从2008年到2020年,美国大陆地区按作物灌总量
P J Ruess1, Megan Konar2, Niko Wanders3
1Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, Urbana, USA.
Scientific data
|April 17, 2024
概括
这项研究介绍了美国灌用水抽取的新数据集,通过使用总灌数据来提高空间覆盖率和准确性. 更新的估计提高了对农业用水资源管理的理解.
科学领域:
- 水文学的水文学
- 农业科学 农业科学
- 环境科学 环境科学
背景情况:
- 准确估计农业用水量对于可持续的水资源管理至关重要.
- 之前的数据集在空间覆盖和包括灌类别的范围方面存在局限性.
研究的目的:
- 根据作物,县,年份和水源,开发一个全面的美国灌用水抽取数据集.
- 通过纳入更具包容性的数据变量和扩大空间覆盖范围来改进之前的估计.
主要方法:
- 利用先前开发的框架创建一个伴随数据集.
- 使用美国地质调查局 (USGS) 的"灌 - 总"变量来划分PCR-GLOBWB 2水文模型估计.
- 扩展了数据集,包括以前缺失的州和额外的灌类别.
主要成果:
- 创建了一个数据集,拥有近250万个数据点,涵盖了13年的3,142个县,3个水源和20个作物.
- 对地表水提取 (SWW),总地下水提取 (GWW) 和不可再生地下水耗尽 (GWD) 的发现显示,与之前的估计相比,空间覆盖率有所改善.
- 由于更广泛的纳入标准和扩大的地理代表性,报告的灌用水量有所增加,特别是捕捉了密西西比海湾水库中的水和大豆灌.
结论:
- 增强的数据集提供了更完整和空间分辨率的美国灌用水提取的图片.
- 这些改进的数据有助于更好地评估农业用水对水资源的影响,并支持明智的水资源管理决策.
- 包括以前未经定量化的灌活动,如密西西比河流域水库,突出了使用综合数据变量的重要性.
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