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Spatial variability of surface water quality in a large Brazilian semiarid reservoir and its main tributaries

机译:大型巴西半干旱水库地表水质的空间变异及其主要支流

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Brazil has one of the greatest hydroelectric potential in the world with high number of reservoirs for the electricity generation. However, little is known about the influence of these environments on the water quality. The water quality monitoring data from 14 stations distributed throughout the Irapé HPP reservoir (lentic environment), and its main tributaries (lotic environment), between the years 2008 and 2018, were evaluated and compared to assess the spatial variability of water quality. The analyzed parameters included total alkalinity, thermotolerant coliforms, electric conductivity, biochemical oxygen demand, dissolved iron, total phosphorus, nitrate, total ammoniacal nitrogen, dissolved oxygen, pH, total dissolved solids, sulfate, water temperature, and turbidity. Cluster analysis (CA), Kruskal–Wallis (KW) tests, Spearman rank-order correlation, and principal component analysis (PCA) were applied to identify and compare the relationship between the main parameters in the lotic and lentic environments. The CA resulted in four clusters according to proximity and the environment type (lotic or lentic). In general, the water quality showed better conditions in the reservoir and in the lotic stations on the immediate surround. The results may be associated with the greater sedimentation in the lentic environment. The analyses indicated that agricultural activities and the geochemical characteristics of the region are the main responsible for changes in the water quality.
机译:巴西在世界上拥有最大的水电潜力之一,为发电量有很多的水库。然而,对这些环境对水质的影响很少。评估并比较2008年和2018年在整个IRAPéHPP储层(犹豫环境)以及2018年之间分布的14个站点的水质监测数据,并进行了评估了水质的空间变异性。分析的参数包括总碱度,热电子大肠菌,电导率,生化氧需求,溶解铁,总磷,硝酸盐,总氨基氮,溶解氧,pH,总溶解固体,硫酸盐,水温和浊度。群集分析(CA),Kruskal-Wallis(kW)测试,Spearman等级相关性和主成分分析(PCA)被应用于识别和比较大陆和偶联环境中的主要参数之间的关系。 CA导致根据邻近和环境类型(奶油或熊熊)的四种簇。一般而言,水质在水库和立即环绕的汽水站中表现出更好的条件。结果可能与辅助环境中的沉降更大。分析表明,该地区的农业活动和地球化学特征是对水质变化的主要负责。

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