the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Resolving effects of leaf pigmentation changes and plant residue on the energy balance of winter wheat cultivation in the ORCHIDEE-CROP model
Abstract. Crop management impacts climate not only through changes in carbon stocks and greenhouse gas budgets, but also through changes in the heat budget. However, the latter aspect is not yet covered by existing cropping system models. The coupling of dedicated crop models with land surface models may be an attempt to quantify those effects, but is hampered by the simplistic representation of surface albedo as a mix of soil albedo and a static vegetation albedo controlled by vegetation cover. Here, we developed ORCHIDEE-CROP, a land surface model integrating the cropping system model STICS, by incorporating time-varying albedo from crop pigmentation during foliar yellowing and post-harvest crop residue soil cover. We further parameterized the effect of crop residues on surface roughness and soil evaporation affecting the heat budget and partitioning between latent and sensible heat fluxes. Using 10 site simulations, we quantified the impacts of these processes on soil temperature, soil moisture, water and heat fluxes of winter wheat crops. Incorporating foliar yellowing and post-harvest residue cover increased surface albedo by an average of 0.07±0.03 during the foliar yellowing period and 0.02±0.02 during the residue cover period, accordingly inducing surface cooling by −0.42±0.65 °C and -1.39±1.07 °C. During each period, sensible heat flux changed by -0.03±2.34 W m-² and 1.30±11.52 W m-², while latent heat flux decreased by -1.23±1.78 W m-² and -3.59±3.90 W m-². Spatiotemporal variability in these effects was driven by site-specific meteorology and soil properties. Simulations of drying climate scenarios reveal that crop residues left on the field can progressively increase plant available water over multiple years under dry conditions. This study underscores that crop pigmentation and residues significantly modulate surface energy partitioning, and demonstrates the potential of its management for climate mitigation. The refined modelling framework enables simultaneous assessment of the biogeochemical and biophysical impacts of field operations on the Earth System.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2025-1861', Anonymous Referee #1, 26 Aug 2025
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AC2: 'Reply on RC1', Ke Yu, 06 Nov 2025
Dear reviewer #1,
Thank you so much for your time in reviewing our manuscript and for your positive feedback on our work. Following your suggestions, the revision of this manuscript is as follows:
(1) Added a sensitivity analysis of key model parameters to analyze the variability of residue effects. The corresponding methodology and results of the sensitivity test were described in section 2.6 and section 3.5; (2) Expanded the discussion of model limitations and uncertainties in section 4.5.
For more details, please find our responses to all of your comments in the response letter (Supplement)
Sincerely,
Ke Yu
on behalf of all co-authors
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AC2: 'Reply on RC1', Ke Yu, 06 Nov 2025
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RC2: 'Comment on egusphere-2025-1861', Anonymous Referee #2, 16 Sep 2025
Yu et al present the ORCHIDEE-CROP model that incorporates a time-varying surface albedo that considers foliar yellowing and crop residue. The effect of crop residue on surface roughness, surface temperature, and surface energy partitioning was also analyzed. Overall, the work is solid and addresses effects not considered in current models, while it may benefit from some clarification on methods and interpretations. I suggest publication of the manuscript after minor revision.
- In several places across the manuscript (e.g., L36), the manuscript claims a significant impact on surface energy balance. However, in most scenarios, the impact seems small (less than a few W/m2) to me, and the uncertainty is at similar magnitudes as the difference. I think the magnitude of the differences can be better addressed.
- L231, L242: It would be good to explain how the calibrations were performed in the supplementary.
- L312: The equation number seems incorrect
- L355: How was the αsurf model trained? Random forest is mentioned here, but Section 2.4.2 describes a direct fitting of the parameters in Eqs. 13 and 14.
- Figure 4: It would be good to show the relative difference in the main text or supplementary to provide more context.
Citation: https://doi.org/10.5194/egusphere-2025-1861-RC2 -
AC1: 'Reply on RC2', Ke Yu, 06 Nov 2025
Dear reviewer#2:
Thank you so much for your time in reviewing our manuscript and for providing your constructive comments and suggestions. The valuable comments helped us improve the paper. Following the comments, our main revision is as below:
(1) Clarified the magnitude of impacts of foliar yellowing and residue covering on water and heat variables in the Abstract, and included the relative changes in targeted variables between the improved model and the initial version in the results sections; (2) Expanded the discussion of the uncertainty and spatiotemporal variability of residue impacts in sections 4.2 and 4.5; (3) Supplemented more details about the calibration of crop development and harvest timing in sections 2.2.5 and 2.3.
Please find our detailed responses to all of your comments in the response letter (Supplement).Sincerely,
Ke Yu
on behalf of all co-authors
Data sets
surface albedo observation from fluxnet and sentinel-2, MODIS LAI, modeling output, management information Ke Yu https://doi.org/10.5281/zenodo.15234443
Sentinel-2 bare soil albedo datasets Ke Yu https://doi.org/10.5281/zenodo.15271053
Model code and software
ORCHIDEE-CROP v2.1: ORCHIDEE-CROP-RES Ke Yu, Yang Su https://doi.org/10.5281/zenodo.15230286
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This manuscript investigates the effects of leaf pigmentation changes and crop residues on the surface energy balance of winter wheat, by improving the ORCHIDEE-CROP model with dynamic albedo, soil evaporation, and surface roughness parameterizations. The study is clearly presented, methodologically sound, and provides valuable insights into biophysical processes often overlooked in land surface models. Some aspects, however, would benefit from refinement: The site-to-site variability in residue effects (on evaporation and roughness) deserves more explicit discussion of limitations. The treatment of uncertainties and sensitivity to input data and climate scenarios could be expanded. Figures are informative but some captions and explanations are too brief; adding interpretive detail would improve readability. Overall, the work is solid and novel. I recommend minor revision before acceptance.