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.
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 Publisher: IOP Publishing. URL: https://dx.doi.org/10.1088/1748-9326/ac7539, doi:10.1088/1748-9326/ac7539.
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 Publisher: John Wiley & Sons, Ltd. 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.
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.
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.