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Winter wheat is a main cereal crop grown in the United States of America (USA), and the USA is the third largest wheat exporter globally. Timely and reliable in-season forecast and year-end estimation of winter wheat grain production in the USA are needed for regional and global food security. In this study, we assessed the consistency between the agricultural statistical reports and satellite-based data for winter wheat over the contiguous US (CONUS) at both the county and national scales. First, we compared the planted area estimates from the National Agricultural Statistics Service (NASS) and the Cropland Data Layer (CDL) from 2008–2018. Second, we investigated the relationship between gross primary production (GPP) estimated by the vegetation photosynthesis model (VPM) and grain production from the NASS. Lastly, we explored the in-season utility of GPPVPM in monitoring seasonal production. Strong spatiotemporal consistency of planted areas was found between the NASS and CDL datasets. However, in the Southern Great Plains, both the CDL and NASS planted acreage were noticeable larger (>20%) than the NASS harvested area, where some winter wheat fields were used as forage for cattle grazing. County-level GPPVPM was linearly related with grain production of winter wheat, with an R2 value of 0.68 across the CONUS. The relationships between grain production and GPPVPM in those counties without a substantial difference (<20%) between planted and harvested area were much stronger and their harvest index (HIGPP) values ranged from 0.2–0.3. GPPVPM in May could explain about 70–90% of the variance of winter wheat grain production. Our findings highlight the potential of GPPVPM in winter wheat monitoring, especially for those high harvested/planted ratio, which could provide useful data to guide planning and marketing for decision makers, stakeholders, and the public.
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Spatial-temporal dynamics of maize and soybean planted area, harvested area, gross primary production, and grain production in the Contiguous United States during 2008-2018
Abstract The United States of America ranked first in maize export and second in soybean export in the world. Accurate and timely data and information on maize and soybean production in the Contiguous United States (CONUS) are important for food security at the regional and global scales. In this study, we firstly compare the maize and soybean planted area from cropland data layer (CDL) with NASS area statistics over the CONUS during 2008-2018, and evaluate the interannual changes of planted and harvested area based on the two datasets. Secondly, we investigate the relationship between grain production and gross primary production (GPP) simulated by Vegetation Photosynthesis Model (VPM) at national and county scales. Finally, we evaluate the linear regression models between grain production and cumulated GPPVPM over time at 8-day resolution. We found strong spatial-temporal consistency between CDL and NASS datasets in maize and soybean planted areas. Maize and soybean planted areas increased by mid-2010s, largely driven by markets and international trade. Severe summer drought in 2012 had little impact on soybean planted and harvested area and maize planted area, but substantially reduced maize harvested area. and grain production. Annual county-level GPPVPM had strong linear relationship with NASS grain production for maize and soybean. The Harvest Index, defined as the ratio between grain production and GPPVPM (HIGPP_VPM), ranged from 0.25 (2012) to 0.36 for maize and from 0.13 to 0.15 for soybean. The linear regression models between grain production and cumulated GPPVPM (GPPVPM_CUM) over time at 8-day resolution showed that by the end of July, GPPVPM_CUM accounted for ~90% of variance in maize and soybean grain production, which was approximately two months before farmers started to harvest. This study clearly shows that VPM and GPPVPM data are useful for monitoring and in-season forecasting of maize and soybean grain production in the CONUS.
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- Award ID(s):
- 1946093
- PAR ID:
- 10211841
- Date Published:
- Journal Name:
- Agricultural and forest meteorology
- Volume:
- 297
- Issue:
- February 2021
- ISSN:
- 0168-1923
- 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/10.1016/j/agrformet.2020.108240
