Abstract:The Aguamilpa Dam is part of the reservoir cascade system formed by four reservoirs in the middle and lower part of the Santiago River. For decades, this system has received urban and industrial wastewater from the metropolitan area of Guadalajara and the runoff of agricultural fields located in the river basin. The present study was carried out to obtain a preliminary assessment on the concentration distribution of heavy metals (Al, Ba, Cd, Cr, Cu, Fe, Hg, Mg, Ni, Pb, and Zn) in surface sediments of the Aguam… Show more
“…The ambient temperature is a factor that could be related to the behavior of the water body. The average ambient temperature (at the reservoir area) is almost 20 • C, very similar to those observed by Rangel-Peraza et al [31] for a tropical reservoir located at a subhumid warm climate area with summer rains. Water contributions and extractions were found with no significant monthly variation, as the volume storage of the reservoir was maintained along the period of time included in the study.…”
Section: Hydrological Conditionssupporting
confidence: 86%
“…Differences between water quality features were shown in the different sampling sites. This spatial behavior meets the characteristics suggested for reservoir water quality modeling [31].…”
Section: Spatial Classification Of Parameters By Probabilistic Neuralsupporting
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.
“…The ambient temperature is a factor that could be related to the behavior of the water body. The average ambient temperature (at the reservoir area) is almost 20 • C, very similar to those observed by Rangel-Peraza et al [31] for a tropical reservoir located at a subhumid warm climate area with summer rains. Water contributions and extractions were found with no significant monthly variation, as the volume storage of the reservoir was maintained along the period of time included in the study.…”
Section: Hydrological Conditionssupporting
confidence: 86%
“…Differences between water quality features were shown in the different sampling sites. This spatial behavior meets the characteristics suggested for reservoir water quality modeling [31].…”
Section: Spatial Classification Of Parameters By Probabilistic Neuralsupporting
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.
“…It has been estimated that in the world at present there are around 45,000 dams with a water column depth of more than 15 meters 30 . However, there are no systematic studies on the influence of dams on the distribution of heavy metals in sediment, considering that a dam alters the free flow of a river to the sea; only recently has work begun in which the seasonal distribution of heavy metals is studied in a dam 31 . Considering that there are dams in a number of rivers in Chile producing disruption of free water flow, and that mineral salts may accumulate in the zone of the dam 32 , the goal of this study was to determine the concentrations of heavy metals in both water and sediments as a labile fraction (soluble, exchangeable or bonded to carbonate) and pseudo-totals in the affluent and effluent of four reservoirs (Cogotí, Corrales, La Paloma, and Recoleta).…”
RIVER flows have constant interaction between water and bed sediments; for this reason knowledge of the characteristics of the sediments is fundamental to understand water chemistry. This study determined the concentrations of heavy metals in water and sediments in the affluents and the effluents of the Mediterranean Chilean reservoirs Cogotí, Corrales, La Paloma, and Recoleta. We explore possible ecological risk and toxicity using the enrichment factor (EF), risk assessment code (RAC), threshold effect concentrations (TEC) and probable effect concentrations (PEC). The results showed that five metals: Al, Fe, Cu, Mn and Zn out of the ten measured metals were detected in both surface water and the sediments. The risk assessment code (RAC) suggested that Fe represents a medium risk in the affluent of Cogotí Reservoir: Cu, Zn and Mn represent a medium to high risk in all the dams and in both zones (affluents and effluents). The enrichment factor (EF) determined that the five metals were lithogenic. Fe, Cu, and Mn are the elements that present the greatest toxicity to microorganisms in these aquatic systems.
“…The clay, sand, silt, and organic particles deposited at the bottom of a water body as sediments come from soil erosion and decay of plants and animals; wind, rain, and anthropogenic activities may carry these particles into aquatic ecosystems especially rivers, lakes, and streams. Once inorganic and organic particulate are in the aquatic environment, heavy metals are adsorbed onto them and are incorporated into sediment resulting in raised levels of heavy metals in bottom sediment [1,2].…”
Section: Introductionmentioning
confidence: 99%
“…From four decades ago, many efforts around the world have been undertaken to assessment the behavior and distribution of heavy metals in sediments from the aquatic ecosystems [2]. In this regards, geochemical study has been used widely to estimate the impact of human activities and the degree of metal pollution on sediment quality [9][10][11].…”
Background: Soil and sediment serve as major reservoir for contaminants as they possess ability to bind various chemicals together. In this study the concentrations of heavy metals Cd, Cr and Cu were analyzed in surface sediments of Agh Gel Wetland in west of Iran. Methods: The sediment samples were taken from 10 stations. The samples were subjected to bulk digestion and chemical partitioning and Cd, Cr and Cu concentrations of the sediments were determined by ICP-OES. Geo-accumulation index (I-geo), Contamination factor (CF) and Pollution load index (PLI) were used to evaluate the magnitude of contaminants in the sediment profile. Results: The mean sediment concentrations (mg kg-1 dry weight) ranged within 0.20-0.29 (Cd), 58-71 (Cr) and 23-36 (Cu). According to the I-geo values, the sediments' qualities are classified as unpolluted to moderately polluted category. According to the CF values, the sediments' qualities are classified as low to moderate contamination. Furthermore, the PLI values indicated that there were no metal pollution exists for all sampling stations. Conclusion: The Agh Gel Wetland is potential to be threatened by chemical pollutants such as agricultural effluent. So to preserve the environment of the Agh Gel Wetland from deterioration, periodically monitoring of the water and sediment qualities is recommended.
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