Publications
2025
Scholarly publications
Ruijsch, D., van Mourik, J., Biemans, H., Hauswirth, S. M., & Wanders, N. (2025, Apr 22). Thrive or Wither: Exploring the Impacts of Multi-Year Droughts on Vegetation. [DOI]
Ruijsch, D., Hauswirth, S. M., Biemans, H., & Wanders, N. (2025, Nov 3). Supplementary material to "Exploring the Potential of LPJmL-5 to Simulate Vegetation Responses to (Multi-Year) Droughts". [DOI]
Verhoeve, S., Hauswirth, S., de Jong, S., & Wanders, N. (2025, Mar 18). Spatial dependence of vegetation recovery after drought events and the spatiotemporal characteristics. [DOI]
Ruijsch, D., van Mourik, J., Biemans, H., Hauswirth, S., & Wanders, N. (2025, Mar 18). Understanding the Impact of Multi-Year Droughts on Vegetation: An Observational and Model Approach. [DOI]
Hauswirth, S. M., & Wanders, N. (2025, Mar 18). Large-scale groundwater drought recovery assessment using a 1km global groundwater model. [DOI]
Biella, R., Shyrokaya, A., Ionita, M., Vignola, R., Sutanto, S. J., Todorovic, A., Teutschbein, C., Cid, D., Llasat, M. C., Alencar, P., Matanó, A., Ridolfi, E., Moccia, B., Pechlivanidis, I., Van Loon, A., Wendt, D. E., Stenfors, E., Russo, F., Vidal, J. P., ... Tallaksen, L. M. (2025). The 2022 drought needs to be a turning point for European drought risk management. Natural Hazards and Earth System Sciences, 25(11), 4475-4501. [DOI] [Portal]
Hauswirth, S. M., Bierkens, M. F. P., Beijk, V., & Wanders, N. (2025). Exploring Water Management Strategies for Mitigating Local Drought Impacts in the Netherlands using Data-Driven methods previously used for Simulations to Projections. Abstract from EGU General Assembly 2024, Vienna, Austria. [DOI]
2024
Scholarly publications
Hauswirth, S. (2024). Hydrological Droughts in the Netherlands: from Simulations to Projections using Data-Driven Methods. [Doctoral thesis 1 (Research UU / Graduation UU), Universiteit Utrecht]. Utrecht University. [DOI] [Repository]
2023
Scholarly publications
Hauswirth, S. M., van der Wiel, K., Bierkens, M. F. P., Beijk, V., & Wanders, N. (2023). Simulating Hydrological Extremes for different Warming Levels – combining Large Scale Climate Ensembles with local observation based Machine Learning models. Abstract from EGU General Assembly 2023, Vienna, Austria. [DOI]
Hauswirth, S. M., Bierkens, M. F. P., Beijk, V., & Wanders, N. (2023). The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting. Hydrology and Earth System Sciences, 27(2), 501–517. [DOI] [Repository]
Hauswirth, S. M., van der Wiel, K., Bierkens, M. F. P., Beijk, V., & Wanders, N. (2023). Simulating hydrological extremes for different warming levels: combining large scale climate ensembles with local observation based machine learning models. Frontiers in Water, 5, 1-13. Article 1108108. [DOI] [Repository]
2022
Scholarly publications
Hauswirth, S. M., Bierkens, M. F. P., Beijk, V., & Wanders, N. (2022). The potential of a hybrid framework including data driven approaches for hydrological forecasting. Abstract from European Geoscience Union (EGU) General Assembly 2022, Vienna, Austria. [DOI]
2021
Scholarly publications
Hauswirth, S. M., Bierkens, M., Beijk, V., & Wanders, N. (2021). The potential of data driven approaches for quantifying hydrological extremes. Abstract from EGU General Assembly 2021, Vienna, Austria. [DOI]
Hauswirth, S. M., Bierkens, M. F. P., Beijk, V., & Wanders, N. (2021). The potential of data driven approaches for quantifying hydrological extremes. Advances in Water Resources, 155, 1-24. Article 104017. [DOI] [Repository]