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机译:通过现场观测和区域规模的基于AL的建模在印度升高地下水砷的发生,预测和危害
Department of Geology and Geophysics Indian Institute of Technology Kharagpur Kharagpur India School of Environmental Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India;
School of Environmental Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India;
Department of Geology and Geophysics Indian Institute of Technology Kharagpur Kharagpur India;
School of Environmental Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India;
School of Environmental Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India;
School of Water Resources Indian Institute of Technology Kharagpur Kharagpur India;
KTH-Intemational Groundwater Arsenic Research Group Department of Sustainable Development Environmental Science and Engineering KTH Royal Institute of Technology Stockholm Sweden;
Centre of Excellence in Artificial Intelligence (Al) Indian Institute of Technology Kharagpur Kharagpur India;
Department of Geology and Geophysics Indian Institute of Technology Kharagpur Kharagpur India;
Arsenic; India; Public health; Machine learning; Groundwater contamination; Tectonics;
机译:在跨界恒河河三角洲,印度和孟加拉国建模区域规模地下水砷危险:用机器学习输注基于物理的模型
机译:印度西孟加拉邦受砷影响地区的补给和深层地下水的区域规模稳定同位素特征
机译:中国山西省地下水中砷与地方性砷的耦合预测模型
机译:巴拉克谷(Assam)地下水的砷浓度的发生和岩石癖控制,印度东北地区
机译:准备制定新的砷法规:饮用水中砷的产生和形态,选择处理工艺时要考虑的因素,确定二氧化硅的干扰以及预测吸附工艺的性能。
机译:稻田地球化学和水文:为什么地下水水浇地在孟加拉国的一个解释是地下水砷的净汇
机译:砷浓度,相关环境因素,以及宾夕法尼亚地下水升高的砷的预测概率