地理空间分布和机器学习算法用于评估摩洛哥地表水体的水质
Rachida El Morabet1, Larbi Barhazi1, Soufiane Bouhafa1
1LADES Lab FLSH-M, Department of Geography, Hassan II University of Casablanca, Mohammedia, Morocco.
Scientific reports
|November 23, 2023
概括
穆罕默迪亚河流中的重金属污染在春季比冬季高. 虽然没有表明对健康有不良影响,但发现了显著的致癌风险,这表明上游污染.
科学领域:
- 环境科学 环境科学
- 评估水质水质的评估.
- 沉重金属污染 沉重金属污染
背景情况:
- 地表水质量对于人类消费至关重要,并且在全球范围内进行监测.
- 摩洛哥穆罕默德省的河流是重要的水源,需要进行质量评估.
研究的目的:
- 评估Nfifikh,Hassar和El Maleh河的重金属污染情况.
- 通过重金属污染指数 (HPI) 评估水质.
- 确定潜在的健康风险,包括危险系数 (HQ) 和致癌风险 (CR).
主要方法:
- 分析,铁,铜,和的度.
- 重金属污染指数 (HPI) 的计算.
- 使用危险系数 (HQ) 和致癌风险 (CR) 的健康风险评估.
- 机器学习模型 (随机森林,SVM,ANN) 的应用用于预测.
主要成果:
- 春季的重金属度比冬季高.
- 冬季HPI值在1.5-2之间,春季HPI值在2-3之间.
- 和铁是Nfifikh河的主要污染物.
- HQ<1表明没有不良健康影响,但CR表明1%的癌症易感性.
- 在河流进入该县之前,污染已经明显,这是杜阿尔·马尔哈湖证实的.
结论:
- 穆罕默迪亚的河水质量受到重金属的影响,季节性变化.
- 由于存在重大致癌风险,需要对上游污染源进行进一步调查.
- 缓解策略需要在县界之前确定污染源.
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