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Efficient irrigation technologies, which seem to promise reduced production costs and water consumption in heavily irrigated areas, may instead be driving increased irrigation use in areas that were not traditionally irrigated. As a result, the total dependence on supplemental irrigation for crop production and revenue is steadily increasing across the contiguous United States. Quantifying this dependence has been hampered by a lack of comprehensive irrigated and dryland yield and harvested area data outside of major irrigated regions, despite the importance and long history of irrigation applications in agriculture. This study used a linear regression model to disaggregate lumped agricultural statistics and estimate average irrigated and dryland yields at the state level for five major row crops: corn, cotton, hay, soybeans, and wheat. For 1945–2015, we quantified crop production, irrigation enhancement revenue, and irrigated and dryland areas in both intensively irrigated and marginally-dependent states, where both irrigated and dryland farming practices are implemented. In 2015, we found that irrigating just the five commodity crops enhanced revenue by ~$7 billion across all states with irrigation. In states with both irrigated and dryland practices, 23% of total produced area relied on irrigation, resulting in 7% more production than from dryland practices. There was a clear response to increasing biofuel demand, with the addition of more than 3.6 million ha of irrigated corn and soybeans in the last decade in marginally-dependent states. Since 1945, we estimate that yield enhancement due to irrigation has resulted in over $465 billion in increased revenue across the contiguous United States (CONUS). Example applications of this dataset include estimating historical water use, evaluating the effects of environmental policies, developing new resource management strategies, economic risk analyses, and developing tools for farmer decision making.
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HarvestGRID: high-resolution harvested crop areas of the United States from 1981 to 2019
Abstract The United States is a major producer and exporter of agricultural goods, fulfilling global demands for food, fiber, and fuel while generating substantial economic benefits. Agriculture in the U.S. not only dominates land use but also ranks as the largest water-consuming sector. High-resolution cropland mapping and insights into cultivation trends are essential to enhance sustainable management of land and water resources. Existing data sources present a trade-off between temporal breadth and spatial resolution, leading to gaps in detailed geographic crop distribution. To bridge this gap, we adopted a data-fusion methodology that leverages the advantages of various data sources, including county-level data from the U.S. Department of Agriculture, along with several gridded land use datasets. This approach enabled us to create annual maps, termed HarvestGRID, of irrigated and harvested areas for 30 key crops across the U.S. from 1981 to 2019 at a resolution of 2.5 arc minutes. Over the past four decades, irrigated harvested area has remained relatively stable nationally; however, several western states exhibit a declining trend, while some eastern states show an upward trend. Notably, more than 50% of the irrigated land in the U.S. lies above three major aquifers: the High Plains, Central Valley, and Mississippi Embayment Aquifers. We assessed the accuracy of HarvestGRID by comparing it with other large-scale gridded cropland databases, identifying both consistencies and discrepancies across different years, regions, and crops. This dataset is pivotal for analyzing long-term cropland use patterns and supports the advancement of more sustainable agricultural practices.
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- Award ID(s):
- 2108196
- PAR ID:
- 10559281
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research: Food Systems
- Volume:
- 2
- Issue:
- 1
- ISSN:
- 2976-601X
- Format(s):
- Medium: X Size: Article No. 015006
- Size(s):
- Article No. 015006
- Sponsoring Org:
- National Science Foundation
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