Articles | Volume 26, issue 5
https://doi.org/10.5194/hess-26-1295-2022
© 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-26-1295-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Mar 2022
Research article |
| 09 Mar 2022
| 09 Mar 2022
Ecosystem adaptation to climate change: the sensitivity of hydrological predictions to time-dynamic model parameters
Laurène J. E. Bouaziz
CORRESPONDING AUTHOR
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Department Catchment and Urban Hydrology, Deltares, Boussinesqweg 1, 2629 HV Delft, the Netherlands
Emma E. Aalbers
Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE De Bilt, the Netherlands
Institute for Environmental Studies (IVM), Vrije Universiteit, Amsterdam, 1081 HV, the Netherlands
Albrecht H. Weerts
Department Catchment and Urban Hydrology, Deltares, Boussinesqweg 1, 2629 HV Delft, the Netherlands
Hydrology and Quantitative Water Management Group, Wageningen University and Research, P.O. Box 47, 6700 AA Wageningen, the Netherlands
Mark Hegnauer
Department Catchment and Urban Hydrology, Deltares, Boussinesqweg 1, 2629 HV Delft, the Netherlands
Hendrik Buiteveld
Rijkswaterstaat, P.O. Box 2232, 3500 GE Utrecht, the Netherlands
Rita Lammersen
Rijkswaterstaat, P.O. Box 2232, 3500 GE Utrecht, the Netherlands
Jasper Stam
Rijkswaterstaat, P.O. Box 2232, 3500 GE Utrecht, the Netherlands
Eric Sprokkereef
Rijkswaterstaat, P.O. Box 2232, 3500 GE Utrecht, the Netherlands
Hubert H. G. Savenije
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Markus Hrachowitz
Department of Water Management, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, the Netherlands
Related authors
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
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
Short summary
Short summary
We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
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
Short summary
Short summary
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.
Hatice Türk, Christine Stumpp, Markus Hrachowitz, Karsten Schulz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci., 29, 3935–3956, https://doi.org/10.5194/hess-29-3935-2025, https://doi.org/10.5194/hess-29-3935-2025, 2025
Short summary
Short summary
Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or if they are also controlled by precipitation intensity. We used soil-moisture-dependent and precipitation-intensity-conditional transfer functions. We showed that a significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential-flow paths) in dry soil conditions for both low- and high-intensity precipitation.
Magali Ponds, Sarah Hanus, Harry Zekollari, Marie-Claire ten Veldhuis, Gerrit Schoups, Roland Kaitna, and Markus Hrachowitz
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
Short summary
Short summary
This research examines how future climate changes impact root zone storage, a key hydrological model parameter. Root zone storage – the soil water accessible to plants – adapts to climate but is often kept constant in models. We estimated climate-adapted storage in six Austrian Alps catchments. While storage increased, streamflow projections showed minimal change, which suggests that dynamic root zone representation is less critical in humid regions but warrants further study in arid areas.
Hatice Türk, Christine Stumpp, Markus Hrachowitz, Peter Strauss, Günter Blöschl, and Michael Stockinger
EGUsphere, https://doi.org/10.5194/egusphere-2025-2597, https://doi.org/10.5194/egusphere-2025-2597, 2025
Short summary
Short summary
This study shows that stream flow isotope data (δ2H) were inadequate for distinguishing preferential groundwater flow. Large passive groundwater storage dampened δ2H variations, obscuring signals of fast groundwater flow and complicating the estimation of older water fractions in the streams. Further, weekly-resolution δ2H sampling yielded deceptively high model performance, highlighting the need for complementary and groundwater-level data to improve catchment-scale transit-time estimates.
Nathalie Rombeek, Markus Hrachowitz, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2025-1502, https://doi.org/10.5194/egusphere-2025-1502, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
On 29 October 2024 Valencia (Spain) was struck by torrential rainfall, triggering devastating floods in this area. In this study, we quantify and describe the spatial and temporal structure of this rainfall event using personal weather stations (PWSs). These PWSs provide near real-time observations at a temporal resolution of ~5 min. This study shows the potential of PWSs for real-time rainfall monitoring and potentially flood early warning systems by complementing dedicated rain gauge networks.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
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
Short summary
Short summary
The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Devi Purnamasari, Adriaan J. Teuling, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci., 29, 1483–1503, https://doi.org/10.5194/hess-29-1483-2025, https://doi.org/10.5194/hess-29-1483-2025, 2025
Short summary
Short summary
This paper introduces a method to identify irrigated areas by combining hydrology models with satellite temperature data. Our method was tested in the Rhine basin and aligns well with official statistics. It performs best in regions with large farms and less well in areas with small farms. Observed differences to existing data are influenced by data resolution and methods.
Wouter R. Berghuijs, Ross A. Woods, Bailey J. Anderson, Anna Luisa Hemshorn de Sánchez, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1319–1333, https://doi.org/10.5194/hess-29-1319-2025, https://doi.org/10.5194/hess-29-1319-2025, 2025
Short summary
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.
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
Short summary
Short summary
Large-sample hydrological studies often overlook the importance of detailed landscape data in explaining river flow variability. Analyzing over 4,000 European catchments, we found that geology becomes a dominant factor—especially for baseflow—when using detailed regional maps. This highlights the need for high-resolution geological data to improve river flow regionalization, particularly in non-monitored areas.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
Short summary
Short summary
Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping to better prepare for and respond to floods.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
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
Short summary
Short summary
To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
Steven Reinaldo Rusli, Victor F. Bense, Syed M. T. Mustafa, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci., 28, 5107–5131, https://doi.org/10.5194/hess-28-5107-2024, https://doi.org/10.5194/hess-28-5107-2024, 2024
Short summary
Short summary
In this paper, we investigate the impact of climatic and anthropogenic factors on future groundwater availability. The changes are simulated using hydrological and groundwater flow models. We find that future groundwater status is influenced more by anthropogenic factors than climatic factors. The results are beneficial for informing responsible parties in operational water management about achieving future (ground)water governance.
Nathalie Rombeek, Markus Hrachowitz, Arjan Droste, and Remko Uijlenhoet
EGUsphere, https://doi.org/10.5194/egusphere-2024-3207, https://doi.org/10.5194/egusphere-2024-3207, 2024
Short summary
Short summary
Rain gauge networks from personal weather stations (PWSs) have a network density 100 times higher than dedicated rain gauge networks in the Netherlands. However, PWSs are prone to several sources of error, as they are generally not installed and maintained according to international guidelines. This study systematically quantifies and describes the uncertainties arising from PWS rainfall estimates. In particular, the focus is on the highest rainfall accumulations.
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
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Hongkai Gao, Markus Hrachowitz, Lan Wang-Erlandsson, Fabrizio Fenicia, Qiaojuan Xi, Jianyang Xia, Wei Shao, Ge Sun, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 4477–4499, https://doi.org/10.5194/hess-28-4477-2024, https://doi.org/10.5194/hess-28-4477-2024, 2024
Short summary
Short summary
The concept of the root zone is widely used but lacks a precise definition. Its importance in Earth system science is not well elaborated upon. Here, we clarified its definition with several similar terms to bridge the multi-disciplinary gap. We underscore the key role of the root zone in the Earth system, which links the biosphere, hydrosphere, lithosphere, atmosphere, and anthroposphere. To better represent the root zone, we advocate for a paradigm shift towards ecosystem-centred modelling.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
Short summary
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.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Fransje van Oorschot, Ruud J. van der Ent, Andrea Alessandri, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 2313–2328, https://doi.org/10.5194/hess-28-2313-2024, https://doi.org/10.5194/hess-28-2313-2024, 2024
Short summary
Short summary
Vegetation plays a crucial role in regulating the water cycle by transporting water from the subsurface to the atmosphere via roots; this transport depends on the extent of the root system. In this study, we quantified the effect of irrigation on roots at a global scale. Our results emphasize the importance of accounting for irrigation in estimating the vegetation root extent, which is essential to adequately represent the water cycle in hydrological and climate models.
Willem J. van Verseveld, Albrecht H. Weerts, Martijn Visser, Joost Buitink, Ruben O. Imhoff, Hélène Boisgontier, Laurène Bouaziz, Dirk Eilander, Mark Hegnauer, Corine ten Velden, and Bobby Russell
Geosci. Model Dev., 17, 3199–3234, https://doi.org/10.5194/gmd-17-3199-2024, https://doi.org/10.5194/gmd-17-3199-2024, 2024
Short summary
Short summary
We present the wflow_sbm distributed hydrological model, recently released by Deltares, as part of the Wflow.jl open-source modelling framework in the programming language Julia. Wflow_sbm has a fast runtime, making it suitable for large-scale modelling. Wflow_sbm models can be set a priori for any catchment with the Python tool HydroMT-Wflow based on globally available datasets, which results in satisfactory to good performance (without much tuning). We show this for a number of specific cases.
Hubert H. G. Savenije
Proc. IAHS, 385, 1–4, https://doi.org/10.5194/piahs-385-1-2024, https://doi.org/10.5194/piahs-385-1-2024, 2024
Short summary
Short summary
Hydrology is the bloodstream of the Earth, acting as a living organism, with the ecosystem as its active agent. The ecosystem optimises its survival within the constraints of energy, water, climate and nutrients. It is capable of adjusting the hydrological system and, through evolution, adjust its efficiency of carbon sequestration and moisture uptake. In trying to understand future functioning of hydrology, we have to take into account the adaptability of the ecosystem.
Jiaxing Liang, Hongkai Gao, Fabrizio Fenicia, Qiaojuan Xi, Yahui Wang, and Hubert H. G. Savenije
EGUsphere, https://doi.org/10.5194/egusphere-2024-550, https://doi.org/10.5194/egusphere-2024-550, 2024
Preprint archived
Short summary
Short summary
The root zone storage capacity (Sumax) is a key element in hydrology and land-atmospheric interaction. In this study, we utilized a hydrological model and a dynamic parameter identification method, to quantify the temporal trends of Sumax for 497 catchments in the USA. We found that 423 catchments (85 %) showed increasing Sumax, which averagely increased from 178 to 235 mm between 1980 and 2014. The increasing trend was also validated by multi-sources data and independent methods.
Marjanne J. Zander, Pety J. Viguurs, Frederiek C. Sperna Weiland, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-274, https://doi.org/10.5194/hess-2023-274, 2023
Manuscript not accepted for further review
Short summary
Short summary
Flash floods are damaging natural hazard which often occur in the European Alps. High resolution climate model output is combined with high resolution distributed hydrological models to model changes in flash flood frequency and intensity. Results show a similar flash flood frequency for autumn in the future, but a decrease in summer. However, the future discharge simulations indicate an increase in the flash flood severity in both summer and autumn leading to more severe flash flood impacts.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, Emanuele Di Carlo, Franco Catalano, Souhail Boussetta, Gianpaolo Balsamo, and Andrea Alessandri
Earth Syst. Dynam., 14, 1239–1259, https://doi.org/10.5194/esd-14-1239-2023, https://doi.org/10.5194/esd-14-1239-2023, 2023
Short summary
Short summary
Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modeling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology and therefore has potential to improve climate predictions of, for example, droughts.
Bas J. M. Wullems, Claudia C. Brauer, Fedor Baart, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci., 27, 3823–3850, https://doi.org/10.5194/hess-27-3823-2023, https://doi.org/10.5194/hess-27-3823-2023, 2023
Short summary
Short summary
In deltas, saltwater sometimes intrudes far inland and causes problems with freshwater availability. We created a model to forecast salt concentrations at a critical location in the Rhine–Meuse delta in the Netherlands. It requires a rather small number of data to make a prediction and runs fast. It predicts the occurrence of salt concentration peaks well but underestimates the highest peaks. Its speed gives water managers more time to reduce the problems caused by salt intrusion.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
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
Short summary
Short summary
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.
Hubert T. Samboko, Sten Schurer, Hubert H. G. Savenije, Hodson Makurira, Kawawa Banda, and Hessel Winsemius
Geosci. Instrum. Method. Data Syst., 12, 155–169, https://doi.org/10.5194/gi-12-155-2023, https://doi.org/10.5194/gi-12-155-2023, 2023
Short summary
Short summary
The study investigates how low-cost technology can be applied in data-scarce catchments to improve water resource management. More specifically, we investigate how drone technology can be combined with low-cost real-time kinematic positioning (RTK) global navigation satellite system (GNSS) equipment and subsequently applied to a 3D hydraulic model so as to generate more physically based rating curves.
Hongkai Gao, Fabrizio Fenicia, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2607–2620, https://doi.org/10.5194/hess-27-2607-2023, https://doi.org/10.5194/hess-27-2607-2023, 2023
Short summary
Short summary
It is a deeply rooted perception that soil is key in hydrology. In this paper, we argue that it is the ecosystem, not the soil, that is in control of hydrology. Firstly, in nature, the dominant flow mechanism is preferential, which is not particularly related to soil properties. Secondly, the ecosystem, not the soil, determines the land–surface water balance and hydrological processes. Moving from a soil- to ecosystem-centred perspective allows more realistic and simpler hydrological models.
Nutchanart Sriwongsitanon, Wasana Jandang, James Williams, Thienchart Suwawong, Ekkarin Maekan, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2149–2171, https://doi.org/10.5194/hess-27-2149-2023, https://doi.org/10.5194/hess-27-2149-2023, 2023
Short summary
Short summary
We developed predictive semi-distributed rainfall–runoff models for nested sub-catchments in the upper Ping basin, which yielded better or similar performance compared to calibrated lumped models. The normalised difference infrared index proves to be an effective proxy for distributed root zone moisture capacity over sub-catchments and is well correlated with the percentage of evergreen forest. In validation, soil moisture simulations appeared to be highly correlated with the soil wetness index.
Emma E. Aalbers, Erik van Meijgaard, Geert Lenderink, Hylke de Vries, and Bart J. J. M. van den Hurk
Nat. Hazards Earth Syst. Sci., 23, 1921–1946, https://doi.org/10.5194/nhess-23-1921-2023, https://doi.org/10.5194/nhess-23-1921-2023, 2023
Short summary
Short summary
To examine the impact of global warming on west-central European droughts, we have constructed future analogues of recent summers. Extreme droughts like 2018 further intensify, and the local temperature rise is much larger than in most summers. Years that went hardly noticed in the present-day climate may emerge as very dry and hot in a warmer world. The changes can be directly linked to real-world events, which makes the results very tangible and hence useful for climate change communication.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Bart Schilperoort, Nick van de Giesen, Imasiku Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 1695–1722, https://doi.org/10.5194/hess-27-1695-2023, https://doi.org/10.5194/hess-27-1695-2023, 2023
Short summary
Short summary
Miombo woodland plants continue to lose water even during the driest part of the year. This appears to be facilitated by the adapted features such as deep rooting (beyond 5 m) with access to deep soil moisture, potentially even ground water. It appears the trend and amount of water that the plants lose is correlated more to the available energy. This loss of water in the dry season by miombo woodland plants appears to be incorrectly captured by satellite-based evaporation estimates.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, https://doi.org/10.5194/hess-26-5971-2022, 2022
Short summary
Short summary
We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
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
Short summary
Short summary
This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Jerom P. M. Aerts, Rolf W. Hut, Nick C. van de Giesen, Niels Drost, Willem J. van Verseveld, Albrecht H. Weerts, and Pieter Hazenberg
Hydrol. Earth Syst. Sci., 26, 4407–4430, https://doi.org/10.5194/hess-26-4407-2022, https://doi.org/10.5194/hess-26-4407-2022, 2022
Short summary
Short summary
In recent years gridded hydrological modelling moved into the realm of hyper-resolution modelling (<10 km). In this study, we investigate the effect of varying grid-cell sizes for the wflow_sbm hydrological model. We used a large sample of basins from the CAMELS data set to test the effect that varying grid-cell sizes has on the simulation of streamflow at the basin outlet. Results show that there is no single best grid-cell size for modelling streamflow throughout the domain.
Hongkai Gao, Chuntan Han, Rensheng Chen, Zijing Feng, Kang Wang, Fabrizio Fenicia, and Hubert Savenije
Hydrol. Earth Syst. Sci., 26, 4187–4208, https://doi.org/10.5194/hess-26-4187-2022, https://doi.org/10.5194/hess-26-4187-2022, 2022
Short summary
Short summary
Frozen soil hydrology is one of the 23 unsolved problems in hydrology (UPH). In this study, we developed a novel conceptual frozen soil hydrological model, FLEX-Topo-FS. The model successfully reproduced the soil freeze–thaw process, and its impacts on hydrologic connectivity, runoff generation, and groundwater. We believe this study is a breakthrough for the 23 UPH, giving us new insights on frozen soil hydrology, with broad implications for predicting cold region hydrology in future.
Mar J. Zander, Pety J. Viguurs, Frederiek C. Sperna Weiland, and Albrecht H. Weerts
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-207, https://doi.org/10.5194/hess-2022-207, 2022
Manuscript not accepted for further review
Short summary
Short summary
We perform a modelling study to research potential future changes in flash flood occurrence in the European Alps. We use new high-resolution numerical climate simulations, which can simulate the type of local, intense rainstorms which trigger flash floods, combined with high-resolution hydrological modelling. We find that flash floods would become less frequent in summers in our future climate scenario, with little change in autumns. However, the maximal severity would increase in both seasons.
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
Short summary
Short summary
This research tested the value of regional groundwater level information to improve landslide predictions with empirical models based on the concept of threshold levels. In contrast to precipitation-based thresholds, the results indicated that relying on threshold models exclusively defined using hydrological variables such as groundwater levels can lead to improved landslide predictions due to their implicit consideration of long-term antecedent conditions until the day of landslide occurrence.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Petra Hulsman, Nick van de Giesen, Imasiku Nyambe, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-114, https://doi.org/10.5194/hess-2022-114, 2022
Manuscript not accepted for further review
Short summary
Short summary
We compare performance of evaporation models in the Luangwa Basin located in a semi-arid and complex Miombo ecosystem in Africa. Miombo plants changes colour, drop off leaves and acquire new leaves during the dry season. In addition, the plant roots go deep in the soil and appear to access groundwater. Results show that evaporation models with structure and process that do not capture this unique plant structure and behaviour appears to have difficulties to correctly estimating evaporation.
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
Short summary
Short summary
We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Hubert T. Samboko, Sten Schurer, Hubert H. G. Savenije, Hodson Makurira, Kawawa Banda, and Hessel Winsemius
Geosci. Instrum. Method. Data Syst., 11, 1–23, https://doi.org/10.5194/gi-11-1-2022, https://doi.org/10.5194/gi-11-1-2022, 2022
Short summary
Short summary
The study was conducted along the Luangwa River in Zambia. It combines low-cost instruments such as UAVs and GPS kits to collect data for the purposes of water management. A novel technique which seamlessly merges the dry and wet bathymetry before application in a hydraulic model was applied. Successful implementation resulted in water authorities with small budgets being able to monitor flows safely and efficiently without significant compromise on accuracy.
Dirk Eilander, Willem van Verseveld, Dai Yamazaki, Albrecht Weerts, Hessel C. Winsemius, and Philip J. Ward
Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, https://doi.org/10.5194/hess-25-5287-2021, 2021
Short summary
Short summary
Digital elevation models and derived flow directions are crucial to distributed hydrological modeling. As the spatial resolution of models is typically coarser than these data, we need methods to upscale flow direction data while preserving the river structure. We propose the Iterative Hydrography Upscaling (IHU) method and show it outperforms other often-applied methods. We publish the multi-resolution MERIT Hydro IHU hydrography dataset and the algorithm as part of the pyflwdir Python package.
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
Short summary
Short summary
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.
Ruben Imhoff, Claudia Brauer, Klaas-Jan van Heeringen, Hidde Leijnse, Aart Overeem, Albrecht Weerts, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 25, 4061–4080, https://doi.org/10.5194/hess-25-4061-2021, https://doi.org/10.5194/hess-25-4061-2021, 2021
Short summary
Short summary
Significant biases in real-time radar rainfall products limit the use for hydrometeorological forecasting. We introduce CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting), a set of fixed bias reduction factors to correct radar rainfall products and to benchmark other correction algorithms. When tested for 12 Dutch basins, estimated rainfall and simulated discharges with CARROTS generally outperform those using the operational mean field bias adjustments.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Hongkai Gao, Chuntan Han, Rensheng Chen, Zijing Feng, Kang Wang, Fabrizio Fenicia, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-264, https://doi.org/10.5194/hess-2021-264, 2021
Manuscript not accepted for further review
Short summary
Short summary
Permafrost hydrology is one of the 23 major unsolved problems in hydrology. In this study, we used a stepwise modeling and dynamic parameter method to examine the impact of permafrost on streamflow in the Hulu catchment in western China. We found that: topography and landscape are dominant controls on catchment response; baseflow recession is slower than other regions; precipitation-runoff relationship is non-stationary; permafrost impacts on streamflow mostly at the beginning of melting season.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
César Dionisio Jiménez-Rodríguez, Miriam Coenders-Gerrits, Bart Schilperoort, Adriana del Pilar González-Angarita, and Hubert Savenije
Hydrol. Earth Syst. Sci., 25, 619–635, https://doi.org/10.5194/hess-25-619-2021, https://doi.org/10.5194/hess-25-619-2021, 2021
Short summary
Short summary
During rainfall events, evaporation from tropical forests is usually ignored. However, the water retained in the canopy during rainfall increases the evaporation despite the high-humidity conditions. In a tropical wet forest in Costa Rica, it was possible to depict vapor plumes rising from the forest canopy during rainfall. These plumes are evidence of forest evaporation. Also, we identified the conditions that allowed this phenomenon to happen using time-lapse videos and meteorological data.
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
Short summary
Short summary
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.
Bart Schilperoort, Miriam Coenders-Gerrits, César Jiménez Rodríguez, Christiaan van der Tol, Bas van de Wiel, and Hubert Savenije
Biogeosciences, 17, 6423–6439, https://doi.org/10.5194/bg-17-6423-2020, https://doi.org/10.5194/bg-17-6423-2020, 2020
Short summary
Short summary
With distributed temperature sensing (DTS) we measured a vertical temperature profile in a forest, from the forest floor to above the treetops. Using this temperature profile we can see which parts of the forest canopy are colder (thus more dense) or warmer (and less dense) and study the effect this has on the suppression of turbulent mixing. This can be used to improve our knowledge of the interaction between the atmosphere and forests and improve carbon dioxide flux measurements over forests.
Fabian von Trentini, Emma E. Aalbers, Erich M. Fischer, and Ralf Ludwig
Earth Syst. Dynam., 11, 1013–1031, https://doi.org/10.5194/esd-11-1013-2020, https://doi.org/10.5194/esd-11-1013-2020, 2020
Short summary
Short summary
We compare the inter-annual variability of three single-model initial-condition large ensembles (SMILEs), downscaled with three regional climate models over Europe for seasonal temperature and precipitation, the number of heatwaves, and maximum length of dry periods. They all show good consistency with observational data. The magnitude of variability and the future development are similar in many cases. In general, variability increases for summer indicators and decreases for winter indicators.
Justus G. V. van Ramshorst, Miriam Coenders-Gerrits, Bart Schilperoort, Bas J. H. van de Wiel, Jonathan G. Izett, John S. Selker, Chad W. Higgins, Hubert H. G. Savenije, and Nick C. van de Giesen
Atmos. Meas. Tech., 13, 5423–5439, https://doi.org/10.5194/amt-13-5423-2020, https://doi.org/10.5194/amt-13-5423-2020, 2020
Short summary
Short summary
In this work we present experimental results of a novel actively heated fiber-optic (AHFO) observational wind-probing technique. We utilized a controlled wind-tunnel setup to assess both the accuracy and precision of AHFO under a range of operational conditions (wind speed, angles of attack and temperature differences). AHFO has the potential to provide high-resolution distributed observations of wind speeds, allowing for better spatial characterization of fine-scale processes.
Cited articles
Aalbers, E., van Meijgaard, E., Lenderink, G., de Vries, H., and van den Hurk, B.:
The 2018 European drought under future climate conditions,
Environ. Res. Lett.,
in preparation, 2022. a
Aalbers, E. E., Lenderink, G., van Meijgaard, E., and van den Hurk, B. J.:
Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?,
Clim. Dynam.,
50, 4745–4766, https://doi.org/10.1007/s00382-017-3901-9, 2018. a
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017. a
Allen, C. D., Macalady, A. K., Chenchouni, H., Bachelet, D., McDowell, N., Vennetier, M., Kitzberger, T., Rigling, A., Breshears, D. D., Hogg, E. H., Gonzalez, P., Fensham, R., Zhang, Z., Castro, J., Demidova, N., Lim, J. H., Allard, G., Running, S. W., Semerci, A., and Cobb, N.:
A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests,
Forest Ecol. Manag.,
259, 660–684, https://doi.org/10.1016/j.foreco.2009.09.001, 2010. a, b
Andréassian, V., Parent, E., and Michel, C.:
A distribution-free test to detect gradual changes in watershed behavior,
Water Resour. Res.,
39, 1–11, https://doi.org/10.1029/2003WR002081, 2003. a
Attema, J. J., Loriaux, J. M., and Lenderink, G.:
Extreme precipitation response to climate perturbations in an atmospheric mesoscale model,
Environ. Res. Lett.,
9, 014003, https://doi.org/10.1088/1748-9326/9/1/014003, 2014. a
Balsamo, G., Viterbo, P., Beijaars, A., van den Hurk, B., Hirschi, M., Betts, A. K., and Scipal, K.:
A revised hydrology for the ECMWF model: Verification from field site to terrestrial water storage and impact in the integrated forecast system,
J. Hydrometeorol.,
10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009. a
Bastin, J. F., Clark, E., Elliott, T., Hart, S., Van Den Hoogen, J., Hordijk, I., Ma, H., Majumder, S., Manoli, G., Maschler, J., Mo, L., Routh, D., Yu, K., Zohner, C. M., and Crowther, T. W.:
Correction: Understanding climate change from a global analysis of city analogues (PLoS ONE (2019) 14:7 (e0217592) https://doi.org/10.1371/journal.pone.0217592),
PLoS ONE,
14, 1–13, https://doi.org/10.1371/journal.pone.0224120, 2019. a
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. a
Berghuijs, W. R., Gnann, S. J., and Woods, R. A.:
Unanswered questions on the Budyko framework,
Hydrol. Process.,
34, 5699–5703, https://doi.org/10.1002/hyp.13958, 2020. a
Blöschl, G. and Montanari, A.:
Climate change impacts-throwing the dice?,
Hydrol. Process.,
24, 374–381, https://doi.org/10.1002/hyp.7574, 2010. a, b, c
Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Széles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A., Andréassian, V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H., Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard, T., de Amorim, P. B., Böttcher, M. E., Boulet, G., Breinl, K., Brilly, M., Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X., Chen, Y., Chen, Y., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke, B., Dathe, A., David, P. C., de Barros, F. P. J., de Rooij, G., Baldassarre, G. D., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H., Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger, D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A., Geris, J., Gharari, S., Gleeson, T., Glendell, M., Bevacqua, A. G., González-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D., Hannah, D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey, M., Hlaváčiková, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz, M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E., Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel, J., Kirkby, M., Knoben, W., Kochanek, K., Kohnová, S., Kolechkina, A., Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M. L. R., Lindquist, E., Link, T., Liu, J., Loucks, D. P., Luce, C., Mahé, G., Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J., Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D., Montanari, A., Müller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C., Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z., Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J., Post, D., Sierra, C. P., Ramos, M.-H., Renner, M., Reynolds, J. E., Ridolfi, E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sá, J. H. M., Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A., Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C., Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser, U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F., Tong, R., Tussupova, K., Tyralis, H., Uijlenhoet, R., van Beek, R., van der Ent, R. J., van der Ploeg, M., Loon, A. F. V., van Meerveld, I., van Nooijen, R., van Oel, P. R., Vidal, J.-P., von Freyberg, J., Vorogushyn, S., Wachniew, P., Wade, A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu, Z., Yilmaz, K. K., and Zhang, Y.:
Twenty-three unsolved problems in hydrology (UPH) – a community perspective,
Hydrolog. Sci. J.,
64, 1141–1158, https://doi.org/10.1080/02626667.2019.1620507, 2019. a
Booij, M. J.:
Impact of climate change on river flooding assessed with different spatial model resolutions,
J. Hydrol.,
303, 176–198, https://doi.org/10.1016/j.jhydrol.2004.07.013, 2005. a
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. a
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. a, b, c, d, e, f, g
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. a, b, c, d
Brogli, R., Kröner, N., Sørland, S. L., Lüthi, D., and Schär, C.:
The role of hadley circulation and lapse-rate changes for the future European summer climate,
J. Climate,
32, 385–404, https://doi.org/10.1175/JCLI-D-18-0431.1, 2019. a
Brown, A. E., Zhang, L., McMahon, T. A., Western, A. W., and Vertessy, R. A.:
A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation,
J. Hydrol.,
310, 28–61, https://doi.org/10.1016/j.jhydrol.2004.12.010, 2005. a
Brunner, I., Herzog, C., Dawes, M. A., Arend, M., and Sperisen, C.:
How tree roots respond to drought, Frontiers in Plant Science, 6, 1–16, https://doi.org/10.3389/fpls.2015.00547, 2015. a
Brunner, M. I., Farinotti, D., Zekollari, H., Huss, M., and Zappa, M.: Future shifts in extreme flow regimes in Alpine regions, Hydrol. Earth Syst. Sci., 23, 4471–4489, https://doi.org/10.5194/hess-23-4471-2019, 2019. a
Budyko, M. I.:
The heat balance of the earth's surface,
Sov. Geogr.,
2, 3–13, 1961. a
Buytaert, W. and Beven, K.:
Regionalization as a learning process,
Water Resour. Res.,
45, 1–13, https://doi.org/10.1029/2008WR007359, 2009. a, b
Calder, I. R., Reid, I., Nisbet, T. R., and Green, J. C.:
Impact of lowland forests in England on water resources: Application of the Hydrological Land Use Change (HYLUC) model,
Water Resour. Res.,
39, 1–10, https://doi.org/10.1029/2003WR002042, 2003. a
Cateau, E., Larrieu, L., Vallauri, D., Savoie, J. M., Touroult, J., and Brustel, H.:
Ancienneté et maturité: Deux qualités complémentaires d'un écosystème forestier,
C. R. Biol.,
338, 58–73, https://doi.org/10.1016/j.crvi.2014.10.004, 2015. a
Clark, M. P., Slater, A. G., Rupp, D. E., Woods, R. A., Vrugt, J. A., Gupta, H. V., Wagener, T., and Hay, L. E.:
Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models,
Water Resour. Res.,
44, 1–14, https://doi.org/10.1029/2007wr006735, 2008. a
Collins, D. B. and Bras, R. L.:
Plant rooting strategies in water-limited ecosystems,
Water Resour. Res.,
43, 1–10, https://doi.org/10.1029/2006WR005541, 2007. a
Cornes, R. C., van der Schrier, G., van den Besselaar, E. J., and Jones, P. D.:
An Ensemble Version of the E-OBS Temperature and Precipitation Data Sets,
J. Geophys. Res.-Atmos.,
123, 9391–9409, https://doi.org/10.1029/2017JD028200, 2018. a, b
Coron, L.:
Les modèles hydrologiques conceptuels sont-ils robustes face à un climat en évolution?,
PhD thesis, https://webgr.irstea.fr/wp-content/uploads/2012/11/these_Coron.pdf (last access: 21 February 2022),
AgroParisTech, France, 2013. a
Coron, L., Andréassian, V., Perrin, C., Lerat, J., Vaze, J., Bourqui, M., and Hendrickx, F.:
Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments,
Water Resour. Res.,
48, 1–17, https://doi.org/10.1029/2011WR011721, 2012. a
de Wit, M. J., van den Hurk, B., Warmerdam, P. M., Torfs, P. J., Roulin, E., and Van Deursen, W. P.:
Impact of climate change on low-flows in the river Meuse,
Climatic Change,
82, 351–372, https://doi.org/10.1007/s10584-006-9195-2, 2007. a, b, c, d
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.,
436-437, 35–50, https://doi.org/10.1016/j.jhydrol.2012.02.033, 2012. a, b, c
Donohue, R. J., Roderick, M. L., McVicar, T. R., and Farquhar, G. D.:
Impact of CO2 fertilization on maximum foliage cover across the globe's warm, arid environments,
Geophys. Res. Lett.,
40, 3031–3035, https://doi.org/10.1002/grl.50563, 2013. a
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. a
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. a, b
Eilander, D., van Verseveld, W., Yamazaki, D., Weerts, A., Winsemius, H. C., and Ward, P. J.: A hydrography upscaling method for scale-invariant parametrization of distributed hydrological models, Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, 2021. a
EU-FP6 project UERRA and the Copernicus Climate Change Service and the data providers in the ECA&D project:
E-OBS gridded dataset (v20.0e), https://www.ecad.eu/download/ensembles/download.php (last access: Last access: 28 May 2020)
2019. a
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. a
Fitzpatrick, M. C. and Dunn, R. R.:
Contemporary climatic analogs for 540 North American urban areas in the late 21st century,
Nat. Commun.,
10, 1–7, https://doi.org/10.1038/s41467-019-08540-3, 2019. a
Frank, D. C., Poulter, B., Saurer, M., Esper, J., Huntingford, C., Helle, G., Treydte, K., Zimmermann, N. E., Schleser, G. H., Ahlström, A., Ciais, P., Friedlingstein, P., Levis, S., Lomas, M., Sitch, S., Viovy, N., Andreu-Hayles, L., Bednarz, Z., Berninger, F., Boettger, T., D'alessandro, C. M., Daux, V., Filot, M., Grabner, M., Gutierrez, E., Haupt, M., Hilasvuori, E., Jungner, H., Kalela-Brundin, M., Krapiec, M., Leuenberger, M., Loader, N. J., Marah, H., Masson-Delmotte, V., Pazdur, A., Pawelczyk, S., Pierre, M., Planells, O., Pukiene, R., Reynolds-Henne, C. E., Rinne, K. T., Saracino, A., Sonninen, E., Stievenard, M., Switsur, V. R., Szczepanek, M., Szychowska-Krapiec, E., Todaro, L., Waterhouse, J. S., and Weigl, M.:
Water-use efficiency and transpiration across European forests during the Anthropocene,
Nat. Clim. Change,
5, 579–583, https://doi.org/10.1038/nclimate2614, 2015. a
Gao, C., Booij, M. J., and Xu, Y.-P.: Assessment of extreme flows and uncertainty under climate change: disentangling the uncertainty contribution of representative concentration pathways, global climate models and internal climate variability, Hydrol. Earth Syst. Sci., 24, 3251–3269, https://doi.org/10.5194/hess-24-3251-2020, 2020. a
Gao, J., Holden, J., and Kirkby, M.:
A distributed TOPMODEL for modelling impacts of land-cover change on river flow in upland peatland catchments,
Hydrol. Process.,
29, 2867–2879, https://doi.org/10.1002/hyp.10408, 2015. a
Gerrits, A. M., Savenije, H. H., Veling, E. J., and Pfister, L.:
Analytical derivation of the Budyko curve based on rainfall characteristics and a simple evaporation model,
Water Resour. Res.,
45, 1–15, https://doi.org/10.1029/2008WR007308, 2009. a
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. a
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. a
Gleeson, T., Wang-Erlandsson, L., Porkka, M., Zipper, S. C., Jaramillo, F., Gerten, D., Fetzer, I., Cornell, S. E., Piemontese, L., Gordon, L. J., Rockström, J., Oki, T., Sivapalan, M., Wada, Y., Brauman, K. A., Flörke, M., Bierkens, M. F., Lehner, B., Keys, P., Kummu, M., Wagener, T., Dadson, S., Troy, T. J., Steffen, W., Falkenmark, M., and Famiglietti, J. S.:
Illuminating water cycle modifications and Earth system resilience in the Anthropocene,
Water Resour. Res.,
56, 1–24, https://doi.org/10.1029/2019WR024957, 2020. a
Guswa, A. J.:
The influence of climate on root depth: A carbon cost-benefit analysis,
Water Resour. Res.,
44, 1–11, https://doi.org/10.1029/2007WR006384, 2008. a, b, c, d
Hakala, K., Addor, N., Gobbe, T., Ruffieux, J., and Seibert, J.: Risks and opportunities for a Swiss hydroelectricity company in a changing climate, Hydrol. Earth Syst. Sci., 24, 3815–3833, https://doi.org/10.5194/hess-24-3815-2020, 2020. a
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. a
Harman, C. and Troch, P. A.: What makes Darwinian hydrology “Darwinian”? Asking a different kind of question about landscapes, Hydrol. Earth Syst. Sci., 18, 417–433, https://doi.org/10.5194/hess-18-417-2014, 2014. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J. N.:
The ERA5 global reanalysis,
Q. J. Roy. Meteor. Soc.,
146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hooghart, J. C. and Lablans, W. N.:
Van Penman naar Makkink: een nieuwe berekeningswijze voor de klimatologische verdampingsgetallen,
De Bilt, Royal Netherlands Meteorological Institute (KNMI),
De Bilt, the Netherlands, 1988. a
Hrachowitz, M., Stockinger, M., Coenders-gerrits, M., Ent, R. V. D., 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, 2021. a, b, c, d, e, f, g, h, i
Hulsman, P., Winsemius, H. C., Michailovsky, C. I., Savenije, H. H. G., and Hrachowitz, M.: Using altimetry observations combined with GRACE to select parameter sets of a hydrological model in a data-scarce region, Hydrol. Earth Syst. Sci., 24, 3331–3359, https://doi.org/10.5194/hess-24-3331-2020, 2020. a
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, 2021. a
Institut National de l'Information Géographique et Forestière: La base de données Forêt version 2.0, Institut National de l'Information Géographique et Forestière, https://inventaire-forestier.ign.fr/spip.php?rubrique227 (last access: 21 February 2022), 2019. a
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. a, b
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. a, b, c
Keenan, T. F., Hollinger, D. Y., Bohrer, G., Dragoni, D., Munger, J. W., Schmid, H. P., and Richardson, A. D.:
Increase in forest water-use efficiency as atmospheric carbon dioxide concentrations rise, Nature, 499, 324–327, https://doi.org/10.1038/nature12291, 2013. a, b
Kervyn, T., Scohy, J.-P., Marchal, D., Collette, O., Hardy, B., Delahaye, L., Wibail, L., Jacquemin, F., Dufrêne, M., and Claessens, H.:
La gestion patrimoniale des forêts anciennes de Wallonie (Belgique), Forêt Nature, 148, 545–560, https://doi.org/10.4267/2042/67878, 2018. a, b
Kleidon, A.:
Global datasets and rooting zone depth inferred from inverse methods,
J. Climate,
17, 2714–2722, https://doi.org/10.1175/1520-0442(2004)017<2714:GDORZD>2.0.CO;2, 2004. a
Kleidon, A. and Heimann, M.:
A method of determining rooting depth from a terrestrial biosphere model and its impacts on the global water and carbon cycle,
Glob. Change Biol.,
4, 275–286, https://doi.org/10.1046/j.1365-2486.1998.00152.x, 1998. a
Klingen, S.:
Twaalf boslessen,
Klingen Bomen, Doorn, 2017. a
Klingler, C., Schulz, K., and Herrnegger, M.: LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe, Earth Syst. Sci. Data, 13, 4529–4565, https://doi.org/10.5194/essd-13-4529-2021, 2021. a
Kovats, R. S., Valentini, R., Bouwer, L. M., Georgopoulou, E., Jacob, D., Martin, E., Rounsevell, M., and Soussana, J. F.:
Europe, Climate Change 2014: Impacts, Adaptation and Vulnerability: Part B: Regional Aspects: Working Group II Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom and NEw York, NY, USA, 1267–1326, https://doi.org/10.1017/CBO9781107415386.003, 2014. a
Latte, N., Lebourgeois, F., Kint, V., Drouet, T., and Claessens, H.:
Le hêtre face au changement climatique: Le cas de la Belgique,
Revue Forestière Française,
69, 205–218, https://doi.org/10.4267/2042/65336, 2017. a
Lebourgeois, F. and Mérian, P.:
La sensibilité au climat des arbres forestiers a-t-elle changé au cours du XXe siècle?,
Revue Forestière Française,
63, 17–32, https://doi.org/10.4267/2042/43091, 2011. a
Levia, D. F., Creed, I. F., Hannah, D. M., Nanko, K., Boyer, E. W., Carlyle-moses, D. E., Giesen, N. V. D., Grasso, D., Guswa, A. J., Hudson, J. E., Hudson, S. A., Iida, S., Jackson, R. B., Katul, G. G., Kumagai, T., Llorens, P., Ribeiro, F. L., Pataki, D. E., Peters, C. A., Carretero, D. S., and Selker, J. S.:
Homogenization of the terrestrial water cycle,
Nat. Geosci.,
13, 656–658, https://doi.org/10.1038/s41561-020-0641-y, 2020. a, b
Mao, D. and Cherkauer, K. A.:
Impacts of land-use change on hydrologic responses in the Great Lakes region,
J. Hydrol.,
374, 71–82, https://doi.org/10.1016/j.jhydrol.2009.06.016, 2009. a
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, 2021. a
Merz, R., Parajka, J., and Blöschl, G.:
Time stability of catchment model parameters: Implications for climate impact analyses,
Water Resour. Res.,
47, 1–17, https://doi.org/10.1029/2010WR009505, 2011. a, b
Mezentsev, V.:
Back to the computation of total evaporation,
Meteorologia i Gidrologia,
5, 24–26, 1955. a
Milly, P. C.:
Climate, interseasonal storage of soil water, and the annual water balance,
Adv. Water Resour.,
17, 19–24, https://doi.org/10.1016/0309-1708(94)90020-5, 1994. a
Milly, P. C., Betancourt, J., Falkenmark, M., Hirsch, R. M., Kundzewicz, Z. W., Lettenmaier, D. P., and Stouffer, R. J.:
Climate change: Stationarity is dead: Whither water management?,
Science,
319, 573–574, https://doi.org/10.1126/science.1151915, 2008. a
Miralles, D. G., Brutsaert, W., Dolman, A. J., and Gash, J. H.:
On the use of the term “Evapotranspiration”,
p. 8, https://doi.org/10.1002/essoar.10503229.1,
Earth and Space Science Open Archive, 2020. a
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. a, b, c, d, e, f, g, h
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. a
Peel, M. C. and Blöschl, G.:
Hydrological modelling in a changing world,
Prog. Phys. Geogr.,
35, 249–261, https://doi.org/10.1177/0309133311402550, 2011. a
Pomeroy, J., Fang, X., and Ellis, C.:
Sensitivity of snowmelt hydrology in Marmot Creek, Alberta, to forest cover disturbance,
Hydrol. Process.,
26, 1891–1904, https://doi.org/10.1002/hyp.9248, 2012. a
Prein, A. F., Rasmussen, R. M., Ikeda, K., Liu, C., Clark, M. P., and Holland, G. J.:
The future intensification of hourly precipitation extremes,
Nat. Clim. Change,
7, 48–52, https://doi.org/10.1038/nclimate3168, 2017. a
Prudhomme, C., Giuntoli, I., Robinson, E. L., Clark, D. B., Arnell, N. W., Dankers, R., Fekete, B. M., Franssen, W., Gerten, D., Gosling, S. N., Hagemann, S., Hannah, D. M., Kim, H., Masaki, Y., Satoh, Y., Stacke, T., Wada, Y., and Wisser, D.:
Hydrological droughts in the 21st century, hotspots and uncertainties from a global multimodel ensemble experiment,
P. Natl. Acad. Sci. USA,
111, 3262–3267, https://doi.org/10.1073/pnas.1222473110, 2014. a
Reaver, N. G. F., Kaplan, D. A., Klammler, H., and Jawitz, J. W.: Reinterpreting the Budyko Framework, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2020-584, in review, 2020. a
Rennó, C. D., Nobre, A. D., Cuartas, L. A., Soares, J. V., Hodnett, M. G., Tomasella, J., and Waterloo, M. J.:
HAND, a new terrain descriptor using SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia,
Remote Sens. Environ.,
112, 3469–3481, https://doi.org/10.1016/j.rse.2008.03.018, 2008. a
Reu, B., Zaehle, S., Bohn, K., Pavlick, R., Schmidtlein, S., Williams, J. W., and Kleidon, A.:
Future no-analogue vegetation produced by no-analogue combinations of temperature and insolation,
Global Ecol. Biogeogr.,
23, 156–167, https://doi.org/10.1111/geb.12110, 2014. a
Rohat, G., Goyette, S., and Flacke, J.:
Characterization of European cities' climate shift – an exploratory study based on climate analogues,
Int. J. Clim. Chang. Str.,
10, 428–452, https://doi.org/10.1108/IJCCSM-05-2017-0108, 2018. a
Rottler, E., Bronstert, A., Bürger, G., and Rakovec, O.: Projected changes in Rhine River flood seasonality under global warming, Hydrol. Earth Syst. Sci., 25, 2353–2371, https://doi.org/10.5194/hess-25-2353-2021, 2021. a
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. a
Savenije, H. H. G.: HESS Opinions “Topography driven conceptual modelling (FLEX-Topo)”, Hydrol. Earth Syst. Sci., 14, 2681–2692, https://doi.org/10.5194/hess-14-2681-2010, 2010. a
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. a
Schaphoff, S., von Bloh, W., Rammig, A., Thonicke, K., Biemans, H., Forkel, M., Gerten, D., Heinke, J., Jägermeyr, J., Knauer, J., Langerwisch, F., Lucht, W., Müller, C., Rolinski, S., and Waha, K.: LPJmL4 – a dynamic global vegetation model with managed land – Part 1: Model description, Geosci. Model Dev., 11, 1343–1375, https://doi.org/10.5194/gmd-11-1343-2018, 2018. a
Schär, C., Frei, C., Lüthi, D., and Davies, H. C.:
Surrogate climate-change scenarios for regional climate models,
Geophys. Res. Lett.,
23, 669–672, https://doi.org/10.1029/96GL00265, 1996. a
Schattan, P., Zappa, M., Lischke, H., Bernhard, L., Thürig, E., and Diekkrüger, B.:
An approach for transient consideration of forest change in hydrological impact studies,
IAHS-AISH Proceedings and Reports,
359, 311–319, 2013. a
Schelhaas, M. J., Nabuurs, G. J., and Schuck, A.:
Natural disturbances in the European forests in the 19th and 20th centuries,
Glob. Change Biol.,
9, 1620–1633, https://doi.org/10.1046/j.1365-2486.2003.00684.x, 2003. a
Schellekens, J., Verseveld, W. V., Visser, M., Winsemius, H. H., de Boer-Euser, T., Bouaziz, L. J., Thiange, C., de Vries, S., Boisgontier, H., Eilander, D., Tollenaar, D., Weerts, A. H., Baart, F., Hazenberg, P., Lutz, A., ten Velden, C., Jansen, M., and Benedict, I.:
openstreams/wflow: Bug fixes and updates for release 2020.1.2, Zenodo, https://doi.org/10.5281/zenodo.4291730, 2020. a
Schymanski, S. J., Sivapalan, M., Roderick, M. L., Beringer, J., and Hutley, L. B.: An optimality-based model of the coupled soil moisture and root dynamics, Hydrol. Earth Syst. Sci., 12, 913–932, https://doi.org/10.5194/hess-12-913-2008, 2008. a, b, c
Schymanski, S. J., Sivapalan, M., Roderick, M. L., Hutley, L. B., and Beringer, J.:
An optimality-based model of the dynamic feedbacks between natural vegetation and the water balance,
Water Resour. Res.,
45, 1–18, https://doi.org/10.1029/2008WR006841, 2009. a
Service Public de Wallonie: Direction générale opérationnelle de la Mobilité et des Voies hydrauliques, Département des Etudes et de l’Appui à la Gestion, Direction de la Gestion hydrologique intégrée (Bld du Nord 8-5000 Namur, Belgium), 2018. a
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. a
Singh, R., Wagener, T., van Werkhoven, K., Mann, M. E., and Crane, R.: A trading-space-for-time approach to probabilistic continuous streamflow predictions in a changing climate – accounting for changing watershed behavior, Hydrol. Earth Syst. Sci., 15, 3591–3603, https://doi.org/10.5194/hess-15-3591-2011, 2011. a, b
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. a
Speich, M. J. R., Zappa, M., Scherstjanoi, M., and Lischke, H.: FORests and HYdrology under Climate Change in Switzerland v1.0: a spatially distributed model combining hydrology and forest dynamics, Geosci. Model Dev., 13, 537–564, https://doi.org/10.5194/gmd-13-537-2020, 2020. a, b
Stephens, C. M., Marshall, L. A., and Johnson, F. M.:
Investigating strategies to improve hydrologic model performance in a changing climate,
J. Hydrol.,
579, 124219, https://doi.org/10.1016/j.jhydrol.2019.124219, 2019. a
Stephens, C. M., Marshall, L. A., Johnson, F. M., Lin, L., Band, L. E., and Ajami, H.:
Is Past Variability a Suitable Proxy for Future Change? A Virtual Catchment Experiment,
Water Resour. Res.,
56, 1–25, https://doi.org/10.1029/2019WR026275, 2020. a, b, c, d
Stevens, D., Miranda, P. M. A., Orth, R., Boussetta, S., Balsamo, G., and Dutra, E.:
Sensitivity of Surface Fluxes in the ECMWF Land Surface Model to the Remotely Sensed Leaf Area Index and Root Distribution: Evaluation with Tower Flux Data,
Atmosphere,
11, 1362, https://doi.org/10.3390/atmos11121362, 2020. a
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. a, b, c
Tietjen, B., Schlaepfer, D. R., Bradford, J. B., Lauenroth, W. K., Hall, S. A., Duniway, M. C., Hochstrasser, T., Jia, G., Munson, S. M., Pyke, D. A., and Wilson, S. D.:
Climate change-induced vegetation shifts lead to more ecological droughts despite projected rainfall increases in many global temperate drylands,
Glob. Change Biol.,
23, 2743–2754, https://doi.org/10.1111/gcb.13598, 2017. a
Troch, P. A., Carrillo, G., Sivapalan, M., Wagener, T., and Sawicz, K.: Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution, Hydrol. Earth Syst. Sci., 17, 2209–2217, https://doi.org/10.5194/hess-17-2209-2013, 2013. a, b
Turc, L.: Le bilan d’eau des sols. Relations entre les précipitations, l’évaporation et l’écoulement, Ann. Agron., 5, 491–596, 1954. a
Ukkola, A. M., Prentice, I. C., Keenan, T. F., Van Dijk, A. I., Viney, N. R., Myneni, R. B., and Bi, J.:
Reduced streamflow in water-stressed climates consistent with CO2 effects on vegetation,
Nat. Clim. Change,
6, 75–78, https://doi.org/10.1038/nclimate2831, 2016. a, b
van Der Sleen, P., Groenendijk, P., Vlam, M., Anten, N. P., Boom, A., Bongers, F., Pons, T. L., Terburg, G., and Zuidema, P. A.:
No growth stimulation of tropical trees by 150 years of CO2 fertilization but water-use efficiency increased,
Nat. Geosci.,
8, 24–28, https://doi.org/10.1038/ngeo2313, 2015. a, b
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. a, b
van Meijgaard, E., Ulft, L. H. V., Bosveld, F. C., Lenderink, G., and Siebesma, a. P.:
The KNMI regional atmospheric climate model RACMO version 2.1, Technical report; TR – 302, KNMI, de Bilt, the Netherlands, p. 43,
2008. a
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.
a, b, c
van Wijk, M. T. and Bouten, W.: Towards understanding tree root profiles: simulating hydrologically optimal strategies for root distribution, Hydrol. Earth Syst. Sci., 5, 629–644, https://doi.org/10.5194/hess-5-629-2001, 2001. a
Vaze, J., Post, D. A., Chiew, F. H., Perraud, J. M., Viney, N. R., and Teng, J.:
Climate non-stationarity – Validity of calibrated rainfall-runoff models for use in climate change studies,
J. Hydrol.,
394, 447–457, https://doi.org/10.1016/j.jhydrol.2010.09.018, 2010. a
Wagener, T.:
Can we model the hydrological impacts of environmental change?,
Hydrol. Process.,
21, 3233–3236, https://doi.org/10.1002/hyp.6873, 2007. a, b
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. a, b, c, d, e
Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and Pavelsky, T. M.:
MERIT Hydro: A High-Resolution Global Hydrography Map Based on Latest Topography Dataset,
Water Resour. Res.,
55, 5053–5073, https://doi.org/10.1029/2019WR024873, 2019. a
Yang, Y., Donohue, R. J., and McVicar, T. R.:
Global estimation of effective plant rooting depth: Implications for hydrological modeling,
Water Resour. Res.,
52, 8260–8276, https://doi.org/10.1002/2016WR019392, 2016. a
Yang, Y., Roderick, M. L., Zhang, S., McVicar, T. R., and Donohue, R. J.:
Hydrologic implications of vegetation response to elevated CO2 in climate projections,
Nat. Clim. Change,
9, 44–48, https://doi.org/10.1038/s41558-018-0361-0, 2019. a
Zhang, B., Hautier, Y., Tan, X., You, C., Cadotte, M. W., Chu, C., Jiang, L., Sui, X., Ren, T., Han, X., and Chen, S.:
Species responses to changing precipitation depend on trait plasticity rather than trait means and intraspecific variation,
Funct. Ecol., 34, 2622–2633, https://doi.org/10.1111/1365-2435.13675, 2020. a
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, 1–14, https://doi.org/10.1029/2003WR002710, 2004. a, b
Short summary
Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.
Assuming stationarity of hydrological systems is no longer appropriate when considering land use...
