基于灰色关系分析的水资源承载能力和作物结构优化研究
Lingyun Xu1,2, Bing Xu1,2,3, Ruizhong Gao1,4,5
1College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China.
Plants (Basel, Switzerland)
|March 17, 2025
概括
在内蒙古黄河流域过度提取地下水威胁着水资源. 优化作物结构可以减少用水量,提高经济效益,确保可持续的灌.
科学领域:
- 农业用水管理农业用水管理
- 水文学的水文学
- 机器学习应用 机器学习应用
背景情况:
- 内蒙古黄河流域的混合作物种植区面临着关键的水资源挑战,包括灌配额不足和地下水过度提取.
- 现有的水资源利用因供需不平衡和效率低下的做法而面临冲突.
研究的目的:
- 通过灰色关系分析评估该地区2023年水资源承载能力.
- 开发基于机器学习的作物结构优化模型,以尽量减少用水量并最大限度地提高经济效益.
主要方法:
- 采用灰色关系分析,评估了五个关键因素:水资源利用效率,灌率,开发和利用程度,供应模块和需求模块.
- 开发了一种机器学习模型,以优化作物结构,以节约水资源和经济收益.
主要成果:
- 地下水资源严重枯竭,许多地区的水承载能力低,供需冲突严重.
- 不合理的种植结构和过度的灌配额导致大量的水浪费.
结论:
- 建议的作物结构调整包括减少粮食作物和增加经济作物和料作物.
- 优化结构可以实现显著的年度节水,提高产量和增强经济效益,促进合理的水资源分配.
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