Using hydrodynamic and water quality variables to assess eutrophication in a tropical hydroelectric reservoir

Terezinha Ferreira De Oliveira,Isabel Leidiany De Sousa Brandão,Chris M Mannaerts,Rachel Ann Hauser-Davis,Antonio Augusto Ferreira De Oliveira,Augusto Cesar Fonseca Saraiva,Michele Araujo De Oliveira,Junior Hiroyuki Ishihara

doi:10.1016/j.jenvman.2019.109932

Abstract

Few studies have examined the influence of reservoir hydrodynamics on the water quality of its limnological zones. In this study, the relationships between the operational phases and the water quality of the limnological zones were assessed for the Amazonian reservoir Tucuruí. Limnological zones were clustered by means of an artiﬁcial neural network technique, and inputs used were water quality variables, measured at twelve stations between 2006 and 2016. Generalized Linear Models (GLMs) were then used to identify the influence of the operational phases of the reservoir on the water quality of its limnological zones. The GLM with a gamma-distributed response variable indicated that Chlorophyll-a concentrations in the riverine and transitional zones differed notably from those observed in the lacustrine zone. Chlorophyll-a concentrations were significantly lower during the operational falling water phase than in the low water phase (p < 0.05). The GLM with an inverse Gaussian-distributed response variable indicated that Secchi depth was significantly lower in the riverine than in the lacustrine limnological zone (p < 0.05). Our results suggest that more eutrophic conditions occur during the operational rising water phase, and that the area most vulnerable to eutrophication is the transitional zone. We demonstrate that the use of GLMs is suitable for determining areas and operational phases most vulnerable to eutrophication. We envisage that this information will be useful to decision-makers when monitoring the water quality of hydroelectric reservoirs with dendritic patterns and dynamic operational phases.

Highlights

Reservoirs built for the purpose of hydropower generation are large scale artificial ecosystems, which are very often used for many and varied purposes affecting the water quality of their basin (Tundisi and Tundisi, 2012)
Results of the separation of zones using the multilayer perceptron method obtained from a training dataset, test, and validation were equal to 73%, 70%, and 76%, respectively
Hydro dynamic and water quality variables that were most important in the classification of limnological zones were local depth (92%) and Secchi depth (100%), total suspended solids (TSS) (94%), total phosphorus (TP) (76%), and Chla (62%), respectively

Summary

Introduction

Reservoirs built for the purpose of hydropower generation are large scale artificial ecosystems, which are very often used for many and varied purposes affecting the water quality of their basin (Tundisi and Tundisi, 2012). These projects provide social and economic develop ment, and have severe ecological and social impacts that may impair the multiple uses of water (Le Moal et al, 2019). Anthropic activities in the areas surrounding reservoirs are known to worsen the water quality of the river basins in which they are located (Wunderlin, 2018) These activities may, in some cases, affect the water quality and volume available for electric power generation and human supply. The combination of climate change and increased nutrient loading from anthropic sources may favor harmful algae blooms (HABs), possibly fostering toxic ones, which may threaten human and animal health

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