Feasibility analysis on the construction of a web solution for hydrometeorological forecasting considering water body management and indicators for the SARS-COV-2 pandemic
Autor: | Patrick Silva Ferraz, Daniel Guimarães Silva, Rizzieri Pedruzzi, Filipe Milani de Souza, Carolina Sacramento Vieira, Marcelo Romero de Moraes, Erick Giovani Sperandio Nascimento, José Roberto Dantas da Silva Júnior, Davidson Martins Moreira |
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Jazyk: | angličtina |
Rok vydání: | 2021 |
Předmět: |
education.field_of_study
Water resources Sanitation Computer science business.industry Population MATOPIBA General Engineering WRF-Hydro Water supply Usability Context (language use) Hydrometeorological forecast Hydrology (agriculture) Artificial Intelligence SARS-CoV-2 (COVID-19) Hydrometeorology education business Environmental planning Research Article |
Zdroj: | AI Perspectives |
ISSN: | 2523-398X |
Popis: | The current scenario of a global pandemic caused by the virus SARS-CoV-2 (COVID19), highlights the importance of water studies in sewage systems. In Brazil, about 35 million Brazilians still do not have treated water and more than 100 million do not have basic sanitation. These people, already exposed to a range of diseases, are among the most vulnerable to COVID-19. According to studies, places that have poor sanitation allow the proliferation of the coronavirus, been observed a greater number of infected people being found in these regions. This social problem is strongly related to the lack of effective management of water resources, since they are the sources for the population's water supply and the recipients of effluents stemming from sanitation services (household effluents, urban drainage and solid waste). In this context, studies are needed to develop technologies and methodologies to improve the management of water resources. The application of tools such as artificial intelligence and hydrometeorological models are emerging as a promising alternative to meet the world's needs in water resources planning, assessment of environmental impacts on a region's hydrology, risk prediction and mitigation. The main model of this type, WRF-Hydro Weather Research and Forecasting Model), represents the state of the art regarding water resources, as well as being the object of study of small and medium-sized river basins that tend to have less water availability. hydrometeorological data and analysis. Thus, this article aims to analyze the feasibility of a web tool for greater software usability and computational cost use, making it possible to use the WRF-Hydro model integrated with Artificial Intelligence tools for short and medium term, optimizing the time of simulations with reduced computational cost, so that it is able to monitor and generate a predictive analysis of water bodies in the MATOPIBA region (Maranhão-Tocantins-Piauí-Bahia), constituting an instrument for water resources management. The results obtained show that the WRF-Hydro model proves to be an efficient computational tool in hydrometeorological simulation, with great potential for operational, research and technological development purposes, being considered viable to implement the web tool for analysis and management of water resources and consequently, assist in monitoring and mitigating the number of cases related to the current COVID-19 pandemic. This research are in development and represents a preliminary results with future perspectives. |
Databáze: | OpenAIRE |
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