Publications

This page provides an overview of the peer-reviewed publications that used Pastas. The list is generated from the public Zotero library with the references. If you have used Pastas in your work, please add the reference to the Zotero library (collection Publications) and it will show up here automatically (after next commit/release). Pastas has also been used in a number of PhD, MSc, and BSc theses and a large number of non-published reports, partly listed in a GitHub repo here.

Peer-reviewed publications

2026

• Raoul A. Collenteur, Joaquin Jimenez-Martinez, Mario Schirmer, and Christian Moeck. A national-scale database of groundwater level data for Switzerland. Scientific Data, May 2026. URL: https://doi.org/10.1038/s41597-026-07353-6, doi:10.1038/s41597-026-07353-6.

2025

• Austin T. Barnes, Mark A. Merrifield, Kian Bagheri, Morgan C. Levy, and Hassan Davani. Flooding Projections Due To Groundwater Emergence Caused by Sea Level Variability. Earth's Future, 13(7):e2025EF006270, July 2025. URL: https://doi.org/10.1029/2025EF006270 (visited on 2025-07-13), doi:10.1029/2025EF006270.

• Raoul A. Collenteur, Martin A. Vonk, and Ezra Haaf. Quantification and Analysis of Hydrograph Behavior Using Groundwater Signatures. Groundwater, April 2025. URL: https://doi.org/10.1111/gwat.13486 (visited on 2025-04-23), doi:10.1111/gwat.13486.

• Luca Piciullo, Minu Treesa Abraham, Ida Norderhaug Drøsdal, and Erling Singstad Paulsen. An operational IoT-based slope stability forecast using a digital twin. Environmental Modelling & Software, 183:106228, January 2025. URL: https://www.sciencedirect.com/science/article/pii/S1364815224002895, doi:10.1016/j.envsoft.2024.106228.

• B. Strijker and M. Kok. The dynamics of peak head responses at Dutch canal dikes and the impact of climate change. Natural Hazards and Earth System Sciences, 25(9):3355–3379, 2025. URL: https://nhess.copernicus.org/articles/25/3355/2025/, doi:10.5194/nhess-25-3355-2025.

• Thomas Wöhling, Alvaro Oliver Crespo Delgadillo, Moritz Kraft, and Anneli Guthke. Comparing Physics-Based, Conceptual and Machine-Learning Models to Predict Groundwater Levels by BMA. Groundwater, April 2025. URL: https://doi.org/10.1111/gwat.13487 (visited on 2025-04-23), doi:10.1111/gwat.13487.

2024

• Alise Babre, Konrāds Popovs, Andis Kalvāns, Marta Jemeļjanova, and Aija Dēliņa. "Forecasting the groundwater levels in the Baltic through standardized index analysis". Weather and Climate Extremes, pages 100728, October 2024. URL: https://www.sciencedirect.com/science/article/pii/S2212094724000896, doi:10.1016/j.wace.2024.100728.

• Hejiang Cai, Haiyun Shi, Zhaoqiang Zhou, Suning Liu, and Vladan Babovic. Explaining the Mechanism of Multiscale Groundwater Drought Events: A New Perspective From Interpretable Deep Learning Model. Water Resources Research, 60(7):e2023WR035139, July 2024. URL: https://doi.org/10.1029/2023WR035139 (visited on 2024-06-28), doi:10.1029/2023WR035139.

• R. A. Collenteur, E. Haaf, M. Bakker, T. Liesch, A. Wunsch, J. Soonthornrangsan, J. White, N. Martin, R. Hugman, E. de Sousa, D. Vanden Berghe, X. Fan, T. J. Peterson, J. Bikše, A. Di Ciacca, X. Wang, Y. Zheng, M. Nölscher, J. Koch, R. Schneider, N. Benavides Höglund, S. Krishna Reddy Chidepudi, A. Henriot, N. Massei, A. Jardani, M. G. Rudolph, A. Rouhani, J. J. Gómez-Hernández, S. Jomaa, A. Pölz, T. Franken, M. Behbooei, J. Lin, and R. Meysami. Data-driven modelling of hydraulic-head time series: results and lessons learned from the 2022 Groundwater Time Series Modelling Challenge. Hydrology and Earth System Sciences, 28(23):5193–5208, 2024. URL: https://hess.copernicus.org/articles/28/5193/2024/, doi:10.5194/hess-28-5193-2024.

• Ryan S. Frederiks, Anner Paldor, Lauren Donati, Glen Carleton, and Holly A. Michael. Drivers of barrier island water-table fluctuations and groundwater salinization. Science of The Total Environment, 946:174102, October 2024. URL: https://www.sciencedirect.com/science/article/pii/S0048969724042505, doi:10.1016/j.scitotenv.2024.174102.

• Ainur Kokimova, Raoul A. Collenteur, and Steffen Birk. Exploring the power of data-driven models for groundwater system conceptualization: a case study of the Grazer Feld Aquifer, Austria. Hydrogeology Journal, September 2024. URL: https://doi.org/10.1007/s10040-024-02830-x, doi:10.1007/s10040-024-02830-x.

• Wout A. Schutten, Michiel Pezij, Rick J. Hogeboom, U. Nicole Jungermann, and Denie C.M. Augustijn. Understanding groundwater droughts using detrended historical meteorological data and long-term groundwater modelling. Netherlands Journal of Geosciences, 103:e25, 2024. Edition: 2024/12/05. URL: https://www.cambridge.org/core/product/A0BFDC7373EB7015535A3AE26014948E, doi:10.1017/njg.2024.22.

• Jenny T. Soonthornrangsan, Mark Bakker, and Femke C. Vossepoel. Linked Data-Driven, Physics-Based Modeling of Pumping-Induced Subsidence with Application to Bangkok, Thailand. Groundwater, October 2024. URL: https://doi.org/10.1111/gwat.13443 (visited on 2024-10-13), doi:10.1111/gwat.13443.

• Martin A. Vonk, Raoul A. Collenteur, Sorab Panday, Frans Schaars, and Mark Bakker. Time Series Analysis of Nonlinear Head Dynamics Using Synthetic Data Generated with a Variably Saturated Model. Groundwater, April 2024. URL: https://doi.org/10.1111/gwat.13403 (visited on 2024-04-08), doi:10.1111/gwat.13403.

2023

• Raoul A. Collenteur, Christian Moeck, Mario Schirmer, and Steffen Birk. Analysis of nationwide groundwater monitoring networks using lumped-parameter models. Journal of Hydrology, 626:130120, November 2023. URL: https://www.sciencedirect.com/science/article/pii/S0022169423010624, doi:10.1016/j.jhydrol.2023.130120.

• Marta Jemeļjanova, Raoul A. Collenteur, Alexander Kmoch, Jānis Bikše, Konrāds Popovs, and Andis Kalvāns. Modeling hydraulic heads with impulse response functions in different environmental settings of the Baltic countries. Journal of Hydrology: Regional Studies, 47:101416, June 2023. URL: https://www.sciencedirect.com/science/article/pii/S2214581823001039, doi:10.1016/j.ejrh.2023.101416.

• Lars T Kreutzer, Edward Gillen, Joshua T Briegal, and Didier Queloz. S-ACF: a selective estimator for the autocorrelation function of irregularly sampled time series. Monthly Notices of the Royal Astronomical Society, 522(4):5049–5061, July 2023. URL: https://doi.org/10.1093/mnras/stad1223 (visited on 2023-06-22), doi:10.1093/mnras/stad1223.

• Max Gustav Rudolph, Raoul Alexander Collenteur, Alireza Kavousi, Markus Giese, Thomas Wöhling, Steffen Birk, Andreas Hartmann, and Thomas Reimann. A data-driven approach for modelling Karst spring discharge using transfer function noise models. Environmental Earth Sciences, 82(13):339, June 2023. URL: https://doi.org/10.1007/s12665-023-11012-z, doi:10.1007/s12665-023-11012-z.

• Henri Schauer, Stefan Schlaffer, Emanuel Bueechi, and Wouter Dorigo. Inundation–Desiccation State Prediction for Salt Pans in the Western Pannonian Basin Using Remote Sensing, Groundwater, and Meteorological Data. Remote Sensing, 2023. doi:10.3390/rs15194659.

• Eivind Stein, Jenny Langford, and Mats Kahlström. Time series modelling: applications for groundwater control in urban tunnelling. Bulletin of Engineering Geology and the Environment, 82(10):391, September 2023. URL: https://doi.org/10.1007/s10064-023-03419-6, doi:10.1007/s10064-023-03419-6.

2022

• A. Babre, A. Kalvāns, Z. Avotniece, I. Retiķe, J. Bikše, K. P. M. Jemeljanova, A. Zelenkevičs, and A. Dēliņa. The use of predefined drought indices for the assessment of groundwater drought episodes in the Baltic States over the period 1989–2018. Journal of Hydrology: Regional Studies, 40:101049, April 2022. location=Estonia, Latvia, Lithuania. URL: https://www.sciencedirect.com/science/article/pii/S2214581822000623, doi:10.1016/j.ejrh.2022.101049.

• D. A. Brakenhoff, M. A. Vonk, R. A. Collenteur, M. Van Baar, and M. Bakker. Application of Time Series Analysis to Estimate Drawdown From Multiple Well Fields. Frontiers in Earth Science, 2022. location=The Netherlands. URL: https://www.frontiersin.org/article/10.3389/feart.2022.907609, doi:10.3389/feart.2022.907609.

• E. Brakkee, M. H. J. van Huijgevoort, and R. P. Bartholomeus. Improved understanding of regional groundwater drought development through time series modelling: the 2018–2019 drought in the Netherlands. Hydrology and Earth System Sciences, 26(3):551–569, 2022. location=The Netherlands. URL: https://hess.copernicus.org/articles/26/551/2022/, doi:10.5194/hess-26-551-2022.

• J. Uwihirwe, M. Hrachowitz, and T. Bogaard. Integration of observed and model-derived groundwater levels in landslide threshold models in Rwanda. Natural Hazards and Earth System Sciences, 22(5):1723–1742, 2022. location=Rwanda. URL: https://nhess.copernicus.org/articles/22/1723/2022/, doi:10.5194/nhess-22-1723-2022.

• S. Zipper, I. Popescu, K. Compare, C. Zhang, and E. C. Seybold. Alternative stable states and hydrological regime shifts in a large intermittent river. Environmental Research Letters, 17(7):074005, June 2022. location=USA. URL: https://dx.doi.org/10.1088/1748-9326/ac7539, doi:10.1088/1748-9326/ac7539.

2021

• R. A. Collenteur. How Good Is Your Model Fit? Weighted Goodness-of-Fit Metrics for Irregular Time Series. Groundwater, 59(4):474–478, July 2021. location=The Netherlands. URL: https://doi.org/10.1111/gwat.13111, doi:10.1111/gwat.13111.

• R. A. Collenteur, M. Bakker, G. Klammler, and S. Birk. Estimation of groundwater recharge from groundwater levels using nonlinear transfer function noise models and comparison to lysimeter data. Hydrology and Earth System Sciences, 25(5):2931–2949, 2021. location=Austria. URL: https://hess.copernicus.org/articles/25/2931/2021/, doi:10.5194/hess-25-2931-2021.

2020

• M. Pezij, D. C. M. Augustijn, D. M. D. Hendriks, and S. J. M. H. Hulscher. Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data. Environmental Modelling & Software, 131:104756, 2020. location=The Netherlands. URL: https://www.sciencedirect.com/science/article/pii/S1364815220300876, doi:https://doi.org/10.1016/j.envsoft.2020.104756.

• A. Urgilez Vinueza, J. Robles, M. Bakker, P. Guzman, and T. Bogaard. Characterization and Hydrological Analysis of the Guarumales Deep-Seated Landslide in the Tropical Ecuadorian Andes. Geosciences, 2020. location=Equador. URL: https://www.mdpi.com/2076-3263/10/7/267, doi:10.3390/geosciences10070267.

2019

• M. Bakker. Time Series Analysis to the Rescue. Groundwater, 57(6):825–825, November 2019. URL: https://doi.org/10.1111/gwat.12930, doi:10.1111/gwat.12930.

• M. Bakker and F. Schaars. Solving Groundwater Flow Problems with Time Series Analysis: You May Not Even Need Another Model. Groundwater, 57(6):826–833, November 2019. location=The Netherlands. URL: https://doi.org/10.1111/gwat.12927, doi:10.1111/gwat.12927.

• R. A. Collenteur, M. Bakker, R. Caljé, S. A. Klop, and F. Schaars. Pastas: Open Source Software for the Analysis of Groundwater Time Series. Groundwater, 57(6):877–885, November 2019. location=USA, The Netherlands. URL: https://doi.org/10.1111/gwat.12925, doi:10.1111/gwat.12925.

• Raoul A. Collenteur, Mark Bakker, Ruben Caljé, Stijn A. Klop, and Frans Schaars. Pastas: Open Source Software for the Analysis of Groundwater Time Series. Groundwater, 57(6):877–885, 2019. _eprint: https://ngwa.onlinelibrary.wiley.com/doi/pdf/10.1111/gwat.12925. URL: https://onlinelibrary.wiley.com/doi/abs/10.1111/gwat.12925 (visited on 2026-04-21), doi:10.1111/gwat.12925.