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Temporal and Spatial Study of Water Quality and Trophic Evaluation of a Large Tropical Reservoir

机译:大型热带水库水质时空研究及营养评价

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A water quality study was carried out at the Adolfo López Mateos (ALM) reservoir, one of the largest tropical reservoirs in Mexico, located within an intensive agricultural region. In this study, the seasonal and spatial variations of nine water quality parameters were evaluated at four different sites along the reservoir semiannually over a period of seven years (2012–2018), considering the spring (dry) and fall (rainy) seasons. An analysis of variance was performed to compare the mean values of the water quality parameters for the different sampling sites. Then, a multiparametric classification analysis was carried out to estimate the spatial density of the sampling points by using a probabilistic neural network (PNN) classifier. The observations (seasonal and spatial) of the water quality parameters at the ALM reservoir revealed no significant influence. The trophic status was evaluated using the Carlson Modified Trophic State Index, finding the trophic state of the reservoir at the mesotrophic level, with nitrogen being the limiting nutrient. The PNN revealed neural interactions between total suspended solids (TSS) and the other four parameters, indicating that the concentration ranges of five parameters are equally distributed and classified.
机译:在AdolfoLópezMateos(ALM)水库进行了水质研究,该水库是墨西哥最大的热带水库之一,位于集约化农业地区。在这项研究中,考虑到春季(干旱)和秋季(雨季),在七年间(2012-2018年)内,每半年对水库四个不同地点的九个水质参数的季节性和空间变化进行评估。进行方差分析以比较不同采样点的水质参数的平均值。然后,使用概率神经网络(PNN)分类器进行了多参数分类分析,以估计采样点的空间密度。对ALM水库水质参数的观测(季节和空间)显示无明显影响。使用卡尔森改良营养状态指数评估营养状态,在中营养水平下发现储层的营养状态,其中氮是限制性营养素。 PNN揭示了总悬浮固体(TSS)与其他四个参数之间的神经相互作用,表明五个参数的浓度范围是均匀分布和分类的。

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