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Evaluation of physico-chemical and microbial parameters on water quality of Narmada River, India

机译:印度纳尔默达河水质的理化和微生物参数评估

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The present study was carried out to ascertain the quality of water at western zone of Narmada River of Madhya Pradesh (India). Due to heavy discharge of harmful and deleterious substances in river, the biological, chemical and physical characteristics of water have changed to a considerable extent. The objectives of this study were to find out the changes in physico-chemical nature as well as biological health of Narmada River. A thorough study was done on the basis of prevailing seasons. The deterioration of water quality was noticed at lower site of water body in a particular season as low temperature, dissolved oxygen and higher concentration of content of chlorine, etc., all pointing towards the nutrient enrichment. This evaluation will be immensely helpful to estimate the effect of impoundments on the quality of water, fisheries development and reservoir management policy. The microbial analysis was also conducted in terms of most probable number (MPN) of total coliforms in water sample and its highest value (1239) was reported from downstream of Omkareshwar dam site of Narmada River. Water quality index of all sites of Narmada River was calculated for three seasons, viz. summer, monsoon and winter and it was found to be highest (123) at Koteshwar dam site of river in monsoon season and the lowest (70) was observed in water of upstream of Omkareshwar dam during winter. The suitable correlation coefficients were calculated for 7 pairs of variables and correlation matrices were then established seasonally.
机译:本研究旨在确定印度中央邦纳尔默达河西部地区的水质。由于河流中有害和有害物质的大量排放,水的生物学,化学和物理特性已在很大程度上发生了变化。这项研究的目的是找出纳尔默达河的理化性质和生物健康方面的变化。根据当前的季节进行了彻底的研究。在特定季节,由于低温,溶解氧和较高的氯含量等,在水体较低的位置发现水质恶化,所有这些都指向营养物富集。该评估将非常有助于评估蓄水对水质,渔业发展和水库管理政策的影响。还根据水样中大肠菌群的最可能数量(MPN)进行了微生物分析,并从纳尔默达河(Narmada River)的Omkareshwar水坝站点的下游报道了其最高值(1239)。纳尔默达河所有站点的水质指数是按三个季节计算的。夏季,季风和冬季,在季风季节河的Koteshwar水坝站点发现最高(123),而冬季在Omkareshwar水坝上游的水中发现最低(70)。计算了7对变量的合适的相关系数,然后季节性地建立相关矩阵。

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