Preprints
https://doi.org/10.5194/egusphere-2023-366
https://doi.org/10.5194/egusphere-2023-366
13 Mar 2023
 | 13 Mar 2023
Status: this preprint is open for discussion.

Evapotranspiration prediction for European forest sites does not improve with assimilation of in-situ soil water content data

Lukas Strebel, Heye Bogena, Harry Vereecken, Mie Andreasen, Sergio Aranda, and Harrie-Jan Hendricks Franssen

Abstract. Land surface models (LSM) are an important tool for advancing our knowledge of the Earth system. LSM are constantly improved to represent the various terrestrial processes in more detail. High quality data, freely available from various observation networks, are providing being used to improve the prediction of terrestrial states and fluxes of water and energy. To optimize LSM 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 thirteen 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, 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 state-of-the-art LSM such as CLM5 still suffer from uncertainties in the representation of soil hydrological processes in forests, e.g. deep root water uptake, or highly uncertain vegetation parameters.

Lukas Strebel et al.

Status: open (until 08 May 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Lukas Strebel et al.

Lukas Strebel et al.

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Short summary
We present the results from using soil water content measurements from 13 European forest sites in a state-of-the-art land surface model. We use data assimilation to perform the combination of observation and modeled soil water content and show the improvements in the representation of soil water content. However, we also look at the impact on evapotranspiration and see no corresponding improvements.