CHALLENGE

The project involves not only the development of the system, but also data collection and all other steps necessary to adjust and validate specific models for the Foz do Chapecó reservoir. In relation to customizing models for the reservoir, one of the main challenges is obtaining the in situ data needed to adjust and validate the models, which should be concomitant with the satellite flyovers and follow a complete acquisition protocol dedicated to data quality. In relation to system development, the main challenge relates to the diversity of technologies being employed in the project, such as cloud storage and processing, satellite image processing, integration of differently formatted data, and the development of a web interface to consult and display data.

DEVELOPMENT

The system was developed in the Python programming language using different cloud computing and storage services offered by Amazon Web Services (AWS). The following technical requirements were considered for its development: (1) operational monitoring capacity, (2) automated processing, (3) ability to customize, (4) scalability, (5) user friendliness and different levels of accessibility. For the pilot application in the Foz do Chapecó reservoir, models for estimating water quality parameters were adjusted and validated using field data collected from the reservoir.

RESULT

The main result of the project is a remote monitoring system for water quality in hydroelectric reservoirs, using multispectral images collected by satellites and cloud storage and computing techniques. The system can be customized to monitor the different parameters required by Brazilian standards (e.g. the CONAMA 37/2005 resolution and the ANEEL/ANA 03/2010 joint resolution). The system also supports the insertion of data obtained in situ to complement the remote monitoring, and allows the calculation of indicators and issuing alerts.