Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4011-2024
© Author(s) 2024. 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-28-4011-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Sep 2024
Research article |
| 03 Sep 2024
| 03 Sep 2024
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, the Netherlands
Markus Hrachowitz
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, the Netherlands
Gerrit Schoups
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628CN Delft, the Netherlands
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Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
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This study shows that previously reported underestimations of water ages are most likely not due to the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and instead adopting StorAge Selection (SAS)-based or comparable model formulations.
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Hydrol. Earth Syst. Sci., 29, 3545–3568, https://doi.org/10.5194/hess-29-3545-2025, https://doi.org/10.5194/hess-29-3545-2025, 2025
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Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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Thiago Victor Medeiros do Nascimento, Julia Rudlang, Sebastian Gnann, Jan Seibert, Markus Hrachowitz, and Fabrizio Fenicia
EGUsphere, https://doi.org/10.5194/egusphere-2025-739, https://doi.org/10.5194/egusphere-2025-739, 2025
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Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
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Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
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Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
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Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661, https://doi.org/10.5194/nhess-22-3641-2022, https://doi.org/10.5194/nhess-22-3641-2022, 2022
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Judith Uwihirwe, Markus Hrachowitz, and Thom Bogaard
Nat. Hazards Earth Syst. Sci., 22, 1723–1742, https://doi.org/10.5194/nhess-22-1723-2022, https://doi.org/10.5194/nhess-22-1723-2022, 2022
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Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
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Laurène J. E. Bouaziz, Emma E. Aalbers, Albrecht H. Weerts, Mark Hegnauer, Hendrik Buiteveld, Rita Lammersen, Jasper Stam, Eric Sprokkereef, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 26, 1295–1318, https://doi.org/10.5194/hess-26-1295-2022, https://doi.org/10.5194/hess-26-1295-2022, 2022
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Punpim Puttaraksa Mapiam, Monton Methaprayun, Thom Bogaard, Gerrit Schoups, and Marie-Claire Ten Veldhuis
Hydrol. Earth Syst. Sci., 26, 775–794, https://doi.org/10.5194/hess-26-775-2022, https://doi.org/10.5194/hess-26-775-2022, 2022
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The density of rain gauge networks plays an important role in radar rainfall bias correction. In this work, we aimed to assess the extent to which daily rainfall observations from a dense network of citizen scientists improve the accuracy of hourly radar rainfall estimates in the Tubma Basin, Thailand. Results show that citizen rain gauges significantly enhance the performance of radar rainfall bias adjustment up to a range of about 40 km from the center of the citizen rain gauge network.
Markus Hrachowitz, Michael Stockinger, Miriam Coenders-Gerrits, Ruud van der Ent, Heye Bogena, Andreas Lücke, and Christine Stumpp
Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, https://doi.org/10.5194/hess-25-4887-2021, 2021
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Deforestation affects how catchments store and release water. Here we found that deforestation in the study catchment led to a 20 % increase in mean runoff, while reducing the vegetation-accessible water storage from about 258 to 101 mm. As a consequence, fractions of young water in the stream increased by up to 25 % during wet periods. This implies that water and solutes are more rapidly routed to the stream, which can, after contamination, lead to increased contaminant peak concentrations.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, and Andrea Alessandri
Earth Syst. Dynam., 12, 725–743, https://doi.org/10.5194/esd-12-725-2021, https://doi.org/10.5194/esd-12-725-2021, 2021
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The roots of vegetation largely control the Earth's water cycle by transporting water from the subsurface to the atmosphere but are not adequately represented in land surface models, causing uncertainties in modeled water fluxes. We replaced the root parameters in an existing model with more realistic ones that account for a climate control on root development and found improved timing of modeled river discharge. Further extension of our approach could improve modeled water fluxes globally.
Sarah Hanus, Markus Hrachowitz, Harry Zekollari, Gerrit Schoups, Miren Vizcaino, and Roland Kaitna
Hydrol. Earth Syst. Sci., 25, 3429–3453, https://doi.org/10.5194/hess-25-3429-2021, https://doi.org/10.5194/hess-25-3429-2021, 2021
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This study investigates the effects of climate change on runoff patterns in six Alpine catchments in Austria at the end of the 21st century. Our results indicate a substantial shift to earlier occurrences in annual maximum and minimum flows in high-elevation catchments. Magnitudes of annual extremes are projected to increase under a moderate emission scenario in all catchments. Changes are generally more pronounced for high-elevation catchments.
Cody C. Routson, Darrell S. Kaufman, Nicholas P. McKay, Michael P. Erb, Stéphanie H. Arcusa, Kendrick J. Brown, Matthew E. Kirby, Jeremiah P. Marsicek, R. Scott Anderson, Gonzalo Jiménez-Moreno, Jessica R. Rodysill, Matthew S. Lachniet, Sherilyn C. Fritz, Joseph R. Bennett, Michelle F. Goman, Sarah E. Metcalfe, Jennifer M. Galloway, Gerrit Schoups, David B. Wahl, Jesse L. Morris, Francisca Staines-Urías, Andria Dawson, Bryan N. Shuman, Daniel G. Gavin, Jeffrey S. Munroe, and Brian F. Cumming
Earth Syst. Sci. Data, 13, 1613–1632, https://doi.org/10.5194/essd-13-1613-2021, https://doi.org/10.5194/essd-13-1613-2021, 2021
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We present a curated database of western North American Holocene paleoclimate records, which have been screened on length, resolution, and geochronology. The database gathers paleoclimate time series that reflect temperature, hydroclimate, or circulation features from terrestrial and marine sites, spanning a region from Mexico to Alaska. This publicly accessible collection will facilitate a broad range of paleoclimate inquiry.
Artemis Roodari, Markus Hrachowitz, Farzad Hassanpour, and Mostafa Yaghoobzadeh
Hydrol. Earth Syst. Sci., 25, 1943–1967, https://doi.org/10.5194/hess-25-1943-2021, https://doi.org/10.5194/hess-25-1943-2021, 2021
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In a combined data analysis and modeling study in the transboundary Helmand River basin, we analyzed spatial patterns of drought and changes therein based on the drought indices as well as on absolute water deficits. Overall the results illustrate that flow deficits and the associated droughts clearly reflect the dynamic interplay between temporally varying regional differences in hydro-meteorological variables together with subtle and temporally varying effects linked to human intervention.
Laurène J. E. Bouaziz, Fabrizio Fenicia, Guillaume Thirel, Tanja de Boer-Euser, Joost Buitink, Claudia C. Brauer, Jan De Niel, Benjamin J. Dewals, Gilles Drogue, Benjamin Grelier, Lieke A. Melsen, Sotirios Moustakas, Jiri Nossent, Fernando Pereira, Eric Sprokkereef, Jasper Stam, Albrecht H. Weerts, Patrick Willems, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, https://doi.org/10.5194/hess-25-1069-2021, 2021
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We quantify the differences in internal states and fluxes of 12 process-based models with similar streamflow performance and assess their plausibility using remotely sensed estimates of evaporation, snow cover, soil moisture and total storage anomalies. The dissimilarities in internal process representation imply that these models cannot all simultaneously be close to reality. Therefore, we invite modelers to evaluate their models using multiple variables and to rely on multi-model studies.
Petra Hulsman, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 25, 957–982, https://doi.org/10.5194/hess-25-957-2021, https://doi.org/10.5194/hess-25-957-2021, 2021
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Satellite observations have increasingly been used for model calibration, while model structural developments largely rely on discharge data. For large river basins, this often results in poor representations of system internal processes. This study explores the combined use of satellite-based evaporation and total water storage data for model structural improvement and spatial–temporal model calibration for a large, semi-arid and data-scarce river system.
Ralf Loritz, Markus Hrachowitz, Malte Neuper, and Erwin Zehe
Hydrol. Earth Syst. Sci., 25, 147–167, https://doi.org/10.5194/hess-25-147-2021, https://doi.org/10.5194/hess-25-147-2021, 2021
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This study investigates the role and value of distributed rainfall in the runoff generation of a mesoscale catchment. We compare the performance of different hydrological models at different periods and show that a distributed model driven by distributed rainfall yields improved performances only during certain periods. We then step beyond this finding and develop a spatially adaptive model that is capable of dynamically adjusting its spatial model structure in time.
Cited articles
AghaKouchak, A., Feldman, D., Hoerling, M., Huxman, T., and Lund, J.: Water and climate: Recognize anthropogenic drought, Nature, 524, 409–411, https://doi.org/10.1038/524409a, 2015.
Ajami, N. K., Gupta, H., Wagener, T., and Sorooshian, S.: Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system, J. Hydrol., 298, 112–135, https://doi.org/10.1016/j.jhydrol.2004.03.033, 2004.
Alila, Y., Kuraś, P. K., Schnorbus, M., and Hudson, R.: Forests and floods: A new paradigm sheds light on age-old controversies, Water Resour. Res., 45, W08416, https://doi.org/10.1029/2008WR007207, 2009.
Bahremand, A. and Hosseinalizadeh, M.: Development of conceptual hydrological FLEX-Topo model for loess watersheds influenced by piping and tunnel erosion in Golestan Province of Iran, Journal of Water and Soil Conservation, 29, 115–133, https://doi.org/10.22069/jwsc.2022.20050.3544, 2022.
Berghuijs, W. R. and Woods, R.: A simple framework to quantitatively describe monthly precipitation and temperature climatology, Int. J. Climatol., 36, 3161–3174, https://doi.org/10.1002/joc.4544, 2016.
Berghuijs, W. R., Larsen, J. R., Van Emmerik, T. H., and Woods, R. A.: A global assessment of runoff sensitivity to changes in precipitation, potential evaporation, and other factors, Water Resour. Res., 53, 8475–8486, https://doi.org/10.1002/2017WR021593, 2017.
BfG: Streamflow datasets in Germany, BfG [data set], https://portal.grdc.bafg.de/applications/public.html?publicuser=PublicUser#dataDownload/Stations, last access: 27 August 2024.
Bouaziz, L., Weerts, A., Schellekens, J., Sprokkereef, E., Stam, J., Savenije, H., and Hrachowitz, M.: Redressing the balance: quantifying net intercatchment groundwater flows, Hydrol. Earth Syst. Sci., 22, 6415–6434, https://doi.org/10.5194/hess-22-6415-2018, 2018.
Bouaziz, L. J., Steele-Dunne, S. C., Schellekens, J., Weerts, A. H., Stam, J., Sprokkereef, E., Winsemius, H. H., Savenije, H. H., and Hrachowitz, M.: Improved understanding of the link between catchment-scale vegetation accessible storage and satellite-derived Soil Water Index, Water Resour. Res., 56, e2019WR026365, https://doi.org/10.1029/2019WR026365, 2020.
Bouaziz, L. J. E., Fenicia, F., Thirel, G., de Boer-Euser, T., Buitink, J., Brauer, C. C., De Niel, J., Dewals, B. J., Drogue, G., Grelier, B., Melsen, L. A., Moustakas, S., Nossent, J., Pereira, F., Sprokkereef, E., Stam, J., Weerts, A. H., Willems, P., Savenije, H. H. G., and Hrachowitz, M.: Behind the scenes of streamflow model performance, Hydrol. Earth Syst. Sci., 25, 1069–1095, https://doi.org/10.5194/hess-25-1069-2021, 2021.
Bouaziz, L. J. E., Aalbers, E. E., Weerts, A. H., Hegnauer, M., Buiteveld, H., Lammersen, R., Stam, J., Sprokkereef, E., Savenije, H. H. G., and Hrachowitz, M.: Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters, Hydrol. Earth Syst. Sci., 26, 1295–1318, https://doi.org/10.5194/hess-26-1295-2022, 2022.
Brath, A., Montanari, A., and Moretti, G.: Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty), J. Hydrol., 324, 141–153, https://doi.org/10.1016/j.jhydrol.2005.10.001, 2006.
Brown, D. G., Johnson, K. M., Loveland, T. R., and Theobald, D. M.: Rural land-use trends in the conterminous United States, 1950–2000, Ecol. Appl., 15, 1851–1863, https://doi.org/10.1890/03-5220, 2005.
Budyko, M. I.: Climate and Life, Academic Press, New York, 508 pp., ISBN 9780080954530, 1974.
Coenders-Gerrits, A. M. J., Van der Ent, R. J., Bogaard, T. A., Wang-Erlandsson, L., Hrachowitz, M., and Savenije, H. H. G.: Uncertainties in transpiration estimates, Nature, 506, E1–E2, https://doi.org/10.1038/nature12925, 2014.
de Boer-Euser, T., McMillan, H. K., Hrachowitz, M., Winsemius, H. C., and Savenije, H. H.: Influence of soil and climate on root zone storage capacity, Water Resour. Res., 52, 2009–2024, https://doi.org/10.1002/2015WR018115, 2016.
Donohue, R. J., Roderick, M. L., and McVicar, T. R.: On the importance of including vegetation dynamics in Budyko's hydrological model, Hydrol. Earth Syst. Sci., 11, 983–995, https://doi.org/10.5194/hess-11-983-2007, 2007.
Donohue, R. J., Roderick, M. L., and McVicar, T. R.: Roots, storms and soil pores: Incorporating key ecohydrological processes into Budyko's hydrological model, J. Hydrol., 436, 35–50, https://doi.org/10.1016/j.jhydrol.2012.02.033, 2012.
Dralle, D. N., Hahm, W. J., Chadwick, K. D., McCormick, E., and Rempe, D. M.: Technical note: Accounting for snow in the estimation of root zone water storage capacity from precipitation and evapotranspiration fluxes, Hydrol. Earth Syst. Sci., 25, 2861–2867, https://doi.org/10.5194/hess-25-2861-2021, 2021.
Duethmann, D., Blöschl, G., and Parajka, J.: Why does a conceptual hydrological model fail to correctly predict discharge changes in response to climate change?, Hydrol. Earth Syst. Sci., 24, 3493–3511, https://doi.org/10.5194/hess-24-3493-2020, 2020.
DWD: Index of /climate_environment/CDC/observations_germany/ climate/daily/more_precip/historical/, DWD [data set], https://opendata.dwd.de/climate_environment/CDC/observations_germany/climate/daily/more_precip/historical/, last access: 27 August 2024.
Efstratiadis, A. and Koutsoyiannis, D.: One decade of multi-objective calibration approaches in hydrological modelling: a review, Hydrolog. Sci. J., 55, 58–78, https://doi.org/10.1080/02626660903526292, 2010.
Ellison, D., Pokorný, J., and Wild, M.: Even cooler insights: On the power of forests to (water the Earth and) cool the planet, Glob. Change Biol., 30, e17195, https://doi.org/10.1111/gcb.17195, 2024.
Euser, T., Hrachowitz, M., Winsemius, H. C., and Savenije, H. H.: The effect of forcing and landscape distribution on performance and consistency of model structures, Hydrol. Process., 29, 3727–3743, https://doi.org/10.1002/hyp.10445, 2015.
Fan, Y., Miguez-Macho, G., Jobbágy, E. G., Jackson, R. B., and Otero-Casal, C.: Hydrologic regulation of plant rooting depth, P. Natl. Acad. Sci. USA, 114, 10572–10577, https://doi.org/10.1073/pnas.1712381114, 2017.
Fenicia, F., Savenije, H. H., Matgen, P., and Pfister, L.: Understanding catchment behavior through stepwise model concept improvement, Water Resour. Res., 44, W01402, https://doi.org/10.1029/2006WR005563, 2008.
Fenicia, F., Savenije, H. H. G., and Avdeeva, Y.: Anomaly in the rainfall-runoff behaviour of the Meuse catchment, Climate, land-use, or land-use management?, Hydrol. Earth Syst. Sci., 13, 1727–1737, https://doi.org/10.5194/hess-13-1727-2009, 2009.
Fu, B.: On the calculation of the evaporation from land surface, Scientia Atmospherica Sinica, 5, 23–31, 1981 (in Chinese).
Gao, H., Hrachowitz, M., Fenicia, F., Gharari, S., and Savenije, H. H. G.: Testing the realism of a topography-driven model (FLEX-Topo) in the nested catchments of the Upper Heihe, China, Hydrol. Earth Syst. Sci., 18, 1895–1915, https://doi.org/10.5194/hess-18-1895-2014, 2014a.
Gao, H., Hrachowitz, M., Schymanski, S., Fenicia, F., Sriwongsitanon, N., and Savenije, H.: Climate controls how ecosystems size the root zone storage capacity at catchment scale, Geophys. Res. Lett., 41, 7916–7923, https://doi.org/10.1002/2014GL061668, 2014b.
Gao, H., Hrachowitz, M., Wang-Erlandsson, L., Fenicia, F., Xi, Q., Xia, J., Shao, W., Sun, G., and Savenije, H.: Root zone in the Earth system, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-332, 2024.
Gentine, P., D'Odorico, P., Lintner, B. R., Sivandran, G., and Salvucci, G.: Interdependence of climate, soil, and vegetation as constrained by the Budyko curve, Geophys. Res. Lett., 39, L19404, https://doi.org/10.1029/2012GL053492, 2012.
Gharari, S., Hrachowitz, M., Fenicia, F., and Savenije, H. H. G.: Hydrological landscape classification: investigating the performance of HAND based landscape classifications in a central European meso-scale catchment, Hydrol. Earth Syst. Sci., 15, 3275–3291, https://doi.org/10.5194/hess-15-3275-2011, 2011.
Gharari, S., Hrachowitz, M., Fenicia, F., and Savenije, H. H. G.: An approach to identify time consistent model parameters: sub-period calibration, Hydrol. Earth Syst. Sci., 17, 149–161, https://doi.org/10.5194/hess-17-149-2013, 2013.
Gharari, S., Hrachowitz, M., Fenicia, F., Gao, H., and Savenije, H. H. G.: Using expert knowledge to increase realism in environmental system models can dramatically reduce the need for calibration, Hydrol. Earth Syst. Sci., 18, 4839–4859, https://doi.org/10.5194/hess-18-4839-2014, 2014.
Goovaerts, P.: Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall, J. Hydrol., 228, 113–129, https://doi.org/10.1016/S0022-1694(00)00144-X, 2000.
Gumbel, E. J.: The return period of flood flows, Ann. Math. Stat., 12, 163–190, https://doi.org/10.1214/aoms/1177731747, 1941.
Guswa, A. J.: The influence of climate on root depth: A carbon cost-benefit analysis, Water Resour. Res., 44, W02427, https://doi.org/10.1029/2007WR006384, 2008.
Hadka, D. and Reed, P.: Borg: An auto-adaptive many-objective evolutionary computing framework, Evolutionary Computation, 21, 231–259, https://doi.org/10.1029/2007WR006384, 2013.
Hanus, S., Hrachowitz, M., Zekollari, H., Schoups, G., Vizcaino, M., and Kaitna, R.: Future changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in Austria, Hydrol. Earth Syst. Sci., 25, 3429–3453, https://doi.org/10.5194/hess-25-3429-2021, 2021.
Hoek van Dijke, A. J., Herold, M., Mallick, K., Benedict, I., Machwitz, M., Schlerf, M., Pranindita, A., Theeuwen, J. J., Bastin, J.-F., and Teuling, A. J.: Shifts in regional water availability due to global tree restoration, Nat. Geosci., 15, 363–368, https://doi.org/10.1038/s41561-022-00935-0, 2022.
Hrachowitz, M. and Weiler, M.: Uncertainty of precipitation estimates caused by sparse gauging networks in a small, mountainous watershed, J. Hydrol. Eng., 16, 460–471, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000331, 2011.
Hrachowitz, M., Fovet, O., Ruiz, L., Euser, T., Gharari, S., Nijzink, R., Freer, J., Savenije, H., and Gascuel-Odoux, C.: Process consistency in models: The importance of system signatures, expert knowledge, and process complexity, Water Resour. Res., 50, 7445–7469, https://doi.org/10.1002/2014WR015484, 2014.
Hrachowitz, M., Stockinger, M., Coenders-Gerrits, M., van der Ent, R., Bogena, H., Lücke, A., and Stumpp, C.: Reduction of vegetation-accessible water storage capacity after deforestation affects catchment travel time distributions and increases young water fractions in a headwater catchment, Hydrol. Earth Syst. Sci., 25, 4887–4915, https://doi.org/10.5194/hess-25-4887-2021, 2021.
Hulsman, P., Hrachowitz, M., and Savenije, H. H.: Improving the representation of long-term storage variations with conceptual hydrological models in data-scarce regions, Water Resour. Res., 57, e2020WR028837, https://doi.org/10.1029/2020WR028837, 2021a.
Hulsman, P., Savenije, H. H. G., and Hrachowitz, M.: Learning from satellite observations: increased understanding of catchment processes through stepwise model improvement, Hydrol. Earth Syst. Sci., 25, 957–982, https://doi.org/10.5194/hess-25-957-2021, 2021b.
Ibrahim, M., Coenders-Gerrits, M., van der Ent, R., and Hrachowitz, M.: Catchments do not strictly follow Budyko curves over multiple decades but deviations are minor and predictable, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2024-120, in review, 2024.
Jaramillo, F. and Destouni, G.: Developing water change spectra and distinguishing change drivers worldwide, Geophys. Res. Lett., 41, 8377–8386, https://doi.org/10.1002/2014GL061848, 2014.
Jaramillo, F., Cory, N., Arheimer, B., Laudon, H., van der Velde, Y., Hasper, T. B., Teutschbein, C., and Uddling, J.: Dominant effect of increasing forest biomass on evapotranspiration: interpretations of movement in Budyko space, Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, 2018.
Jasechko, S.: Plants turn on the tap, Nat. Clim. Change, 8, 562–563, https://doi.org/10.1038/s41558-018-0212-z, 2018.
Kleidon, A.: Beyond Gaia: Thermodynamics of Life and Earth System Functioning, Climatic Change, 66, 271–319, https://doi.org/10.1023/B:CLIM.0000044616.34867.ec, 2004.
Laio, F., Porporato, A., Ridolfi, L., and Rodriguez-Iturbe, I.: Plants in water-controlled ecosystems: active role in hydrologic processes and response to water stress: II. Probabilistic soil moisture dynamics, Adv. Water Resour., 24, 707–723, https://doi.org/10.1016/S0309-1708(01)00005-7, 2001.
Liancourt, P., Sharkhuu, A., Ariuntsetseg, L., Boldgiv, B., Helliker, B. R., Plante, A. F., Petraitis, P. S., and Casper, B. B.: Temporal and spatial variation in how vegetation alters the soil moisture response to climate manipulation, Plant Soil, 351, 249–261, https://doi.org/10.1007/s11104-011-0956-y, 2012.
Lloyd, C.: Assessing the effect of integrating elevation data into the estimation of monthly precipitation in Great Britain, J. Hydrol., 308, 128–150, https://doi.org/10.1016/j.jhydrol.2004.10.026, 2005.
McCormick, E. L., Dralle, D. N., Hahm, W. J., Tune, A. K., Schmidt, L. M., Chadwick, K. D., and Rempe, D. M.: Widespread woody plant use of water stored in bedrock, Nature, 597, 225–229, https://doi.org/10.1038/s41586-021-03761-3, 2021.
McMurtrie, R. E., Iversen, C. M., Dewar, R. C., Medlyn, B. E., Näsholm, T., Pepper, D. A., and Norby, R. J.: Plant root distributions and nitrogen uptake predicted by a hypothesis of optimal root foraging, Ecol. Evol., 2, 1235–1250, https://doi.org/10.1002/ece3.266, 2012.
Merz, R., Parajka, J., and Blöschl, G.: Time stability of catchment model parameters: Implications for climate impact analyses, Water Resour. Res., 47, W02531, https://doi.org/10.1029/2010WR009505, 2011.
Mianabadi, A., Coenders-Gerrits, M., Shirazi, P., Ghahraman, B., and Alizadeh, A.: A global Budyko model to partition evaporation into interception and transpiration, Hydrol. Earth Syst. Sci., 23, 4983–5000, https://doi.org/10.5194/hess-23-4983-2019, 2019.
Miralles, D. G., Brutsaert, W., Dolman, A. J., and Gash, J. H.: On the use of the term “evapotranspiration”, Water Resour. Res., 56, e2020WR028055, https://doi.org/10.1029/2020WR028055, 2020.
Nijzink, R., Hutton, C., Pechlivanidis, I., Capell, R., Arheimer, B., Freer, J., Han, D., Wagener, T., McGuire, K., Savenije, H., and Hrachowitz, M.: The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change?, Hydrol. Earth Syst. Sci., 20, 4775–4799, https://doi.org/10.5194/hess-20-4775-2016, 2016a.
Nijzink, R. C., Samaniego, L., Mai, J., Kumar, R., Thober, S., Zink, M., Schäfer, D., Savenije, H. H. G., and Hrachowitz, M.: The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models, Hydrol. Earth Syst. Sci., 20, 1151–1176, https://doi.org/10.5194/hess-20-1151-2016, 2016b.
Nijzink, R., Almeida, S., Pechlivanidis, I., Capell, R., Gustafssons, D., Arheimer, B., Parajka, J., Freer, J., Han, D., and Wagener, T.: Constraining conceptual hydrological models with multiple information sources, Water Resour. Res., 54, 8332–8362, https://doi.org/10.1029/2017WR021895, 2018.
Ol'Dekop, E.: On evaporation from the surface of river basins, Transactions on Meteorological Observations, 4, 200, https://scholar.google.com/scholar_lookup?hl=en&volume=4&publication_year=1911&pages=200&journal=Trans.+Meteorol.+Obs.+Univ.+Tartu&author=E.+M.+Ol%27dekop&title=On+evaporation+from+the+surface+of+river+basins (last access: 27 August 2024), 1911.
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil, F., and Loumagne, C.: Which potential evapotranspiration input for a lumped rainfall–runoff model?: Part 2—Towards a simple and efficient potential evapotranspiration model for rainfall–runoff modelling, J. Hydrol., 303, 290–306, https://doi.org/10.1016/j.jhydrol.2004.08.026, 2005.
Oudin, L., Andréassian, V., Lerat, J., and Michel, C.: Has land cover a significant impact on mean annual streamflow? An international assessment using 1508 catchments, J. Hydrol., 357, 303–316, https://doi.org/10.1016/j.jhydrol.2008.05.021, 2008.
Prenner, D., Kaitna, R., Mostbauer, K., and Hrachowitz, M.: The value of using multiple hydrometeorological variables to predict temporal debris flow susceptibility in an alpine environment, Water Resour. Res., 54, 6822–6843, https://doi.org/10.1029/2018WR022985, 2018.
Reaver, N. G. F., Kaplan, D. A., Klammler, H., and Jawitz, J. W.: Theoretical and empirical evidence against the Budyko catchment trajectory conjecture, Hydrol. Earth Syst. Sci., 26, 1507–1525, https://doi.org/10.5194/hess-26-1507-2022, 2022.
Roberts, K. J., Dietrich, J. C., Wirasaet, D., Pringle, W. J., and Westerink, J. J.: Dynamic load balancing for predictions of storm surge and coastal flooding, Environ. Modell. Softw., 140, 105045, https://doi.org/10.1016/j.envsoft.2021.105045, 2021.
Roderick, M. L. and Farquhar, G. D.: A simple framework for relating variations in runoff to variations in climatic conditions and catchment properties, Water Resour. Res., 47, W00G07, https://doi.org/10.1029/2010WR009826, 2011.
Rodríguez-Iturbe, I. and Porporato, A.: Ecohydrology of water-controlled ecosystems: soil moisture and plant dynamics, Cambridge University Press, ISBN 9780521036740, https://www.cambridge.org/us/universitypress/subjects/earth-and-environmental-science/hydrology-hydrogeology-and-water-resources/ecohydrology-water-controlled-ecosystems-soil-moisture-and-plant-dynamics?format=PB&isbn=9780521036740 (last access: 27 August 2024), 2007.
Roodari, A., Hrachowitz, M., Hassanpour, F., and Yaghoobzadeh, M.: Signatures of human intervention – or not? Downstream intensification of hydrological drought along a large Central Asian river: the individual roles of climate variability and land use change, Hydrol. Earth Syst. Sci., 25, 1943–1967, https://doi.org/10.5194/hess-25-1943-2021, 2021.
Sadayappan, K., Keen, R., Jarecke, K. M., Moreno, V., Nippert, J. B., Kirk, M. F., Sullivan, P. L., and Li, L.: Drier streams despite a wetter climate in woody-encroached grasslands, J. Hydrol., 627, 130388, https://doi.org/10.1016/j.jhydrol.2023.130388, 2023.
Savenije, H. H.: The importance of interception and why we should delete the term evapotranspiration from our vocabulary, Hydrol. Process., 18, 1507–1511, https://doi.org/10.1002/hyp.5563, 2004.
Savenije, H. H. G. and Hrachowitz, M.: HESS Opinions “Catchments as meta-organisms – a new blueprint for hydrological modelling”, Hydrol. Earth Syst. Sci., 21, 1107–1116, https://doi.org/10.5194/hess-21-1107-2017, 2017.
Schenk, H. J. and Jackson, R. B.: Rooting depths, lateral root spreads and below-ground/above-ground allometries of plants in water-limited ecosystems, J. Ecol., 90, 480–494, https://www.jstor.org/stable/3072232 (last access: 24 August 2024), 2002.
Schreiber, P.: Über die Beziehungen zwischen dem Niederschlag und der Wasserführung der Flüsse in Mitteleuropa, Z. Meteorol., 21, 441–452, 1904.
Scrivner, C. and Ruppert, D.: Thickness of soil solum as a parameter of plant-available water storage capacity in soils underlain by carbonate rocks, University of Missouri-Columbia, https://hdl.handle.net/10355/91873 (last access: 24 August 2024), 1970.
Singh, C., Wang-Erlandsson, L., Fetzer, I., Rockström, J., and Van Der Ent, R.: Rootzone storage capacity reveals drought coping strategies along rainforest-savanna transitions, Environ. Res. Lett., 15, 124021, https://doi.org/10.1088/1748-9326/abc377, 2020.
Sivandran, G. and Bras, R. L.: Identifying the optimal spatially and temporally invariant root distribution for a semiarid environment, Water Resour. Res., 48, W12525, https://doi.org/10.1029/2012WR012055, 2012.
Sivandran, G. and Bras, R. L.: Dynamic root distributions in ecohydrological modeling: A case study at Walnut Gulch Experimental Watershed, Water Resour. Res., 49, 3292–3305, https://doi.org/10.1002/wrcr.20245, 2013.
Speich, M. J. R., Lischke, H., and Zappa, M.: Testing an optimality-based model of rooting zone water storage capacity in temperate forests, Hydrol. Earth Syst. Sci., 22, 4097–4124, https://doi.org/10.5194/hess-22-4097-2018, 2018.
Sriwongsitanon, N., Jandang, W., Williams, J., Suwawong, T., Maekan, E., and Savenije, H. H. G.: Using normalised difference infrared index patterns to constrain semi-distributed rainfall–runoff models in tropical nested catchments, Hydrol. Earth Syst. Sci., 27, 2149–2171, https://doi.org/10.5194/hess-27-2149-2023, 2023.
Stephens, C. M., Lall, U., Johnson, F., and Marshall, L. A.: Landscape changes and their hydrologic effects: Interactions and feedbacks across scales, Earth-Sci. Rev., 212, 103466, https://doi.org/10.1016/j.earscirev.2020.103466, 2021.
Stevens, J. T., Boisramé, G. F., Rakhmatulina, E., Thompson, S. E., Collins, B. M., and Stephens, S. L.: Forest vegetation change and its impacts on soil water following 47 years of managed wildfire, Ecosystems, 23, 1547–1565, https://doi.org/10.1007/s10021-020-00489-5, 2020.
Stocker, B. D., Tumber-Dávila, S. J., Konings, A. G., Anderson, M. C., Hain, C., and Jackson, R. B.: Global patterns of water storage in the rooting zones of vegetation, Nat. Geosci., 16, 250–256, https://doi.org/10.1038/s41561-023-01125-2, 2023.
Tempel, N. T., Bouaziz, L., Taormina, R., van Noppen, E., Stam, J., Sprokkereef, E., and Hrachowitz, M.: Vegetation Response to Climatic Variability: Implications for Root Zone Storage and Streamflow Predictions, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-115, 2024.
Teuling, A. J. and Hoek van Dijke, A. J.: Forest age and water yield, Nature, 578, E16-E18, https://doi.org/10.1038/s41586-020-1941-5, 2020.
Teuling, A. J., de Badts, E. A. G., Jansen, F. A., Fuchs, R., Buitink, J., Hoek van Dijke, A. J., and Sterling, S. M.: Climate change, reforestation/afforestation, and urbanization impacts on evapotranspiration and streamflow in Europe, Hydrol. Earth Syst. Sci., 23, 3631–3652, https://doi.org/10.5194/hess-23-3631-2019, 2019.
Tixeront, J.: Prévision des apports des cours d'eau, Publication de l'Association internationale d'hydrologie scientifique, 63, 118–126, http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=19271864 (last access: 24 August 2024), 1964.
Tong, R., Parajka, J., Széles, B., Greimeister-Pfeil, I., Vreugdenhil, M., Komma, J., Valent, P., and Blöschl, G.: The value of satellite soil moisture and snow cover data for the transfer of hydrological model parameters to ungauged sites, Hydrol. Earth Syst. Sci., 26, 1779–1799, https://doi.org/10.5194/hess-26-1779-2022, 2022.
Van der Velde, Y., Vercauteren, N., Jaramillo, F., Dekker, S. C., Destouni, G., and Lyon, S. W.: Exploring hydroclimatic change disparity via the Budyko framework, Hydrol. Process., 28, 4110–4118, https://doi.org/10.1002/hyp.9949, 2014.
Van Loon, A. F., Stahl, K., Di Baldassarre, G., Clark, J., Rangecroft, S., Wanders, N., Gleeson, T., Van Dijk, A. I. J. M., Tallaksen, L. M., Hannaford, J., Uijlenhoet, R., Teuling, A. J., Hannah, D. M., Sheffield, J., Svoboda, M., Verbeiren, B., Wagener, T., and Van Lanen, H. A. J.: Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches, Hydrol. Earth Syst. Sci., 20, 3631–3650, https://doi.org/10.5194/hess-20-3631-2016, 2016.
van Oorschot, F., van der Ent, R. J., Hrachowitz, M., and Alessandri, A.: Climate-controlled root zone parameters show potential to improve water flux simulations by land surface models, Earth Syst. Dynam., 12, 725–743, https://doi.org/10.5194/esd-12-725-2021, 2021.
van Oorschot, F., van der Ent, R. J., Alessandri, A., and Hrachowitz, M.: Influence of irrigation on root zone storage capacity estimation, Hydrol. Earth Syst. Sci., 28, 2313–2328, https://doi.org/10.5194/hess-28-2313-2024, 2024.
Verdin, K. L.: Hydrologic Derivatives for Modeling and Applications (HDMA) database: U. S. Geological Survey data release, U.S. Geological Survey data release, https://doi.org/10.5066/F7S180ZP, 2017.
Wagener, T., McIntyre, N., Lees, M., Wheater, H., and Gupta, H.: Towards reduced uncertainty in conceptual rainfall-runoff modelling: Dynamic identifiability analysis, Hydrol. Process., 17, 455–476, https://doi.org/10.1002/hyp.1135, 2003.
Wang, S. and Hrachowitz, M.: Data and code underlying the publication: Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability has minor effects on the hydrological response in the Neckar basin, Germany, 4TU.ResearchData [code and data set], https://doi.org/10.4121/922d30de-a26b-4c81-8644-ad036182239c, last access: 27 August 2024.
Wang, S., Hrachowitz, M., Schoups, G., and Stumpp, C.: Stable water isotopes and tritium tracers tell the same tale: no evidence for underestimation of catchment transit times inferred by stable isotopes in StorAge Selection (SAS)-function models, Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, 2023.
Wang-Erlandsson, L., Bastiaanssen, W. G. M., Gao, H., Jägermeyr, J., Senay, G. B., van Dijk, A. I. J. M., Guerschman, J. P., Keys, P. W., Gordon, L. J., and Savenije, H. H. G.: Global root zone storage capacity from satellite-based evaporation, Hydrol. Earth Syst. Sci., 20, 1459–1481, https://doi.org/10.5194/hess-20-1459-2016, 2016.
Yang, Y., Zhu, Q., Peng, C., Wang, H., Xue, W., Lin, G., Wen, Z., Chang, J., Wang, M., and Liu, G.: A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China, Sci. Rep.-UK, 6, 24110, https://doi.org/10.1038/srep24110, 2016.
Zhang, L., Dawes, W., and Walker, G.: Response of mean annual evapotranspiration to vegetation changes at catchment scale, Water Resour. Res., 37, 701–708, https://doi.org/10.1029/2000WR900325, 2001.
Zhang, L., Hickel, K., Dawes, W. R., Chiew, F. H., Western, A. W., and Briggs, P. R.: A rational function approach for estimating mean annual evapotranspiration, Water Resour. Res., 40, W02502, https://doi.org/10.1029/2003WR002710, 2004.
Zhou, S., Yu, B., Huang, Y., and Wang, G.: The complementary relationship and generation of the Budyko functions, Geophys. Res. Lett., 42, 1781–1790, https://doi.org/10.1002/2015GL063511, 2015.
Short summary
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting...
