Articles | Volume 26, issue 10
https://doi.org/10.5194/hess-26-2715-2022
© Author(s) 2022. 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-26-2715-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Quantifying multi-year hydrological memory with Catchment Forgetting Curves
Alban de Lavenne
CORRESPONDING AUTHOR
Swedish Meteorological and Hydrological Institute (SMHI), Hydrology Research Department, Norrköping, Sweden
Université Paris‐Saclay, INRAE, UR HYCAR, Antony, France
Vazken Andréassian
Université Paris‐Saclay, INRAE, UR HYCAR, Antony, France
Louise Crochemore
Swedish Meteorological and Hydrological Institute (SMHI), Hydrology Research Department, Norrköping, Sweden
INRAE, UR RiverLy, Lyon, France
Université Grenoble Alpes, CNRS, IRD, Grenoble INP, IGE, Grenoble, France
Göran Lindström
Swedish Meteorological and Hydrological Institute (SMHI), Hydrology Research Department, Norrköping, Sweden
Berit Arheimer
Swedish Meteorological and Hydrological Institute (SMHI), Hydrology Research Department, Norrköping, Sweden
Viewed
Total article views: 4,193 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Jun 2021)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
3,103 | 1,024 | 66 | 4,193 | 80 | 55 |
- HTML: 3,103
- PDF: 1,024
- XML: 66
- Total: 4,193
- BibTeX: 80
- EndNote: 55
Total article views: 2,817 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 May 2022)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
2,253 | 528 | 36 | 2,817 | 58 | 40 |
- HTML: 2,253
- PDF: 528
- XML: 36
- Total: 2,817
- BibTeX: 58
- EndNote: 40
Total article views: 1,376 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 24 Jun 2021)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
850 | 496 | 30 | 1,376 | 22 | 15 |
- HTML: 850
- PDF: 496
- XML: 30
- Total: 1,376
- BibTeX: 22
- EndNote: 15
Viewed (geographical distribution)
Total article views: 4,193 (including HTML, PDF, and XML)
Thereof 3,869 with geography defined
and 324 with unknown origin.
Total article views: 2,817 (including HTML, PDF, and XML)
Thereof 2,580 with geography defined
and 237 with unknown origin.
Total article views: 1,376 (including HTML, PDF, and XML)
Thereof 1,289 with geography defined
and 87 with unknown origin.
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Country | # | Views | % |
---|
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Total: | 0 |
HTML: | 0 |
PDF: | 0 |
XML: | 0 |
- 1
1
Cited
15 citations as recorded by crossref.
- Temporal hydrological drought clustering varies with climate and land-surface processes M. Brunner & K. Stahl 10.1088/1748-9326/acb8ca
- Seasonal catchment memory of high mountain rivers in the Tibetan Plateau H. Gu et al. 10.1038/s41467-023-38966-9
- Toward interpretable LSTM-based modeling of hydrological systems L. De la Fuente et al. 10.5194/hess-28-945-2024
- Assessing fluctuations of long-memory environmental variables based on the robustified dynamic Orlicz risk H. Yoshioka & Y. Yoshioka 10.1016/j.chaos.2023.114336
- Decoding lake water dynamics to optimize watershed agriculture through isotopic analyses of memory effects and hydrological connectivity J. Wu et al. 10.1016/j.ecolind.2024.112826
- How can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models? R. Hashemi et al. 10.5194/hess-26-5793-2022
- Winter post-droughts amplify extreme nitrate concentrations in German rivers F. Saavedra et al. 10.1088/1748-9326/ad19ed
- Evaluation of Earth Observations and In Situ Data Assimilation for Seasonal Hydrological Forecasting J. Musuuza et al. 10.1029/2022WR033655
- Sensitive or resilient catchment?: A Budyko-based modeling approach for climate change and anthropogenic stress under historical to CMIP6 future scenarios S. Swain et al. 10.1016/j.jhydrol.2023.129651
- Is the ‘Year Without a Summer’ imprinted in continental varve thickness records? K. Pleskot & B. Zolitschka 10.1016/j.quascirev.2024.109085
- Estimation of seasonal precipitation memory curves for major rivers in the Tibetan Plateau based on GRACE satellites data H. Gu et al. 10.1016/j.ejrh.2024.101942
- Can the young water fraction reduce predictive uncertainty in water transit time estimations? A. Borriero et al. 10.1016/j.jhydrol.2024.132238
- Review article: Drought as a continuum – memory effects in interlinked hydrological, ecological, and social systems A. Van Loon et al. 10.5194/nhess-24-3173-2024
- Exploring groundwater drought responsiveness in lowland post-glacial environments M. Nygren et al. 10.1007/s10040-022-02521-5
- Impact of the North Sea–Caspian pattern on meteorological drought and vegetation response over diverging environmental systems in western Eurasia Q. He et al. 10.1002/eco.2446
14 citations as recorded by crossref.
- Temporal hydrological drought clustering varies with climate and land-surface processes M. Brunner & K. Stahl 10.1088/1748-9326/acb8ca
- Seasonal catchment memory of high mountain rivers in the Tibetan Plateau H. Gu et al. 10.1038/s41467-023-38966-9
- Toward interpretable LSTM-based modeling of hydrological systems L. De la Fuente et al. 10.5194/hess-28-945-2024
- Assessing fluctuations of long-memory environmental variables based on the robustified dynamic Orlicz risk H. Yoshioka & Y. Yoshioka 10.1016/j.chaos.2023.114336
- Decoding lake water dynamics to optimize watershed agriculture through isotopic analyses of memory effects and hydrological connectivity J. Wu et al. 10.1016/j.ecolind.2024.112826
- How can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models? R. Hashemi et al. 10.5194/hess-26-5793-2022
- Winter post-droughts amplify extreme nitrate concentrations in German rivers F. Saavedra et al. 10.1088/1748-9326/ad19ed
- Evaluation of Earth Observations and In Situ Data Assimilation for Seasonal Hydrological Forecasting J. Musuuza et al. 10.1029/2022WR033655
- Sensitive or resilient catchment?: A Budyko-based modeling approach for climate change and anthropogenic stress under historical to CMIP6 future scenarios S. Swain et al. 10.1016/j.jhydrol.2023.129651
- Is the ‘Year Without a Summer’ imprinted in continental varve thickness records? K. Pleskot & B. Zolitschka 10.1016/j.quascirev.2024.109085
- Estimation of seasonal precipitation memory curves for major rivers in the Tibetan Plateau based on GRACE satellites data H. Gu et al. 10.1016/j.ejrh.2024.101942
- Can the young water fraction reduce predictive uncertainty in water transit time estimations? A. Borriero et al. 10.1016/j.jhydrol.2024.132238
- Review article: Drought as a continuum – memory effects in interlinked hydrological, ecological, and social systems A. Van Loon et al. 10.5194/nhess-24-3173-2024
- Exploring groundwater drought responsiveness in lowland post-glacial environments M. Nygren et al. 10.1007/s10040-022-02521-5
Latest update: 26 Dec 2024
Short summary
A watershed remembers the past to some extent, and this memory influences its behavior. This memory is defined by the ability to store past rainfall for several years. By releasing this water into the river or the atmosphere, it tends to forget. We describe how this memory fades over time in France and Sweden. A few watersheds show a multi-year memory. It increases with the influence of groundwater or dry conditions. After 3 or 4 years, they behave independently of the past.
A watershed remembers the past to some extent, and this memory influences its behavior. This...