Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data
<p>Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2024-02-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | https://hess.copernicus.org/articles/28/1001/2024/hess-28-1001-2024.pdf |
| _version_ | 1797292690577031168 |
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| author | L. Strebel L. Strebel L. Strebel H. Bogena H. Bogena H. Vereecken H. Vereecken M. Andreasen S. Aranda-Barranco H.-J. Hendricks Franssen H.-J. Hendricks Franssen |
| author_facet | L. Strebel L. Strebel L. Strebel H. Bogena H. Bogena H. Vereecken H. Vereecken M. Andreasen S. Aranda-Barranco H.-J. Hendricks Franssen H.-J. Hendricks Franssen |
| author_sort | L. Strebel |
| collection | DOAJ |
| description | <p>Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSMs with observations, data assimilation methods and tools have been developed in the past decades. We apply the coupled Community Land Model version 5 (CLM5) and Parallel Data Assimilation Framework (PDAF) system (CLM5-PDAF) for 13 forest field sites throughout Europe covering different climate zones. The goal of this study is to assimilate in situ soil moisture measurements into CLM5 to improve the modeled evapotranspiration fluxes. The modeled fluxes will be evaluated using the predicted evapotranspiration fluxes with eddy covariance (EC) systems. Most of the sites use point-scale measurements from sensors placed in the ground; however, for three of the forest sites we use soil water content data from cosmic-ray neutron sensors, which have a measurement scale closer to the typical land surface model grid scale and EC footprint. Our results show that while data assimilation reduced the root-mean-square error for soil water content on average by 56 % to 64 %, the root-mean-square error for the evapotranspiration estimation is increased by 4 %. This finding indicates that only improving the soil water content (SWC) estimation of state-of-the-art LSMs such as CLM5 is not sufficient to improve evapotranspiration estimates for forest sites. To improve evapotranspiration estimates, it is also necessary to consider the representation of leaf area index (LAI) in magnitude and timing, as well as uncertainties in water uptake by roots and vegetation parameters.</p> |
| first_indexed | 2024-03-07T20:01:14Z |
| format | Article |
| id | doaj.art-7d69857bcedc426980b1017b452c52bb |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-03-07T20:01:14Z |
| publishDate | 2024-02-01 |
| publisher | Copernicus Publications |
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| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-7d69857bcedc426980b1017b452c52bb2024-02-28T08:12:25ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382024-02-01281001102610.5194/hess-28-1001-2024Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content dataL. Strebel0L. Strebel1L. Strebel2H. Bogena3H. Bogena4H. Vereecken5H. Vereecken6M. Andreasen7S. Aranda-Barranco8H.-J. Hendricks Franssen9H.-J. Hendricks Franssen10Institute of Bio- and Geosciences, Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, GermanyCentre for High-Performance Scientific Computing in Terrestrial Systems (HPSC TerrSys), Geoverbund ABC/J, Leo-Brandt-Strasse, 52425 Jülich, GermanyDepartment of Geosciences and Geography, RWTH Aachen University, Aachen, GermanyInstitute of Bio- and Geosciences, Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, GermanyCentre for High-Performance Scientific Computing in Terrestrial Systems (HPSC TerrSys), Geoverbund ABC/J, Leo-Brandt-Strasse, 52425 Jülich, GermanyInstitute of Bio- and Geosciences, Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, GermanyCentre for High-Performance Scientific Computing in Terrestrial Systems (HPSC TerrSys), Geoverbund ABC/J, Leo-Brandt-Strasse, 52425 Jülich, GermanyGeological Survey of Denmark and Greenland, Copenhagen, DenmarkDepartment of Ecology, University of Granada, Granada 18071, SpainInstitute of Bio- and Geosciences, Agrosphere (IBG-3), Research Centre Jülich, 52425 Jülich, GermanyCentre for High-Performance Scientific Computing in Terrestrial Systems (HPSC TerrSys), Geoverbund ABC/J, Leo-Brandt-Strasse, 52425 Jülich, Germany<p>Land surface models (LSMs) are an important tool for advancing our knowledge of the Earth system. LSMs are constantly improved to represent the various terrestrial processes in more detail. High-quality data, freely available from various observation networks, are being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSMs with observations, data assimilation methods and tools have been developed in the past decades. We apply the coupled Community Land Model version 5 (CLM5) and Parallel Data Assimilation Framework (PDAF) system (CLM5-PDAF) for 13 forest field sites throughout Europe covering different climate zones. The goal of this study is to assimilate in situ soil moisture measurements into CLM5 to improve the modeled evapotranspiration fluxes. The modeled fluxes will be evaluated using the predicted evapotranspiration fluxes with eddy covariance (EC) systems. Most of the sites use point-scale measurements from sensors placed in the ground; however, for three of the forest sites we use soil water content data from cosmic-ray neutron sensors, which have a measurement scale closer to the typical land surface model grid scale and EC footprint. Our results show that while data assimilation reduced the root-mean-square error for soil water content on average by 56 % to 64 %, the root-mean-square error for the evapotranspiration estimation is increased by 4 %. This finding indicates that only improving the soil water content (SWC) estimation of state-of-the-art LSMs such as CLM5 is not sufficient to improve evapotranspiration estimates for forest sites. To improve evapotranspiration estimates, it is also necessary to consider the representation of leaf area index (LAI) in magnitude and timing, as well as uncertainties in water uptake by roots and vegetation parameters.</p>https://hess.copernicus.org/articles/28/1001/2024/hess-28-1001-2024.pdf |
| spellingShingle | L. Strebel L. Strebel L. Strebel H. Bogena H. Bogena H. Vereecken H. Vereecken M. Andreasen S. Aranda-Barranco H.-J. Hendricks Franssen H.-J. Hendricks Franssen Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data Hydrology and Earth System Sciences |
| title | Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data |
| title_full | Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data |
| title_fullStr | Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data |
| title_full_unstemmed | Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data |
| title_short | Evapotranspiration prediction for European forest sites does not improve with assimilation of in situ soil water content data |
| title_sort | evapotranspiration prediction for european forest sites does not improve with assimilation of in situ soil water content data |
| url | https://hess.copernicus.org/articles/28/1001/2024/hess-28-1001-2024.pdf |
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