Articles | Volume 29, issue 5
https://doi.org/10.5194/hess-29-1319-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-1319-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Mar 2025
Research article |
| 11 Mar 2025
| 11 Mar 2025
Annual memory in the terrestrial water cycle
Department of Earth Sciences, Free University Amsterdam, Amsterdam, the Netherlands
Ross A. Woods
School of Civil, Aerospace, and Design Engineering, University of Bristol, Bristol, United Kingdom
Bailey J. Anderson
WSL Institute for Snow and Avalanche Research SLF, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Davos Dorf, Switzerland
Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Anna Luisa Hemshorn de Sánchez
Department of Earth Sciences, Free University Amsterdam, Amsterdam, the Netherlands
Markus Hrachowitz
Department of Water Management, Delft University of Technology, Delft, the Netherlands
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17 citations as recorded by crossref.
- New morphology of the water cycle: A reaction–diffusion framework for evapotranspiration dynamics in degraded landscapes beyond empiricism A. Paredes https://doi.org/10.1016/j.advwatres.2026.105326
- Multifractal detrended fluctuation analysis of hydroclimatic series across Uganda in East Africa M. Opwonya & C. Onyutha https://doi.org/10.1016/j.hydrch.2026.100007
- A study of the relationship between GRACE-TWSA and large-scale atmospheric-oceanic patterns B. Vaheddoost & B. Mohammadi https://doi.org/10.1080/02626667.2025.2537851
- Sensitivities of mean and extreme streamflow to climate variability across Europe A. Hemshorn de Sánchez et al. https://doi.org/10.5194/hess-30-2667-2026
- Integrated Multi-scale Assessment of CHIRPS and PERSIANN-CDR for Meteorological, Agricultural, and Hydrological Drought Monitoring in Semi-arid Environments O. Laassilia et al. https://doi.org/10.1007/s41748-026-01120-8
- More concentrated precipitation decreases terrestrial water storage C. Lesk & J. Mankin https://doi.org/10.1038/s41586-026-10487-7
- Data-Driven Detection of Climate–Streamflow Dependencies and Multi-Year Hydrological Persistence in Brazilian Reservoir Systems L. Mendoza et al. https://doi.org/10.3390/w18121499
- Improving Streamflow Forecasting with Multisource Data and ANNs: A Case Study in the Miranda River Basin, Brazil C. Bouix et al. https://doi.org/10.3390/ai7080295
- Hybrid models generalize better to warmer climate conditions than process-based and purely data-driven models J. Bohl et al. https://doi.org/10.5194/hess-30-4667-2026
- Multi-model integration framework for monthly runoff prediction based on variational mode decomposition (VMD) and trend-based modeling S. Wang et al. https://doi.org/10.1007/s00477-026-03170-w
- Augmenting observation network design and assimilation frequency in distributed hydrological models: insights from the LISFLOOD-based hydrological data assimilation framework K. Kurugama et al. https://doi.org/10.1016/j.jhydrol.2025.134853
- Integrating machine learning models with ground sensors to enhance soil moisture prediction in agroecosystems of Texas G. Tefera et al. https://doi.org/10.1016/j.compag.2025.111358
- Hydrological response to drought-flood and flood-drought transitions in the Geul River basin, Netherlands S. Hariharan Sudha et al. https://doi.org/10.1016/j.ejrh.2026.103727
- Streamflow forecasting using Kolmogorov-Arnold network V. Varma & J. Patel https://doi.org/10.1088/2631-8695/addd66
- Hydrometric assessment of Himalayan springs using classical hydrological methods for springshed management B. Dass et al. https://doi.org/10.1038/s41598-026-44533-1
- A runoff prediction method for arid regions integrating physics-guided signal extraction and temporally adaptive feature selection Z. Li et al. https://doi.org/10.1016/j.ejrh.2025.103034
- Multi-step ahead streamflow forecasting method using Embedding Multi-Layer Perceptron Y. Li & S. Yang https://doi.org/10.1016/j.ejrh.2026.103349
Saved (final revised paper)
Latest update: 11 Aug 2026
Short summary
Water balances of catchments will often strongly depend on their state in the recent past, but such memory effects may persist at annual timescales. We use global data sets to show that annual memory is typically absent in precipitation but strong in terrestrial water stores and also present in evaporation and streamflow (including low flows and floods). Our experiments show that hysteretic models provide behaviour that is consistent with these observed memory behaviours.
Water balances of catchments will often strongly depend on their state in the recent past, but...
