Articles | Volume 27, issue 14
https://doi.org/10.5194/hess-27-2827-2023
https://doi.org/10.5194/hess-27-2827-2023
Research article
 | 
31 Jul 2023
Research article |  | 31 Jul 2023

Point-scale multi-objective calibration of the Community Land Model (version 5.0) using in situ observations of water and energy fluxes and variables

Tanja Denager, Torben O. Sonnenborg, Majken C. Looms, Heye Bogena, and Karsten H. Jensen

Related authors

HESS Opinions: Towards a common vision for the future of hydrological observatories
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
EGUsphere, https://doi.org/10.5194/egusphere-2024-1678,https://doi.org/10.5194/egusphere-2024-1678, 2024
Short summary
Lack of robustness of hydrological models: A large-sample diagnosis and an attempt to identify the hydrological and climatic drivers
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80,https://doi.org/10.5194/hess-2024-80, 2024
Preprint under review for HESS
Short summary
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-Barranco, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 28, 1001–1026, https://doi.org/10.5194/hess-28-1001-2024,https://doi.org/10.5194/hess-28-1001-2024, 2024
Short summary
Incorporating interpretation uncertainties from deterministic 3D hydrostratigraphic models in groundwater models
Trine Enemark, Rasmus Bødker Madsen, Torben O. Sonnenborg, Lærke Therese Andersen, Peter B. E. Sandersen, Jacob Kidmose, Ingelise Møller, Thomas Mejer Hansen, Karsten Høgh Jensen, and Anne-Sophie Høyer
Hydrol. Earth Syst. Sci., 28, 505–523, https://doi.org/10.5194/hess-28-505-2024,https://doi.org/10.5194/hess-28-505-2024, 2024
Short summary
Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023,https://doi.org/10.5194/hess-27-3143-2023, 2023
Short summary

Related subject area

Subject: Global hydrology | Techniques and Approaches: Modelling approaches
Influence of irrigation on root zone storage capacity estimation
Fransje van Oorschot, Ruud J. van der Ent, Andrea Alessandri, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 2313–2328, https://doi.org/10.5194/hess-28-2313-2024,https://doi.org/10.5194/hess-28-2313-2024, 2024
Short summary
River flow in the near future: a global perspective in the context of a high-emission climate change scenario
Omar V. Müller, Patrick C. McGuire, Pier Luigi Vidale, and Ed Hawkins
Hydrol. Earth Syst. Sci., 28, 2179–2201, https://doi.org/10.5194/hess-28-2179-2024,https://doi.org/10.5194/hess-28-2179-2024, 2024
Short summary
A high-resolution perspective of extreme rainfall and river flow under extreme climate change in Southeast Asia
Mugni Hadi Hariadi, Gerard van der Schrier, Gert-Jan Steeneveld, Samuel J. Sutanto, Edwin Sutanudjaja, Dian Nur Ratri, Ardhasena Sopaheluwakan, and Albert Klein Tank
Hydrol. Earth Syst. Sci., 28, 1935–1956, https://doi.org/10.5194/hess-28-1935-2024,https://doi.org/10.5194/hess-28-1935-2024, 2024
Short summary
Unveiling hydrological dynamics in data-scarce regions: experiences from the Ethiopian Rift Valley Lakes Basin
Ayenew D. Ayalew, Paul D. Wagner, Dejene Sahlu, and Nicola Fohrer
Hydrol. Earth Syst. Sci., 28, 1853–1872, https://doi.org/10.5194/hess-28-1853-2024,https://doi.org/10.5194/hess-28-1853-2024, 2024
Short summary
Technical note: Comparing three different methods for allocating river points to coarse-resolution hydrological modelling grid cells
Juliette Godet, Eric Gaume, Pierre Javelle, Pierre Nicolle, and Olivier Payrastre
Hydrol. Earth Syst. Sci., 28, 1403–1413, https://doi.org/10.5194/hess-28-1403-2024,https://doi.org/10.5194/hess-28-1403-2024, 2024
Short summary

Cited articles

Andreasen, M., Jensen, K. H., Bogena, H., Desilets, D., Zreda, M., and Looms, M. C.: Cosmic Ray Neutron Soil Moisture Estimation Using Physically Based Site-Specific Conversion Functions, Water Resour. Res., 56, 1–20, https://doi.org/10.1029/2019WR026588, 2020. 
Boas, T., Bogena, H., Grünwald, T., Heinesch, B., Ryu, D., Schmidt, M., Vereecken, H., Western, A., and Franssen, H. J. H.: Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0, Geosci. Model Dev., 14, 573–601, https://doi.org/10.5194/gmd-14-573-2021, 2021. 
Bogena, H. R., Montzka, C., Huisman, J. A., Graf, A., Schmidt, M., Stockinger, M., von Hebel, C., Hendricks-Franssen, H. J., van der Kruk, J., Tappe, W., Lücke, A., Baatz, R., Bol, R., Groh, J., Pütz, T., Jakobi, J., Kunkel, R., Sorg, J., and Vereecken, H.: The TERENO-Rur Hydrological Observatory: A Multiscale Multi-Compartment Research Platform for the Advancement of Hydrological Science, Vadose Zone J., 17, 1–22, https://doi.org/10.2136/vzj2018.03.0055, 2018. 
Carrillo-Rojas, G., Schulz, H. M., Orellana-Alvear, J., Ochoa-Sánchez, A., Trachte, K., Célleri, R., and Bendix, J.: Atmosphere-surface fluxes modeling for the high Andes: The case of páramo catchments of Ecuador, Sci. Total Environ., 704, 135372, https://doi.org/10.1016/j.scitotenv.2019.135372, 2020. 
Download
Short summary
This study contributes to improvements in the model characterization of water and energy fluxes. The results show that multi-objective autocalibration in combination with mathematical regularization is a powerful tool to improve land surface models. Using the direct measurement of turbulent fluxes as the target variable, parameter optimization matches simulations and observations of latent heat, whereas sensible heat is clearly biased.