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289 results for “Regional assessment”
Figure 1. from: Unicorn–Open science for assessing environmental state, human health and regional economy - Research Ideas and Outcomes 2: e9232 (16 May 2016) https://doi.org/10.3897/rio.2.e9232
Figure 1. - Links and interactions between the work packages
Geospatial dataset for Cumulative Impact assessment, Sea Use conflict analysis and Marine Ecosystem Services assessment in the Adriatic Ionian Region
<p>Geospatial dataset for Cumulative Impact assessment, Sea Use conflict analysis and Marine Ecosystem Services assessment in the Adriatic Ionian Region (reference year 2014).</p> <p>The datasets are derived from ADRIPLAN Portal (http://data.adriplan.eu/).</p>
RAM Legacy Stock Assessment Database Geospatial Regions
<p>This data archive describes region definitions for the RAM Legacy Stock Assessment Database. Within the RAM Legacy database, stock assessments are associated with named areas. We approximate coordinates and bounding boxes for each of these areas, using country EEZs and fishing area shapefiles when appropriate. In addition, we develop a simple language to encode the GIS shapes of the areas, along with an interpreter to translate these codes into polygons. The syntax supports using political entities, shapefile regions, circles and rectangles, clipped versions of these, and combinations of these.</p> <p>The archive contains the following contents:</p> <p> - syntax.pdf: This document describes the geocoding syntax, and lists all of the geocoding descriptions for the assessment regions.</p> <p> - results: This folder contains a shapefile of assessment regions (ram.shp) and a summary file of each region's centroid and size.</p> <p> - sources: This folder contains shapefiles for FAO regions and New Zealand fishing regions, used by the syntax system, and latlon.csv which contains the region descriptions for each assessment region.</p> <p> - code: load_areas.R contains functions that interpret the geocoding syntax and genshape.R generates the ram.shp shapefile.</p>
Current and Future Flood maps for Flood risk assessment under the Shared Socioeconomic Pathways in the Greater Accra region, Ghana
<p>The study used 15 flood conditioning factors in simulating current and future flood conditions under the SSP scenarios using the Frequency Ratio (FR) model </p>
Assessing Heavy Metal Contamination in Agricultural Soils: A Predictive Model Integrating GIS Tools and Probability-Risk Matrix – Case Study: Guarda Region, Portugal
<p>In these files we can find the final risk map of heavy metal contamination for the guarding area in Portugal obtained according to the methodology explained in the paper "Assessing Heavy Metal Contamination in Agricultural Soils: A Predictive Model Instegrating GIS Tools and Probability-Risk Matrix - Case Study: Guarda Region (Portugal)</p> <p>Final Risk Equal.tiff: GeoTiff with a pixel size of 30m. EPSG:3763 - ETRS89 / Portugal TM06</p> <p>Also attached is the symbolisation for the image in .qml (Quantum GIS Layer Style File) format.</p> <p>A file called RISK RECLASS is also available, where you can find the risk classification maps for each of the studied factors: </p> <ul> <li>Proximity to roads</li> <li>Proximity to industrial areas</li> <li>Ph</li> <li>Soil organic content</li> <li>Slope</li> <li>Soil texture</li> <li>Mining extraction areas </li> <li>Drainage</li> </ul> <p>finally a DATABASE file where the data of the 360 points for the calculation of the risk maps can be found. </p>
Dataset related to the publication "An Invar-based dual Fabry–Perot cavity refractometer for assessment of pressure with a pressure independent uncertainty in the sub-mPa region"
<p>The data set consists of; The published paper, all figures that present measurement or simulation data in .png and .fig format and the underlying data plotted in the figures in text format.<span> </span>The published plots were generated from the fig files. The text files were generated by reading the plotted data from the fig files. The files are named Fig_XX were XX corresponds to the figure number in the publication.<span> </span>The format of the text file is as follows. Before every data set there is a header consisting of; The number of the subplot where the data is plotted (Plot: XX), the number of the data set in the sub plot (DataSet: XX), and the color of the line or marker in the plot (Color: XX). The description of what each color represents can be found in the publication.</p>
Data used in "The daily-resolved Southern Ocean mixed layer: regional contrasts assessed using glider observations"
<p>These are the data used in the analysis and creation of figures in du Plessis et al. 2022: <em>The daily-resolved Southern Ocean mixed layer: regional contrasts assessed using glider observations</em> in support of open-code, transparency, and repeatability.</p> <p>Abstract:</p> <p>Water mass transformation in the Southern Ocean is vital for driving the large-scale overturning circulation, which transports heat from the surface to the ocean interior. Using profiling gliders, this study investigates the role of summertime buoyancy forcing and wind-driven processes on the intraseasonal (1-10 days) mixed layer thermohaline variability in three Southern Ocean regions southwest of Africa important for water mass transformation - the Subantarctic Zone (SAZ), Polar Frontal Zone (PFZ) and Marginal Ice Zone (MIZ). At intraseasonal time scales, heat flux was shown as the main driver of buoyancy gain in all regions. In the SAZ and MIZ, shallow mixed layers and strong stratification enhanced mixed layer buoyancy gain by trapping incoming heat, while buoyancy loss resulted primarily from the entrainment of cold, salty water from below. In the PFZ, rapid mixing linked to Southern Ocean storms set persistently deep mixed layers and suppressed mixed layer intraseasonal (1-10 days) thermohaline variability. In the polar regions, lateral stirring of meltwater from seasonal sea-ice melt dominated daily mixed layer salinity variability. We propose that these meltwater fronts are advected to the PFZ during late summer, indicating the potential for seasonal sea-ice freshwater to impact a region where the upwelling limb of overturning circulation reaches the surface. This study reveals a regional dependence of how the mixed layer thermohaline properties respond to small spatio-temporal processes, emphasizing the importance of surface forcing occurring between 1-10 days on the mixed layer water mass transformation in the Southern Ocean.</p> <p><strong>Related code:</strong> The accompanying code can be found at: <a href="http://doi.org/10.5281/zenodo.5076119">http://doi.org/10.5281/zenodo.5076119. </a>Navigate to github.com/marcelduplessis/duplessis-2021-SO-thermohaline for the latest version</p>
Resolved EXiobase (REX II) with regionalized biodiversity loss impact assessment of global mining – second version of a highly-resolved MRIO database for the year 2014
<p>This repository provides a new version of the highly-resolved global multi-regional input-output database called REX II (Resolved EXiobase) for the year 2014 with improved data quality for all mining and metals processing sectors, including a regionalized biodiversity impact assessment for all mining sectors. This regionalized impact assessment is based on the global mining area data set of Maus et al (2020). The database REX II is described in the study <em>"Hotspots of mining-related biodiversity loss in global supply chains and the potential for reduction by renewable electricity".</em></p> <p>Study: <a href="https://doi.org/10.1021/acs.est.2c04003">https://doi.org/10.1021/acs.est.2c04003</a></p> <p>Open-access preprint: <a href="https://doi.org/10.31223/X5T064">https://doi.org/10.31223/X5T064</a></p> <p> </p> <p>An earlier version of this database (REX I) with time series from 1995–2015 is provided under: <a href="http://doi.org/10.5281/zenodo.3993659">http://doi.org/10.5281/zenodo.3993659</a> and described here: <a href="https://doi.org/10.1016/j.scitotenv.2020.142587">https://doi.org/10.1016/j.scitotenv.2020.142587</a></p> <p> </p> <p>The repository REXIA_2014 contains the following files (<em>*.mat-files</em>) referring to the year 2014:<br> T_REXIA: transaction matrix<br> Y_REXIA: final demand matrix<br> Ext_REXIA and Ext_hh_REXIA: the satellite matrices of the economy and the final demand<br> The labels of all matrices are described in the excel file Labels_REXIA.xlsx</p>
Wave climate simulations for Denmark - for paper 'Coinciding storm surge and wave setup: A regional assessment of sea level rise impact'
<p>This wave climate dataset are the results for the paper titled 'Coinciding storm surge and wave setup: A regional assessment of sea level rise impact'.</p> <p>The operational wave forecasting service provided by DMI-WAM uses the WAM Cycle version 4.5.4, a third-generation spectral wave model. DMI-WAM is used for the wave climate simulations. The meteorological forcing used in this study was obtained from the regional climate model DMI-HIRHAM, developed by the Danish Meteorological Institute (DMI). It is a component of the CORDEX (Coordinated Regional Climate Downscaling Experiment) ensemble in Europe. Regarding the selection of the time frame and IPCC scenarios in our study, we adhered to the recommendations provided by municipalities. Municipalities are keenly interested in obtaining near-future wind wave data for the specific purpose of using them for risk management. Therefore, the examination of forthcoming weather extremes in the near future within the context of the high greenhouse gas emission scenario (RCP8.5 scenario) is of significance within this investigation. We conduct simulations that encompass two distinct time periods: the historical period spanning from 1976 to 2005, and the near-future period from 2041 to 2070. We analyse the WAM model results for wave climate under both present climate conditions (1976-2005) and future climate scenarios (2041-2070) under the RCP8.5 scenario. Furthermore, note that while our wave climate simulations provide valuable insights into the dynamics of wind-induced waves, the mean SLR is not explicitly taken into account. The mean SLR component is considered in the storm surge simulations.</p> <p>Description of files:</p> <p><a href="../api/records/11052226/draft/files/sla.swh.slope.hist.final.max.nc/content" target="_blank" rel="noopener noreferrer">sla.swh.slope.hist.final.max.nc</a> - Maximum sea level, significant wave height, wave length and slope for the historical period.</p> <p><a href="../api/records/11052226/draft/files/sla.swh.slope.rcp85.final.max.MSLR35.nc/content" target="_blank" rel="noopener noreferrer">sla.swh.slope.rcp85.final.max.MSLR35.nc</a> - Maximum sea level, significant wave height, wave length and slope for the RCP8.5 period.</p> <p><a href="../api/records/11052226/draft/files/wavesetup.hist.final.max.nc/content" target="_blank" rel="noopener noreferrer">wavesetup.hist.final.max.nc</a> - Maximum wave setup for the historical period.</p> <p><a href="../api/records/11052226/draft/files/wavesetup.rcp85.final.max.MSLR35.nc/content" target="_blank" rel="noopener noreferrer">wavesetup.rcp85.final.max.MSLR35.nc</a> - Maximum wave setup for the RCP8.5 period.</p> <p><a href="../api/records/11052226/draft/files/wam.grib.his.swh.98p.nc/content" target="_blank" rel="noopener noreferrer">wam.grib.his.swh.98p.nc</a> - 2% exceedence of significant wave height for the historical period.</p> <p><a href="../api/records/11052226/draft/files/wam.grib.rcp8.swh.98p.nc/content" target="_blank" rel="noopener noreferrer">wam.grib.rcp8.swh.98p.nc</a> - 2% exceedence of significant wave height for the RCP8.5 period.</p>
Considerations for high-resolution regional meteorological wind modelling over complex terrain: a typhoon case study for assessing forestry damage (data)
<p>This is the experiment data.</p> <p>The Weather Research and Forecasting (WRF) model is a popular and easily used as a numerical weather prediction (NWP) model, but configuring WRF to produce accurate results can be time-consuming. This is especially so when simulating extreme events, over complex terrain, or at high resolutions. In this study, a strong wind event from Tropical Cyclone (TC) Thad in year 1981 was simulated at 200 m resolution over an experiment forest in a mountainous region of Hokkaido island, Japan. The simulation configuration is challenging, in order to cover a larger area to produce a TC with appropriate track and intensity, and at the same time to resolve the smallest domain of sub-km grid spacing with computational stability. A mixed nesting method was applied with two-way nesting up for the first three domains, followed a separate simulation over the smallest domain. The mixed method could produce 10 min wind speed distributions similar to that of the full simulation with two-way nesting of all four domains, if a 30-minute boundary update interval was used for the separate simulation. Mixed nesting improves the efficiency of the simulation process, since the larger phenomenon scale and smaller human impact scale can be tuned separately. </p>
Regional Assessments of Glacier Mass Change (RAGMAC) experiment dataset
<p>This repository contains the dataset that was distributed to the participants of the Regional Assessments of Glacier Mass Change (RAGMAC) working<br>group of the International Association of Cryospheric Science (IACS, 2023).</p> <p>In short, the dataset is divided in 5 study sites: Hintereisferner (Austrian Alps - HEF_AT), Grosser Aletschgletscher (Swiss Alps - ALE_CH), Vestre Svartisen ice cap (Scandes, Norway - VES_NO), Baltoro glacier (Karakoram, Pakistan - BAL_PK), and the Northern Patagonian Icefield (Andes, Chile - NPI_CL).</p> <p>For each site, we provide series of Digital Elevation Models (DEMs) derived from SRTM, ASTER and TanDEM-X sensors. Additionally, we provide glacier outlines extracted from the Randolph Glacier Inventory version 6, for all glaciers in the study area, and selected glaciers for which participants were required to calculate the geodetic mass balance.</p> <p>Additionally, we provide the airborne DEMs that were used as reference data to evaluate the spaceborne DEMs. These are available for the cases HEF_AT, ALE_CH and VES_NO, all included in the single zip file “validation_data.zip”.</p> <p>For details on the dataset, experiment and any reference to this dataset, please refer to the following publication: Piermattei et al. (2024) "Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data" The Cryosphere, DOI: <a href="https://doi.org/10.5194/egusphere-2023-2309">10.5194/egusphere-2023-2309</a> (to be updated upon final acceptance).</p> <p><strong>NOTE: </strong>As of July 2024, the TanDEM-X DEMs cannot be publicly shared due to license restrictions. We are discussing future opportunities to share the data in a future version of this repository.</p> <p> </p>
Regional-scale assessment of groundwater recharge and the water balance for Austria
<p><strong>Version 1.0 - This version is the final revised one. <br></strong></p> <p>This dataset accompanies the paper: Zeitfogel et al. (2025), Regional-scale assessmentof groundwater recharge and the water balance for Austria, published at Journal of Hydrology: Regional Studies.</p> <p>The dataset includes spatially distributed maps of groundwater recharge rates, precipitation, runoff, and actual evapotranspiration for Austria, resulting from an Austria-wide implementation of the rainfall-runoff model COSERO. By downloading these datasets, you acknowledge that neither the authors nor the providers of the source datasets can be held liable for the accuracy or completeness of the data.</p> <p>The model parameterization of soil information was based on regionalized soil hydraulic property maps.</p> <p>The basins_info file provides spatial information about the delinated model basins, the corresponding gauges, and the calibration stages. </p> <p>This study was funded by the Austrian Academy of Science (Project RechAUT), the Austrian Federal Ministry of Agriculture, Regions and Tourism (Project InfCapAT), and by the Austrian Climate Research Program (ACRP) - 14th call, under grant agreement No. KR21KB0K00001 (HyMELT-CC).</p>
Resilience Evaluation Table (Regional Climate Resilience Assessment)
<p>Assessment of regional resiliences of the five ClimEmpower regions: Costa del Sol in Andalusia, Spain, Trodos Mountains in Cyprus, Osjek-Baranja county in Croatia, Central Greece and Sicily, Italy. Result of initial ClimEmpower climate Resilience Asssessment (CLIM-RA) of these five regions, related to project deliverable D1.2.</p>
Fig. 19. Representative Nimbadon lavarackorum occipital regions. A in First Crania and Assessment of Species Boundaries in Nimbadon (Marsupialia: Diprotodontidae) from the Middle Miocene of Australia
Fig. 19. Representative Nimbadon lavarackorum occipital regions. A, QM F31377; B, QM F31541.
Supporting Information - Fabbri et al. 2022 - Evaluation of sugar feedstocks for bio-based chemicals: A consequential, regionalized life cycle assessment
<p>The supporting information of the journal article "Evaluation of sugar feedstocks for bio-based chemicals: A consequential, regionalized life cycle assessment" from Fabbri et al. (2022) includes one file with the following content:</p> <p>S1 Details of consequential modelling: feedstock<br> S1.1 Identification type of changes (demand or supply)<br> S1.2 Identification of constrains in the market<br> S1.3 Identification of product substitutions<br> S1.4 Identification of affected production technology<br> S1.5 Identification of marginal crop and marginal supplier<br> S2 Details of consequential modelling: by-products<br> S3 Model parameters and unit processes<br> S3.1 Sugar beet<br> S3.2 Sugar cane<br> S3.3 Wheat<br> S3.4 Maize<br> S3.5 Wood<br> S3.6 Residual woodchips and sawdust<br> S4 Review of land use change accounting methods<br> S4.1 Direct land use change (dLUC)<br> S4.2. Indirect land use change (iLUC)<br> S5 Additional results<br> S5.1 Influence of spatial differentiation in LCIA<br> S5.2 Influence of indirect land use change (iLUC)<br> S6 References</p>
North American Regional Reanalysis (NARR) data used in "Passive Tracer Modelling at Super-Resolution with WRF-ARW to Assess Mass-Balance Schemes"
<p>North American Regional Reanalysis (NARR) data from National Oceanic and Atmospheric Administration (NOAA) - 20 August 2013, 26 August 2013, 2 September 2013 - used as input information (initial and boundary condition) for WRF simulations described in "Passive Tracer Modelling at Super-Resolution with WRF-ARW to Assess Mass-Balance Schemes" (Fathi et al., 2022 - egusphere-2022-1125). NARR data can be accessed and downloaded at the following web address "https://www.ncei.noaa.gov/products/weather-climate-models/north-american-regional/". </p>
Data from: Evaluation of primer pairs for eDNA‐based assessment of Ephemeroptera, Plecoptera, and Trichoptera across a biogeographically diverse region
<p><span>Macroinvertebrates serve as key indicators in ecological assessments of aquatic ecosystems, where the composition and richness of their communities is indicative of environmental and anthropogenic drivers. Established monitoring of macroinvertebrates is expensive, time-consuming, and relies on expert taxonomic knowledge. In contrast, biomonitoring based on molecular tools can support faster characterization of aquatic communities but needs validation for the target taxonomic groups and the study region. Here, we used data from a biomonitoring program covering a large biogeographic gradient to compare the routine kick-net method with eDNA metabarcoding. We used two primer pairs targeting COI, one targeting a broad metazoan spectrum (miCOIintF/jgHCO2198) and another more recently developed primer pair optimized for the detection of freshwater invertebrates (fwhF2/EPTDr2n). We used the data of the macroinvertebrate monitoring with a focus on the orders of Ephemeroptera, Plecoptera, and Trichoptera across 92 rivers in Switzerland, covering four continental drainage basins and an elevational range from 198 to 1650 m a.s.l. Across all sampled sites, the kick-net detected more distinct taxa than either of the metabarcoding approaches. At a site level, however, both primer pairs detected on average more species. Comparing both primer pairs, the fwhF2/EPTDr2n primer pair captured more species assigned to the indicator groups Ephemeroptera, Plecoptera, and Trichoptera, and showed a significantly larger overlap with the kick-net method. However, the community composition still varied significantly among the different approaches. Fewer Trichopterans were recovered by eDNA metabarcoding, whereas the fwhF2/EPTDr2n primer pair detected more Plecopterans than the other two approaches. This study highlights the importance of optimization and validation of novel molecular approaches under consideration of the target organismal group and the study area.</span></p>
Isoprene concentrations data used in the paper "Assessment of isoprene and near surface ozone sensitivities to water stress over the Euro-Mediterranean region"
<p>Isoprene concentrations collected by E. Bourtsoukidis and J. Williams during a field-campaign that took place in Cyprus (site field: Ineia; Latitude: 34.96° N, Longitude: 32.39° E) during the summer 2014 (from July 7 to August 3; data collected every 45 minutes) using the technique of gas chromatography - mass spectrometry (GC-MS) (Derstroff et al., 2017). These data have been used to validate isoprene concentrations simulated by the regional climate model RegCM applied in the study "<em>Assessment of isoprene and near surface ozone sensitivities to water stress over the Euro-Mediterranean region</em>" (https://doi.org/10.5194/egusphere-2022-1522).</p>
Data from: Evaluation of primer pairs for eDNA‐based assessment of Ephemeroptera, Plecoptera, and Trichoptera across a biogeographically diverse region
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Empowering regional conservation: Genetic diversity assessments as a tool for eelgrass management
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