Multi‐Decadal Soil Moisture and Crop Yield Variability—A Case Study With the Community Land Model (CLM5)

Abstract While the impacts of climate change on global food security have been studied extensively, the capability of emerging tools that couple land surface processes and crop growth in reproducing inter‐annual yield variability at regional scale remains to be tested rigorously. In this study, we analyzed the effects of weather variations between years (1999–2019) on regional crop productivity for two agriculturally managed regions with contrasting climate and cropping conditions: the German state of North Rhine‐Westphalia (DE‐NRW) and the Australian state of Victoria (AUS‐VIC), using the latest version of the Community Land Model (CLM5) and the WFDE5 (WATCH Forcing Data methodology applied to ECMWF reanalysis version 5) reanalysis. Overall, the simulation results were able to reproduce the total annual crop yields of certain crops, while also capturing the differences in total yield magnitudes between the domains. However, the simulations showed limitations in correctly capturing inter‐annual differences of crop yield compared to official yield records, which resulted in relatively low correlation coefficients between 0.07 and 0.39 in AUS‐VIC and between 0.11 and 0.42 in DE‐NRW. The mean absolute deviation of simulated winter wheat yields was up to 4.6 times lower compared to state‐wide records from 1999 to 2019. Our results suggest the following limitations of CLM5: (a) limitations in simulating yield responses from plant hydraulic stress; (b) errors in simulating soil moisture contents compared to satellite‐derived data; and (c) errors in the representation of cropland in general, for example, crop parameterizations and human influences.

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Publication Details

Journal
Journal of Advances in Modeling Earth Systems
Published
2024-09-01
DOI
https://doi.org/10.1029/2023ms004023
Citations
4
Primary Topic
Climate change impacts on agriculture
Type
article
Field-Weighted Citation Impact
4.12

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article

Multi‐Decadal Soil Moisture and Crop Yield Variability—A Case Study With the Community Land Model (CLM5)

Harrie‐Jan Hendricks Franssen, Heye Bogena, Andrew W. Western, Theresa Boas et al.
4 citations
Journal of Advances in Modeling Earth Systems
Climate change impacts on agriculture
4.12
article

Multi‐Decadal Soil Moisture and Crop Yield Variability—A Case Study With the Community Land Model (CLM5)

Harrie‐Jan Hendricks Franssen, Heye Bogena, Andrew W. Western, Theresa Boas, Dongryeol Ryu
article en
4 citations

Abstract

Abstract While the impacts of climate change on global food security have been studied extensively, the capability of emerging tools that couple land surface processes and crop growth in reproducing inter‐annual yield variability at regional scale remains to be tested rigorously. In this study, we analyzed the effects of weather variations between years (1999–2019) on regional crop productivity for two agriculturally managed regions with contrasting climate and cropping conditions: the German state of North Rhine‐Westphalia (DE‐NRW) and the Australian state of Victoria (AUS‐VIC), using the latest version of the Community Land Model (CLM5) and the WFDE5 (WATCH Forcing Data methodology applied to ECMWF reanalysis version 5) reanalysis. Overall, the simulation results were able to reproduce the total annual crop yields of certain crops, while also capturing the differences in total yield magnitudes between the domains. However, the simulations showed limitations in correctly capturing inter‐annual differences of crop yield compared to official yield records, which resulted in relatively low correlation coefficients between 0.07 and 0.39 in AUS‐VIC and between 0.11 and 0.42 in DE‐NRW. The mean absolute deviation of simulated winter wheat yields was up to 4.6 times lower compared to state‐wide records from 1999 to 2019. Our results suggest the following limitations of CLM5: (a) limitations in simulating yield responses from plant hydraulic stress; (b) errors in simulating soil moisture contents compared to satellite‐derived data; and (c) errors in the representation of cropland in general, for example, crop parameterizations and human influences.

Journal of Advances in Modeling Earth SystemsVol. 16(9)
The University of Melbourne (AU), Forschungszentrum Jülich (DE), Ernst Ruska Centre (DE)
Deutsche Forschungsgemeinschaft
Zero hunger
Openalex Percentile: Top 7%
Climate change impacts on agriculture
4.12
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