A spatiotemporal analysis of the physicochemical parameters after the operation of the Corumbá IV reservoir (Midwest Brazil) to support better management decision

Environ Monit Assess. 2021 Apr 6;193(5):247. doi: 10.1007/s10661-021-09039-5.

Abstract

The study presents the characterization of the water quality of the Corumbá IV reservoir in the State of Goiás, in the Brazilian Cerrado biome, based on data from the operation period between 2007 and 2017. Few are known about the temporal and spatial variations in the water quality of the reservoir. Up to now, the water quality has been analyzed only from the point of view of compliance with the limits required by Brazilian environmental legislation. Therefore, the integrated analysis of water quality parameters and water body dynamics may bring important information to support decision-making in reservoir management. An exploratory analysis of the limnological data series provided by the company in charge of the hydroelectric plant was then carried out. Univariate and multivariate statistical techniques were applied to analyze the data period from 2007 to 2017. The results identify four distinct limnological phases representing the transition of the environment. The first phase (2007 to 2009) characterized by the decomposition of the flooded vegetal organic matter and subsequent phases, after 8 years (2010 to 2017), have featured the transition process from the lotic condition to the consolidation of the lentic environment. The spatial analysis of the results demonstrates that tributaries influence the water quality of the reservoir differently, probably due to the different impacts suffered in the sub-basins (e.g., sewage discharges; runoff). Although it is possible to evidence the impact of anthropic activities on water quality, the reservoir still presents characteristics of an environment with low trophic status.

Keywords: Brazil; Corumbá IV reservoir; Limnological; Spatiotemporal; Univariate and Multivariate; Water quality monitoring.

MeSH terms

  • Brazil
  • Ecosystem
  • Environmental Monitoring*
  • Rivers
  • Spatio-Temporal Analysis
  • Water Quality*