the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 09 Jan 2023
Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt
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 used formula, adding uncertainty to the outcomes of hydrological models using ET. Climate change may cause additional uncertainty as 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 (Pandas) and gridded datasets (xarray). Most 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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RC1: 'Comment on hess-2022-417', Anonymous Referee #1, 27 Feb 2023
Summary
In this study, entitled ‘Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt’ , the authors present a new python-based software to calculate potential evaporation using a variety of semi-empirical equations. The paper is well-written and the package, in my opinion, is a useful addition to the variety of tools available for calculating hydrologic fluxes. I only have a few comments which can be addressed relatively easily.
Comments
- A major issue I have is the suitability of HESS for this study. To me the study is the presentation of a software package and does not present ‘new developments, significant advances, and novel aspects of experimental and theoretical methods and technique…’ as required of a ‘technical note’. It reads more like a GMD paper rather than a HESS paper.
- The name PyEt is misleading as the python package calculates potential evaporation rather than evaporation.
- The manuscript is missing details of compute times. I think this information is vital for any software package. How fast is the computation for gridded datasets? It would also be useful to have information about how efficient the software is regarding memory usage. I guess the use of xarray allows lazy loading and thus alleviates large memory usage.
- Potential evaporation is not just used in hydrologic studies but in several ecological and climate-impact related studies. Therefore, the title does not completely do justice to potential use cases of the package.
- Line 65–70: ‘hydrologists’ is misspelled.
- Line 2015: ‘regions’ should be ‘region’.
Citation: https://doi.org/10.5194/hess-2022-417-RC1 - AC1: 'Reply on RC1', Matevž Vremec, 03 Apr 2023
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RC2: 'Comment on hess-2022-417', Anonymous Referee #2, 27 Feb 2023
The authors present a Python package that could help the community to implement evaporation equations. The package can easily compare differences between methods, intercalibrate models, and assess the effect of climate change by temperature and CO2. The package is open-source and is available in the now commonly used Python language. The manuscript is submitted as Technical note in HESSD. After checking the HESSD guidelines:"Technical notes report new developments, significant advances, and novel aspects of experimental and theoretical methods and techniques which are relevant for scientific investigations within the journal scope. Manuscripts of this type should be short (a few pages only). Highly detailed and specific technical information such as computer programme code or user manuals can be included as electronic supplements. The manuscript title must start with "Technical note:". For manuscripts focused on the development and description of numerical models and model components, we recommend submission to the EGU interactive open-access journal Geoscientific Model Development (GMD).", I would advice to move this manuscript to GMD.
Additionally, and more importantly, I doubt the advancement in science by this study. As said in Line 50, there already exist a similar package in R. So what is the added values of this work? Recoding from R to Python? I do realize that PyEt has some nice extra features, but in my view this is too little for a publication.
Furthermore, I do see some risks in this package. Of course, it the responsibility of modeller to select the right equation, and not of the developer; however, the current package seems not to have any disclaimers on the use and validity of certain models. At least, as how it is presented in the paper, the authors present the equations as interchangeable which is not correct. How can the user see that 'penman' and 'pm' are meant for different surfaces (open water, vegetated surface respectively)? How does the user know that Makkink is developed for Dutch landscapes (the factor 0,65 is a 'calibration' parameter)? I am rather sure other methods also have their limitations (e.g., local calibtation, model assumption, time scale). This is especially worrisome if I see Figure 3 where spatial patterns of PET are presented. I think PyEt should at least try to warn user for using proper formula's.
Moreover, I also wonder how the package deals with the different inputs. Solar radiation is rather easy to obtain, but how does the package deal with e.g., Penman (-Monteith)/FAO that requires net radation minus ground heat flux?
Hence, to conclude: I appreciate the effords of the authors to make the implementation of ET-models easier. I would have loved to have this package before, as I can't count the times how often I programmed certain formula's. However, I think the advancement in science it too little to merit publication in HESS.
Minor comments:
- L21: it's funny that you prefer to use the term Evapotranspiration and cite in the same sentence the work of Miralles et al, 2020 where it is claimed that evaporation is the right term. Hence, I would advocate for call it 'potential evaporation'.
- Eq 2: ln should not be in italic
- Eq 1&2: are these input parameter (LAI, CO2, zm, zom, d, zoh, etc) all fixed in the package and used for all equation?
- Example 4: this example is a nice add-on, but it's just on method of assessing the effect of climate change. So to me, it seems a bit a random choice (but not necessarily wrong btw).
Citation: https://doi.org/10.5194/hess-2022-417-RC2 - AC2: 'Reply on RC2', Matevž Vremec, 03 Apr 2023
Status: closed
-
RC1: 'Comment on hess-2022-417', Anonymous Referee #1, 27 Feb 2023
Summary
In this study, entitled ‘Technical note: Improved handling of potential evapotranspiration in hydrological studies with PyEt’ , the authors present a new python-based software to calculate potential evaporation using a variety of semi-empirical equations. The paper is well-written and the package, in my opinion, is a useful addition to the variety of tools available for calculating hydrologic fluxes. I only have a few comments which can be addressed relatively easily.
Comments
- A major issue I have is the suitability of HESS for this study. To me the study is the presentation of a software package and does not present ‘new developments, significant advances, and novel aspects of experimental and theoretical methods and technique…’ as required of a ‘technical note’. It reads more like a GMD paper rather than a HESS paper.
- The name PyEt is misleading as the python package calculates potential evaporation rather than evaporation.
- The manuscript is missing details of compute times. I think this information is vital for any software package. How fast is the computation for gridded datasets? It would also be useful to have information about how efficient the software is regarding memory usage. I guess the use of xarray allows lazy loading and thus alleviates large memory usage.
- Potential evaporation is not just used in hydrologic studies but in several ecological and climate-impact related studies. Therefore, the title does not completely do justice to potential use cases of the package.
- Line 65–70: ‘hydrologists’ is misspelled.
- Line 2015: ‘regions’ should be ‘region’.
Citation: https://doi.org/10.5194/hess-2022-417-RC1 - AC1: 'Reply on RC1', Matevž Vremec, 03 Apr 2023
-
RC2: 'Comment on hess-2022-417', Anonymous Referee #2, 27 Feb 2023
The authors present a Python package that could help the community to implement evaporation equations. The package can easily compare differences between methods, intercalibrate models, and assess the effect of climate change by temperature and CO2. The package is open-source and is available in the now commonly used Python language. The manuscript is submitted as Technical note in HESSD. After checking the HESSD guidelines:"Technical notes report new developments, significant advances, and novel aspects of experimental and theoretical methods and techniques which are relevant for scientific investigations within the journal scope. Manuscripts of this type should be short (a few pages only). Highly detailed and specific technical information such as computer programme code or user manuals can be included as electronic supplements. The manuscript title must start with "Technical note:". For manuscripts focused on the development and description of numerical models and model components, we recommend submission to the EGU interactive open-access journal Geoscientific Model Development (GMD).", I would advice to move this manuscript to GMD.
Additionally, and more importantly, I doubt the advancement in science by this study. As said in Line 50, there already exist a similar package in R. So what is the added values of this work? Recoding from R to Python? I do realize that PyEt has some nice extra features, but in my view this is too little for a publication.
Furthermore, I do see some risks in this package. Of course, it the responsibility of modeller to select the right equation, and not of the developer; however, the current package seems not to have any disclaimers on the use and validity of certain models. At least, as how it is presented in the paper, the authors present the equations as interchangeable which is not correct. How can the user see that 'penman' and 'pm' are meant for different surfaces (open water, vegetated surface respectively)? How does the user know that Makkink is developed for Dutch landscapes (the factor 0,65 is a 'calibration' parameter)? I am rather sure other methods also have their limitations (e.g., local calibtation, model assumption, time scale). This is especially worrisome if I see Figure 3 where spatial patterns of PET are presented. I think PyEt should at least try to warn user for using proper formula's.
Moreover, I also wonder how the package deals with the different inputs. Solar radiation is rather easy to obtain, but how does the package deal with e.g., Penman (-Monteith)/FAO that requires net radation minus ground heat flux?
Hence, to conclude: I appreciate the effords of the authors to make the implementation of ET-models easier. I would have loved to have this package before, as I can't count the times how often I programmed certain formula's. However, I think the advancement in science it too little to merit publication in HESS.
Minor comments:
- L21: it's funny that you prefer to use the term Evapotranspiration and cite in the same sentence the work of Miralles et al, 2020 where it is claimed that evaporation is the right term. Hence, I would advocate for call it 'potential evaporation'.
- Eq 2: ln should not be in italic
- Eq 1&2: are these input parameter (LAI, CO2, zm, zom, d, zoh, etc) all fixed in the package and used for all equation?
- Example 4: this example is a nice add-on, but it's just on method of assessing the effect of climate change. So to me, it seems a bit a random choice (but not necessarily wrong btw).
Citation: https://doi.org/10.5194/hess-2022-417-RC2 - AC2: 'Reply on RC2', Matevž Vremec, 03 Apr 2023
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Cited
2 citations as recorded by crossref.
- PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia R. Aguayo et al. 10.1038/s41597-023-02828-2
- Spatiotemporal analysis of tropical vegetation ecosystems and their responses to multifaceted droughts in Mainland Southeast Asia using satellite-based time series T. Ha et al. 10.1080/15481603.2024.2387385