The role of secondary data in estimating groundwater levels in the Iberian Peninsula
| dc.contributor.affiliation | Departamento de Ingeniería Hidráulica y Medio Ambiente | |
| dc.contributor.affiliation | Instituto Universitario de Ingeniería del Agua y del Medio Ambiente | |
| dc.contributor.affiliation | Escuela Técnica Superior de Ingeniería de Caminos, Canales y Puertos | |
| dc.contributor.author | Ben-Salem, Nahed | es_ES |
| dc.contributor.author | Rouhani, Amir | es_ES |
| dc.contributor.author | Copty, Nadim K. | es_ES |
| dc.contributor.author | Varouchakis, Emmanouil A. | es_ES |
| dc.contributor.author | Gómez-Hernández, J. Jaime | |
| dc.contributor.author | Karatzas, George P. | es_ES |
| dc.contributor.author | Rode, Michael | es_ES |
| dc.contributor.author | Jomaa, Seifeddine | es_ES |
| dc.contributor.funder | FUNDACION PRIMA | es_ES |
| dc.contributor.funder | European Commission | es_ES |
| dc.contributor.funder | Bundesministerium für Bildung und Forschung, Alemania | es_ES |
| dc.date.accessioned | 2026-03-11T11:39:53Z | |
| dc.date.available | 2026-03-11T11:39:53Z | |
| dc.date.issued | 2026-05 | es_ES |
| dc.description.abstract | [EN] Mapping groundwater levels at the regional scale is often hindered by the lack of high-density direct head measurements. In this study, we explore the value of incorporating different secondary data with cokriging to assess the spatial variability of groundwater levels for the entire Iberian Peninsula, a region characterized by pronounced hydroclimatic variability and rising water demand. The analysis uses more than 60 years of groundwater level measurements from 3822 observation wells across the region, combined with readily available secondary data, including a digital elevation model, precipitation data, and hydrogeological information. Because of the time series length, the analysis was divided into four periods, each containing a different number of measurements. The performance of the geostatistical models was rigorously evaluated through cross-validation and statistical metrics. Results showed that for earlier periods, characterized by a limited number of observation wells, incorporating groundwater data from subsequent periods and hydrogeological information led to the most significant improvement in groundwater level mapping. Average annual precipitation data did not correlate with groundwater level data and had minimal impact on the interpolation, whereas digital elevation models had a mixed effect. Overall, the study underlines the value of incorporating secondary data through cokriging to map groundwater levels at a regional scale when in-situ data are scarce. | es_ES |
| dc.description.accrualMethod | S | es_ES |
| dc.description.bibliographicCitation | Ben-Salem, N.; Rouhani, A.; Copty, NK.; Varouchakis, EA.; Gómez-Hernández, J. Jaime; Karatzas, GP.; Rode, M.... (2026). The role of secondary data in estimating groundwater levels in the Iberian Peninsula. Groundwater for Sustainable Development. 33. https://doi.org/10.1016/j.gsd.2026.101594 | es_ES |
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| dc.description.references | Wada, Y., van Beek, L. P. H., van Kempen, C. M., Reckman, J. W. T. M., Vasak, S., & Bierkens, M. F. P. (2010). Global depletion of groundwater resources. Geophysical Research Letters, 37(20). Portico. https://doi.org/10.1029/2010gl044571 | es_ES |
| dc.description.references | Xiao, H., Tang, Y., Li, H., Zhang, L., Ngo-Duc, T., Chen, D., & Tang, Q. (2021). Saltwater intrusion into groundwater systems in the Mekong Delta and links to global change. Advances in Climate Change Research, 12(3), 342-352. https://doi.org/10.1016/j.accre.2021.04.005 | es_ES |
| dc.description.references | Zhang. (2019). Upscaling groundwater processes in large-scale models. Water Resour. Res. | es_ES |
| dc.description.references | Zimmerman. (2006). Optimal prediction of spatial random fields. J. Stat. Plan. Inference. | es_ES |
| dc.description.references | Zimmerman. (2020). Spatial statistical modeling. Stat. Sci. | es_ES |
| dc.description.sponsorship | This work was supported by the German Federal Ministry of Edu-cation and Research (BMBF, Germany, Grant number 01DH19015) under the Project Sustain-COAST, co-funded by the EU PRIMA 2018 program. This work was also supported by the Our MED PRIMA Program project funded by the European Union's Horizon 2020 Research and Innovation under grant agreement No. 2222. | es_ES |
| dc.description.volume | 33 | es_ES |
| dc.identifier.doi | 10.1016/j.gsd.2026.101594 | es_ES |
| dc.identifier.eissn | 2352-801X | es_ES |
| dc.identifier.uri | https://riunet.upv.es/handle/10251/233313 | |
| dc.language | Inglés | es_ES |
| dc.publisher | Elsevier | es_ES |
| dc.relation.ispartof | Groundwater for Sustainable Development | es_ES |
| dc.relation.pasarela | S\576179 | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/BMBF//01DH19015/ | es_ES |
| dc.relation.publisherversion | https://doi.org/10.1016/j.gsd.2026.101594 | es_ES |
| dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
| dc.rights.accessRights | Abierto | es_ES |
| dc.subject | Multi-decadal analysis | es_ES |
| dc.subject | Kriging | es_ES |
| dc.subject | Cokriging | es_ES |
| dc.subject | Groundwater level | es_ES |
| dc.subject | Geostatistics | es_ES |
| dc.subject | Spatial variability | es_ES |
| dc.subject | Iberian Peninsula | es_ES |
| dc.title | The role of secondary data in estimating groundwater levels in the Iberian Peninsula | es_ES |
| dc.type | Artículo | es_ES |
| dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
| dspace.entity.type | Publication | es_ES |
| person.identifier | 3352 | |
| person.identifier.orcid | 0000-0002-0720-2196 | |
| relation.isAuthorOfPublication | dc809784-2521-432b-aafd-9be1b6ebd0d8 | |
| relation.isAuthorOfPublication.latestForDiscovery | dc809784-2521-432b-aafd-9be1b6ebd0d8 | |
| relation.isOrgUnitOfPublication | e8876040-9428-45e8-b805-b5bbc20e9e1e | |
| relation.isOrgUnitOfPublication | 937991bf-5e71-4f67-ae2a-1fb780a35167 | |
| relation.isOrgUnitOfPublication | a4b47ff5-95f4-430f-a1a3-541cb8eaa9b7 | |
| relation.isOrgUnitOfPublication.latestForDiscovery | e8876040-9428-45e8-b805-b5bbc20e9e1e | |
| upv.uuid | f55626c2-0305-4791-a996-5972847843eb | es_ES |
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