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The climate crisis has caused profound changes in river basins; in various parts of the world, water availability has decreased and demand has increased. In Northern Rio de Janeiro State, conflicts over water use have intensified in recent years. Several users dispute the right to water use permits, thus generating conflicts. Mapping these conflicts contributes to water management and environmental education.

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1. Review the literature on conflicts over water use in Northern Rio de Janeiro State.

2. Catalog and classify the existing conflicts over water use within the River Basin Committees.

3. Create a digital map showing the existing conflicts.

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Mapping conflicts over water use in river basins.

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Mussels cultivated in mariculture are important for human consumption but may be exposed to microplastic contamination. As filter feeders, they can ingest these particles, which may affect their health.

In the present study aims to assess the quality of mussels, identify the presence of microplastics, and evaluate their physiological and reproductive parameters.

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1 - To assess the quality of maricultured mussels

2- To identify microplastics in mussels

3 - To evaluate their physiological and reproductive parameters

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Ecotoxicological Risk Assessment of Microplastics in the Mussel Perna Perna (Linnaeus, 1758): Impacts on the Production Chain of a Mariculture

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The continuous development of the petroleum exploration and production in the Campos basin is a great problem for the marine environment, with strong impacts on local production sites and surrounding areas. My research makes a scientific and professional contribution to the understanding of the news approach to reducing several impacts, developing technologies and applications on the site, forming new professionals, and approaching the same problems with a different vision about it. Analytical techniques, chemical characterization, and news composition of the residual effluents, machine learning are the methods to be created and development along of the doctoral program.

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1- Bibliographic analysis,

2- Academic credits for better knowledge,

3- To write and submit the articles in scientific and speciality journals,

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Produced Water in a petroleum well; Treatment, reuse an technologies development.

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Five federal rivers run through the Northwest Fluminense Region. Since the riparian zones of these water bodies are essential for protecting water resources, mapping the actions of the Public Authorities to safeguard these Permanent Preservation Areas in this region is very important. Current federal, state, and municipal legislations, satellite imagery, and any legal issues need to be analyzed for proper mapping. This will enable public actions to improve and conserve these important areas.

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1- Examine current environmental regulations;

2- Collect data from municipalities and public agencies on planning and actions for the prevention, conservation, and restoration of urban Permanent Preservation Areas;

3- Prepare a diagnosis regarding the Northwest Fluminense Region and specific to each municipality.

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Urban Permanent Preservation Areas: Mapping the actions of the Public Authorities in the Northwest Fluminense Region for their protection.

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The project aims to develop an intelligent computational assistance platform integrated with GRIPP to support researchers in the analysis, optimization, and execution of scientific code. By combining artificial intelligence with code analysis techniques, the platform is designed to identify computational bottlenecks, suggest optimization strategies, and support code parallelization and execution in a more efficient and accessible way.

The platform will also be integrated with GRIPP to assist workflows related to inverse problems and other scientific applications. Its methodology involves the use of intelligent tools for code inspection, performance analysis, and contextual support during computational tasks. In this way, the project seeks to improve efficiency, accessibility, and reproducibility in scientific research environments.

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1 - Analysis of scientific code.

2 - Identification of computational bottlenecks.

3 - Support for code parallelization and execution.

4 - Integration with GRIPP for inverse problems.

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Intelligent Computational Assistance Platform for Code Analysis, Optimization, and Execution Integrated with GRIPP (General Inverse Problem Platform)

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Technologies as Business Process Management (BPM), Data Mining (DM) and Machine Learning (ML), applyed towards the same objective, can be crucial for institutional performance and best results.

In this regard, knowledge extraction from organizational business process, related to hydric resources management, specific about the sustainability of water reuse is the main objective of the study.

This integration can enable more than the process modeling and automation, it can provide predictive insights based on actual data on water consumption, discharge, and reuse, which are essential for water governance.

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1 - Identify gaps in the literature about water governance

2 - Applly Business Process Management and AI

3 - Create a method about water reuse

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Water governance and technologies

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The city of Campos dos Goytacazes has a history of significant and recurring urban flooding due to the overflowing of the Paraíba do Sul River, the uneven occupation of urban space, and extensive urbanization in the city center. Therefore, the objective of this work is to perform hydrological simulations of flood events occurring on the left bank of the Paraíba do Sul River, within the city's urban perimeter, using hydrological models, geoprocessing tools, and the software IBER and Blender. The Blender software produces a three-dimensional simulation of the floods, developed from data generated and analyzed using the IBER software.

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1- To create maps;

2- Produce a three-dimensional (3D) representation;

3- Perform hydrodynamic simulations.

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Simulation of flood events in Campos dos Goytacazes using IBER and Blender 3D software.

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Monitoring Soil Moisture

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Water is an essential resource for life. Among the different forms in which water is stored in the environment, soil water stands out, with its availability expressed as soil moisture, a key variable in the hydrological cycle, climate, and meteorological conditions. Its understanding is relevant in several fields, including agriculture, the prediction of hydrological events, and the study of hazards related to mass movements.

Soil moisture can be monitored directly through in situ sensors, providing point-based measurements. However, the costs associated with their installation and maintenance limit their application on a large scale. In this context, remote sensing emerges as an alternative, based on biophysical variables derived from satellite sensors, enabling soil moisture estimation across different spatial and temporal scales.

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1 - Importance of water and soil moisture

2 - Applications of soil moisture

3 - Monitoring approaches

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The TSOLV project aims to develop an intelligent solver based on Physics-Informed Learning (PIL) to address direct and inverse problems in heat and mass transfer. By embedding partial differential equations (PDEs) into machine learning models, the approach ensures that predictions remain consistent with fundamental physical laws while leveraging the flexibility of data-driven methods.

The solver will be implemented in Python using deep learning frameworks such as PyTorch, TensorFlow, or DeepXDE. Its methodology incorporates PDE residuals into the loss function, enabling accurate solutions even with limited data. The model will be validated against analytical and classical numerical solutions, with a focus on stability, convergence, and computational performance.

Beyond its scientific contribution, TSOLV is designed for integration into broader AI platforms, enabling advanced simulation and decision-support capabilities. Its applications extend to engineering and environmental systems, particularly in scenarios involving complex physical processes and scarce or uncertain data.

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1 - Capability to solve direct and inverse problems.

2 - Use of physics-informed AI for data-scarce environmental systems.

3 - Development of digital twins for water systems.

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TSOLV: Intelligent Solver for Mass and Heat Transfer Problems

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Gamification has been used to engage people around the world in different topics. It refers to the use of game elements in different contexts, such as water resource management.

Currently, there are many concerns regarding water resources, especially due to the water crisis caused by the indiscriminate use of water. Nowadays, this issue has become a global concern, as highlighted by the Sustainable Development Goals (ODS).

Another important aspect is the issue of gender, as women are the main users of water but are often excluded from management and decision-making processes.

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1- Gamification

2- Water Resources

3- Gender

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Gamification for Water Resources with a gender perspective

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1 - Unwrap the science behind ordinary forward problem in oil tracking.
2 - Identify the stochasticity over trajectory patterns.
3 - Provide optimised methods to diminish the stochasticity inputs.
4 - Provide a reliable and systematic approach to find the emission point based on a random - though actual - observation at a random time.

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Computational modelling proved to be the best method to reach the forward problem in case of an oil spill. Nevertheless, this method tends to use a significant load of randomness in its inner source-codes whilst retrieving its data. Mastering these codes is of great support to calibrate the user's intentions and hold control over the output.

Needless to say that it is unexpected - to date - that science will provide an alternative to stochasticity, as there is likely to be countless phenomena, which are still to be learnt. Notwithstanding the intention of replacing the stochasticity, the aim here is to have better control over it. Consequently, providing a new and "natural" approach to find the forward problem.

As the next step in this pursuit, complex methods such as "Artificial Neural Network" and other nature-based mathematics could be applied in a classical trajectory standard so as to use a more natural approach.

The computational cost is still a matter to be resolved, due to the complexity and interaction among several different mathematical behaviour and the computer's capacity to run it thoroughly. As a step ahead: heading toward a systematic approach to find the source of a pollutant can be handy to identify illegal emissions and environmental threat origins, allowing this research to assist with the mitigation procedures.

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Pollutant trajectory identification