Feasibility Analysis on the Construction of a Solution for Monitoring and Hydrometeorological Forecasting

Júnior, José Roberto Dantas da Silva; Souza, Filipe Milani de; Silva, Daniel Guimarães; Ferraz, Patrick Silva; Moares, Marcelo Romero de; Schafer, Alexandro Gularte; Nascimento, Erick Giovani Sperandio; Moreira, Davidson Martins

doi:10.5151/siintec2020-feasibilityanalysis

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…These models will also be costly during the training process, but assuming a sufficiently large amount of data, with proper processing of features, can be generalized proving a good accuracy and not being restricted to a period. With this, it is possible to integrate an AI module into the proposed architecture in [43] containing previously trained models and the possibility of managing algorithms to perform validations and study of comparations between these approaches and the results of the WRF-Hydro model, in the short and mediumterm, proving knowledge for long-term evaluations, optimizing the time and cost of in.…”

Section: Ai Application Modulementioning

confidence: 99%

Feasibility Analysis on the Construction of a Web Solution for Hydrometeorological Forecasting Considering Water Body Management and Indicators for the Pandemic of SARS-COV-2

Silva

Pedruzzi

Souza

et al. 2021

Preprint

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Currently, the NCAR (U.S. National Center for Atmospheric Research), the institution responsible for the WRF-Hydro (Weather Research and Forecasting - Hydro) model initiative, highlights four major global challenges: floods, pollution, droughts, and biodiversity. Thus, given the current scenario of a global pandemic caused by the Sars-CoV-2 virus (Covid19), the importance of hydrological studies, their correlation with contamination levels, and incidence of COVID-19 cases are also in the spotlight. Among the challenges around water resources management, the lack of good and representative data, especially for small water bodies and developing countries, to perform inferences and to manage these natural resources is critical. This situation applies not only to observational data and but also to input data for hydrological models. In this context, the WRF-Hydro system represents the state of the art for hydrometeorological modeling. Thus, the model emerges as a computational tool that becomes possible to provide auxiliary data for patterns analysis in time series and computational prediction. Also, with the evolution of artificial intelligence (AI), it is possible to consider the integration of this modern approach with the WRF-Hydro model simulations. Therefore, the main of this study is to analyze the feasibility of a web tool that integrates these functionalities. The coupled WRF-Hydro with AI will support the management and generate a water predictability analysis in the MATOPIBA region (Maranhão-Tocantins-Piauí-Bahia), northeastern Brazil, the focus area of this study. Although the WRF-Hydro system demonstrates efficiency in the hydrometeorological simulation for the region, the model has a range of subprocesses which has a high computational cost, especially for long-term studies. Therefore, due to the possibility of integrating these computational tools, it is proposed to develop and analyze the construction of a web tool using the WRF-Hydro system for the short and medium-term with AI tools for the short term (a few hours to a few days), to optimize the computational cost. Thus, the combined application of the WRF-Hydro and AI system can improve the water bodies management and assist the identification of contamination levels by Sars-CoV-2, given the presence of the virus in water bodies and the correlation of the pandemic with hydrological variables.

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Section: Ai Application Modulementioning

confidence: 99%

Feasibility Analysis on the Construction of a Web Solution for Hydrometeorological Forecasting Considering Water Body Management and Indicators for the Pandemic of SARS-COV-2

Silva

Pedruzzi

Souza

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Feasibility analysis on the construction of a web solution for hydrometeorological forecasting considering water body management and indicators for the SARS-COV-2 pandemic

et al. 2021

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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.

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Feasibility Analysis on the Construction of a Solution for Monitoring and Hydrometeorological Forecasting

Cited by 2 publications

References 4 publications

Feasibility Analysis on the Construction of a Web Solution for Hydrometeorological Forecasting Considering Water Body Management and Indicators for the Pandemic of SARS-COV-2

Feasibility Analysis on the Construction of a Web Solution for Hydrometeorological Forecasting Considering Water Body Management and Indicators for the Pandemic of SARS-COV-2

Feasibility analysis on the construction of a web solution for hydrometeorological forecasting considering water body management and indicators for the SARS-COV-2 pandemic

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