Articles | Volume 26, issue 8
https://doi.org/10.5194/hess-26-2147-2022
© 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-26-2147-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Unraveling the contribution of potential evaporation formulation to uncertainty under climate change
Thibault Lemaitre-Basset
CORRESPONDING AUTHOR
CNRS, EPHE, UMR 7619 METIS, Sorbonne Université, Case 105, 4 place Jussieu, 75005 Paris, France
Université Paris-Saclay, INRAE, HYCAR Research Unit, Antony, France
Ludovic Oudin
CNRS, EPHE, UMR 7619 METIS, Sorbonne Université, Case 105, 4 place Jussieu, 75005 Paris, France
Guillaume Thirel
Université Paris-Saclay, INRAE, HYCAR Research Unit, Antony, France
Lila Collet
Université Paris-Saclay, INRAE, HYCAR Research Unit, Antony, France
now at: OSIRIS Department, EDF Research and Development Division, EDF Lab Paris-Saclay, Palaiseau, France
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Cited
14 citations as recorded by crossref.
- Brazilian Water Security Threatened by Climate Change and Human Behavior A. Ballarin et al. 10.1029/2023WR034914
- PyEt v1.3.1: a Python package for the estimation of potential evapotranspiration M. Vremec et al. 10.5194/gmd-17-7083-2024
- Modeling present and future flows in a tailings pile at the former Le Cellier uranium mine (France) P. L’Hermite et al. 10.1016/j.ejrh.2024.101984
- Analyzing the uncertainty of potential evapotranspiration models in drought projections derived for a semi-arid watershed U. Okkan et al. 10.1007/s00704-023-04817-2
- Hydraulic Issues Concerning Injection of Harvested Rainwater to the Subsurface Through Drywells: Insight From Numerical Simulations of Flow in a Realistic Combined Vadose Zone‐Groundwater Flow System D. Russo et al. 10.1029/2021WR031881
- CMIP6 multi-model ensemble projection of reference evapotranspiration using machine learning algorithms M. Nouri & S. Veysi 10.1016/j.agwat.2024.109190
- Which Potential Evapotranspiration Formula to Use in Hydrological Modeling World‐Wide? R. Pimentel et al. 10.1029/2022WR033447
- Influence of age, soil volume, and climate change on water availability at urban tree sites L. Rosenberger et al. 10.1016/j.scs.2024.105680
- Effects of Climate Change on Hydrological Indicators of Subsurface Drainage for a Representative French Drainage Site A. Jeantet et al. 10.3389/fenvs.2022.899226
- Uncertainty propagation in a modelling chain of climate change impact for a representative French drainage site A. Jeantet et al. 10.1080/02626667.2023.2203322
- On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration S. Wi & S. Steinschneider 10.5194/hess-28-479-2024
- Hydro-PE: gridded datasets of historical and future Penman–Monteith potential evaporation for the United Kingdom E. Robinson et al. 10.5194/essd-15-4433-2023
- Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning R. Nawaz Bashir et al. 10.32604/iasc.2023.030844
- Evapotranspiration in hydrological models under rising CO2: a jump into the unknown T. Lemaitre-Basset et al. 10.1007/s10584-022-03384-1
13 citations as recorded by crossref.
- Brazilian Water Security Threatened by Climate Change and Human Behavior A. Ballarin et al. 10.1029/2023WR034914
- PyEt v1.3.1: a Python package for the estimation of potential evapotranspiration M. Vremec et al. 10.5194/gmd-17-7083-2024
- Modeling present and future flows in a tailings pile at the former Le Cellier uranium mine (France) P. L’Hermite et al. 10.1016/j.ejrh.2024.101984
- Analyzing the uncertainty of potential evapotranspiration models in drought projections derived for a semi-arid watershed U. Okkan et al. 10.1007/s00704-023-04817-2
- Hydraulic Issues Concerning Injection of Harvested Rainwater to the Subsurface Through Drywells: Insight From Numerical Simulations of Flow in a Realistic Combined Vadose Zone‐Groundwater Flow System D. Russo et al. 10.1029/2021WR031881
- CMIP6 multi-model ensemble projection of reference evapotranspiration using machine learning algorithms M. Nouri & S. Veysi 10.1016/j.agwat.2024.109190
- Which Potential Evapotranspiration Formula to Use in Hydrological Modeling World‐Wide? R. Pimentel et al. 10.1029/2022WR033447
- Influence of age, soil volume, and climate change on water availability at urban tree sites L. Rosenberger et al. 10.1016/j.scs.2024.105680
- Effects of Climate Change on Hydrological Indicators of Subsurface Drainage for a Representative French Drainage Site A. Jeantet et al. 10.3389/fenvs.2022.899226
- Uncertainty propagation in a modelling chain of climate change impact for a representative French drainage site A. Jeantet et al. 10.1080/02626667.2023.2203322
- On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration S. Wi & S. Steinschneider 10.5194/hess-28-479-2024
- Hydro-PE: gridded datasets of historical and future Penman–Monteith potential evaporation for the United Kingdom E. Robinson et al. 10.5194/essd-15-4433-2023
- Leaching Fraction (LF) of Irrigation Water for Saline Soils Using Machine Learning R. Nawaz Bashir et al. 10.32604/iasc.2023.030844
1 citations as recorded by crossref.
Latest update: 13 Dec 2024
Short summary
Increasing temperature will impact evaporation and water resource management. Hydrological models are fed with an estimation of the evaporative demand of the atmosphere, called potential evapotranspiration (PE). The objectives of this study were (1) to compute the future PE anomaly over France and (2) to determine the impact of the choice of the method to estimate PE. Our results show that all methods present similar future trends. No method really stands out from the others.
Increasing temperature will impact evaporation and water resource management. Hydrological...