Supporting STakeholders for Adaptive, Resilient and Sustainable Water Management

Risultati finali

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

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

Review of existing observational systems

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)

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

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

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)

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)

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

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: XIII Congreso Ibérico de Gestión y Planificación del Agua, 2025, ISBN 978-84-608-2132-8
Editore: Fundación Nueva Cultura del Agua

Temporal Scaling Laws for Wetting and Drying in Variably Saturated Soils

Autori: Sami Miaari, Stefan J Kollet
Pubblicato in: AGU24 Annual Meeting, 2024
Editore: AGU

Monitoring Long-Term Land Cover Transformations in the Danube Delta using Landsat Satellite Imagery

Autori: Albert Scrieciu, Andrei Toma
Pubblicato in: 2025
Editore: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-16549

The impact of Climate change on Water stress in a highly regulated River: Sensitivity to Changes in ENergy Demand, Water Use and Regulations

Autori: Hegdahl, T. J., Engeland, K., Huang, S., Gelati, E., Veie, C.A.
Pubblicato in: Nordic Hydrological Conference 2025, 2025
Editore: Nordic Hydrological Conference 2025

Integrating GRACE and ERA5-Land with simulations to estimate monthly groundwater table depth anomalies based on Random Forest and LSTM networks over the Seine River Basin

Autori: Avila, L., Kollet, S., de Lavenne, A., and Ramos, M.-H.
Pubblicato in: AGU24 Annual Meeting, 2024
Editore: AGU

Climate change impacts on hydropower production and water availability in the Drammen river basin in Norway

Autori: Engeland, K., Ayrault, N., Gelati, E., Hegdahl, T. J., Huang, S., and Veie, C. A.
Pubblicato in: 8th Conference on Modelling Hydrology, Climate and Land surface processes 2025, 2025
Editore: 8th Conference on Modelling Hydrology, Climate and Land surface processes 2025

"Climate change impacts on reservoir operations and water availability &#8211; a case study from Drammen river basin in Norway&#160;"

Autori: Kolbjorn Engeland, Emiliano Gelati, Trine Jahr Hegdahl, Shaochun Huang, Carl Andreas Veie
Pubblicato in: 2025
Editore: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-15110

RIBASIM Danube: Modeling water allocation in the Danube Basin with a focus on low-flow conditions

Autori: Tamara Graf, Martin Glas, Fatima Monji, Mario Klösch, Max Preiml, Judith ter Maat, Andrei Toma, Albert Scrieciu, Helmut Habersack
Pubblicato in: 2025
Editore: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-6640

Implications of incorporating anthropogenic water use in the hydrological model simulations of the Rhine basin

Autori: Devi Purnamasari, Willem van Verseveld, Joost Buitink, Frederiek Sperna Weiland, Brendan Dalmijn, Adriaan Teuling, Albrecht Weerts
Pubblicato in: 2025
Editore: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-15753

Nitrate spatial predictions by means of machine learning to improve groundwater monitoring networks

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

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.

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

Assessing water management vulnerability under future climate scenarios: the case of the reservoirs in the Seine River basin

Autori: Julie Collignan, Maria-Helena Ramos, Alban de Lavenne, Charlotte Barbé, Philippe Riboust
Pubblicato in: 2025
Editore: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-8618

Toward understanding transport and chloride dynamics at the catchment scale by combining StorAge Selection functions and a hydrological model

Autori: Amal Rabah, Alban de Lavenne, Maria-Helena Ramos
Pubblicato in: 2025
Editore: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-9559

A multi-reservoir machine learning model for forecasting reservoir storage at monthly and seasonal timescales

Autori: Helen Baron, Rishma Chengot, Nathan Rickards, Virginie Keller
Pubblicato in: 2025
Editore: Copernicus GmbH
DOI: 10.5194/EGUSPHERE-EGU25-9347

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

Enhancing Ribasim for reservoir operations: validating a new version with Canteen and expanding to the Drammen basin

Autori: Monji, F., Engeland, K., Gijsbers, P., Hegdahl, T.J., Kucharski, J., Visser, M., de Koning, B., Pronk. M., ter Maart, J., Duel, H., Hisdal, H.
Pubblicato in: Nordic Hydrological Conference 2025, 2025
Editore: Nordic Hydrological Conference 2025

Machine learning as a tool to improve groundwater monitoring networks

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

Extra constraint on actual evaporation in a semi-distributed conceptual model to improve model physical realism

Autori: Shu-Chen Hsu, Alban de Lavenne, Charles Perrin, Vazken Andréassian
Pubblicato in: Hydrological Sciences Journal, Numero 70, 2025, ISSN 0262-6667
Editore: Informa UK Limited
DOI: 10.1080/02626667.2025.2468846

A Machine Learning Approach to Map the Vulnerability of Groundwater Resources to Agricultural Contamination

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

Estimation of Monthly Water Table Depth Anomalies Based on the Integration of GRACE and ERA5-Land with Large-Scale Simulations Using Random Forest and LSTM Networks

Autori: Leandro Avila, Alban de Lavenne, Maria-Helena Ramos, Stefan Kollet
Pubblicato in: Water Resources Management, Numero 39, 2025, ISSN 0920-4741
Editore: Springer Science and Business Media LLC
DOI: 10.1007/S11269-025-04097-7

Modelling regional effects of artificial groundwater recharge in a multilayer aquifer characterized by perched water tables

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

Identifying irrigated areas using land surface temperature and hydrological modelling: application to the Rhine basin

Autori: Devi Purnamasari, Adriaan J. Teuling, Albrecht H. Weerts
Pubblicato in: Hydrology and Earth System Sciences, Numero 29, 2025, ISSN 1607-7938
Editore: Copernicus GmbH
DOI: 10.5194/HESS-29-1483-2025

A machine learning approach to site groundwater contamination monitoring wells

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

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

Risultati finali

Pubblicazioni

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