在Hetao地区的上世水层中的危害和影响因素,使用机器学习建模
Yu Fu1, Wengeng Cao2, Tian Nan3
1North China University of Water Resources and Electric Power, Zhengzhou 450011, China; The Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Science (CAGS), Shijiazhuang 050061, China.
The Science of the total environment
|January 25, 2024
概括
在Hetao地区的度很高.
科学领域:
- 环境科学 环境科学
- 水文地质学 水文地质学
- 公共卫生 公共卫生
背景情况:
- 河地区面临着地下水中严重的污染.
- 丰富对当地居民造成重大健康风险.
- 了解地下水质量和分布对于资源管理和健康至关重要.
研究的目的:
- 综合评估地下水质量和高的空间分布.
- 确定影响水平的环境因素.
- 为了估计暴露在地下水中不安全的含量的人口.
主要方法:
- 利用机器学习算法:支持矢量机,极端梯度增强和随机森林.
- 分析了六个环境因素:气候,人类活动,沉积环境,水文地质学,土壤等.
- 绘制高含量地下水和估计的人口暴露的地图.
主要成果:
- 近一半的采样井超过了世卫组织对的指导方针.
- 地下水化学主要是Na-HCO3-Cl或Na-Mg-HCO3-Cl类型.
- 含量高的地下水集中在古老的河流道和黄河喷中.
- 沉积环境,气候和人类活动是影响因素的关键因素.
- 随机森林模型准确地预测了高分布.
- 过度含的地下水覆盖了该地区38.81%.
- 据估计,约有94万人可能会接触到高的地下水.
结论:
- 沉积环境是高地下水的主要驱动因素.
- 机器学习有效地模拟和绘制污染的地图.
- 赫塔奥地区有很大一部分人口面临高含量地下水的风险.
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