Submitted as: model description paper
15 Apr 2024
Submitted as: model description paper |  | 15 Apr 2024
Status: this preprint is currently under review for the journal GMD.

PyEt v1.3.1: a Python package for the estimation of potential evapotranspiration

Matevž Vremec, Raoul Collenteur, and Steffen Birk

Abstract. Evapotranspiration (ET) is a crucial flux of the hydrological water balance, commonly estimated using (semi-)empirical formulas. The estimated flux may strongly depend on the formula used, adding uncertainty to the outcomes of environmental studies using ET. Climate change may cause additional uncertainty, as the ET estimated by each formula may respond differently to changes in meteorological input data. To include the effects of model uncertainty and climate change, and facilitate the use of these formulas in a consistent, tested, and reproducible workflow, we present PyEt. PyEt is an open-source Python package for the estimation of daily potential evapotranspiration (PET) using available meteorological data. It allows the application of twenty different PET methods on both time series and gridded datasets. The majority of the implemented methods are benchmarked against literature values and tested with continuous integration to ensure the correctness of the implementation. This article provides an overview of PyEt’s capabilities, including the estimation of PET with twenty PET methods for station, and gridded data, a simple procedure for calibrating the empirical coefficients in the alternative PET methods, and estimation of PET under warming and elevated atmospheric CO2 concentration. Further discussion on the advantages of using PyEt estimates as input for hydrological models, sensitivity/uncertainty analyses, and hind/forecasting studies, especially in data-scarce regions, is provided.

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Matevž Vremec, Raoul Collenteur, and Steffen Birk

Status: open (until 10 Jun 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2024-63', Anonymous Referee #1, 13 May 2024 reply
  • RC2: 'Comment on gmd-2024-63', Anonymous Referee #2, 18 May 2024 reply
Matevž Vremec, Raoul Collenteur, and Steffen Birk
Matevž Vremec, Raoul Collenteur, and Steffen Birk


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Short summary
Geoscientists commonly use various Potential EvapoTranpiration (PET) formulas for environmental studies, which can be prone to errors and sensitive to climate change. PyEt, a tested and open-source Python package, simplifies the application of 20 PET methods for both time series and gridded data, ensuring accurate and consistent PET estimations suitable for a wide range of environmental applications.