Articles | Volume 29, issue 18
https://doi.org/10.5194/hess-29-4395-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-4395-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Sep 2025
Research article |
| 16 Sep 2025
| 16 Sep 2025
Unveiling the impact of potential evapotranspiration method selection on trends in hydrological cycle components across Europe
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Prague – Suchdol, Czech Republic
Yannis Markonis
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Prague – Suchdol, Czech Republic
Rohini Kumar
Department Computational Hydrosystems, UFZ-Helmholtz Centre for Environmental Research, Leipzig, Germany
Johanna Ruth Thomson
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Prague – Suchdol, Czech Republic
Mijael Rodrigo Vargas Godoy
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Prague – Suchdol, Czech Republic
River-Coastal Science & Engineering, Tulane University, New Orleans, Louisiana 70118, USA
Martin Hanel
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Prague – Suchdol, Czech Republic
Oldrich Rakovec
Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 16500 Prague – Suchdol, Czech Republic
Related authors
No articles found.
Pia Ebeling, Alexander Hubig, Alexander Wachholz, Ulrike Scharfenberger, Sarah Haug, Tam Nguyen, Fanny Sarrazin, Masooma Batool, Andreas Musolff, and Rohini Kumar
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-450, https://doi.org/10.5194/essd-2025-450, 2025
Preprint under review for ESSD
Short summary
Short summary
This update of the water quality dataset QUADICA for 1386 German catchments adds new data on water quality, flow, and drivers. Additions include water temperature and concentrations of oxygen and others, as well as catchment-wise time series on pollution sources and improved integration with other relevant datasets. This expanded dataset will help researchers and practitioners better understand how human activities affect water quality and ecosystems, and make more informed decisions.
Rajani Kumar Pradhan, Yannis Markonis, Francesco Marra, Efthymios I. Nikolopoulos, Simon Michael Papalexiou, and Vincenzo Levizzani
Hydrol. Earth Syst. Sci., 29, 4929–4949, https://doi.org/10.5194/hess-29-4929-2025, https://doi.org/10.5194/hess-29-4929-2025, 2025
Short summary
Short summary
This study compared global satellite and reanalysis precipitation datasets to assess diurnal variability. We found that all datasets capture key diurnal precipitation patterns, with maximum precipitation in the afternoon over land and early morning over the ocean. However, there are differences in the exact timing and amount of precipitation. This suggests that it is better to use a combination of datasets for potential applications rather than relying on a single dataset.
Hossein Abbasizadeh, Petr Maca, Martin Hanel, Mads Troldborg, and Amir AghaKouchak
Hydrol. Earth Syst. Sci., 29, 4761–4790, https://doi.org/10.5194/hess-29-4761-2025, https://doi.org/10.5194/hess-29-4761-2025, 2025
Short summary
Short summary
Here, we represented catchments as networks of variables connected by cause-and-effect relationships. By comparing the performance of statistical and machine learning methods with and without incorporating causal information to predict runoff properties, we showed that causal information can enhance models' robustness by reducing the accuracy drop between the training and testing phases, improving the model's interpretability, and mitigating overfitting issues, especially with small training samples.
Katoria Lekarkar, Oldrich Rakovec, Rohini Kumar, Stefaan Dondeyne, and Ann van Griensven
EGUsphere, https://doi.org/10.5194/egusphere-2025-4526, https://doi.org/10.5194/egusphere-2025-4526, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Belgium has faced intense droughts in recent years, causing major losses across sectors. To assess their rarity, we used a hydrological model to reconstruct fifty years of soil moisture in the country. We show that 2011–2020 experienced the most severe droughts since 1971, with nearly 30 % of the decade under drought. We also show that rainfall-based indicators underestimate soil moisture droughts, so including soil moisture monitoring can give decision-makers a clearer picture of drought risks.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, Yannis Markonis, and Miroslav Trnka
Hydrol. Earth Syst. Sci., 29, 3341–3358, https://doi.org/10.5194/hess-29-3341-2025, https://doi.org/10.5194/hess-29-3341-2025, 2025
Short summary
Short summary
We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, with clusters of 775 and 630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Pia Ebeling, Andreas Musolff, Rohini Kumar, Andreas Hartmann, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 29, 2925–2950, https://doi.org/10.5194/hess-29-2925-2025, https://doi.org/10.5194/hess-29-2925-2025, 2025
Short summary
Short summary
Groundwater is a crucial resource at risk due to droughts. To understand drought effects on groundwater levels in Germany, we grouped 6626 wells into six regional and two national patterns. Weather explained half of the level variations with varied response times. Shallow groundwater responds fast and is more vulnerable to short droughts (a few months). Dampened deep heads buffer short droughts but suffer from long droughts and recoveries. Two nationwide trend patterns were linked to human water use.
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 25, 2007–2029, https://doi.org/10.5194/nhess-25-2007-2025, https://doi.org/10.5194/nhess-25-2007-2025, 2025
Short summary
Short summary
The July 2021 flood in central Europe was one of the deadliest floods in Europe in the recent decades and the most expensive flood in Germany. In this paper, we show that the hydrological impact of this event in the Ahr valley could have been even worse if the rainfall footprint trajectory had been only slightly different. The presented methodology of spatial counterfactuals generates plausible unprecedented events and helps to better prepare for future extreme floods.
Hannes Müller Schmied, Simon Newland Gosling, Marlo Garnsworthy, Laura Müller, Camelia-Eliza Telteu, Atiq Kainan Ahmed, Lauren Seaby Andersen, Julien Boulange, Peter Burek, Jinfeng Chang, He Chen, Lukas Gudmundsson, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Aristeidis Koutroulis, Rohini Kumar, Guoyong Leng, Junguo Liu, Xingcai Liu, Inga Menke, Vimal Mishra, Yadu Pokhrel, Oldrich Rakovec, Luis Samaniego, Yusuke Satoh, Harsh Lovekumar Shah, Mikhail Smilovic, Tobias Stacke, Edwin Sutanudjaja, Wim Thiery, Athanasios Tsilimigkras, Yoshihide Wada, Niko Wanders, and Tokuta Yokohata
Geosci. Model Dev., 18, 2409–2425, https://doi.org/10.5194/gmd-18-2409-2025, https://doi.org/10.5194/gmd-18-2409-2025, 2025
Short summary
Short summary
Global water models contribute to the evaluation of important natural and societal issues but are – as all models – simplified representation of reality. So, there are many ways to calculate the water fluxes and storages. This paper presents a visualization of 16 global water models using a standardized visualization and the pathway towards this common understanding. Next to academic education purposes, we envisage that these diagrams will help researchers, model developers, and data users.
Robert Reinecke, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
EGUsphere, https://doi.org/10.5194/egusphere-2025-1181, https://doi.org/10.5194/egusphere-2025-1181, 2025
Short summary
Short summary
Here we describe a collaborative effort to improve predictions of how climate change will affect groundwater. The ISIMIP groundwater sector combines multiple global groundwater models to capture a range of possible outcomes and reduce uncertainty. Initial comparisons reveal significant differences between models in key metrics like water table depth and recharge rates, highlighting the need for structured model intercomparisons.
Masooma Batool, Fanny J. Sarrazin, and Rohini Kumar
Earth Syst. Sci. Data, 17, 881–916, https://doi.org/10.5194/essd-17-881-2025, https://doi.org/10.5194/essd-17-881-2025, 2025
Short summary
Short summary
Our paper presents a reconstruction and analysis of the gridded P surplus in European landscapes from 1850 to 2019 at a 5 arcmin resolution. By utilizing 48 different estimates, we account for uncertainties in major components of the P surplus. Our findings highlight substantial historical changes, with the total P surplus in the EU 27 tripling over 170 years. Our dataset enables flexible aggregation at various spatial scales, providing critical insights for land and water management strategies.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Shailendra Pratap, Yannis Markonis, and Cécile Blanchet
Clim. Past Discuss., https://doi.org/10.5194/cp-2024-68, https://doi.org/10.5194/cp-2024-68, 2024
Preprint withdrawn
Short summary
Short summary
Our study investigates the influence of oceanic changes on regional hydroclimate (precipitation and temperature) patterns, in Europe and North America during the Medieval Climate Anomaly period. Our findings suggest that centennial-scale variations in terrestrial thermodynamics, sea surface temperatures, and shifts in the Intertropical Convergence Zone likely played a role in shaping regional hydroclimate patterns. Our outcomes will offer insights into how hydroclimate may evolve in the future.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
Short summary
Short summary
Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
Short summary
Short summary
We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Kingsley Nnaemeka Ogbu, Oldrich Rakovec, Luis Samaniego, Gloria Chinwendu Okafor, Bernhard Tischbein, and Hadush Meresa
Proc. IAHS, 385, 211–218, https://doi.org/10.5194/piahs-385-211-2024, https://doi.org/10.5194/piahs-385-211-2024, 2024
Short summary
Short summary
In this study, the MPR-mHM technique was applied in four data-scarce basins in Nigeria. Remotely sensed rainfall datasets were used as model forcings to evaluate the mHM capability in reproducing observed stream discharge under single and multivariable model calibration frameworks. Overall, model calibration performances displayed satisfactory outputs as evident in the Kling-Gupta Efficiency (KGE) scores across most basins.
Mijael Rodrigo Vargas Godoy, Yannis Markonis, Oldrich Rakovec, Michal Jenicek, Riya Dutta, Rajani Kumar Pradhan, Zuzana Bešťáková, Jan Kyselý, Roman Juras, Simon Michael Papalexiou, and Martin Hanel
Hydrol. Earth Syst. Sci., 28, 1–19, https://doi.org/10.5194/hess-28-1-2024, https://doi.org/10.5194/hess-28-1-2024, 2024
Short summary
Short summary
The study introduces a novel benchmarking method based on the water cycle budget for hydroclimate data fusion. Using this method and multiple state-of-the-art datasets to assess the spatiotemporal patterns of water cycle changes in Czechia, we found that differences in water availability distribution are dominated by evapotranspiration. Furthermore, while the most significant temporal changes in Czechia occur during spring, the median spatial patterns stem from summer changes in the water cycle.
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023, https://doi.org/10.5194/hess-27-2989-2023, 2023
Short summary
Short summary
We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.
Petr Kavka, Jiří Cajthaml, Adam Tejkl, and Martin Hanel
Abstr. Int. Cartogr. Assoc., 6, 120, https://doi.org/10.5194/ica-abs-6-120-2023, https://doi.org/10.5194/ica-abs-6-120-2023, 2023
Carolin Winter, Tam V. Nguyen, Andreas Musolff, Stefanie R. Lutz, Michael Rode, Rohini Kumar, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 27, 303–318, https://doi.org/10.5194/hess-27-303-2023, https://doi.org/10.5194/hess-27-303-2023, 2023
Short summary
Short summary
The increasing frequency of severe and prolonged droughts threatens our freshwater resources. While we understand drought impacts on water quantity, its effects on water quality remain largely unknown. Here, we studied the impact of the unprecedented 2018–2019 drought in Central Europe on nitrate export in a heterogeneous mesoscale catchment in Germany. We show that severe drought can reduce a catchment's capacity to retain nitrogen, intensifying the internal pollution and export of nitrate.
Markéta Součková, Roman Juras, Kryštof Dytrt, Vojtěch Moravec, Johanna Ruth Blöcher, and Martin Hanel
Nat. Hazards Earth Syst. Sci., 22, 3501–3525, https://doi.org/10.5194/nhess-22-3501-2022, https://doi.org/10.5194/nhess-22-3501-2022, 2022
Short summary
Short summary
Avalanches are natural hazards that threaten people and infrastructure. With climate change, avalanche activity is changing. We analysed the change in frequency and size of avalanches in the Krkonoše Mountains, Czechia, and detected important variables with machine learning tools from 1979–2020. Wet avalanches in February and March have increased, and slab avalanches have decreased and become smaller. The identified variables and their threshold levels may help in avalanche decision-making.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
Short summary
Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
Short summary
Short summary
This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
Short summary
Short summary
Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
Short summary
Short summary
The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Joni Dehaspe, Fanny Sarrazin, Rohini Kumar, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 25, 6437–6463, https://doi.org/10.5194/hess-25-6437-2021, https://doi.org/10.5194/hess-25-6437-2021, 2021
Short summary
Short summary
Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Camelia-Eliza Telteu, Hannes Müller Schmied, Wim Thiery, Guoyong Leng, Peter Burek, Xingcai Liu, Julien Eric Stanislas Boulange, Lauren Seaby Andersen, Manolis Grillakis, Simon Newland Gosling, Yusuke Satoh, Oldrich Rakovec, Tobias Stacke, Jinfeng Chang, Niko Wanders, Harsh Lovekumar Shah, Tim Trautmann, Ganquan Mao, Naota Hanasaki, Aristeidis Koutroulis, Yadu Pokhrel, Luis Samaniego, Yoshihide Wada, Vimal Mishra, Junguo Liu, Petra Döll, Fang Zhao, Anne Gädeke, Sam S. Rabin, and Florian Herz
Geosci. Model Dev., 14, 3843–3878, https://doi.org/10.5194/gmd-14-3843-2021, https://doi.org/10.5194/gmd-14-3843-2021, 2021
Short summary
Short summary
We analyse water storage compartments, water flows, and human water use sectors included in 16 global water models that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b. We develop a standard writing style for the model equations. We conclude that even though hydrologic processes are often based on similar equations, in the end these equations have been adjusted, or the models have used different values for specific parameters or specific variables.
Erwin Rottler, Axel Bronstert, Gerd Bürger, and Oldrich Rakovec
Hydrol. Earth Syst. Sci., 25, 2353–2371, https://doi.org/10.5194/hess-25-2353-2021, https://doi.org/10.5194/hess-25-2353-2021, 2021
Short summary
Short summary
The mesoscale hydrological model (mHM) forced with an ensemble of climate projection scenarios was used to assess potential future changes in flood seasonality in the Rhine River basin. Results indicate that future changes in flood characteristics are controlled by increases in precipitation sums and diminishing snowpacks. The decreases in snowmelt can counterbalance increasing precipitation, resulting in only small and transient changes in streamflow maxima.
Manuela I. Brunner, Lieke A. Melsen, Andrew W. Wood, Oldrich Rakovec, Naoki Mizukami, Wouter J. M. Knoben, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 105–119, https://doi.org/10.5194/hess-25-105-2021, https://doi.org/10.5194/hess-25-105-2021, 2021
Short summary
Short summary
Assessments of current, local, and regional flood hazards and their future changes often involve the use of hydrologic models. A reliable model ideally reproduces both local flood characteristics and regional aspects of flooding. In this paper we investigate how such characteristics are represented by hydrologic models. Our results show that both the modeling of local and regional flood characteristics are challenging, especially under changing climate conditions.
Cited articles
Ajami, H., Sharma, A., Band, L. E., Evans, J. P., Tuteja, N. K., Amirthanathan, G. E., and Bari, M. A.: On the non-stationarity of hydrological response in anthropogenically unaffected catchments: an Australian perspective, Hydrol. Earth Syst. Sci., 21, 281–294, https://doi.org/10.5194/hess-21-281-2017, 2017. a
Aouissi, J., Benabdallah, S., Lili Chabaâne, Z., and Cudennec, C.: Evaluation of potential evapotranspiration assessment methods for hydrological modelling with SWAT – Application in data-scarce rural Tunisia, Agr. Water Manage., 174, 39–51, https://doi.org/10.1016/j.agwat.2016.03.004, 2016. a
Arino, O., Ramos Perez, J. J., Kalogirou, V., Bontemps, S., Defourny, P., and Van Bogaert, E.: Global Land Cover Map for 2009 (GlobCover 2009), PANGAEA [data set], https://doi.org/10.1594/PANGAEA.787668, 2012. a
Arnold, J. G., Srinivasan, R., Muttiah, R. S., and Williams, J. R.: large area hydrologic modeling and assessment Part I: model development, J. Am. Water Resour. Assoc., 34, 73–89, https://doi.org/10.1111/j.1752-1688.1998.tb05961.x, 1998. a
Bai, P., Liu, X., Liang, K., and Liu, C.: Comparison of performance of twelve monthly water balance models in different climatic catchments of China, J. Hydrol., 529, 1030–1040, https://doi.org/10.1016/j.jhydrol.2015.09.015, 2015. a
Bai, P., Liu, X., Yang, T., Li, F., Liang, K., Hu, S., and Liu, C.: Assessment of the Influences of Different Potential Evapotranspiration Inputs on the Performance of Monthly Hydrological Models under Different Climatic Conditions, J. Hydrometeorol., 17, 2259–2274, https://doi.org/10.1175/JHM-D-15-0202.1, 2016. a, b, c, d, e, f
Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Dutra, E., Fink, G., Orth, R., and Schellekens, J.: Global evaluation of runoff from 10 state-of-the-art hydrological models, Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, 2017. a
Berghuijs, W. R., Larsen, J. R., van Emmerik, T. H. M., 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, b
Birhanu, D., Kim, H., Jang, C., and Park, S.: Does the Complexity of Evapotranspiration and Hydrological Models Enhance Robustness?, Sustainability, 10, 2837, https://doi.org/10.3390/su10082837, 2018. a
Boeing, F., Wagener, T., Marx, A., Rakovec, O., Kumar, R., Samaniego, L., and Attinger, S.: Increasing influence of evapotranspiration on prolonged water storage recovery in Germany, Environ. Res. Lett., 19, 024047, https://doi.org/10.1088/1748-9326/ad24ce, 2024. a, b
Bruno, G. and Duethmann, D.: Increases in Water Balance‐Derived Catchment Evapotranspiration in Germany During 1970s–2000s Turning Into Decreases Over the Last Two Decades, Despite Uncertainties, Geophys. Res. Lett., 51, e2023GL107753, https://doi.org/10.1029/2023GL107753, 2024. a, b
Caloiero, T., Caloiero, P., and Frustaci, F.: Long‐term precipitation trend analysis in Europe and in the Mediterranean basin, Water Environ. J., 32, 433–445, https://doi.org/10.1111/wej.12346, 2018. a
Cheng, W., Dan, L., Deng, X., Feng, J., Wang, Y., Peng, J., Tian, J., Qi, W., Liu, Z., Zheng, X., Zhou, D., Jiang, S., Zhao, H., and Wang, X.: Global monthly gridded atmospheric carbon dioxide concentrations under the historical and future scenarios, Sci. Data, 9, 83, https://doi.org/10.1038/s41597-022-01196-7, 2022. a, b
Clerc-Schwarzenbach, F., Selleri, G., Neri, M., Toth, E., van Meerveld, I., and Seibert, J.: Large-sample hydrology – a few camels or a whole caravan?, Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, 2024. a
Deardorff, J. W.: Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation, J. Geophys. Res.-Oceans, 83, 1889–1903, https://doi.org/10.1029/JC083iC04p01889, 1978. a
Fang, B., Bevacqua, E., Rakovec, O., and Zscheischler, J.: An increase in the spatial extent of European floods over the last 70 years, Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, 2024. a
Guo, D., Westra, S., and Maier, H. R.: Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones, Hydrol. Earth Syst. Sci., 21, 2107–2126, https://doi.org/10.5194/hess-21-2107-2017, 2017. a
Hamon, W. R.: Estimating Potential Evapotranspiration, J. Hydraul. Div., 87, 107–120, https://doi.org/10.1061/JYCEAJ.0000599, 1961. a, b
Hanselmann, N., Osuch, M., Wawrzyniak, T., and Alphonse, A. B.: Evaluating potential evapotranspiration methods in a rapidly warming Arctic region, SW Spitsbergen (1983–2023), J. Hydrol., 56, 101979, https://doi.org/10.1016/j.ejrh.2024.101979, 2024. a
Hargreaves and Samani: Reference Crop Evapotranspiration from Temperature, Appl. Eng. Agr., 1, 96–99, https://doi.org/10.13031/2013.26773, 1985. a, b
Hartmann, J. and Moosdorf, N.: The new global lithological map database GLiM: A representation of rock properties at the Earth surface, Geochem. Geophy. Geosy., 13, 2012GC004370, https://doi.org/10.1029/2012GC004370, 2012. 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.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hua, D., Hao, X., Zhang, Y., and Qin, J.: Uncertainty assessment of potential evapotranspiration in arid areas, as estimated by the Penman-Monteith method, J. Arid Land, 12, 166–180, https://doi.org/10.1007/s40333-020-0093-7, 2020. a
Jensen, M. E. and Haise, H. R.: Estimating Evapotranspiration from Solar Radiation, J. Irr. Drain.-Div., 89, 15–41, https://doi.org/10.1061/JRCEA4.0000287, 1963. a, b
Kendall, M.: Rank correlation methods, Rank correlation methods, Griffin, Oxford, England, ISBN 0-85264-199-0 , 1948. a
Kingston, D. G., Todd, M. C., Taylor, R. G., Thompson, J. R., and Arnell, N. W.: Uncertainty in the estimation of potential evapotranspiration under climate change, Geophys. Res. Lett., 36, 2009GL040267, https://doi.org/10.1029/2009GL040267, 2009. a
Kuentz, A., Arheimer, B., Hundecha, Y., and Wagener, T.: Understanding hydrologic variability across Europe through catchment classification, Hydrol. Earth Syst. Sci., 21, 2863–2879, https://doi.org/10.5194/hess-21-2863-2017, 2017. a
Kumar, R., Livneh, B., and Samaniego, L.: Toward computationally efficient large-scale hydrologic predictions with a multiscale regionalization scheme, Water Resour. Res., 49, 5700–5714, https://doi.org/10.1002/wrcr.20431, 2013a. a, b, c
Kumar, R., Samaniego, L., and Attinger, S.: Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations, Water Resour. Res., 49, 360–379, https://doi.org/10.1029/2012WR012195, 2013b. a, b, c
Kumar, R., Heße, F., Rao, P. S. C., Musolff, A., Jawitz, J. W., Sarrazin, F., Samaniego, L., Fleckenstein, J. H., Rakovec, O., Thober, S., and Attinger, S.: Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe, Nat. Commun., 11, 6302, https://doi.org/10.1038/s41467-020-19955-8, 2020. a
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res.-Atmos., 99, 14415–14428, https://doi.org/10.1029/94JD00483, 1994. a
Liu, C., Wang, Z., Zheng, H., Zhang, L., and Wu, X.: Development of Hydro-Informatic Modelling System and its application, Sci. China Ser. E, 51, 456–466, https://doi.org/10.1007/s11431-008-0040-x, 2008. a
Liu, Y., Jiang, Q., Wang, Q., Jin, Y., Yue, Q., Yu, J., Zheng, Y., Jiang, W., and Yao, X.: The divergence between potential and actual evapotranspiration: An insight from climate, water, and vegetation change, Sci. Total Environ., 807, 150648, https://doi.org/10.1016/j.scitotenv.2021.150648, 2022. a
Lu, J., Sun, G., McNulty, S. G., and Amatya, D. M.: A COMPARISON OF SIX POTENTIAL EVAPOTRANSPIRATION METHODS FOR REGIONAL USE IN THE SOUTHEASTERN UNITED STATES, J. Am. Water Resour. Assoc., 41, 621–633, https://doi.org/10.1111/j.1752-1688.2005.tb03759.x, 2005. a
Maček, U., Bezak, N., and Šraj, M.: Reference evapotranspiration changes in Slovenia, Europe, Agr. Forest Meteorol., 260-261, 183–192, https://doi.org/10.1016/j.agrformet.2018.06.014, 2018. a
Markonis, Y.: On the Definition of Extreme Evaporation Events, Geophys. Res. Lett., 52, e2024GL113038, https://doi.org/10.1029/2024GL113038, 2025. a
Markonis, Y., Papalexiou, S. M., Martinkova, M., and Hanel, M.: Assessment of Water Cycle Intensification Over Land using a Multisource Global Gridded Precipitation DataSet, J. Geophys. Res.-Atmos., 124, 11175–11187, https://doi.org/10.1029/2019JD030855, 2019. a
Markonis, Y., Kumar, R., Hanel, M., Rakovec, O., Máca, P., and AghaKouchak, A.: The rise of compound warm-season droughts in Europe, Sci. Adv., 7, eabb9668, https://doi.org/10.1126/sciadv.abb9668, 2021. a
Markonis, Y., Vargas Godoy, M. R., Pradhan, R. K., Pratap, S., Thomson, J. R., Hanel, M., Paschalis, A., Nikolopoulos, E., and Papalexiou, S. M.: Spatial partitioning of terrestrial precipitation reveals varying dataset agreement across different environments, Commun. Earth Environ., 5, 217, https://doi.org/10.1038/s43247-024-01377-9, 2024. a
Massari, C., Avanzi, F., Bruno, G., Gabellani, S., Penna, D., and Camici, S.: Evaporation enhancement drives the European water-budget deficit during multi-year droughts, Hydrol. Earth Syst. Sci., 26, 1527–1543, https://doi.org/10.5194/hess-26-1527-2022, 2022. a, b, c
Mazzoleni, M., Brandimarte, L., and Amaranto, A.: Evaluating precipitation datasets for large-scale distributed hydrological modelling, J. Hydrol., 578, 124076, https://doi.org/10.1016/j.jhydrol.2019.124076, 2019. a
Milly, P. C. D. and Dunne, K. A.: Potential evapotranspiration and continental drying, Nat. Clim. Change, 6, 946–949, https://doi.org/10.1038/nclimate3046, 2016. a, b
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021. a, b, c, d, e, f, g
Ndiaye, P. M., Bodian, A., Dezetter, A., Ogilvie, A., and Goudiaby, O.: Sensitivity of global hydrological models to potential evapotranspiration estimation methods in the Senegal River Basin (West Africa), J. Hydrol., 53, 101823, https://doi.org/10.1016/j.ejrh.2024.101823, 2024. a
Oudin, L., Michel, C., and Anctil, F.: Which potential evapotranspiration input for a lumped rainfall-runoff model?, J. Hydrol., 303, 275–289, https://doi.org/10.1016/j.jhydrol.2004.08.025, 2005. a, b, c, d
Park, C.-E., Jeong, S.-J., Joshi, M., Osborn, T. J., Ho, C.-H., Piao, S., Chen, D., Liu, J., Yang, H., Park, H., Kim, B.-M., and Feng, S.: Keeping global warming within 1.5 °C constrains emergence of aridification, Nat. Clim. Change, 8, 70–74, https://doi.org/10.1038/s41558-017-0034-4, 2018. a
Pfeifroth, U., Sanchez‐Lorenzo, A., Manara, V., Trentmann, J., and Hollmann, R.: Trends and Variability of Surface Solar Radiation in Europe Based On Surface‐ and Satellite‐Based Data Records, J. Geophys. Res.-Atmos., 123, 1735–1754, https://doi.org/10.1002/2017JD027418, 2018. a
Pimentel, R., Arheimer, B., Crochemore, L., Andersson, J. C. M., Pechlivanidis, I. G., and Gustafsson, D.: Which Potential Evapotranspiration Formula to Use in Hydrological Modeling World‐Wide?, Water Resour. Res., 59, e2022WR033447, https://doi.org/10.1029/2022WR033447, 2023. a, b, c
Pohl, F., Rakovec, O., Rebmann, C., Hildebrandt, A., Boeing, F., Hermanns, F., Attinger, S., Samaniego, L., and Kumar, R.: Long-term daily hydrometeorological drought indices, soil moisture, and evapotranspiration for ICOS sites, Sci. Data, 10, 281, https://doi.org/10.1038/s41597-023-02192-1, 2023. a
Proutsos, N., Tigkas, D., Tsevreni, I., Alexandris, S. G., Solomou, A. D., Bourletsikas, A., Stefanidis, S., and Nwokolo, S. C.: A Thorough Evaluation of 127 Potential Evapotranspiration Models in Two Mediterranean Urban Green Sites, Remote Sens., 15, 3680, https://doi.org/10.3390/rs15143680, 2023. a, b, c
Rakovec, O., Kumar, R., Mai, J., Cuntz, M., Thober, S., Zink, M., Attinger, S., Schäfer, D., Schrön, M., and Samaniego, L.: Multiscale and Multivariate Evaluation of Water Fluxes and States over European River Basins, J. Hydrometeorol., 17, 287–307, https://doi.org/10.1175/JHM-D-15-0054.1, 2016. a, b, c, d, e
Rakovec, O., Mizukami, N., Kumar, R., Newman, A. J., Thober, S., Wood, A. W., Clark, M. P., and Samaniego, L.: Diagnostic Evaluation of Large‐Domain Hydrologic Models Calibrated Across the Contiguous United States, J. Geophys. Res.-Atmos., 124, 13991–14007, https://doi.org/10.1029/2019JD030767, 2019. a
Rakovec, O., Samaniego, L., Hari, V., Markonis, Y., Moravec, V., Thober, S., Hanel, M., and Kumar, R.: The 2018–2020 Multi‐Year Drought Sets a New Benchmark in Europe, Earth's Future, 10, e2021EF002394, https://doi.org/10.1029/2021EF002394, 2022. a
Rakovec, O., Kumar, R., Shrestha, P. K., and Samaniego, L.: Global assessment of hydrological components using a seamless multiscale modelling system, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11945, https://doi.org/10.5194/egusphere-egu23-11945, 2023. a
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. a
Samaniego, L., Kumar, R., and Attinger, S.: Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., 46, W05523, https://doi.org/10.1029/2008WR007327, 2010. a, b, c, d
Samaniego, L., Thober, S., Wanders, N., Pan, M., Rakovec, O., Sheffield, J., Wood, E. F., Prudhomme, C., Rees, G., Houghton-Carr, H., Fry, M., Smith, K., Watts, G., Hisdal, H., Estrela, T., Buontempo, C., Marx, A., and Kumar, R.: Hydrological Forecasts and Projections for Improved Decision-Making in the Water Sector in Europe, B. Am. Meteorol. Soc., 100, 2451–2472, https://doi.org/10.1175/BAMS-D-17-0274.1, 2019. a, b, c, d
Schulzweida, U.: CDO User Guide, Zenodo, https://doi.org/10.5281/ZENODO.7112925, 2022. a
Seiller, G. and Anctil, F.: How do potential evapotranspiration formulas influence hydrological projections?, Hydrolog. Sci. J., 61, 2249–2266, https://doi.org/10.1080/02626667.2015.1100302, 2016. a, b
Sen, P. K.: Estimates of the Regression Coefficient Based on Kendall's Tau, J. Am. Stat. Assoc., 63, 1379–1389, https://doi.org/10.1080/01621459.1968.10480934, 1968. a
Shah, J., Kumar, R., Samaniego, L., Markonis, Y., Hanel, M., Attinger, S., Hari, V., and Rakovec, O.: On the role of antecedent meteorological conditions on flash drought initialization in Europe, Environ. Res. Lett., 18, 064039, https://doi.org/10.1088/1748-9326/acd8d3, 2023. a
Shaw, S. B. and Riha, S. J.: Assessing temperature-based PET equations under a changing climate in temperate, deciduous forests, Hydrol. Process., 25, 1466–1478, https://doi.org/10.1002/hyp.7913, 2011. a
Shi, H., Luo, G., Hellwich, O., He, X., Kurban, A., De Maeyer, P., and Van de Voorde, T.: Global dryland aridity changes indicated by atmospheric, hydrological, and vegetation observations at meteorological stations, Hydrol. Earth Syst. Sci., 27, 4551–4562, https://doi.org/10.5194/hess-27-4551-2023, 2023a. a
Shi, L., Wang, B., Liu, D. L., Feng, P., Cleverly, J., Li, L., Zhang, G., and Yu, Q.: Performance of potential evapotranspiration models across different climatic stations in New South Wales, Australia, J. Hydrol., 50, 101573, https://doi.org/10.1016/j.ejrh.2023.101573, 2023b. a
Shrestha, P. K., Samaniego, L., Rakovec, O., Kumar, R., Mi, C., Rinke, K., and Thober, S.: Toward Improved Simulations of Disruptive Reservoirs in Global Hydrological Modeling, Water Resour. Res., 60, e2023WR035433, https://doi.org/10.1029/2023WR035433, 2024. a
Tang, G., Clark, M. P., and Papalexiou, S. M.: SC-Earth: A Station-Based Serially Complete Earth Dataset from 1950 to 2019, J. Climate, 34, 6493–6511, https://doi.org/10.1175/JCLI-D-21-0067.1, 2021. a
Tang, G., Clark, M. P., Knoben, W. J. M., Liu, H., Gharari, S., Arnal, L., Beck, H. E., Wood, A. W., Newman, A. J., and Papalexiou, S. M.: The Impact of Meteorological Forcing Uncertainty on Hydrological Modeling: A Global Analysis of Cryosphere Basins, Water Resour. Res., 59, e2022WR033767, https://doi.org/10.1029/2022WR033767, 2023. a, b, c
Tarek, M., Brissette, F. P., and Arsenault, R.: Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America, Hydrol. Earth Syst. Sci., 24, 2527–2544, https://doi.org/10.5194/hess-24-2527-2020, 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
Thackeray, C. W., Hall, A., Norris, J., and Chen, D.: Constraining the increased frequency of global precipitation extremes under warming, Nat. Clim. Change, 12, 441–448, https://doi.org/10.1038/s41558-022-01329-1, 2022. a
Thakur, V.: Data for plots and analsysis, Zenodo [data set], https://doi.org/10.5281/zenodo.14008649, 2024. a
Thober, S., Cuntz, M., Kelbling, M., Kumar, R., Mai, J., and Samaniego, L.: The multiscale routing model mRM v1.0: simple river routing at resolutions from 1 to 50 km, Geosci. Model Dev., 12, 2501–2521, https://doi.org/10.5194/gmd-12-2501-2019, 2019. a
Thornthwaite, C. W.: An Approach toward a Rational Classification of Climate, Geograph. Rev., 38, 55, https://doi.org/10.2307/210739, 1948. a, b, c
Tucker, C. J., Pinzon, J. E., Brown, M. E., Slayback, D. A., Pak, E. W., Mahoney, R., Vermote, E. F., and El Saleous, N.: An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data, Int. J. Remote Sens., 26, 4485–4498, https://doi.org/10.1080/01431160500168686, 2005. a
Vicente-Serrano, S. M., Azorin-Molina, C., Sanchez-Lorenzo, A., Revuelto, J., López-Moreno, J. I., González-Hidalgo, J. C., Moran-Tejeda, E., and Espejo, F.: Reference evapotranspiration variability and trends in Spain, 1961–2011, Global Planet. Change, 121, 26–40, https://doi.org/10.1016/j.gloplacha.2014.06.005, 2014. a
World Meteorological Organization (WMO): State of Global Water Resources 2022, Tech. rep., Geneva, Switzerland, https://wmo.int/publication-series/state-of-global-water-resources-2022 (last access: 2 July 2025), 2023. a
Xiang, K., Li, Y., Horton, R., and Feng, H.: Similarity and difference of potential evapotranspiration and reference crop evapotranspiration – a review, Agr. Water Manage., 232, 106043, https://doi.org/10.1016/j.agwat.2020.106043, 2020. a
Xu, C.-Y. and Singh, V. P.: Evaluation and generalization of radiation-based methods for calculating evaporation, Hydrol. Process., 14, 339–349, https://doi.org/10.1002/(SICI)1099-1085(20000215)14:2<339::AID-HYP928>3.0.CO;2-O, 2000. 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, b
Yin, Z., Lin, P., Riggs, R., Allen, G. H., Lei, X., Zheng, Z., and Cai, S.: A synthesis of Global Streamflow Characteristics, Hydrometeorology, and Catchment Attributes (GSHA) for large sample river-centric studies, Earth Syst. Sci. Data, 16, 1559–1587, https://doi.org/10.5194/essd-16-1559-2024, 2024. a
Zhang, D., Liu, X., Zhang, Q., Liang, K., and Liu, C.: Investigation of factors affecting intra-annual variability of evapotranspiration and streamflow under different climate conditions, J. Hydrol., 543, 759–769, https://doi.org/10.1016/j.jhydrol.2016.10.047, 2016. a, b, c
Zhang, Y., He, B., Guo, L., Liu, J., and Xie, X.: The relative contributions of precipitation, evapotranspiration, and runoff to terrestrial water storage changes across 168 river basins, J. Hydrol., 579, 124194, https://doi.org/10.1016/j.jhydrol.2019.124194, 2019. a
Zhao, L., Xia, J., Xu, C.-y., Wang, Z., Sobkowiak, L., and Long, C.: Evapotranspiration estimation methods in hydrological models, J. Geograph. Sci., 23, 359–369, https://doi.org/10.1007/s11442-013-1015-9, 2013. a
Zhou, J., Li, Q., Ye, A., Xu, S., Yuan, Y., Xu, S., Zhang, D., Zhao, X., Zhu, Y., Zhao, Y., Xue, D., Dou, J., Liu, C., Shi, W., Wei, W., and Yang, X.: An improved methodology for quantifying the impact of human activities on hydrological drought change, J. Hydrol., 50, 101603, https://doi.org/10.1016/j.ejrh.2023.101603, 2023. a
Short summary
Understanding the changes in water movement in earth is crucial for everyone. To quantify this water movement there are several techniques. We examined how different methods of estimating evaporation impact predictions of various types of water movement across Europe. We found that, while these methods generally agree on whether changes are increasing or decreasing, they differ in magnitude. This means selecting the right evaporation method is crucial for accurate predictions of water movement.
Understanding the changes in water movement in earth is crucial for everyone. To quantify this...
