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En el instante 23 de junio de 2026, 16:14:08 UTC,
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Modificado el valor del campo
spatial_coverage
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en Water table prediction through causal reasoning modelling
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| 89 | "notes": "This research is mainly aimed to analyze and model the | 89 | "notes": "This research is mainly aimed to analyze and model the | ||
| 90 | relationship of the binomial Rainfall-Piezometry. In this sense, the | 90 | relationship of the binomial Rainfall-Piezometry. In this sense, the | ||
| 91 | inherent causality contained in temporal hourly Rainfall and | 91 | inherent causality contained in temporal hourly Rainfall and | ||
| 92 | Groundwater levels (piezometry) data records has been taken. This has | 92 | Groundwater levels (piezometry) data records has been taken. This has | ||
| 93 | been done through Bayesian Causal Reasoning (BCR) which is technique | 93 | been done through Bayesian Causal Reasoning (BCR) which is technique | ||
| 94 | belonging to Artificial Intelligence (AI) based on Bayesian Theorem. | 94 | belonging to Artificial Intelligence (AI) based on Bayesian Theorem. | ||
| 95 | The methodology comprises two main stages, first an analytical method | 95 | The methodology comprises two main stages, first an analytical method | ||
| 96 | from classic regression analysis, and second, a Bayesian Causal | 96 | from classic regression analysis, and second, a Bayesian Causal | ||
| 97 | Modelling Translation (BCMT) that itself comprises sev- eral iterative | 97 | Modelling Translation (BCMT) that itself comprises sev- eral iterative | ||
| 98 | steps. This research ultimately becomes a tool for aquifers management | 98 | steps. This research ultimately becomes a tool for aquifers management | ||
| 99 | that comprises a bivariate func- ti on made of two variables Rainfall | 99 | that comprises a bivariate func- ti on made of two variables Rainfall | ||
| 100 | and Piezometry (Temporal Groundwater level evolution). This innovative | 100 | and Piezometry (Temporal Groundwater level evolution). This innovative | ||
| 101 | methodology has been successfully applied in the Quaternary aquifer of | 101 | methodology has been successfully applied in the Quaternary aquifer of | ||
| 102 | the Campo de Cartagena groundwater body, which is an aquifer system | 102 | the Campo de Cartagena groundwater body, which is an aquifer system | ||
| 103 | that directly is connected to Mar Menor coastal lagoon (Murcia region, | 103 | that directly is connected to Mar Menor coastal lagoon (Murcia region, | ||
| 104 | SE Spain).", | 104 | SE Spain).", | ||
| 105 | "notes_translated": { | 105 | "notes_translated": { | ||
| 106 | "es": "This research is mainly aimed to analyze and model the | 106 | "es": "This research is mainly aimed to analyze and model the | ||
| 107 | relationship of the binomial Rainfall-Piezometry. In this sense, the | 107 | relationship of the binomial Rainfall-Piezometry. In this sense, the | ||
| 108 | inherent causality contained in temporal hourly Rainfall and | 108 | inherent causality contained in temporal hourly Rainfall and | ||
| 109 | Groundwater levels (piezometry) data records has been taken. This has | 109 | Groundwater levels (piezometry) data records has been taken. This has | ||
| 110 | been done through Bayesian Causal Reasoning (BCR) which is technique | 110 | been done through Bayesian Causal Reasoning (BCR) which is technique | ||
| 111 | belonging to Artificial Intelligence (AI) based on Bayesian Theorem. | 111 | belonging to Artificial Intelligence (AI) based on Bayesian Theorem. | ||
| 112 | The methodology comprises two main stages, first an analytical method | 112 | The methodology comprises two main stages, first an analytical method | ||
| 113 | from classic regression analysis, and second, a Bayesian Causal | 113 | from classic regression analysis, and second, a Bayesian Causal | ||
| 114 | Modelling Translation (BCMT) that itself comprises sev- eral iterative | 114 | Modelling Translation (BCMT) that itself comprises sev- eral iterative | ||
| 115 | steps. This research ultimately becomes a tool for aquifers management | 115 | steps. This research ultimately becomes a tool for aquifers management | ||
| 116 | that comprises a bivariate func- ti on made of two variables Rainfall | 116 | that comprises a bivariate func- ti on made of two variables Rainfall | ||
| 117 | and Piezometry (Temporal Groundwater level evolution). This innovative | 117 | and Piezometry (Temporal Groundwater level evolution). This innovative | ||
| 118 | methodology has been successfully applied in the Quaternary aquifer of | 118 | methodology has been successfully applied in the Quaternary aquifer of | ||
| 119 | the Campo de Cartagena groundwater body, which is an aquifer system | 119 | the Campo de Cartagena groundwater body, which is an aquifer system | ||
| 120 | that directly is connected to Mar Menor coastal lagoon (Murcia region, | 120 | that directly is connected to Mar Menor coastal lagoon (Murcia region, | ||
| 121 | SE Spain)." | 121 | SE Spain)." | ||
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| 255 | "uri": | 226 | "uri": | ||
| 256 | ttp://datos.gob.es/recurso/sector-publico/territorio/Pais/Espa\u00f1a" | 227 | ttp://datos.gob.es/recurso/sector-publico/territorio/Pais/Espa\u00f1a" | ||
| 257 | } | 228 | } | ||
| 258 | ], | 229 | ], | ||
| 259 | "spatial_uri": | 230 | "spatial_uri": | ||
| 260 | tp://datos.gob.es/recurso/sector-publico/territorio/Pais/Espa\u00f1a", | 231 | tp://datos.gob.es/recurso/sector-publico/territorio/Pais/Espa\u00f1a", | ||
| 261 | "state": "active", | 232 | "state": "active", | ||
| 262 | "study_variables": { | 233 | "study_variables": { | ||
| 263 | "es": "" | 234 | "es": "" | ||
| 264 | }, | 235 | }, | ||
| 265 | "tag_uri": [ | 236 | "tag_uri": [ | ||
| 266 | 237 | ||||
| 267 | tp://inspire.ec.europa.eu/metadata-codelist/TopicCategory/environment" | 238 | tp://inspire.ec.europa.eu/metadata-codelist/TopicCategory/environment" | ||
| 268 | ], | 239 | ], | ||
| 269 | "tags": [ | 240 | "tags": [ | ||
| 270 | { | 241 | { | ||
| 271 | "display_name": "gestion_costera", | 242 | "display_name": "gestion_costera", | ||
| 272 | "id": "ebe6e81d-8ae8-42e4-a52a-d40ef876ef7d", | 243 | "id": "ebe6e81d-8ae8-42e4-a52a-d40ef876ef7d", | ||
| 273 | "name": "gestion_costera", | 244 | "name": "gestion_costera", | ||
| 274 | "state": "active", | 245 | "state": "active", | ||
| 275 | "vocabulary_id": null | 246 | "vocabulary_id": null | ||
| 276 | }, | 247 | }, | ||
| 277 | { | 248 | { | ||
| 278 | "display_name": "marino", | 249 | "display_name": "marino", | ||
| 279 | "id": "004084d1-68d8-46ca-842a-c10278540bc9", | 250 | "id": "004084d1-68d8-46ca-842a-c10278540bc9", | ||
| 280 | "name": "marino", | 251 | "name": "marino", | ||
| 281 | "state": "active", | 252 | "state": "active", | ||
| 282 | "vocabulary_id": null | 253 | "vocabulary_id": null | ||
| 283 | }, | 254 | }, | ||
| 284 | { | 255 | { | ||
| 285 | "display_name": "medidas_de_gestion", | 256 | "display_name": "medidas_de_gestion", | ||
| 286 | "id": "c82d981c-d4ad-45e5-8229-afe383d5ea3d", | 257 | "id": "c82d981c-d4ad-45e5-8229-afe383d5ea3d", | ||
| 287 | "name": "medidas_de_gestion", | 258 | "name": "medidas_de_gestion", | ||
| 288 | "state": "active", | 259 | "state": "active", | ||
| 289 | "vocabulary_id": null | 260 | "vocabulary_id": null | ||
| 290 | }, | 261 | }, | ||
| 291 | { | 262 | { | ||
| 292 | "display_name": "tecnologia", | 263 | "display_name": "tecnologia", | ||
| 293 | "id": "0b3381bc-073c-43fe-a133-4efcf0e36300", | 264 | "id": "0b3381bc-073c-43fe-a133-4efcf0e36300", | ||
| 294 | "name": "tecnologia", | 265 | "name": "tecnologia", | ||
| 295 | "state": "active", | 266 | "state": "active", | ||
| 296 | "vocabulary_id": null | 267 | "vocabulary_id": null | ||
| 297 | } | 268 | } | ||
| 298 | ], | 269 | ], | ||
| 299 | "thematic_area": [ | 270 | "thematic_area": [ | ||
| 300 | "espacios_protegidos" | 271 | "espacios_protegidos" | ||
| 301 | ], | 272 | ], | ||
| 302 | "theme_es": [ | 273 | "theme_es": [ | ||
| 303 | "http://datos.gob.es/kos/sector-publico/sector/medio-ambiente" | 274 | "http://datos.gob.es/kos/sector-publico/sector/medio-ambiente" | ||
| 304 | ], | 275 | ], | ||
| 305 | "title": "Water table prediction through causal reasoning | 276 | "title": "Water table prediction through causal reasoning | ||
| 306 | modelling", | 277 | modelling", | ||
| 307 | "title_translated": { | 278 | "title_translated": { | ||
| 308 | "es": "Water table prediction through causal reasoning modelling" | 279 | "es": "Water table prediction through causal reasoning modelling" | ||
| 309 | }, | 280 | }, | ||
| 310 | "topic": | 281 | "topic": | ||
| 311 | "http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/biota", | 282 | "http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/biota", | ||
| 312 | "type": "dataset", | 283 | "type": "dataset", | ||
| 313 | "url": | 284 | "url": | ||
| 314 | //iepnb.es:443/catalogo/dataset/070071e8-e1be-59fb-8953-edf35b775f10", | 285 | //iepnb.es:443/catalogo/dataset/070071e8-e1be-59fb-8953-edf35b775f10", | ||
| 315 | "version_notes": { | 286 | "version_notes": { | ||
| 316 | "es": "" | 287 | "es": "" | ||
| 317 | } | 288 | } | ||
| 318 | } | 289 | } |