Gaps and strategies for accurate simulation of waterlogging impacts on crop productivity

Margarita Garcia-Vila¹, Murilo Dos Santos Vianna^{2

3}, Matthew Tom Harrison⁴, Ke Liu^{4

5}, Rogério de S Nóia-Júnior⁶, Tobias K D Weber⁷, Jin Zhao⁸, Marco Acutis⁹, Sotirios Archontoulis¹⁰, Senthold Asseng¹¹, Pierre Aubry¹², Juraj Balkovic¹³, Bruno Basso¹⁴, Xianguan Chen¹⁵, Yi Chen¹⁶, Quirijn de Jong van Lier¹⁷, Mathieu Delandmeter¹², Allard de Wit¹⁸, Benjamin Dumont¹², Roberto Ferrise¹⁹, Christian Folberth¹³, Mara Gabbrielli⁹, Thomas Gaiser³, Aram Gorooei³, Gerrit Hoogenboom²⁰, Kurt Christian Kersebaum^{21

22}, Yean-Uk Kim²¹, David Kraus²³, Bing Liu²⁴, Lioba Martin²³, Klaas Metselaar¹⁸, Claas Nendel^{21

22

25}, Gloria Padovan¹⁹, Alessia Perego⁹, Diana Maria Seserman²¹, Clemens Scheer²³, Vakhtang Shelia²⁰, Valentina Stocca¹¹, Fulu Tao¹⁶, Enli Wang²⁶, Heidi Webber²¹, Zhigan Zhao²⁶, Yan Zhu²⁴, Taru Palosuo²⁷

Affiliations

¹ Instituto de Agricultura Sostenible, CSIC, Córdoba, Spain. mgarcia-vila@ias.csic.es.
² Institute of Bio- and Geosciences, Agrosphere (IBG-3), Forschungszentrum Jülich GmbH, Jülich, Germany.
³ University of Bonn, Bonn, Germany.
⁴ Tasmanian Institute of Agriculture, University of Tasmania, Launceston, Tasmania, Australia.
⁵ Yangtze University, Jingzhou, China.
⁶ LEPSE, Université de Montpellier, INRAE, Institut Agro Montpellier, Montpellier, France.
⁷ University of Kassel, Kassel, Germany.
⁸ China Agricultural University, Beijing, China.
⁹ University of Milan, Milan, Italy.
¹⁰ Iowa State University, Ames, IA, USA.
¹¹ Department of Life Science Engineering, Digital Agriculture, HEF World Agricultural Systems Center, Technical University of Munich, Munich, Germany.
¹² Gembloux Agro-Bio Tech, Liege University, Gembloux, Belgium.
¹³ International Institute for Applied Systems Analysis, Laxenburg, Austria.
¹⁴ Michigan State University, East Lansing, MI, USA.
¹⁵ Fujian Agriculture and Forestry University, Fuzhou, China.
¹⁶ Chinese Academy of Sciences, Beijing, China.
¹⁷ University of São Paulo, Piracicaba, Brazil.
¹⁸ Wageningen University and Research, Wageningen, the Netherlands.
¹⁹ University of Florence, Florence, Italy.
²⁰ University of Florida, Gainesville, FL, USA.
²¹ Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.
²² Global Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic.
²³ KIT/IMK-IFU, Garmisch-Partenkirchen, Germany.
²⁴ National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, China.
²⁵ Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany.
²⁶ CSIRO Agriculture and Food, Canberra, Australian Capital Territory, Australia.
²⁷ Natural Resources Institute Finland (Luke), Helsinki, Finland.

PMID: 40481339
DOI: 10.1038/s43016-025-01179-y

Review

Gaps and strategies for accurate simulation of waterlogging impacts on crop productivity

Margarita Garcia-Vila et al. Nat Food. 2025 Jun.

. 2025 Jun;6(6):553-562.

doi: 10.1038/s43016-025-01179-y. Epub 2025 Jun 6.

Authors

Affiliations

¹ Instituto de Agricultura Sostenible, CSIC, Córdoba, Spain. mgarcia-vila@ias.csic.es.
² Institute of Bio- and Geosciences, Agrosphere (IBG-3), Forschungszentrum Jülich GmbH, Jülich, Germany.
³ University of Bonn, Bonn, Germany.
⁴ Tasmanian Institute of Agriculture, University of Tasmania, Launceston, Tasmania, Australia.
⁵ Yangtze University, Jingzhou, China.
⁶ LEPSE, Université de Montpellier, INRAE, Institut Agro Montpellier, Montpellier, France.
⁷ University of Kassel, Kassel, Germany.
⁸ China Agricultural University, Beijing, China.
⁹ University of Milan, Milan, Italy.
¹⁰ Iowa State University, Ames, IA, USA.
¹¹ Department of Life Science Engineering, Digital Agriculture, HEF World Agricultural Systems Center, Technical University of Munich, Munich, Germany.
¹² Gembloux Agro-Bio Tech, Liege University, Gembloux, Belgium.
¹³ International Institute for Applied Systems Analysis, Laxenburg, Austria.
¹⁴ Michigan State University, East Lansing, MI, USA.
¹⁵ Fujian Agriculture and Forestry University, Fuzhou, China.
¹⁶ Chinese Academy of Sciences, Beijing, China.
¹⁷ University of São Paulo, Piracicaba, Brazil.
¹⁸ Wageningen University and Research, Wageningen, the Netherlands.
¹⁹ University of Florence, Florence, Italy.
²⁰ University of Florida, Gainesville, FL, USA.
²¹ Leibniz Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany.
²² Global Change Research Institute of the Czech Academy of Sciences, Brno, Czech Republic.
²³ KIT/IMK-IFU, Garmisch-Partenkirchen, Germany.
²⁴ National Engineering and Technology Center for Information Agriculture, Engineering Research Center of Smart Agriculture, Ministry of Education, Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture, Nanjing Agricultural University, Nanjing, China.
²⁵ Institute of Biochemistry and Biology, University of Potsdam, Potsdam, Germany.
²⁶ CSIRO Agriculture and Food, Canberra, Australian Capital Territory, Australia.
²⁷ Natural Resources Institute Finland (Luke), Helsinki, Finland.

PMID: 40481339
DOI: 10.1038/s43016-025-01179-y

Abstract

With the changing climate, soil waterlogging is a growing threat to food security. Yet, contemporary approaches employed in crop models to simulate waterlogging are in their infancy. By analysing 21 crop models, we show that critical deficiencies persist in accurately simulating capillary rise, crop resistance to transient periods of waterlogging, crop recovery mechanisms, and the effects on soil nitrogen processes, phenology and yield components. This hinders the ability of such models to reliably simulate the impacts of excessive soil moisture. Advanced crop modelling analytics will enable scenario analysis and, with time, farming systems adaptation to climate change and increasing frequency of crop failure due to waterlogging.

PubMed Disclaimer

Conflict of interest statement

Competing interests: The authors declare no competing interests.

References

1. de S. Nóia Júnior, R. et al. A call to action for global research on the implications of waterlogging for wheat growth and yield. Agric. Water Manage. 284, 108334 (2023). - DOI
1. Liu, K. et al. Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates. Nat. Commun. 14, 765 (2023). - PubMed - PMC - DOI
1. Kuppel, S., Houspanossian, J., Nosetto, M. D. & Jobbágy, E. G. What does it take to flood the Pampas? Lessons from a decade of strong hydrological fluctuations. Water Resour. Res. 51, 2937–2950 (2015). - DOI
1. Status of the World’s Soil Resources: Main Report (FAO, 2015).
1. Alam, M. S., Sasaki, N. & Datta, A. Waterlogging, crop damage and adaptation interventions in the coastal region of Bangladesh: a perception analysis of local people. Environ. Dev. 23, 22–32 (2017). - DOI

Publication types

Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

Gaps and strategies for accurate simulation of waterlogging impacts on crop productivity

Affiliations

Gaps and strategies for accurate simulation of waterlogging impacts on crop productivity

Authors

Affiliations

Abstract

Conflict of interest statement

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources