自然和人为输入对 Beenaganj-Chachura 区块地下水污染的相互作用

Yogesh Murthy, Sanjeev Kumar Ahirwar, Nitin Kumar Samaiya
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引用次数: 0

摘要

本研究调查了自然和人为输入对印度中央邦 Beenaganj-Chachura 地区地下水化学和水质的影响。共对 50 个地下水样本进行了硝酸盐、氟化物、氯化物、溶解性总固体、钙、镁、pH 值、总硬度和电导率的检测,并采用中心复合设计,通过响应面方法(RSM)研究了它们对熵加权水质指数和地下水污染指数(PIG)的影响。分析结果表明,Ca、Mg、Cl-、SO42- 和 NO3-超出了印度标准局(BIS)和世界卫生组织(WHO)规定的理想限值和允许限值。根据 PIG 的调查结果,分别有 76%、16% 和 8%的地下水样本属于微量、低度和中度污染类别。实验数据的二次 RSM 模型的回归系数结果非常好。因此,RSM 是获得输入参数优化值的绝佳方法,可将 PIG 值降至最低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interplay of natural and anthropogenic inputs on the groundwater contamination of Beenaganj-Chachura block
The present research work investigates the impact of natural and anthropogenic inputs on the chemistry and quality of the groundwater in the Beenaganj-Chachura block of Madhya Pradesh, India. A total of 50 groundwater samples were examined for nitrates, fluoride, chlorides, total dissolved solids, calcium, magnesium, pH, total hardness, and conductivity, and their impact on entropy-weighted water quality index and pollution index of groundwater (PIG) was investigated via the response surface methodology (RSM) using the central composite design. According to analytical findings, Ca, Mg, Cl−, SO42−, and NO3− exceed the desired limit and permitted limit set by the Bureau of Indian Standards (BIS) and the World Health Organization (WHO). According to PIG findings, 76, 16, and 8% of groundwater samples, respectively, fell into the insignificant, low, and moderate pollution categories. The regression coefficients of the quadratic RSM models for the experimental data provided excellent results. Thus, RSM provides an excellent means to obtain the optimized values of input parameters to minimize the PIG values.
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