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CORDIS - Risultati della ricerca dell’UE
CORDIS

Supporting STakeholders for Adaptive, Resilient and Sustainable Water Management

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Description of integrated indicators (si apre in una nuova finestra)

A report describing a set of climate risk indicators at the river basin level that will help to better monitor, evaluate and assess developments in water resources availability and impacts of climate change.

Gaps analysis of existing tools (si apre in una nuova finestra)

A set of reports of the benchmarking of existing operational models within the 7 Hubs against identified stakeholder requirements.

Review of existing observational systems (si apre in una nuova finestra)

This report consists of an inventory of existing data information systems for water resources management, including data sets that are currently used by the river basin hubs as well as new developments at EU or global level.

Dissemination and communication strategy plan (2nd release) (si apre in una nuova finestra)

Drafting of the Dissemination Strategy Plan (DSP), to ensure the coherent streamlining of the project outputs into targeted high-quality dissemination products, and their dissemination to specific target audiences.

Needs assessment stakeholders (si apre in una nuova finestra)

After setting up the stakeholder communities, the needs and knowledge questions need to be identified for each RBO and will be reported as an important milestone.WP2 (data services) and WP3 (modelling tools) will take up the results of this assessment.

Stakeholder engagement work plan (si apre in una nuova finestra)

To facilitate the stakeholder engagement, a work plan will be developed. This work plan will describe the activities and result for each task, and expected input of the participants. The process of developing the work plan also serves to set up and strengthen the collaboration, within and between the RBO’s and the STARS4Water consortium.

Dissemination and communication strategy plan (1st release) (si apre in una nuova finestra)

Drafting of the Dissemination Strategy Plan (DSP), to ensure the coherent streamlining of the project outputs into targeted high-quality dissemination products, and their dissemination to specific target audiences.

Metadata portal (1st release) (si apre in una nuova finestra)

A metadata portal for unlocking EU and national data sets and making data sets accessible in the context of water resources planning. Data sets include data on meteorological, hydrological, basin features, water governance and water infrastructure.

Stars4Water website (si apre in una nuova finestra)

Development and maintenance of the Stars4Water website (to be maintained for 5 more years after the project ends, and used to disseminate updates on activities, deliverables, interesting news/posts, events, etc.).

Pubblicazioni

Evaluating the quantitative status of water bodies applied to the Duero River Basin. Development of a groundwater availability index.

Autori: García Menéndez, O.; Aguilera Alonso, H.; de la Hera Portillo, A.
Pubblicato in: 2025
Editore: Fundación Nueva Cultura del Agua

Nitrate spatial predictions by means of machine learning to improve groundwater monitoring networks (si apre in una nuova finestra)

Autori: Gómez-Escalonilla V, Martínez-Santos P, Pacios D, Ruíz-Álvarez L, Díaz-Alcaide S, Montero-González E, Martín-Loeches M, De la Hera-Portillo A, Aguilera H
Pubblicato in: EGU General Assembly 2024, 2024
Editore: European Geophysical Union
DOI: 10.5194/EGUSPHERE-EGU24-10066

Better mapping of groundwater-surface water exchanges over the Seine River catchment in a surface hydrological model (si apre in una nuova finestra)

Autori: Hsu, S.-C., de Lavenne, A., Andréassian, V., Rabah, A., and Ramos, M.-H.
Pubblicato in: EGU General Assembly 2024, 2024
Editore: EGU
DOI: 10.5194/egusphere-egu24-15833

A machine learning application for the development of groundwater vulnerability studies. (si apre in una nuova finestra)

Autori: Gómez-Escalonilla V, Martínez-Santos P, De la Hera-Portillo A, Díaz-Alcaide S, Montero E, Martín-Loeches M
Pubblicato in: 15th International Conference on Hydroinformatics, 2024
Editore: IWRA
DOI: 10.3850/iahr-hic2483430201-378

GIS-based machine learning applications as decision support systems to enhance groundwater monitoring networks.

Autori: Gómez-Escalonilla V, Martínez-Santos P, Díaz-Alcaide S, Montero-González E, Martín-Loeches M
Pubblicato in: 15th International Conference on Hydroinformatics, 2024
Editore: IWRA

Identification of socio-economic scenarios through participatory processes for improving water management in the Duero River Basin

Autori: De la Hera Portillo, A.; García Menéndez, O.; Moreno Merino, L.; Aguilera Alonso, H.; Martínez Santos, P.; Rodríguez del Rosario, M.
Pubblicato in: XIII Congreso Ibérico de Gestión y Planificación del Agua., 2025, ISBN 978-84-608-2132-8
Editore: Fundación Nueva Cultura del Agua

Machine learning as a tool to improve groundwater monitoring networks (si apre in una nuova finestra)

Autori: Pacios D, Coleto I, Verzier P, Gómez-Escalonilla V, Martinez-Santos P
Pubblicato in: 50th IAH Congress, 2024
Editore: IAH
DOI: 10.1007/s13201-024-02320-1

A Machine Learning Approach to Map the Vulnerability of Groundwater Resources to Agricultural Contamination (si apre in una nuova finestra)

Autori: Victor Gómez-Escalonilla, Pedro Martínez-Santos
Pubblicato in: Hydrology, Numero 11, 2025, ISSN 2306-5338
Editore: MDPI
DOI: 10.3390/HYDROLOGY11090153

Modelling regional effects of artificial groundwater recharge in a multilayer aquifer characterized by perched water tables (si apre in una nuova finestra)

Autori: Gómez-Escalonilla V, Heredia J, Martínez-Santos P, López-Gutiérrez J, De la Hera-Portillo A
Pubblicato in: Hydrological Processes, Numero 38, 2024, ISSN 1099-1085
Editore: Wiley
DOI: 10.1002/hyp.15085

A machine learning approach to site groundwater contamination monitoring wells (si apre in una nuova finestra)

Autori: V. Gómez-Escalonilla, E. Montero-González, S. Díaz-Alcaide, M. Martín-Loeches, M. Rodríguez del Rosario, P. Martínez-Santos
Pubblicato in: Applied Water Science, Numero 14, 2024, ISSN 2190-5487
Editore: Springer Science and Business Media LLC
DOI: 10.1007/S13201-024-02320-1

A surrogate approach to model groundwater level in time and space based on tree regressors (si apre in una nuova finestra)

Autori: Pedro Martínez-Santos, Víctor Gómez-Escalonilla, Silvia Díaz-Alcaide, Manuel Rodríguez del Rosario, Héctor Aguilera
Pubblicato in: Applied Water Science, Numero 15, 2025, ISSN 2190-5487
Editore: Springer Science and Business Media LLC
DOI: 10.1007/S13201-025-02572-5

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