Resultados totales (Incluyendo duplicados): 35622
Encontrada(s) 3563 página(s)
Encontrada(s) 3563 página(s)
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/269577
Dataset. 2022
PIRAGUA_RESOURCES [DATASET]
- Beguería, Santiago
- Palazón Tabuenca, Leticia
- Travesset, Oriol
- Le Coent, Philippe
- Forey, Ingrid
- POCTEFA-PIRAGUA Team
[EN] Contains 17 compressed folders (.zip) with shapefiles (.shp; requires a specific Geographic Information System GIS software) and one PDF file. Under a Open Data Commons Open Database License (ODbL)., [ES] Contiene 17 carpetas comprimidas (.zip) con shapefiles (.shp; requiere software específico para Sistemas de Información Geográfica, SIG) y un archivo PDF. Bajo una "Open Data Commons Open Database License (ODbL)"., [EN] Geospatial data about water use and exploitation in the Pyrenees (France, Spain, Andorra), generated within the project EFA210/16 PIRAGUA Project ("Evaluation and prospective of the water resources of the Pyrenees in a context of climate change, and adaptation measures with impact on the territory")., [ES] Información geoespacial sobre usos y explotación de los recursos hídricos en los Pirineos (Francia, España y Andorra), generada en el contexto del proyecto EFA210/16 PIRAGUA ("Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio")., [FR] Information géospatiale sur les usages et l'exploitation des ressources en eau dans les Pyrénées (France, Espagne et Andorre), générées dans le cadre du projet EFA210/16 PIRAGUA ("Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d'adaptation ayant un impact sur le territoire")., This dataset was developed within the project EFA210/16 PIRAGUA (“Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio / Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d’adaptation avec un impact sur le territoire”), co-funded by the European Regional Development Fund (ERDF) through the Interreg V-A Spain France Andorra program (POCTEFA 2014-2020) (65%) and the project’s partners: CSIC, UPV/EHU, UB, OE, IGME, CNRS, BRGM, INRAE and OBSA (35%)., Files in the data set:
GIS shapefiles, point layers:
- centrales.shp: hydroelectric stations.
- est_ski.shp: ski resorts.
- cap_embalses.shp: reservoirs.
Capas SIG, lineales:
- river_net.shp: hydrographic network.
Capas SIG, poligonales:
- demarcaciones.shp: hydrographic units (basin agencies).
- juntas.shp: hydrographic management units (within hydrographic units).
-uso_global.shp: total water use, per hydrographic management units.
-uso_agri.shp: agricultural water use, per hydrographic management units.
-uso_dom.shp: urban water use, per hydrographic management units..
-uso_ind.shp: industrial water use, per hydrographic management units..
-origen_sub.shp: total water use from subsurface origin, per hydrographic management units..
-origen_sup.shp: total water use from surface origin, per hydrographic management units..
-cap_embalsado.shp: capacidad de embalsado, por juntas de explotación hidrográfica.
-dom_ski.shp: skiable domain, per hydrographic management units..
-prod_hydro.shp: hydro-power installed power and production, per hydrographic management units.
-reservoirs.shp: reservoirs.
-zonas_protegidas.shp: nature reserves., Data fields:
central.shp:
- name, name of the panel.
- operator, operator.
- power_MW, installed power, in megawatts.
- power, installed power (class).
- since, year of start of operations.
- production, current average annual production, in GWh.
- jump_m, vertical distance of the hydraulic jump, in m.
est_ski.shp:
- name, name of the station.
- alt_min_m, minimum elevation, in m above sea level.
- alt_max_m, maximum elevation, in m above sea level.
- snow_p_%, percentage of the ski area with artificial snow cover.
- snow_p_km, ski area with artificial snow cover, in km.
- domain_km, ski area, in km.
- capacity_p, lift capacity, in people per hour.
cap_reservoirs.shp:
- name, name of the reservoir.
- operator, operator.
- use, main uses (A, supply; V, ; H, ; R, ; S, ; ND; not available).
- capacity_h, reservoir capacity, in mm^3 (hm^3).
- size, size, in classes.
- height_m, height of the dam, in m.
- area_km2, maximum surface of the sheet of water, in km^2.
- since, year of start of operations.
river_net.shp:
- OBJECTID, identifier of the river section.
- REX, country (ES, Spain; FR, France; AD, Andorra).
- STRAHLER, order of the river reach, according to Strahler's classification.
demarcations.shp:
- NOM_DEMAR, name of the river basin district.
- ORG_CUENCA, responsible body.
- CENTRO_DIR, directing center.
- DIRECCION, Address.
- WEB, web page.
- TELEPHONE, telephone.
joints.shp:
- Basin, river basin district to which it belongs.
Name, name of the exploitation board.
- Area_km2, surface, in km^2.
usage_global.shp:
- Name, name of the exploitation board.
- U_tot_av, uso del agua promedio anual, en Mm^3 (hm^3).
uso_agri.shp:
- Name, nombre de la junta de explotación.
- U_agr_av, uso del agua promedio anual en el sector agrícola, en Mm^3 (hm^3).
- U_agr_av_p, uso del agua promedio anual en el sector agrícola, porcentaje sobre el uso total.
uso_dom.shp:
- Name, nombre de la junta de explotación.
- U_dom_av, uso del agua promedio anual para abastecimiento, en Mm^3 (hm^3).
- U_dom_av_p, uso del agua promedio anual para abastecimiento, porcentaje sobre el uso total.
uso_ind.shp:
- Name, nombre de la junta de explotación.
- U_ind_av, uso del agua promedio anual industrial, en Mm^3 (hm^3).
- U_ind_av_p, uso del agua promedio anual industrial, porcentaje sobre el uso total.
origen_sub.shp:
- Name, nombre de la junta de explotación.
- U_und_av, uso del agua de origen subterráneo, promedio anual, en Mm^3 (hm^3).
- U_und_av_p, uso del agua de origen subterráneo, promedio anual, porcentaje sobre el uso total.
origen_sup.shp:
- Name, nombre de la junta de explotación.
- U_sup_av, uso del agua de origen superficial, promedio anual, en Mm^3 (hm^3).
- U_sup_av_p, uso del agua de origen superficial, promedio anual, porcentaje sobre el uso total.
cap_embalsado.shp:
- Name, nombre de la junta de explotación.
- Reservoirs, número de embalses.
- Res_hm3, capacidad de embalsado total, en Mm^3 (hm^3).
- Capacity, capacidad de embalsado, en clases.
dom_ski.shp:
- Name, nombre de la junta de explotación.
- Ski_num, número de estaciones de esquí.
- Ski_km, dominio esquiable total, en km.
- Ski_prod_%, dominio esquiable con producción de nieve artificial, en porcentaje sobre el dominio esquiable total.
prod_hydro.shp:
- Name, nombre de la junta de explotación.
- Hydropow_num, número de centrales hidroeléctricas.
- Hydropow _MW, potencia instalada, en MW.
- Hydropow_GWh, producción media anual, en GWh.
reservoirs.shp:
- NOMBRE, nombre del embalse.
zonas_protegidas.shp:
- Name, nombre de la zona protegida.
- type, tipo de figura de protección, en la lengua vernácula.
- typeEnglish, tipo de figura de protección, en inglés.
- legalRef, referencia legal.
- legalDoc, documento legal.
- legalFound, fecha de inicio de la figura de protección.
- Authority, autoridad competente.
- Leyenda, tipo de figura de protección, agrupado en clases principales.
- Country, país (ES, España; FR, Francia; AD, Andorra)., No
Proyecto: //
DOI: http://hdl.handle.net/10261/269577, https://doi.org/10.20350/digitalCSIC/14641
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/269577
HANDLE: http://hdl.handle.net/10261/269577, https://doi.org/10.20350/digitalCSIC/14641
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/269577
PMID: http://hdl.handle.net/10261/269577, https://doi.org/10.20350/digitalCSIC/14641
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/269577
Ver en: http://hdl.handle.net/10261/269577, https://doi.org/10.20350/digitalCSIC/14641
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/269577
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270445
Dataset. 2014
PRESS, TEMPERATURE AND HUMIDITY DECEMBER 2013
- Aguilar, Fernando
PTU Cuerda del Pozo. December 2013, Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/270445
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270445
HANDLE: http://hdl.handle.net/10261/270445
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270445
PMID: http://hdl.handle.net/10261/270445
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270445
Ver en: http://hdl.handle.net/10261/270445
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270445
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270501
Dataset. 2014
WIND MAY 2013
- Aguilar, Fernando
Wind speed and direction from Cuerda del Pozo reservoir. May 2013, Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/270501
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270501
HANDLE: http://hdl.handle.net/10261/270501
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270501
PMID: http://hdl.handle.net/10261/270501
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270501
Ver en: http://hdl.handle.net/10261/270501
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270501
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270508
Dataset. 2014
PRESS, TEMPERATURE AND HUMIDITY APRIL 2013
- Aguilar, Fernando
PTU Cuerda del Pozo. April 2013, Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/270508
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270508
HANDLE: http://hdl.handle.net/10261/270508
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270508
PMID: http://hdl.handle.net/10261/270508
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270508
Ver en: http://hdl.handle.net/10261/270508
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/270508
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271433
Dataset. 2022
PIRAGUA_HYDRO_ANALYSIS [DATASET]
- Beguería, Santiago
- Palazón Tabuenca, Leticia
- Grusson, Youen
- Sánchez Pérez, José Miguel
- Sauvage, Sabine
- Cakir, Roxelane
- Quintana-Seguí, Pere
- Barella, Anaïs
- Vidal, Jean-Philippe
- POCTEFA-PIRAGUA Team
[EN] Contains five compressed folders (.zip): one with shapefiles (.shp; requires a specific Geographic Information System GIS software) and four data tables in plain text (.csv). One PDF file explains the dataset details., [ES] Contiene cinco carpetas comprimidas (.zip): uno con shapefiles (.shp; requiere software específico para Sistemas de Información Geográfica, SIG) y cuatro tablas de datos en texto plano (.csv). Un archivo PDF explica el contenido del conjunto de datos., [EN] Geospatial information on the water balance components and river discharge over the Pyrenees for the period 1981-2010. The data is based on the application of two hydrological models (SWAT and SASER), forced with the PIRAGUA_atmos_analysis dataset. It includes information on the following variables: temperature, precipitation, snowfall, snowmelt, potential evapotranspiration, actual evapotranspiration, soil water storage, snowpack, aquifer recharge, runoff generation and river discharge. The temporal resolution is monthly, and the spatial aggregation is at the level of hydrographic sub-basins. The dataset was generated within the project EFA210/16 PIRAGUA Project ("Evaluation and prospective of the water resources of the Pyrenees in a context of climate change, and adaptation measures with impact on the territory")., [ES] Información geoespacial sobre componentes del balance hídrico y caudales sobre los Pirineos para el periodo 1981-2010. Los datos se basan en la aplicación de dos modelos hidrológicos (SWAT y SASER), forzados con el conjunto de datos PIRAGUA_atmos_analysis. Incluye información sobre las siguientes variables: temperatura, precipitación, innivación, fusión nival, evapotranspiración potencial, evapotranspiración real, almacenamiendo de agua en el suelo, paquete de nieve, recarga de acuífero, generación de escorrentía y caudales. La resolución temporal es mensual, y la agregación espacial es a nivel de sub-cuencas hidrográficas. El conjunto de datos fue generado en el contexto del proyecto EFA210/16 PIRAGUA ("Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio")., [FR] Information géospatiale sur les composantes du bilan hydrique et débits fluviales sur les Pyrénées pour la période 1981-2010. Les données sont basées sur l'application de deux modèles hydrologiques (SWAT et SASER), forcés avec le jeu de données PIRAGUA_atmos_analysis. Il comprend des informations sur les variables suivantes : température, précipitations, chutes de neige, fonte des neiges, évapotranspiration potentielle, évapotranspiration réelle, stockage de l'eau dans le sol, manteau neigeux, recharge de l'aquifère, génération de ruissellement et débits. La résolution temporelle est mensuelle, et l'agrégation spatiale se fait au niveau des sous-bassins hydrographiques. Le jeu de données a été généré dans le cadre du projet EFA210/16 PIRAGUA ("Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d'adaptation ayant un impact sur le territoire")., This dataset was developed within the project EFA210/16 PIRAGUA (“Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio / Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d’adaptation avec un impact sur le territoire”), co-funded by the European Regional Development Fund (ERDF) through the Interreg V-A Spain France Andorra program (POCTEFA 2014-2020) (65%) and the project’s partners: CSIC, UPV/EHU, UB, OE, IGME, CNRS, BRGM, INRAE and OBSA (35%)., Files in the data set:
- PIRAGUA_hydro_analysis_s-mode: Average values of the water cycle components for the period 1981-2010, at the sub-basin (water bodies catchments) spatial scale.
- PIRAGUA_hydro_analysis_t-mode: Annual time series of the water cycle components at the annual or monthly scale, at the Pyrenees, basin or sub-basin spatial scales.
- GIS: Arc-GIS shapefiles of the different spatial aggregation scales: Pyrenees, basins, sub-basins, and stream reaches. The id field in each shapefile allows matching the spatial units with the data files., Data fields (columns):
Common fields:
- month: month, one of ('annual', 1:12).
- mod_hydro: one of ('SWAT', 'SASER').
- variable: one of ('PRECIP', 'SNOFALL', 'SNOMELT', 'TMPAV', 'ET', 'PET', 'ETPET', 'SW', 'SWE', 'DARCHG', 'WYLD', 'SNOWYLD', 'CONTRIB_CMS', 'CONTRIB_HM3'). See variable explanation below.
- value: data value.
- units: one of ('mm', 'ºC', 'mm/mm', 'm3/s', 'Mm3').
Only in in s-mode file:
- id: identifier of the spatial unit (sub-basins) that matches the ids on files basins.shp and subbasins.shp.
- horizon: always '1981-2010'.
- support: spatial support, one of ('Pyrenees', 'AD', 'ES', 'FR', [basin names]).
- area: area of the sub-basin, in km^2.
Only in t-mode file:
- year: year.
- date: date, in year-month-day format.
- monthabb: month abbreviation., Water balance variables:
(Files: PIRAGUAhydroanalysis_s-mode, PIRAGUAhydroanalysis_t-mode)
- PRECIP: precipitacion, sum of liquid and solid over time period (mm).
- SNOFALL: snowfall (solid precipitation), total over time period (mm).
- SNOMELT: snowmelt, total over time period (mm).
- TMP_AV: daily mean temperature, average over time period (ºC).
- TMP_MX: daily maximum temperature, average over time period (ºC).
- TMP_MN: daily minimum temperature, average over time period (ºC).
- ET: real evapotranspiration, total over time period (mm).
- PET: potential evapotranspiration, total over time period (mm).
- ET_PET: ratio of real over potential evapotranspiration (mm/mm).
- SW: soil water, mean storage over time period (mm).
- SWE: snow water equivalent, mean over time period (mm).
- DA_RCHG: deep aquifer recharge, total over time period (mm).
- WYLD: water yield, total over time period (mm).
- SNO_WYLD: contribution of snowmelt to total water yield (mm/mm).
- CONTRIB_CMS: mean discharge at the sub-basins' outlet (m^3 / s).
- CONTRIB_HM3: mean contribution at the sub-basins' outlet (Mm^3)., Transformation to other units:
- mm to mm/day: value_mm_day = value_mm / ndays_in_month_year.
- mm to hm3: value_hm3 = value_mm * 1000000 * area_in_km2 * 1.0e-09.
- mm to m3/s: value_m3_s = value_mm_day * 1000000 * area_in_km2 * 1.2e-08., Shapefiles in the GIS directory:
- pyrenees.shp: polygon shapefile with the limits of the study area.
- basins.shp: polygon shapefile with the limits of the river basins, corresponding to field id in the s-mode data file.
- subbasins.shp: polygon shapefile with the limits of the river basins, corresponding to field id in the s-mode data file.
- reaches.shp: line shapefile with the river reaches, corresponding to field id in the s-mode data file., No
Proyecto: //
DOI: http://hdl.handle.net/10261/271433, https://doi.org/10.20350/digitalCSIC/14667
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271433
HANDLE: http://hdl.handle.net/10261/271433, https://doi.org/10.20350/digitalCSIC/14667
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271433
PMID: http://hdl.handle.net/10261/271433, https://doi.org/10.20350/digitalCSIC/14667
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271433
Ver en: http://hdl.handle.net/10261/271433, https://doi.org/10.20350/digitalCSIC/14667
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271433
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271451
Dataset. 2022
PIRAGUA_HYDRO_CLIMATE [DATASET]
- Beguería, Santiago
- Palazón Tabuenca, Leticia
- Grusson, Youen
- Sánchez Pérez, José Miguel
- Sauvage, Sabine
- Cakir, Roxelane
- Quintana-Seguí, Pere
- Barella, Anaïs
- Vidal, Jean-Philippe
- POCTEFA-PIRAGUA Team
[EN] Contains five compressed folders (.zip): one with shapefiles (.shp; requires a specific Geographic Information System GIS software) and four data tables in plain text (.csv). One PDF file explains the dataset details., [ES] Contiene cinco carpetas comprimidas (.zip): uno con shapefiles (.shp; requiere software específico para Sistemas de Información Geográfica, SIG) y cuatro tablas de datos en texto plano (.csv). Un archivo PDF explica el contenido del conjunto de datos., [EN] Geospatial information on the water balance components over the Pyrenees under climate change, covering the period 1981-2100. The data is based on the application of two hydrological models (SWAT and SASER), forced with the climate projections in the PIRAGUA_atmos_climate dataset. It includes information on the following variables: temperature, precipitation, snowfall, snowmelt, potential evapotranspiration, actual evapotranspiration, soil water storage, snowpack, aquifer recharge, and runoff generation. The temporal resolution is monthly, and the spatial aggregation is at the level of hydrographic sub-basins. The dataset was generated within the project EFA210/16 PIRAGUA Project ("Evaluation and prospective of the water resources of the Pyrenees in a context of climate change, and adaptation measures with impact on the territory")., [ES] Información geoespacial sobre componentes del balance hídrico sobre los Pirineos en condiciones de cambio climático, para el periodo 1981-2100. Los datos se basan en la aplicación de dos modelos hidrológicos (SWAT y SASER), forzados con las proyecciones climáticas del conjunto de datos PIRAGUA_atmos_climate. Incluye información sobre las siguientes variables: temperatura, precipitación, innivación, fusión nival, evapotranspiración potencial, evapotranspiración real, almacenamiendo de agua en el suelo, paquete de nieve, recarga de acuífero, y generación de escorrentía. La resolución temporal es mensual, y la agregación espacial es a nivel de sub-cuencas hidrográficas. El conjunto de datos fue generado en el contexto del proyecto EFA210/16 PIRAGUA ("Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio")., [FR] Information géospatiale sur les composantes du bilan hydrique des Pyrénées dans des conditions de changement climatique, pour la période 1981-2100. Les données sont basées sur l'application de deux modèles hydrologiques (SWAT et SASER), forcés avec les projections climatiques du jeu de données PIRAGUAatmosclimate. Il comprend des informations sur les variables suivantes : température, précipitations, chutes de neige, fonte des neiges, évapotranspiration potentielle, évapotranspiration réelle, stockage de l'eau dans le sol, manteau neigeux, recharge de l'aquifère et génération de ruissellement. La résolution temporelle est mensuelle, et l'agrégation spatiale se fait au niveau des sous-bassins hydrographiques. Le jeu de données a été généré dans le cadre du projet EFA210/16 PIRAGUA ("Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d'adaptation ayant un impact sur le territoire")., This dataset was developed within the project EFA210/16 PIRAGUA (“Evaluación y prospectiva de los recursos hídricos de los Pirineos en un contexto de cambio climático, y medidas de adaptación con impacto en el territorio / Evaluation et prospective des ressources en eau des Pyrénées dans un contexte de changement climatique, et mesures d’adaptation avec un impact sur le territoire”), co-funded by the European Regional Development Fund (ERDF) through the Interreg V-A Spain France Andorra program (POCTEFA 2014-2020) (65%) and the project’s partners: CSIC, UPV/EHU, UB, OE, IGME, CNRS, BRGM, INRAE and OBSA (35%)., Files in the data set:
- PIRAGUA_hydro_climate_s-mode: Average values of the main water cycle components computed at different time horizons during the 21st century (short, medium and long term), together with the corresponding reference values (average over period 1981-2010), and absolute and relative change with respect to the reference period, at the sub-basin (water bodies catchments) spatial scale, for six different GCM/RCMs and two hydrological models.
- PIRAGUA_hydro_climate_t-mode: Annual time series of the main water cycle components at the annual or monthly temporal scale, at the Pyrenees, basin or sub-basin spatial scales, for six different GCM/RCMs and two hydrological models.
- GIS: shapefiles of the different spatial aggregation scales: Pyrenees, basins, sub-basins, and stream reaches. The id field in each shapefile allows matching the spatial units with the data files., Data fields (columns):
Common fields:
- month: month, one of ('annual', 1:12).
- mod_hydro: one of ('SWAT', 'SASER').
- model: GCM/RCM model, one of ('bcc-csm1-1', 'CNRM-CM5', 'inmcm4', 'MIROC-ESM', 'MPI-ESM-MR', 'MRI-CGCM3'), or 'median' for the median of the six GCM/RCM (only in s-mode), or one of ('q10', 'q50', 'q90') for 10, 50 (median) and 90 quantiles (only in t-mode).
- scenario: emissions scenario, one ov ('HISTORICAL', 'RCP45', 'RCP85').
- variable: one of ('PRECIP', 'SNOFALL', 'SNOMELT', 'TMPAV', 'ET', 'PET', 'ETPET', 'SW', 'SWE', 'DARCHG', 'WYLD', 'SNOWYLD', 'CONTRIB_CMS', 'CONTRIB_HM3'). See variable explanation below.
- value: data value corresponding to the horizon / scenario / mod_hydro.
- delta.absolute: change between value and value.hist in absolute units.
- delta.relative: change between value and value.hist in relative units.
- units: one of ('mm', 'ºC', 'mm/mm', 'm3/s', 'Mm3').
Only in in s-mode file:
- id: identifier of the spatial unit (sub-basins) that matches the ids on file subbasins.shp.
- horizon: always '1981-2010'.
- support: spatial support, one of ('Pyrenees', 'AD', 'ES', 'FR', [basin names]).
- area: area of the sub-basin, in km^2.
- value.hist: reference value during the historical period (1981-2010).
Only in in t-mode file:
- year: year.
- monthabb: month abbreviation.
- date: date, in year-month-day format., Variables:
- PRECIP: precipitacion, sum of liquid and solid over time period (mm).
- SNOFALL: snowfall (solid precipitation), total over time period (mm).
- SNOMELT: snowmelt, total over time period (mm).
- TMP_AV: daily mean temperature, average over time period (ºC).
- TMP_MX: daily maximum temperature, average over time period (ºC).
- TMP_MN: daily minimum temperature, average over time period (ºC).
- ET: real evapotranspiration, total over time period (mm).
- PET: potential evapotranspiration, total over time period (mm).
- ET_PET: ratio of real over potential evapotranspiration (mm/mm).
- SW: soil water, mean storage over time period (mm).
- SWE: snow water equivalent, mean over time period (mm).
- DA_RCHG: deep aquifer recharge, total over time period (mm).
- WYLD: water yield, total over time period (mm).
- SNO_WYLD: contribution of snowmelt to total water yield (mm/mm).
- CONTRIB_CMS: mean discharge at the sub-basins' outlet (m^3 / s).
- CONTRIB_HM3: mean contribution at the sub-basins' outlet (Mm^3)., Transformation to other units:
- mm to mm/day: value_mm_day = valuemm / ndays_in_month_year.
- mm to hm3: value_hm3 = value_mm * 1000000 * area_in_km2 * 1.0e-09.
- mm to m3/s: value_m3_s = value_mm_day * 1000000 * area_in_km2 * 1.2e-08., Shapefiles in the GIS directory:
- pyrenees.shp: polygon shapefile with the limits of the study area.
- basins.shp: polygon shapefile with the limits of the river basins, corresponding to field id in the s-mode data file.
- subbasins.shp: polygon shapefile with the limits of the river basins, corresponding to field id in the s-mode data file.
- reaches.shp: line shapefile with the river reaches, corresponding to field id in the s-mode data file., No
Proyecto: //
DOI: http://hdl.handle.net/10261/271451, https://doi.org/10.20350/digitalCSIC/14668
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271451
HANDLE: http://hdl.handle.net/10261/271451, https://doi.org/10.20350/digitalCSIC/14668
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271451
PMID: http://hdl.handle.net/10261/271451, https://doi.org/10.20350/digitalCSIC/14668
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271451
Ver en: http://hdl.handle.net/10261/271451, https://doi.org/10.20350/digitalCSIC/14668
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/271451
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282024
Dataset. 2021
DATA FOR: TIME AT RISK: INDIVIDUAL SPATIAL BEHAVIOUR DRIVES EFFECTIVENESS OF MARINE PROTECTED AREAS AND FITNESS
- Villegas-Ríos, David
- Claudet, Joachim
- Freitas, Carla
- Moland, Even
- Thorbjørnsen, Susanna Huneide
- Alonso-Fernández, Alexandre
- Olsen, Esben Moland
[Methods] Acoustic telemetry.--[Usage Notes] There is one file per species and year of tagging. Each file is an R object. Opening it with R, the estimated centers of activity for each group of fish will be shown; these centers of activity are then used for subsequent analyses. An excel file is also provided containing the biological characteristics of the tagged animals., The effectiveness of Marine Protected Areas (MPAs) depends on the mobility of the populations that are the target of protection, with sedentary species likely to spend more time under protection even within small MPAs. However, little is understood about how individual variation in mobility may influence the risk of crossing an MPA border, as well as the fitness costs associated with being exposed to spillover fisheries. Here we investigated the repeatability of spatial behaviour, its role in determining the probability of being at risk (i.e. exposed to the fishery) and the fitness consequences for the individuals. We acoustically tracked the movements and fate of 282 individuals of three fish species during 8 years in a southern Norwegian fjord. We found that for individuals with a home range centroid inside the MPA, the probability of being at risk outside the MPA increased rapidly with reduced distance from the home range centroid to MPA borders, particularly for individuals having larger and more dispersed home ranges. We also detected that the seasonal expansions of the home range are associated with increased time at risk. Last, we show that individuals spending more time at risk were also more likely to be harvested by the fishery operating outside the MPA. Our study provides clear links between individual fish behaviour, fisheries-induced selection, and the effectiveness of protected areas. These links highlight the importance of intraspecific trait variation for understanding the spatial dynamics of populations and emphasize the need to consider individual behaviour when designing and implementing MPAs., cleanCOAS_ballan2013.rds.-- cleanCOAS_ballan2015.rds.-- cleanCOAS_ballan2016.rds.-- cleanCOAS_ballan2017.rds.-- cleanCOAS_ballan2018.rds.-- cleanCOAS_cod2011.rds.-- cleanCOAS_cod2012.rds.-- cleanCOAS_cod2013.rds.-- cleanCOAS_cod2014.rds.-- cleanCOAS_cod2015.rds.-- cleanCOAS_cod2016.rds.-- cleanCOAS_cod2017.rds.-- cleanCOAS_cod2018.rds.-- cleanCOAS_pollack2015.rds.-- cleanCOAS_pollack2016.rds.-- cleanCOAS_pollack2017.rds.-- cleanCOAS_pollack2018.rds.-- fish_data.csv, Peer reviewed
Proyecto: //
DOI: dataset/doi:10.5061/dryad.5hqbzkh6m" target="_blank">http://hdl.handle.net/10261/282024, http://datadryad.org/stash/dataset/doi:10.5061/dryad.5hqbzkh6m
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282024
HANDLE: dataset/doi:10.5061/dryad.5hqbzkh6m" target="_blank">http://hdl.handle.net/10261/282024, http://datadryad.org/stash/dataset/doi:10.5061/dryad.5hqbzkh6m
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282024
PMID: dataset/doi:10.5061/dryad.5hqbzkh6m" target="_blank">http://hdl.handle.net/10261/282024, http://datadryad.org/stash/dataset/doi:10.5061/dryad.5hqbzkh6m
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282024
Ver en: dataset/doi:10.5061/dryad.5hqbzkh6m" target="_blank">http://hdl.handle.net/10261/282024, http://datadryad.org/stash/dataset/doi:10.5061/dryad.5hqbzkh6m
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282024
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282794
Dataset. 2018
FIGURE 5 FROM: AGUIRRE MP, ORTEGO J, CORDERO PJ (2018) INFLUENCE OF GRAZING ON POPULATIONS OF THE SPECIALIST GRASSHOPPER MIOSCIRTUS WAGNERI INHABITING HYPERSALINE HABITATS IN LA MANCHA REGION, CENTRAL SPAIN. JOURNAL OF ORTHOPTERA RESEARCH 27(1): 75-81. HTTPS://DOI.ORG/10.3897/JOR.27.21064
- Aguirre, María P.
- Ortego, Joaquín
- Cordero, Pedro J.
Related identifiers: Part of 10.3897/jor.27.21064, Figure 5 Relationship between number of Mioscirtus wagneri per square meter (ABUNDANCE) and A. Cover (%) of Suaeda vera (SEEPWEED), and B. Livestock droppings per square meter (DROPPINGS). Open circles may correspond to one or more overlapping data points., Peer reviewed
Proyecto: //
DOI: http://hdl.handle.net/10261/282794, https://doi.org/10.3897/jor.27.21064.figure5
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282794
HANDLE: http://hdl.handle.net/10261/282794, https://doi.org/10.3897/jor.27.21064.figure5
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282794
PMID: http://hdl.handle.net/10261/282794, https://doi.org/10.3897/jor.27.21064.figure5
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282794
Ver en: http://hdl.handle.net/10261/282794, https://doi.org/10.3897/jor.27.21064.figure5
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/282794
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/295478
Dataset. 2022
VALORIZATION OF DIFFERENT LANDRACE AND COMMERCIAL SORGHUM (SORGHUM BICOLOR (L.) MOENCH) STRAW VARIETIES BY ANAEROBIC DIGESTION [DATASET]
- De la Lama-Calvente, David
- Fernández-Rodríguez, M. J.
- Gandullo, Jacinto
- Desena, Irene
- de la Osa, Clara
- Feria, Ana Belén
- Jiménez-Rodríguez, Antonia
- Borja Padilla, Rafael
The provided data are the raw or primary data used to create the figures and tables in the article: Valorization of different landrace and commercial sorghum (Sorghum bicolor (L.) Moench) straw varieties by anaerobic digestion.-- 2 Excel files, To reduce the impact on the environment and enhance the sustainability of resources, it is necessary to promote and strengthen the use of landrace cultivars that advocate regenerative agriculture. In this study, the growth and development as well as the anaerobic digestion (AD) of six different landrace cultivars, two commercial hybrids cultivars and a public genotype of Sorghum bicolor have been evaluated. The landrace cultivars, in general, presented greater heights, biomass yields and compactness shoots as well as similar or an improvement in grain production compare to the commercial varieties. The AD of the different sorghum straws was performed in batch mode at mesophilic temperature (35°C). The landrace cultivar Zahina (ZH) obtained the highest final methane yield (413 ± 79 NL CH4 kg−1 VS, volatile solids) but the landrace cultivars Zahina gigante (ZHG) and Trigomillo (TG) were the ones that obtained the highest methane per biomass production (13.7 and 12.7 NL CH4 shoot unit−1, respectively). By contrast, the commercial varieties were the ones that obtained the lowest methane yields. Two mathematical models, first-order kinetics and the Transference Function model, were used to fit the experimental data with the aim of describing and simulating the anaerobic biodegradation of these S. bicolor straw varieties and obtaining the kinetic constants. Both models allowed for adequately fitting the experimental results of methane production with time. In particular, the fastest biomethanization occurred using the commercial variety PR88Y20 (PR88) (specific rate constant k = 0.148 ± 0.008 days−1), while the slowest one was obtained from Panizo (PAN) variety (k = 0.064 ± 0.005 days−1). In addition, the highest values of the maximum methane production rate, Rm, were attained for the varieties ZH and PR88, which were 87.1% and 71.3% higher than that achieved for the PAN variety, which exhibited the lowest value., Regional government of Andalucía, Junta de Andalucía, Consejería de Transformación Económica, Industria, Conocimiento y Universidades. Grant Number: Project FEDER UPO-1380782, Peer reviewed
Proyecto: //
DOI: https://zenodo.org/record/7462051#.Y_Sdzh_MKUl, http://hdl.handle.net/10261/295478, https://doi.org/10.20350/digitalCSIC/15138
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/295478
HANDLE: https://zenodo.org/record/7462051#.Y_Sdzh_MKUl, http://hdl.handle.net/10261/295478, https://doi.org/10.20350/digitalCSIC/15138
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/295478
PMID: https://zenodo.org/record/7462051#.Y_Sdzh_MKUl, http://hdl.handle.net/10261/295478, https://doi.org/10.20350/digitalCSIC/15138
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/295478
Ver en: https://zenodo.org/record/7462051#.Y_Sdzh_MKUl, http://hdl.handle.net/10261/295478, https://doi.org/10.20350/digitalCSIC/15138
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/295478
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/296942
Dataset. 2023
STRAUSS WAVE PARAMETERS OBTAINED FROM RBR DUO, ATLANTIC OCEAN - RÍA DE VIGO - LIMENS (NW IBERIA) - OCT. 2021 - JUN 2022
- Martínez Fernández, Adrián
- Villacieros-Robineau, Nicolás
- Gilcoto, Miguel
This item is made of 2 files: the dataset in netcdf format, a Readme.txt file including a small description of the computed variables, and 1 figure showing the instrument used, Wave parameters obtained from RBR Duo in Limens from October 2021 to Jun 2022 under the framework of the STRAUSS project in order to evaluate the effects of ocean waves in selected biological case studies of the Rías Baixas Upwelling System, Funding for this deployment was provided by Project 𝐏𝐈𝐃𝟐𝟎𝟏𝟗-𝟏𝟎𝟔𝟎𝟎𝟖𝐑𝐁-𝐂𝟐𝟏, funded by MCIN/AEI/10.13039/501100011033 in the R&D Projects “Research Challenges” modality, Peer reviewed
DOI: http://hdl.handle.net/10261/296942, https://doi.org/10.20350/digitalCSIC/15155
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/296942
HANDLE: http://hdl.handle.net/10261/296942, https://doi.org/10.20350/digitalCSIC/15155
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/296942
PMID: http://hdl.handle.net/10261/296942, https://doi.org/10.20350/digitalCSIC/15155
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/296942
Ver en: http://hdl.handle.net/10261/296942, https://doi.org/10.20350/digitalCSIC/15155
Digital.CSIC. Repositorio Institucional del CSIC
oai:digital.csic.es:10261/296942
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