A study of the water quality of the Adolfo López Mateos Reservoir (ALMD) was developed through different indicators from a spatial and seasonal perspective. Variables related to the general characteristics of water quality, trophic level, and ecological risk were assessed through the National Sanitation Foundation–Brown Water Quality Index (WQINSF–BROWN), the Carlson Trophic State Index (TSICARLSON) and the Håkanson Ecological Risk Index (RIHÅKANSON). Using data from physical, chemical, and biological parameters obtained from four sampling points in the ALMD, the water quality was assessed in each model used. The results indicated that the reservoir presents a water quality classified as “medium” (WQINSF–BROWN = 70), where significant variations in the concentrations of some parameters are observed. The reservoir showed a general trophic state (TSIGENERAL-AVERAGE = 43.04) classified as “mesotrophic”. The ecological risk analysis achieved the best classification of the methodology, discarding contamination by heavy metals in surface waters. This type of applied methodology will help in decision-making tools in the dam, and can be applied in other dams in the region.
A water quality index (WQI) for the Adolfo López Mateos Dam (ALMD) was developed based on statistical multiparameter tools assisted with linear programming. ALMD was selected due to its social and economic significance in Sinaloa, the state with the highest agricultural production in Mexico. Twenty-six water-quality parameters were analyzed for four sampling points distributed along the dam during 2012–2017. The data were analyzed using Pearson's correlation matrix, principal components analysis (PCA) and sensitivity analysis (SA). Results indicated that variables explaining spatial and temporal water quality distribution at ALMD were total suspended solids, fecal coliforms, pH, dissolved oxygen, chemical oxygen demand, nitrate nitrogen, organic nitrogen, ammonium nitrogen, total phosphorus, orthophosphates and chlorophyll a. A series of pondering weights (Wi) were obtained from the PCA analysis. Every Wi was multiplied by the probability function of the specific parameter (SIi) to generate the WQIALMD model. The model was applied to address water quality at ALMD which describes the general overall water quality in the dam as ‘good’. Finally, a sensitivity analysis for the model showed that the most sensitive WQI variables were: fecal coliforms, total phosphorus, organic nitrogen, and chlorophyll a.
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.
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