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首页> 外文期刊>Environmental engineering and management journal >PREDICTION OF WATER QUALITY INDEX OF AN INDIAN RIVER USING ARITHMETIC INDEX AND REGRESSION MODELS
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PREDICTION OF WATER QUALITY INDEX OF AN INDIAN RIVER USING ARITHMETIC INDEX AND REGRESSION MODELS

机译:用算术指标和回归模型预测印度河流水质指数

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摘要

This paper focuses on the effect of some water quality parameters of river water which helps in the calculation of water quality index (WQI) that culminates in the development of a regression model for prediction of WQI of the river system in India. The index was calculated by arithmetic index method using twelve various experimentally estimated water quality parameters such as potential hydrogen, chlorides, dissolved oxygen saturation, nitrates, sulphates, phosphates, total dissolved solids, biochemical oxygen demand, electrical conductivity, total hardness, turbidity and total coliform of the water at eight locations, for a 55 km stretch of Chalakkudy river November 2013 to December 2018. It was identified that total coliform is the major parameter contributing to the bad quality of water. Water quality regression model has been developed as a function of total coliform content. The performance of the model in predicting the WQI has been tested by comparing with the calculated WQI for the following year 2018. The regression model has been found to be good with an absolute average relative error and root mean square error values of 0.693 and 0.5 respectively. The results indicate that the basin is slowly getting into a serious drinking water crisis.
机译:本文重点介绍了河水一些水质参数的影响,这有助于计算水质指数(WQI),这些指数(WQI)达到了在印度河流系统WQI预测的回归模型中的开发。该指数由算术指数法计算使用12种各种实验估计的水质参数,例如潜在的氢,氯化物,溶解的氧饱和度,硝酸盐,硫酸盐,磷酸盐,总溶解固体,生物化学需氧量,导电性,总硬度,浊度和总量2013年11月至2018年11月,八个地点的水大肠各地,为55公里的Chalakkudy River河。确定总大肠菌群是有助于水质量不好的主要参数。水质回归模型已作为总大肠杆菌含量的函数开发。通过与次年计算的WQI进行比较,测试了模型预测WQI的性能。已经发现回归模型具有绝对平均相对误差和0.693和0.5的根均方误差值。 。结果表明,盆地正在慢慢进入严重的饮用水危机。

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