| 29 Apr 2026
A 1-km dataset of crop residue production and usage pathways in the conterminous U.S. from 2001 to 2021
Abstract. Crop residues represent an important biomass resource that supports soil organic carbon maintenance, livestock production, and emerging bioeconomy sectors. In the United States, crop residue production is concentrated in a few dominant cropping systems, whereas residue demand for livestock and other off-field uses is often geographically separated from production regions. However, spatially explicit datasets that jointly quantify crop residue production, allocation pathways, and spatial imbalances between production and consumption remain limited. Here, we developed a 1 km × 1 km gridded dataset of crop residue production and usage pathways across the conterminous United States for 2001–2021, covering nine major crops. A mass-balance framework was applied to reconcile residue production and consumption, allocating residues into four pathways: left on field, animal-use, off-field use, and burnt. An implied domestic transfer layer was also derived as an indicator of spatial mismatches between residue production and consumption. Results indicate that total U.S. residue production averaged 4.91×1011 kg/yr, with corn residue consistently contributing over 60 % of the total biomass. Residues left on field dominated nationally, accounting for 86.4 % of total residue production. Livestock use and off-field uses represented smaller but spatially heterogeneous pathways (13.4 % combined), while burnt residue accounted for less than 0.2 %. Residue production was concentrated in the Midwest, whereas higher consumption demand occurred in the Southeast, West Coast, and the Southern Great Plains. The national production-consumption mismatch ratio increased from 7.6 % to 8.4 % over the study period, highlighting a growing spatial imbalance between residue availability and consumption demand. By providing 1-km gridded, mass-balanced estimates of residue production, allocation pathways, and regional production-consumption mismatches, this dataset offers a spatially explicit foundation for quantifying crop residue flows across U.S. agricultural landscapes and supports improved representation of residue management in terrestrial biosphere models, soil carbon dynamics assessments, and sustainable residue biomass utilization strategies. The dataset is available at https://doi.org/10.5281/zenodo.18453064 (Zhang et al., 2026).
The manuscript reports a dataset for the production and usage of crop residues in the USA. There is a clear need for high quality national level datasets on residue production and usage, for example as a key input to model changes in soil organic carbon stocks. The methodology is quite similar to that used to produce a similar dataset on a global scale by Smerald et al. However, the use of more detailed, national-level input data and assumptions and a considerably finer spatial resolution means that, for the USA, this dataset is almost certainly superior to the global dataset.
In my opinion the methodology is reasonable and clearly described. I have a few relatively minor points that the authors may like to include, but overall my recommendation is to publish this manuscript.
1. Does national level data allow for crop-specific residue management to be determined? For example soybean and maize cultivation produce residues in very different amounts and with different nutritional qualities, presumably leading to different management choices. Knowing crop-specific management would, for example, be very useful for driving biogeochemical models. If the available data doesn't allow for separating crop-specific management, it may be worth adding a sentence or two to the discussion about why this is not currently possible and what data would be required.
2. Does the USA have data about where maize is grown for silage as opposed to for grain? When maize is harvested for silage the majority of the above ground plant is normally removed. Maybe this could help further improve the dataset or give an additional way to validate it (especially what is fed to animals).
3. In my understanding the redistribution of crop residues between surplus and deficit grid cells does not take the distance between the grid cells into account. Since residue transport is expensive, I assume there is a strong incentive to keep the transport distances as small as possible. I don't see this as a very critical point, since only quite a small amount of residue (7-8%) is moved between grid cells. However, it may be worth adding a sentence or two about this to the discussion/limitations section.
4. Is there any way to quantify the uncertainty for residue production?
5. I assume all values for biomass weights are given in dry matter as opposed to fresh matter. It is probably worth stating this somewhere to avoid possible confusion. If you needed to convert e.g. grain yields from fresh to dry matter using standard crop-specific conversion factors it is probably worth documenting these values in the supplementary material.