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Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS
Characterization of model errors is important when applying satellite-driven evapotranspiration (ET) models to water resource management problems. This study examines how uncertainty in meteorological forcing data and land surface modeling propagate through to errors in final ET data calculated usin...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509309/ https://www.ncbi.nlm.nih.gov/pubmed/36172251 http://dx.doi.org/10.1007/s00271-022-00808-9 |
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author | Doherty, Conor T. Johnson, Lee F. Volk, John Mauter, Meagan S. Bambach, Nicolas McElrone, Andrew J. Alfieri, Joseph G. Hipps, Lawrence E. Prueger, John H. Castro, Sebastian J. Alsina, Maria Mar Kustas, William P. Melton, Forrest S. |
author_facet | Doherty, Conor T. Johnson, Lee F. Volk, John Mauter, Meagan S. Bambach, Nicolas McElrone, Andrew J. Alfieri, Joseph G. Hipps, Lawrence E. Prueger, John H. Castro, Sebastian J. Alsina, Maria Mar Kustas, William P. Melton, Forrest S. |
author_sort | Doherty, Conor T. |
collection | PubMed |
description | Characterization of model errors is important when applying satellite-driven evapotranspiration (ET) models to water resource management problems. This study examines how uncertainty in meteorological forcing data and land surface modeling propagate through to errors in final ET data calculated using the Satellite Irrigation Management Support (SIMS) model, a computationally efficient ET model driven with satellite surface reflectance values. The model is applied to three instrumented winegrape vineyards over the 2017–2020 time period and the spatial and temporal variation in errors are analyzed. We illustrate how meteorological data inputs can introduce biases that vary in space and at seasonal timescales, but that can persist from year to year. We also observe that errors in SIMS estimates of land surface conductance can have a particularly strong dependence on time of year. Overall, meteorological inputs introduced RMSE of 0.33–0.65 mm/day (7–27%) across sites, while SIMS introduced RMSE of 0.55–0.83 mm/day (19–24%). The relative error contribution from meteorological inputs versus SIMS varied across sites; errors from SIMS were larger at one site, errors from meteorological inputs were larger at a second site, and the error contributions were of equal magnitude at the third site. The similar magnitude of error contributions is significant given that many satellite-driven ET models differ in their approaches to estimating land surface conductance, but often rely on similar or identical meteorological forcing data. The finding is particularly notable given that SIMS makes assumptions about the land surface (no soil evaporation or plant water stress) that do not always hold in practice. The results of this study show that improving SIMS by eliminating these assumptions would result in meteorological inputs dominating the error budget of the model on the whole. This finding underscores the need for further work on characterizing spatial uncertainty in the meteorological forcing of ET. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00271-022-00808-9. |
format | Online Article Text |
id | pubmed-9509309 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-95093092022-09-26 Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS Doherty, Conor T. Johnson, Lee F. Volk, John Mauter, Meagan S. Bambach, Nicolas McElrone, Andrew J. Alfieri, Joseph G. Hipps, Lawrence E. Prueger, John H. Castro, Sebastian J. Alsina, Maria Mar Kustas, William P. Melton, Forrest S. Irrig Sci Original Paper Characterization of model errors is important when applying satellite-driven evapotranspiration (ET) models to water resource management problems. This study examines how uncertainty in meteorological forcing data and land surface modeling propagate through to errors in final ET data calculated using the Satellite Irrigation Management Support (SIMS) model, a computationally efficient ET model driven with satellite surface reflectance values. The model is applied to three instrumented winegrape vineyards over the 2017–2020 time period and the spatial and temporal variation in errors are analyzed. We illustrate how meteorological data inputs can introduce biases that vary in space and at seasonal timescales, but that can persist from year to year. We also observe that errors in SIMS estimates of land surface conductance can have a particularly strong dependence on time of year. Overall, meteorological inputs introduced RMSE of 0.33–0.65 mm/day (7–27%) across sites, while SIMS introduced RMSE of 0.55–0.83 mm/day (19–24%). The relative error contribution from meteorological inputs versus SIMS varied across sites; errors from SIMS were larger at one site, errors from meteorological inputs were larger at a second site, and the error contributions were of equal magnitude at the third site. The similar magnitude of error contributions is significant given that many satellite-driven ET models differ in their approaches to estimating land surface conductance, but often rely on similar or identical meteorological forcing data. The finding is particularly notable given that SIMS makes assumptions about the land surface (no soil evaporation or plant water stress) that do not always hold in practice. The results of this study show that improving SIMS by eliminating these assumptions would result in meteorological inputs dominating the error budget of the model on the whole. This finding underscores the need for further work on characterizing spatial uncertainty in the meteorological forcing of ET. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00271-022-00808-9. Springer Berlin Heidelberg 2022-08-13 2022 /pmc/articles/PMC9509309/ /pubmed/36172251 http://dx.doi.org/10.1007/s00271-022-00808-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper Doherty, Conor T. Johnson, Lee F. Volk, John Mauter, Meagan S. Bambach, Nicolas McElrone, Andrew J. Alfieri, Joseph G. Hipps, Lawrence E. Prueger, John H. Castro, Sebastian J. Alsina, Maria Mar Kustas, William P. Melton, Forrest S. Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS |
title | Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS |
title_full | Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS |
title_fullStr | Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS |
title_full_unstemmed | Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS |
title_short | Effects of meteorological and land surface modeling uncertainty on errors in winegrape ET calculated with SIMS |
title_sort | effects of meteorological and land surface modeling uncertainty on errors in winegrape et calculated with sims |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509309/ https://www.ncbi.nlm.nih.gov/pubmed/36172251 http://dx.doi.org/10.1007/s00271-022-00808-9 |
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