Water quality longitudinal profile of the Paraíba do Sul River, Brazil during an extreme drought event. (7th June 2017)

• Record Type: Journal Article
• Authors: Pacheco, Felipe S.; Miranda, Marcela; Pezzi, Luciano P.; Assireu, Arcilan; Marinho, Marcelo M.; Malafaia, Márcio; Reis, André; Sales, Matias; Correia, Gilsinéia; Domingos, Patrícia; Iwama, Allan; Rudorff, Conrado; Oliva, Pedro; Ometto, Jean P.
• Other Names: Xenopoulos Marguerite guestEditor.; Downing John A. guestEditor.; Kumar M. Dileep guestEditor.; Menden‐Deuer Susanne guestEditor.; Voss Maren guestEditor.
• Is Part Of: Limnology and oceanography. Volume 62(2017)Supplement 1
• Page Start: S131
• Page End: S146
• Publication Date: 2017-06-07
• Subjects: Limnology -- Periodicals; Oceanography -- Periodicals; Océanographie; Limnologie; Limnology; Oceanography; Computer network resources; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); Periodicals; 551.4805
• DOI: 10.1002/lno.10586
• Languages: English
• ISSNs: 0024-3590

Abstract

Abstract: This work addresses the relationships between Land Use/Land Cover (LULC) and water quality in the Paraíba do Sul River (PSR), located in one of the most populated regions in Brazil. We conducted a water sampling program (analyzing nitrate, ammonium, phosphate, turbidity, total carbon, oxygen concentration, and conductivity) during a severe drought period from 2014 to 2016. The 210 samples were spaced about 5 km apart from headwaters to the Atlantic Ocean and taken over 63 d. We calculated a water quality index and applied a self‐organizing map (SOM) to explore the relationship between LULC and water quality. There was a significant influence on water quality from the urban area's socioeconomic profile. This observation reflects the influence of cities with a high population density and a low economic condition, which leads to further degradation and erosion of the riverbanks. The most degraded reservoir of the PSR (Funil) partially buffers these effects by retaining deposited sediments and nutrient loads, leading to downstream water quality improvement. Better management practices of the riverbanks in the lower reach contribute to additional water quality improvements. Three major clusters identified using the SOM had completely different and explainable water quality patterns, suggesting an abrupt change in water quality due to human interventions. This information is crucial to improve management projects for the river at a watershed level, and with the expectation of future water shortages.