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Er gibt einen \u00dcberblick \u00fcber die Kohlenstoffvorr\u00e4te bis 0,3 m, 1 m und 2 m Tiefe unter der Gel\u00e4ndeoberfl\u00e4che im Land Brandenburg. Die Karte basiert auf den Legendeneinheiten der Boden\u00fcbersichtskarte (B\u00dcK300) mit entsprechender Zuordnung von parametrisierten Fl\u00e4chenbodenformen, die durch Gel\u00e4nde- und Laboruntersuchungen bestimmt wurden. Dazu wurden f\u00fcr gleiche Horizont-Substrat-Kombinationen die entsprechenden Parameter (wie Corg-Gehalte) statistisch abgeleitet (i.d.R. der Medianwert). Die Abfolge von Horizont-Substrat-Kombinationen der Fl\u00e4chenbodenformen mit ihren Corg-Gehalten bildet die Grundlage f\u00fcr die Mengenberechnung in t/ha. Diese wurden in Stufen von je 30 t/ha klassifiziert. Gem\u00e4\u00df der INSPIRE-Datenspezifikation Soil (D2.8.III.3_v3.0) liegen die Inhalte der Boden\u00fcbersichtskarte INSPIRE-konform vor. Der WMS beinhaltet die folgenden Layer:      - SO.organicCarbonStock (30 cm): Kohlenstoffvorr\u00e4te beschreibt die im Boden gespeichert Menge an organischem Kohelnstoff Corg in t/ha bei einer Tiefe von 30 cm.     - SO.organicCarbonStock (100 cm): Kohlenstoffvorr\u00e4te beschreibt die im Boden gespeichert Menge an organischem Kohelnstoff Corg in t/ha bei einer Tiefe von 100 cm.     - SO.organicCarbonStock (200 cm): Kohlenstoffvorr\u00e4te beschreibt die im Boden gespeichert Menge an organischem Kohelnstoff Corg in t/ha bei einer Tiefe von 200 cm.     - SO.SoilBody: Abgegrenzter und hinsichtlich bestimmter Bodeneigenschaften und/oder r\u00e4umlicher Muster homogener Teil der Bodendecke.     ---      The compliant INSPIRE-WMS Soil / Kohlenstoffvorr\u00e4te im Boden Brandenburg is a view service that delivers data in the annex schema Soil (derived from the original data set: Carbon stocks in the soil Brandenburg). It provides an overview of the carbon stocks up to 0.3 m, 1 m and 2 m depth below ground level in the state of Brandenburg. The map is based on the legend units of the soil map (B\u00dcK300) with corresponding assignment of parameterized soil forms determined by field and laboratory investigations. For the same horizon-substrate combinations, the corresponding parameters (such as Corg contents) were statistically derived (usually the median value). The sequence of horizon-substrate combinations of the soil forms with their Corg contents formed the basis for the quantity calculation in t/ha. These were classified in steps of 30 t/ha each. The content of the soil map is compliant to the INSPIRE data specification for the annex theme Soil (D2.8.III.3_v3.0). The WMS includes the following layers:      - SO.organicCarbonStock (30 cm): Carbon stock indicates the amount of organic carbon stored in soil up to a depth of 2 m in t/ha (in this case 30 cm).      - SO.organicCarbonStock (100 cm): Carbon stock indicates the amount of organic carbon stored in soil up to a depth of 2 m in t/ha (in this case 100 cm).      - SO.organicCarbonStock (200 cm): Carbon stock indicates the amount of organic carbon stored in soil up to a depth of 2 m in t/ha (in this case 200 cm).      - SO.SoilBody: Part of the soil cover that is delineated and that is homogeneous with regard to certain soil properties and/or spatial patterns.", "formats": [{"name": "HTML"}], "keywords": ["bboxbebb", "boden", "bodenkunde", "bodenschutz", "brandenburg", "de", "depthinterval", "derivedsoilprofile", "geologie", "infomapaccessservice", "inspireidentifiziert", "interoperabel", "interoperability", "kohlenstoff", "kohlenstoffvorra\u0308te", "kohlenstoffvorra\u0308te-im-boden-brandenburg", "om_observation", "opendata", "organic-carbon-stock", "organiccarbonstock", "process", "soil", "soilbody", "soilderivedobject", "soillayer", "topsoil", "wms"], "contacts": [{"organization": "Landesamt f\u00fcr Bergbau, Geologie und Rohstoffe Brandenburg (LBGR)", "roles": ["creator"]}]}, "links": [{"href": "https://geoportal.brandenburg.de/detailansichtdienst/render?view=gdibb&url=https%3A%2F%2Fgeoportal.brandenburg.de%2Fgs-json%2Fxml%3Ffileid%3De2478c9e-97b5-44f3-a610-27dac1f362f5"}, {"href": "https://inspire.brandenburg.de/services/so_cvorr_wms?REQUEST=GetCapabilities&SERVICE=WMS"}, {"href": "http://data.europa.eu/88u/dataset/e2478c9e-97b5-44f3-a610-27dac1f362f5~~1"}, {"rel": "self", "type": "application/geo+json", "title": "e2478c9e-97b5-44f3-a610-27dac1f362f5", "name": "item", "description": "e2478c9e-97b5-44f3-a610-27dac1f362f5", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/e2478c9e-97b5-44f3-a610-27dac1f362f5"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "e2b12611-18ac-4831-868a-77b83d14e38f", "type": "Feature", "geometry": null, "properties": {"updated": "2025-09-06T06:22:12.685626", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Umidit\u00e0 del suolo (volumetrica) - (2025-09-05 ore 12 UTC).", "description": "Umidit\u00e0 del suolo (volumetrica). Corsa del 2025-09-05 ore 12 UTC - Valido dalle ore 12 UTC del 2025-09-05 alle ore 00 UTC del 2025-09-09. 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Corsa del 2025-04-10 ore 12 UTC - Valido dalle ore 12 UTC del 2025-04-10 alle ore 00 UTC del 2025-04-14. 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Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data reused from the BonaRes Data Centre www.bonares.de. This data were created as part of the BonaRes Module A-Project - InnoSoilPhos's research activities.\" Although every care has been taken in preparing and testing the data, the BonaRes Module A-Project - InnoSoilPhos and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the BonaRes Module A-Project - InnoSoilPhos and the BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The BonaRes Module A-Project - InnoSoilPhos and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner / author.", "updated": "2021-04-13", "type": "Dataset", "created": "2021-02-15", "language": "eng", "title": "Normalized FT-IR-spectra of pH-dependend phosphorus adsorption on goethite", "description": "P adsorption was investigated on synthetic and commercially available goethite (99 %, Alfa Aesar). The composition and crystallinity was confirmed by X-ray diffraction analyses with an Empyrean powder diffractometer (PANalytical) with Cu K\u03b1 radiation (\u03bb=0.15418 nm). The determination of the d-values and the verification of the calculated lattice parameter were performed using the XPowder software. The specific surface area of 17.2 m2 g-1 was determined with an Autosorb-1 (Quantachrome) using a five-point BET measurement and N2. The point of zero charge (PZC) was determined using potentiometric titration, which was 8.8 for pure goethite without adsorbed P.\nP adsorption on goethite was studied in a batch setup at the pH values of 4, 6, 8, 10, and 12. Therefore, goethite sample material (5 g) for the respective pH steps was adjusted to pH 4, 6, 8, 10, or 12, respectively, in ultrapure water with 0.01 M HCl (pH 4), or 0.1 M to 5 M KOH (pH 6 to 12) using a Potentiometric Compact Titrator G20S and combined DGi115-SC pH electrode (Mettler-Toledeo) under continuous stirring. For P adsorption, 0.5 g of goethite and 40 ml of a 0.15 mmol l-1 KH2PO4, solution, adjusted to pH 4, 6, 8, 10, or 12 as well, were mixed to achieve a solid-solution ratio of 1:80. The goethite- KH2PO4 mixture was shaken horizontally at 150 motions min-1 for 24 h. The P concentration in the solution was determined after reaction times of 2, 24, 48, and 168 h. The samples have been centrifuged for 15 min at 3500 rpm and the clear supernatant was filtrated by using P-poor Whatmann 512 \u00bd filters. The concentrations of P and Fe were determined using inductively coupled plasma atomic emission spectroscopy (ICP-AES). \nUnder real conditions in the soil, an influence of the P sorption on the pH is to be expected. Therefore, the pH change was taken into account both at the beginning and at the end of the adsorption experiments. The pH change was measured in a reference experiment that was treated exactly under the same conditions as P adsorption experiment. The amount of adsorbed P was referred to both the initial and the final pH.\nFor FT-IR spectroscopic measurements, the solid goethite samples after an adsorption time of 2 and 168 h were dried for 24 h at 40\u00b0C, and stored in a desiccator. The samples were analyzed without further treatment prior to FT-IR measurements. IR spectroscopic analyses were carried out by measurement of the absorbance in the FT-IR Drift mode (Tensor 27 HTS-XT, Bruker) and a wavenumber range from 400 to 4000 cm-1. The spectrum of each treatment was created by generate the average of the 2 replicated samples by using the software Essential FTIR\u00ae (Operant LLC), where each sample included 40 scans. For evaluation, all spectra together were truncated in the range 1300 to 800 cm-1, baseline corrected, and normalized with respect to the highest absorbance.\nAfter 2 h adsorption time, the amount of adsorbed P was 0.52 \u00b5mol m-2 at pH 4, 0.65 \u00b5mol m-2 for pH 6, 0.58 \u00b5mol m-2 for pH 8, 0.29 \u00b5mol m-2 for pH 10, and 0.14 \u00b5mol m-2 for pH 12. Considering the initial pH, P adsorption on goethite after an adsorption time of 168 h was highest for pH 8, yielding a P surface coverage of 0.75 \u00b5mol m-2 after a reaction time of 168 h, followed by pH 6 with 0.72 \u00b5mol m-2, and pH 4 with 0.68 \u00b5mol m-2. The extent of adsorption decreased from pH 8 to 10 with 0.58 \u00b5mol m-2 and was lowest for pH 12 with 0.18 \u00b5mol m-2. The solution pH decreased for the initial pH 4 to 3.9., and for the initial pH of 6, the final pH was 5.0. For initial pH values 8.0 and 10.0, the corresponding final pH values were 6.7 and 7.6, respectively. At initial pH 12.0, the decrease of the solution pH weakened with a final pH of 11.6.\n\n\nResearch domain: Soil Sciences\n\nResearch question: How does the solution-pH affect the amount and binding motiv of adsorbed phosphorus on the goethite surface?", "formats": [{"name": "CSV"}], "keywords": ["Soil", "Fourier transforms", "goethite", "phosphorus", "absorbance", "FT-IR spectrsocopy", "goethite", "phosphorus", "adsorption", "absorbance", "opendata", "Boden", "Phosphor", "Adsorption", "Spektroskopie"], "contacts": [{"name": "Stella Gypser", "organization": "Brandenburgische Technische Universit\u00e4t Cottbus-Senftenberg", "position": "Researcher", "roles": ["dataCollector"], "phones": [{"value": "00 49 (0) 355 693318"}], "emails": [{"value": "stella.gypser@b-tu.de"}], "addresses": [{"deliveryPoint": ["Konrad-Wachsmann-Allee 6"], "city": "Cottbus", "administrativeArea": "Brandenburg", "postalCode": "03046", "country": "Germany"}], "links": [{"href": {"url": "https://orcid.org", "protocol": null, "protocol_url": "", "name": "0000-0002-4765-8067", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "Stella Gypser", "organization": "Brandenburgische Technische Universit\u00e4t Cottbus-Senftenberg", "position": "Researcher", "roles": ["author"], "phones": [{"value": "00 49 (0) 355 693318"}], "emails": [{"value": "stella.gypser@b-tu.de"}], "addresses": [{"deliveryPoint": ["Konrad-Wachsmann-Allee 6"], "city": "Cottbus", "administrativeArea": "Brandenburg", "postalCode": "03046", "country": "Germany"}], "links": [{"href": {"url": "https://orcid.org/", "protocol": null, "protocol_url": "", "name": "0000-0002-4765-8067", "name_url": "", "description": "ORCID", "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}, {"name": "BonaRes Data Centre", "organization": "Leibniz Centre for Agricultural Landscape Research (ZALF)", "position": "Research Platform 'Data Analysis & Simulation' - WG Geodata", "roles": ["publisher"], "phones": [{"value": "+49 33432 82 171"}], "emails": [{"value": "bonares-datenzentrum@zalf.de"}], "addresses": [{"deliveryPoint": ["Eberswalder Strasse 84"], "city": "M\u00fcncheberg", "administrativeArea": "Brandenburg", "postalCode": "15374", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Dirk Freese", "organization": "Brandenburgische Technische Universit\u00e4t Cottbus-Senftenberg", "position": "Researcher", "roles": ["workPackageLeader"], "phones": [{"value": "00 49 (0) 355 694238"}], "emails": [{"value": "dirk.freese@b-tu.de"}], "addresses": [{"deliveryPoint": ["Konrad-Wachsmann-Allee 6"], "city": "Cottbus", "administrativeArea": "Brandenburg", "postalCode": "03046", "country": "Germany"}], "links": [{"href": null}]}, {"name": "Leinweber, Peter", "organization": "University of Rostock", "position": "Professor", "roles": ["projectLeader"], "phones": [{"value": "+49 381 498 3120"}], "emails": [{"value": "peter.leinweber@uni-rostock.de"}], "addresses": [{"deliveryPoint": ["Justus-von-Liebig-Weg 6"], "city": "Rostock", "administrativeArea": "Mecklenburg-Vorpommern", "postalCode": "18051", "country": "Germany"}], "links": [{"href": null}]}, {"organization": "Brandenburgische Technische Universit\u00e4t Cottbus-Senftenberg", "roles": ["contributor"]}]}, "links": [{"href": "https://maps.bonares.de/mapapps/resources/apps/bonares/index.html?lang=en&mid=e2d7a740-8c6e-4fc1-92db-21bf6d95cd0d", "rel": "download"}, {"rel": "self", "type": "application/geo+json", "title": "e2d7a740-8c6e-4fc1-92db-21bf6d95cd0d", "name": "item", "description": "e2d7a740-8c6e-4fc1-92db-21bf6d95cd0d", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/e2d7a740-8c6e-4fc1-92db-21bf6d95cd0d"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-04-13T00:00:00Z"}}, {"id": "e31d13f6-e692-4954-9c80-d5150b60396b", "type": "Feature", "geometry": null, "properties": {"updated": "2025-06-09T11:21:03.698613Z", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Umidit\u00e0 del suolo (volumetrica) - (2025-06-09 ore 00 UTC).", "description": "Umidit\u00e0 del suolo (volumetrica). 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The Irish Soil Information System adopted a unique methodology combining digital soil mapping techniques with traditional soil survey application. Developing earlier work conducted by An Foras Tal\u00fantais, the project generated soil-landscape models for previously surveyed counties. These soil-landscape (\u2018soilscape\u2019) models formed the basis for training statistical \u2018inference engines\u2019 for predicting soil mapping units, checked during field survey. 213 soil series are identified, each with differing characteristics, having contrasting environmental and agronomic responses. Properties were recorded in a database able to satisfy national and EU policy requirements. The Irish soil map and related soil property data will also serve public interest, providing the means to learn online about Irish soil resources. Use the Symbology layer file 'SOIL_SISNationalSoil.lyr' based on Value Field 'Association_Unit'. SIS SOIL DRAINAGE:In Ireland, soil drainage category is considered to have a predominant influence on soil processes (Schulte et al., 2012). The maritime climate of Ireland drives wet soil conditions, such that excess soil moisture in combination with heavy textured soils is considered a key constraint in relation to achieving productivity and environmental targets. Both soil moisture content and the rate at which water drains from the soil are critical indicators of soil physical quality and the overall functional capacity of soil. Therefore, a natural extension to the Irish Soil Information System included the development of an indicative soil drainage map for Ireland. The soil subgroup map was used to develop the indicative drainage map, based on diagnostic criteria relating to the subgroup categorization. Use the Symbology layer file 'SOIL_SISSoilDrainage.lyr' based on Value Field 'Drainage'. SIS SOIL DEPTH: Soil depth is a measure of the thickness of the soil cover and reflects the relationship between parent material and length of soil forming processes. Soil depth determines the potential rooting depth of plants and any restrictions within the soil that may hinder rooting depth. Plants derive nearly 80 per cent of their water needs from the upper part of the soil solum, i.e. where the root system is denser. The rooting depths depend on plant physiology, type of soil and water availability. Generally, vegetables (beans, tomatoes, potatoes, parsnip, carrots, leek, broccoli, etc.) are shallow rooted, about 50\u201360 cm; fruit trees and some other plants have medium rooting depths, 70\u2013120 cm and other crops such as barley, wheat, oats, and maize may have deeper roots. Furthermore, rooting depths vary according to the age of the plants. The exact soil depth is difficult to define accurately due to its high variability across the landscape. The effective soil depth can be reduced by the presence of bedrock or impermeable layers. Use the Symbology layer file 'SOIL_SISSoilDepth.lyr' based on Valued Field 'Depth'. SIS SOIL TEXTURE:Soil texture is an important soil characteristic that influences processes such as water infiltration rates, rootability, gas exchanges, leaching, chemical activity, susceptibility to erosion and water holding capacity. The soil textural class is determined by the percentage of sand, silt, and clay. Soil texture also influences how much water is available to the plant; clay soils have a greater water holding capacity than sandy soils. Use the Symbology layer file 'SOIL_SISSoilTexture.lyr' based on Value Field 'Texture'. SIS SOIL SOC:In the previous national soil survey conducted by An Foras Taluntais, 14 counties were described in detail with soil profile descriptions provided for the representative soil series found within a county. Soil samples were taken at each soil horizon to a depth of 1 meter and analyses performed for a range of measurements, including soil organic carbon, texture, cation exchange capacity, pH; however in most cases no bulk density measurements were taken. This meant that while soil organic carbon concentrations were available this could not be related to a stock for a given soil series. In 2012/2013, 246 profile pits were sampled and analysed as part of the Irish Soil Information System project to fill in gaps in the description of representative profile data for Ireland. 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Reports, articles, papers, scientific and non - scientific works of any form, including tables, maps, or any other kind of output, in printed or electronic form, based in whole or in part on the data supplied, must contain an acknowledgement of the form: \"Data reused from the BonaRes Data Centre www.bonares.de. This data were created as part of the BonaRes Module A-Project - SUSALPS's research activities.\" Although every care has been taken in preparing and testing the data, the BonaRes Module A-Project - SUSALPS and the BonaRes Data Centre cannot guarantee that the data are correct; neither does the BonaRes Module A-Project - SUSALPS and the BonaRes Data Centre accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The BonaRes Module A-Project - SUSALPS and BonaRes Data Centre will not be responsible for any direct or indirect use which might be made of the data. The access to this data is restricted during embargo time. If prior access is requested, contact the data owner / author.", "updated": "2021-04-13", "type": "Dataset", "created": "2021-02-18", "language": "eng", "title": "Gross rates of N mineralization and nitrification", "description": "Data for the calculation of gross rates of mineralization and nitrification based on the 15N pool dilution method\n\nResearch domain: Soil nitrogen\n\nResearch question: The data set contains fundamental information for environmental sciences and, thus, serves as the base for many research questions. 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Corsa del 2025-07-11 ore 12 UTC - Valido dalle ore 12 UTC del 2025-07-11 alle ore 00 UTC del 2025-07-15. 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Such an acquisition\u2014in its complexity of formulation, definitions as well as skills and abilities\u2014is a challenge for educational stakeholders. At the same time, the search for effective solutions, approaches and models for implementation in the educational process remains open and needs to be analysed and evaluated. This paper aims to analyse the benefits of learning through gaining experience with the aim of mastering entrepreneurship as one of the key competencies required for self-actualisation, lifelong development and achieving global competitiveness in the labour market. It describes, analyses and identifies elements of experiential learning as a prerequisite for the acquisition of entrepreneurial competence. The paper presents the results of research conducted on a specific educational model for entrepreneurship: The Centre for Entrepreneurial Excellence of Vara\u017edin County (Croatia). From the analysis and interpretation of the obtained results, the findings show that the concepts of experiential learning and teaching at the Centre have been implemented through didactic-methodical work with students. Thus, these concepts are an effective approach for the development of entrepreneurship among students", "keywords": ["entrepreneurial competence", ": experiential pedagogy", "4. Education", "8. 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Modello meteorologico WRF (Weather Research and Forecasting model), core ARW (versione 3.2) con risoluzione spaziale a 3km, risoluzione temporale 60 ore, intervallo 1 ora.", "formats": [{"name": "PNG"}], "keywords": ["120000", "2025-07-03", "20250703t120000000z", "3km", "arw", "below", "between", "content", "depths", "it", "lamma", "layer", "moisture", "soil", "surface", "two", "volumetric"], "contacts": [{"organization": "regione-toscana", "roles": ["creator"]}]}, "links": [{"href": "http://geoportale.lamma.rete.toscana.it/geoserver/ARW_3KM_RUN12/ows"}, {"href": "http://www.lamma.rete.toscana.it/"}, {"href": "https://dati.toscana.it/dataset/modello-wrf-arw-a-3km-umidita-del-suolo-volumetrica-2025-07-03-ore-12-utc#"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z_150_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z_25_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z_5_0.zip"}, {"href": "https://geoportale.lamma.rete.toscana.it/download/arw_3km_run12/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z/arw_3km_Volumetric_soil_moisture_content_layer_between_two_depths_below_surface_layer_20250703T120000000Z_70_0.zip"}, {"href": "http://data.europa.eu/88u/dataset/ebe04ae7-ef30-472c-9c7c-cdd8739bd38a"}, {"rel": "self", "type": "application/geo+json", "title": "ebe04ae7-ef30-472c-9c7c-cdd8739bd38a", "name": "item", "description": "ebe04ae7-ef30-472c-9c7c-cdd8739bd38a", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/ebe04ae7-ef30-472c-9c7c-cdd8739bd38a"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"null": "date"}}, {"id": "ec96be43-c10a-4580-8b6f-4db46ec29bbd", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[7.5, 30.2], [7.5, 37.4], [11.6, 37.4], [11.6, 30.2], [7.5, 30.2]]]}, "properties": {"themes": [{"concepts": [{"id": "geoscientificInformation"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}, {"concepts": [{"id": "Soil science"}], "scheme": "Stratum"}, {"concepts": [{"id": "Africa"}, {"id": "North Africa"}, {"id": "Tunisia"}], "scheme": "Region"}], "updated": "2022-01-17T07:49:57", "type": "Dataset", "language": "eng", "title": "SOTER-based soil parameter estimates (SOTWIS) for Tunisia", "description": "This harmonized set of soil parameter estimates for Tunisia. It has been derived from the 1:1 million scale Soil and Terrain Database for the country (SOTER_TN, ver. 1.0) and the ISRIC-WISE soil profile database, using standardized taxonomy-based pedotransfer (taxotransfer) procedures. \n\nThe land surface of Tunisia, covering some 164,150 km2, has been characterized in SOTER_TN using 250 unique SOTER units. Each map unit consists of up to four different soil components. In so far as possible, each soil component has been characterized by a regionally representative profile, selected and classified by national soil experts (see Dijkshoorn et al. 2008). Conversely, in the absence of any measured legacy data, soil components were characterized using synthetic profiles for which only the FAO-Unesco (1988) classification is known.\n\nSoil components in SOTER_TN have been characterized using 100 profiles of which 44 are synthetic. The latter represent some 59 per cent of the territory. Comprehensive sets of measured attribute data are not available for most of the measured profiles (56) collated in SOTER_TN, as these were not considered in the source materials. Consequently, to permit modelling, gaps in the soil analytical data have been filled using consistent taxotransfer procedures. Modal soil property estimates necessary to populate the taxotransfer procedure were derived from statistical analyses of soil profiles held in the ISRIC-WISE database \u2015 the current taxotransfer procedure only considers profiles in WISE that: (a) have FAO soil unit names identical to those mapped for Tunisia in SOTER, and (b) originate from regions having similar K\u00f6ppen climate zones (n= 3566). \n\nProperty estimates are presented for 18 soil variables by soil unit for fixed depth intervals of 0.2 m to 1 m depth: organic carbon, total nitrogen, pH(H2O), CECsoil, CECclay, base saturation, effective CEC, aluminium saturation, CaCO3 content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity (ECe), bulk density, content of sand, silt and clay, content of coarse fragments (less than 2 mm), and volumetric water content (-33 kPa to -1.5 MPa). These attributes have been identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil carbon stocks and change, and studies of global environmental change. \n\nThe soil property estimates can be linked to the spatial data (map), using GIS, through the unique SOTER-unit code; database applications should consider the full map unit composition and depth range. \n\nThe derived data presented here may be used for exploratory assessments at national scale or broader (greater than 1:1 000 000). They should be seen as best estimates based on the current, still limited, selection of soil profiles in SOTER_TN and data clustering procedure \u2015 the type of taxotransfer rules used to fill gaps in the measured data has been flagged to provide an indication of confidence in the derived data", "formats": [{"name": "zip"}, {"name": "WWW:DOWNLOAD-1.0-ftp--download"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["calcium", "carbon", "cation exchange capacity", "electrical conductivity", "nitrogen", "organic matter", "bulk density", "soil profiles", "pH", "salinity", "texture", "water holding capacity", "nutrients", "Soil science", "Africa", "North Africa", "Tunisia"], "contacts": [{"name": "Niels Batjes", "organization": "ISRIC - World Soil Information", "position": "Senior Soil Scientist", "roles": ["Author"], "phones": [{"value": null}], "emails": [{"value": "niels.batjes@isric.org"}], "addresses": [{"deliveryPoint": ["PO Box 353"], "city": "Wageningen", "administrativeArea": null, "postalCode": "6700AJ", "country": "Netherlands"}], "links": [{"href": null}]}, {"name": "Data infodesk", "organization": "ISRIC - World Soil Information", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "data@isric.org"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": null, "country": null}], "links": [{"href": null}]}], "denominator": "1000000"}, "links": [{"href": "https://files.isric.org/public/sotwis/SOTWIS_TN.zip", "name": "Download", "protocol": "WWW:DOWNLOAD-1.0-ftp--download", "rel": "download"}, {"href": "https://isric.org/projects/harmonized-continental-soter-derived-database-sotwis", "name": "Project webpage", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://isric.org/sites/default/files/isric_report_2010_01.pdf", "name": "Report", "protocol": "WWW:LINK-1.0-http--related", "rel": "information"}, {"href": "https://files.isric.org/public/thumbnails/sotwis/SOTWIS_TN.jpg", "name": "preview", "description": "Web image thumbnail (URL)", "protocol": "WWW:LINK-1.0-http--image-thumbnail", "rel": "preview"}, {"rel": "self", "type": "application/geo+json", "title": "ec96be43-c10a-4580-8b6f-4db46ec29bbd", "name": "item", "description": "ec96be43-c10a-4580-8b6f-4db46ec29bbd", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/ec96be43-c10a-4580-8b6f-4db46ec29bbd"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["1963-01-01T00:00:00Z", "2004-01-01T00:00:00Z"]}}, {"id": "ecf3b7e9-978d-481e-aee5-8a2184335e33", "type": "Feature", "geometry": null, "properties": {"updated": "2025-05-30T06:27:02.034340", "type": "Dataset", "language": "it", "title": "MODELLO WRF-ARW a 3km - Umidit\u00e0 del suolo (volumetrica) - (2025-05-29 ore 12 UTC).", "description": "Umidit\u00e0 del suolo (volumetrica). Corsa del 2025-05-29 ore 12 UTC - Valido dalle ore 12 UTC del 2025-05-29 alle ore 00 UTC del 2025-06-02. 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Corsa del 2025-04-25 ore 12 UTC - Valido dalle ore 12 UTC del 2025-04-25 alle ore 00 UTC del 2025-04-29. 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Corsa del 2025-07-05 ore 12 UTC - Valido dalle ore 12 UTC del 2025-07-05 alle ore 00 UTC del 2025-07-09. 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The map is based on the legend units of the soil map (B\u00dcK300) with corresponding assignment of parameterized soil forms determined by field and laboratory investigations. For this purpose, the corresponding parameters (soil type, humus content, pH value) were statistically derived for the same horizon-substrate combinations (usually the median value). The sequence of horizon-substrate combinations in the soil forms with their parameters (soil type, humus content, pH value, upper limit of the Go horizon) formed the basis for the calculation of the relative sorption strength for heavy metals (see Methodendokumentation Bodenkunde, Hennings 2000, methods 7.1 to 7.3). The content of the soil map is compliant to the INSPIRE data specification for the annex theme Soil (D2.8.III.3_v3.0). 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The purpose of this study was to investigate the impacts of agricultural intensification in Europe, and to understand its environmental impact. Metal concentrations in soils were used from two consecutive Europe-wide geochemical surveys, sampled in 1998 (FOREGS survey) and 2009 (GEMAS survey). For land use, the 2010 Eurostat data were used. \n\nThe metals included in this data set are cadmium (Cd), copper (Cu), lead (Pb) and zinc (Zn). The results on the fate of Nitrogen (N) and Phosphorus (P) are included in a separate dataset. Cu and Zn are minor nutrients but at high inputs, they may cause adverse impacts on soil biodiversity, whereas Cd and Pb are toxic metals that may lead to soil degradation, by both affecting soil biodiversity and food quality. Metal budgets based on spatially explicit input and output data were calculated using the INTEGRATOR model; approximately 40,000 so-called NCUs as unique combinations of soil type, administrative region, slope class and altitude class were used. Available critical limits for food, water and soil organisms, from different existing regulations and studies, were converted to soil property-dependent critical metal concentrations (soil-based quality standards), which were then used to calculate critical metal inputs. \n\nThe results allow for the first time to identifying spatial hot spots for critical environmental impact of soil pollution for the four most abundant heavy metals. It thus informs policy processes important for planning and guiding sustainable agriculture and soil management. The work is methodologically novel, as it applies endpoint risk to thresholds in soils, and thus guides future impact studies. 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