Articles | Volume 27, issue 16
https://doi.org/10.5194/hess-27-3143-2023
https://doi.org/10.5194/hess-27-3143-2023
Research article
 | 
29 Aug 2023
Research article |  | 29 Aug 2023

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

Related authors

Online xylem water isotope monitoring and soil water content profiling reveal spatial root water uptake dynamics in sunflower
Youri Rothfuss, Samuel Le Gall, Nicolas Brüggemann, Sharmin Jahan, Mathieu Javaux, Julian Klaus, Harry Vereecken, and Dagmar van Dusschoten
Hydrol. Earth Syst. Sci., 30, 6095–6114, https://doi.org/10.5194/hess-30-6095-2026,https://doi.org/10.5194/hess-30-6095-2026, 2026
Short summary
A long-term multiscale Critical Zone dataset integrating environmental monitoring and an open-air laboratory: The Alento River Catchment Observatory
Nunzio Romano, Harry Vereecken, Heye R. Bogena, Giorgio Cassiani, Matteo Censini, Giovanna Armiento, Marco Proposito, Lorenzo De Silvestri, Eyal Ben Dor, Nicolas Francos, Christian Massari, János Mészáros, Tünde Takáts, Caterina Mazzitelli, Benedetto Sica, Ugo Lazzaro, and Paolo Nasta
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-725,https://doi.org/10.5194/essd-2026-725, 2026
Preprint under review for ESSD
Short summary
Wheat biomass estimation across crop development using UAV LiDAR structure–intensity fusion alongside multispectral and thermal data
Jordan Steven Bates, Carsten Montzka, Rajina Bajracharya, Harry Vereecken, and François Jonard
Biogeosciences, 23, 6179–6210, https://doi.org/10.5194/bg-23-6179-2026,https://doi.org/10.5194/bg-23-6179-2026, 2026
Short summary
Retrieving root-zone soil moisture from land surface modelling and GRACE/-FO and validating its dynamics with in-situ data over West Africa
Loudi Yap, Jürgen Kusche, Bamidele Oloruntoba, Helena Gerdener, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 30, 5023–5047, https://doi.org/10.5194/hess-30-5023-2026,https://doi.org/10.5194/hess-30-5023-2026, 2026
Short summary
From Sensors to Irrigation Decisions: An Automated Data–Model Pipeline for Real-Time Soil Moisture Forecasting in Agriculture
Haojin Zhao, Richard Hoffmann, Heye Bogena, Cosimo Brogi, Alexandre Belleflamme, Klaus Görgen, Johannes Keller, Lukas Strebel, and Harrie-Jan Hendricks Franssen
EGUsphere, https://doi.org/10.5194/egusphere-2026-4630,https://doi.org/10.5194/egusphere-2026-4630, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary

Cited articles

ABARES – Australian Bureau of Agricultural and Resource Economics and Sciences: Australian Crop Report, February 2021, Canberra, https://doi.org/10.25814/xqy3-sx57, 2020. 
Ash, A., McIntosh, P., Cullen, B., Carberry, P., and Smith, M. S.: Constraints and opportunities in applying seasonal climate forecasts in agriculture, Aust. J. Agric. Res., 58, 952–965, https://doi.org/10.1071/AR06188, 2007. 
Baatz, R., Hendricks Franssen, H.-J., Han, X., Hoar, T., Bogena, H. R., and Vereecken, H.: Evaluation of a cosmic-ray neutron sensor network for improved land surface model prediction, Hydrol. Earth Syst. Sci., 21, 2509–2530, https://doi.org/10.5194/hess-21-2509-2017, 2017. 
Bauer, P., Thorpe, A., and Brunet, G.: The quiet revolution of numerical weather prediction, Nature, 525, 47–55, https://doi.org/10.1038/nature14956, 2015. 
Bennett, A., Hamman, J., and Nijssen, B.: MetSim: A Python package for estimation and disaggregation of meteorological data, J. Open Source Softw., 5, 2042, https://doi.org/10.21105/joss.02042, 2020. 
Download
Short summary
In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Share