Authors
Luanna Costa Dias, Luiza Carla Girard Mendes Teixeira, Lindemberg Lima Fernandes, João Batista Marcelo de Lima, Hugo de Souza Ferreira, Vinicius Silva de Oliveira
Published in
Environmental management. Volume 76. Issue 7. Jun 25, 2026. Epub Jun 25, 2026.
Abstract
Water quality monitoring is essential for water resources management, especially when conducted systematically (continuous, standardized, and with data available to users), as it generates historical time series for each observed variable. The Amazon River basin plays a crucial role in biodiversity conservation and climate regulation, in addition to supporting a wide range of economic activities, making systematic monitoring extremely valuable for decision-making. Therefore, the objective of this study is to evaluate the systematic water quality monitoring landscape in this basin. This research identified five networks operating in the region: the National Hydrometeorological Network (RHN), the Surface Water Quality Monitoring Network (RNQA), the virtual Hidrosat network, the Amazon Water, Air, and Soil Quality Monitoring Program (ProQAS/AM), and the international So Hybam Observatory.The RHN is the oldest network and has the best spatial distribution; however, it measures only basic parameters and presents temporal gaps. Hidrosat exclusively estimates suspended sediment concentration through satellite data. ProQAS/AM operates systematically in the region of Manaus (Amazonas State, Brazil), providing data for the Water Quality Index (WQI) variables of the Negro River. The RNQA is a recent initiative that includes microbiological data, established by the Brazilian National Water and Sanitation Agency (ANA) and coordinated by Brazilian states to generate continuous information; however, its stations are spatially concentrated, leaving geographic gaps. Finally, the So Hybam Observatory stands out as an international cooperation initiative focused on transboundary rivers along the Amazon system from the Andes, measuring geochemical parameters and isotopes since 2003, albeit with restrictions in temporal frequency. This study demonstrates that each dataset has specific characteristics and faces monitoring gaps in the Amazon, highlighting the need for expansion and better standardization. Nevertheless, the integration of these networks enables the development of novel studies on temporal analysis and water body classification, which are fundamental for water resources management. Furthermore, the international landscape reveals that the most recent research focuses on system integration and sampling efficiency, positioning this article as a milestone for information unification in the region.
PMID:
42348016
Bibliographic data and abstract were imported from PubMed on 25 Jun 2026.
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