Water! The most precious natural resource on our planet is also suffering from the virus outbreak. Social distance, hygiene, and the necessity of constant environment decontamination are pushing our hydric bodies to the limit.
"Wash your hands!" "Wash your clothes straight away once you arrive at home." "Surfaces must be cleaned several times to avoid virus contamination." – These are sentences that are listened to worldwide and reinforced by the media every minute. We are scared, we need to be safe, and something that is either the possibility of help or collapse ends up to be put aside once the virus keeps spreading.
In our society, usually, our consumption standards give a hard time to nature while global warming is modifying weather behaviour. Water management systems are struggling to keep up with the changes in our habits while the use of chemical sanitizers skyrocketed. At the end of every day, our sewage systems unbalance the hydric bodies. Governments and institutions need the information to ensure the actions are taken in the speed that needs to be made to avoid any other environmental catastrophe.
In the light of science, it is possible to distinguish contaminants particles diluted in water. Physical, chemical, geological, and biological indicators derived from the theory of propagation and reflection of light by materials can be used for this purpose. Our multidisciplinary team created an algorithm that combines the use of spectral signature images and advances in remote sensing, to study temporal and spatial evolution of the suspended sediment concentration (SSC). As well, the estimate of the volume of domestic effluents diluted in water from the parameterization of the chlorophyll-a concentration index (ChlaI) can be achieved using Sentinel-2 images.
Lagoa dos Patos is the largest lagoon in Brazil and the largest barrier-lagoon in South America. It covers an area of 10,100 km2 (3,900 sq mi). The surroundings of Porto Alegre city (which have 33 municipalities) have a large concentration of industries in the oil and gas, chemical, fertilizers, and the area is inhabited by more than 4.3 million people. Industries and the high densely populated area are responsible for the generation of large volumes of effluents. Due to the characteristics of the region and the lack of efficient water monitoring systems, this gigantic natural freshwater reservoir can be easily contaminated.
Due to the social isolation imposed by the Covid-19 pandemic, it was possible to directly infer the influence of industrial production and population consumption on the quality of the water body. Since the region experiences several drought cycles and consequently pressure on water resources, the action of society and public institutions must become fast enough to encourage activities that may reduce the impact of cities on this essential resource for human life, and necessary for the fight against the epidemic. We present the case study of the Rio Guaíba lake (north lagoon).
Regarding the technical development of a solution, Sentinel-2 images were acquired, adjusted, and processed using the QGIS software (free and customizable software with our algorithms for this solution). The whole process was divided into five steps:
(1) Radiometric calibration and atmospheric correction;
(2) Calculation of the SSC value, adjusting to estimate the solid contaminants suspended in water;
(3) Estimative of the volume of domestic effluents diluted in water by the parameterization of the chlorophyll-a index;
(4) Clipping scenes of the area of interest (Rio Guaiba);
(5) Converting the results to the web interface using the Qgis2Web plugin.
Step (1) uses the SCP plugin. A restricted area of interest was selected to accelerate the application and demonstrate the efficiency of the methods in a 48 hours period. The data were extracted from data from satellite sensors (available by NASA / ESA). In the future, with the use of cloud processing through the Google Earth Engine tool, for example, we can extend the solution globally. In order to do it in a robust way we can use methods to manage big data such as deep learning and artificial intelligence.
The results provided could help to understand the potability and health of extensive water reservoirs that supply large regions, which is essential to reduce costs and time with water quality analysis.
The possibility of fast water quality analysis, as well as measuring the Ecological Footprint related to human activity on drinking water bodies, once available for public use, could help our society to avoid the damage in the environment if the pandemic increases.
The list of the data and resources used in this project is as following: