Water quality of river water examined at 23 stations in the upstream of Bhadra River basin from Kudrekmukh National Park (KNP) to Bhadra Wildlife Sanctuary (BWS) in India. Spatial cluster analysis performed on 23 sampling stations revealed three clusters depending on the similarities in the water quality variables that could delineate the number of sampling stations required for optimal sampling. Sample cluster analysis classified the 24 environmental variables in the data set into seven clusters depending on the similarities in the water quality variables. Principal component analysis of water produced 7 components, which accounted for 88.15 % of total variance. Factor analysis was performed on principal components extracted seven variance factors (VFs) after rotation with all VFs having eigenvectors of high (> 0.70) and moderate (> 0.50) loadings. The VF 1 accounted for 37.93 % of total variance with 9 eigenvectors (loading > 0.70) such as conductivity, total alkalinity, total hardness, Ca, Mg, Na, K, chloride and silicate. On total eigenvectors generated on 24 water quality data sets of river water were classified into four types viz. safe (normal), low polluted, medium polluted and highly polluted waters with corresponding total eigenvectors of < 0.50, > 0.50 - < 1.00, > 1.00 - < 1.50 and > 1.50, respectively. Total factor score produced for 23 sampling stations revealed a total of five types of sampling stations with safe, low, medium, high and very high levels of pollution with corresponding total factor scores of less than zero (< 0.0), > 0.0 - < 1.50), (> 1.50 - < 3.00), (> 3.00 - < 4.50) and (> 4.50), respectively.

中文翻译：

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印度西高止山脉Tungabhadra河支流巴德拉河上游水质的空间变异：多元统计技术的应用

从印度库德拉克穆赫国家公园（KNP）到印度巴德拉野生动物保护区（BWS）的巴德拉河流域上游23个站点检查的河水水质。对23个采样站进行的空间聚类分析显示了三个聚类，这取决于水质变量的相似性，可以描述最佳采样所需的采样站数量。样本聚类分析根据水质变量的相似性将数据集中的24个环境变量分为七个聚类。水的主成分分析产生了7个成分，占总方差的88.15％。对旋转后提取的七个方差因子（VF）的主成分进行因子分析，所有VF的特征向量均为高（> 0.70）和中等（> 0）。50）负载。VF 1占总方差的37.93％，具有9个特征向量（载荷> 0.70），例如电导率，总碱度，总硬度，Ca，Mg，Na，K，氯化物和硅酸盐。在24个河水水质数据集上生成的总特征向量分为四种类型即。安全（正常），低污染，中污染和高污染水域，相应的总特征向量分别分别为<0.50，> 0.50-<1.00，> 1.00-<1.50和> 1.50。为23个采样站生成的总因子得分显示总共五种类型的采样站具有安全，低，中，高和非常高的污染水平，相应的总因子得分小于零（<0.0），> 0.0-<1.50 ），（> 1.50-<3.00），（> 3.00-<4.50）和（> 4.50）。