the temporal behavior of the system with a simple and fast analytical model. Furthermore,thanks to its narrow width,DTS can be used and installed in boreholes for long-term monitoring while heat-pulse flow metering may lead to head losses in the borehole and may not be always possible depending on some borehole conditions. One of the limitations of the approach proposed is the proper knowledge of the thermal properties of media required to infer the flow rate from the temperature. Nevertheless,surface rate measurement can be useful to constrain these properties and reduce the flow profiling uncertainty. Thus,the method proposed appears to be an interesting and complementary method for characterizing borehole flows and groundwater dynamics in fractured media such as for instance,monitoring the recharge dynamic

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    This borehole hydrogeophysical logging data include optical imaging,acoustic logging,induction and electrical resistivity,natural and spectral gamma radioactivity,fiber optic measurements an d multiparameter probe logs.

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    Available data include monitoring data (weather parameters,piezometric levels and pumping flow rates). Note that soil and flux tower parameters are available in the dataset Soil-atmosphere exchange.