In the present study, evaluation of spatial variations and interpretation of Zohrehh River water quality data were made by using multivariate analytical techniques including factor analysis and cluster analysis also the Arc GIS® software was used. The research method was formulated to achieve objectives herein, including field observation, numerical modeling, and laboratory analyses. The results showed that dataset consisted of 11,250 observations of seven-year monitoring program (measurement of 15 variables at 3 main stations from April 2010 to March 2017). Factor analysis with principal component analysis extraction of the dataset yielded seven varactors contributing to 82% of total variance and evaluated the incidence of each varactor on the total variance. The results of cluster analysis became complete with t-test and made water quality comparison between two clusters possible. Results of factor analysis were employed to facilitate t-test analysis. The t-test revealed the significant difference in a confidence interval of 95% between the mean of calculated varactors 1, 2, 6 and 7 between two clusters, but there was no significant difference in the mean of other varactors 3, 4 and 5 between two groups. The result shows the effect of agricultural fertilizers on stations located at downstream of the ASK dam.

在本研究中，通过使用包括因子分析和聚类分析在内的多变量分析技术以及 Arc GIS® 软件，对 Zohrehh 河水质数据进行了空间变化评估和解释。研究方法的制定是为了实现本文的目标，包括实地观察、数值建模和实验室分析。结果表明，该数据集由对7年监测程序的11,250次观测组成（从2010年4月至2017年3月在3个主站测量了15个变量）。对数据集进行主成分分析提取的因子分析产生了占总方差 82% 的七个变容器，并评估了每个变容器在总方差上的发生率。聚类分析的结果通过 t 检验变得完整，并使两个聚类之间的水质比较成为可能。因子分析的结果用于促进 t 检验分析。t 检验显示两个聚类之间计算的变容二极管 1、2、6 和 7 的均值在 95% 的置信区间存在显着差异，但其他变容二极管 3、4 和 5 的均值之间没有显着差异。两组。结果显示了农业肥料对位于 ASK 大坝下游的站点的影响。但两组之间其他变容二极管3、4和5的平均值无显着差异。结果显示了农业肥料对位于 ASK 大坝下游的站点的影响。但两组之间其他变容二极管3、4和5的平均值没有显着差异。结果显示了农业肥料对位于 ASK 大坝下游的站点的影响。