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Abstract. Understanding and assessing the spatiotemporal patterns in crop-specific phosphorus (P) fertilizer management are crucial for enhancing crop yield and mitigating environmental problems. The existing P fertilizer dataset, derived from sales data, depicts an average application rate over total cropland at the county level but overlooks cross-crop variations. Conversely, the survey-based dataset offers crop-specific application details at the state level yet lacks inter-state variability. By reconciling these two datasets, we developed long-term gridded maps to characterize crop-specific P fertilizer application rates, timing, and methods across the contiguous US at a resolution of 4 km × 4 km from 1850 to 2022. We found that P fertilizer application rate over fertilized areas in the US increased from 0.9 g P m−2 yr−1 in 1940 to 1.9 g P m−2 yr−1 in 2022, with substantial variations among crops. However, approximately 40 % of cropland nationwide has remained unfertilized in the recent decade. The hotspots for P fertilizer use have shifted from the southeastern and eastern US to the Midwest and the Great Plains over the past century, reflecting changes in cropland area, crop choices, and P fertilizer use across different crops. Pre-planting (fall and spring) and broadcast application are prevalent among corn, soybean, and cotton in the Midwest and the Southeast, indicating a high P loss risk in these regions. In contrast, wheat and barley in the Great Plains receive the most intensive P fertilization at planting and via non-broadcast application. The P fertilizer management dataset developed in this study can advance our comprehension of agricultural P budgets and facilitate the refinement of best P fertilizer management practices to optimize crop yield and to reduce P loss. Datasets are available at https://doi.org/10.5281/zenodo.10700821 (Cao et al., 2024).
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Monitoring Crop Status in the Continental United States Using the SMAP Level-4 Carbon Product
Accurate monitoring of crop condition is critical to detect anomalies that may threaten the economic viability of agriculture and to understand how crops respond to climatic variability. Retrievals of soil moisture and vegetation information from satellite-based remote-sensing products offer an opportunity for continuous and affordable crop condition monitoring. This study compared weekly anomalies in accumulated gross primary production (GPP) from the SMAP Level-4 Carbon (L4C) product to anomalies calculated from a state-scale weekly crop condition index (CCI) and also to crop yield anomalies calculated from county-level yield data reported at the end of the season. We focused on barley, spring wheat, corn, and soybeans cultivated in the continental United States from 2000 to 2018. We found that consistencies between SMAP L4C GPP anomalies and both crop condition and yield anomalies increased as crops developed from the emergence stage (r: 0.4–0.7) and matured (r: 0.6–0.9) and that the agreement was better in drier regions (r: 0.4–0.9) than in wetter regions (r: −0.8–0.4). The L4C provides weekly GPP estimates at a 1-km scale, permitting the evaluation and tracking of anomalies in crop status at higher spatial detail than metrics based on the state-level CCI or county-level crop yields. We demonstrate that the L4C GPP product can be used operationally to monitor crop condition with the potential to become an important tool to inform decision-making and research.
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- Award ID(s):
- 1633831
- PAR ID:
- 10278916
- Date Published:
- Journal Name:
- Frontiers in Big Data
- Volume:
- 3
- ISSN:
- 2624-909X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/fdata.2020.597720
