Prezados alunos,

Neste mês de Março de 2023 estaremos recebendo três professores estrangeiros que irão ministrar disciplinas no PPGTA-UFMS. Este intercâmbio faz parte do projeto de internacionalização CAPES PrInt “Urban water: toward water security” coordenado pelo Prof. José Marcato Junior.

Para se inscrever na disciplina envie para e-mail do PPGTA (pgta.faeng@ufms.br) até o dia 12/03/2023  as seguintes informações:

Nome:

RGA:

Disciplinas que pretende cursar (ver abaixo):

Segue abaixo as três disciplinas que serão oferecidas em Inglês no mês de Março, 2023:

1. Hydrologic Data Visualization (13/03/2023 a 17/03/2023) – 30h (08 às 11h e 14 às 17h)

Prof. Samuel Zipper, Kansas Geological Survey/Department of Geology, University of Kansas

https://geo.ku.edu/people/sam-zipper

Course overview:  A picture is worth 1000 words, but only if the graphic is well-designed to convey the appropriate message to the target audience of the visualization. This short course will provide hydrology-oriented training in effective visualization techniques that will help students understand the hydrologic phenomena they are investigating and clearly convey their findings. Students will get hands-on experience with the development of figures that are common in hydrologic applications including conceptual models and quantitative plots, with a focus on best practices for designing effective, accessible, and reproducible visualizations. The course will include strategies for how visualizations can be designed to meet the needs of different target audiences (scientists, stakeholders, public) and presentation formats (paper, report, poster, web). Course participants will develop and improve figures using their own data, provide peer-to-peer feedback, and leave the course with a portfolio of visualizations and strategies that can be used in future presentations and publications.

2. Flood forecasting and early warning systems (20/03/2023 a 24/03/2023) – 15h (14 às 17h)

Profa. Maria-Helena Ramos (INRAE, France)

https://blogs.egu.eu/divisions/hs/author/ramos/

Course overview:  Flash floods are characterized by the fast rise time of water levels (often less than 6 to 12 hours), typically in steep and small or medium sized catchments. They are usually the result of high intensity, convective rain falling over catchments with localized saturated soils or infiltration excess in areas where the soil has a reduced infiltration capacity. Understanding the space-time variability of flood-generating processes is key for effective catchment modelling and flood forecasting. There is a variety of hydrological modelling approaches in the literature for flood forecasting: from conceptual models (mostly used by operational flood-forecasting services) to physically-based models, as well as from lumped (at the catchment scale) models to semi-distributed or fully distributed (grid-based) rainfall-runoff models. Regardless of the type of modelling approach adopted, hydrological models have a common goal towards reproducing the catchment’s dynamics and response to rainfall events. They are developed with a specified model structure, which is often based on a certain number of hypotheses and on the modeller’s perceptions of the relevant processes to be considered in the rainfall-runoff transformation. Understanding how hydrological models work is crucial for flood forecasting and to design early warning systems in support to decision-making.

3. State-of-the-art deep learning for environmental applications (27/03/2023 a 30/03/2023) – 15h (14 às 17h)

Prof. Keiller Nogueira (University of Stirling, UK)

https://www.stir.ac.uk/people/1427473

Course overview:  Flooding in urban areas from extreme rainfalls has caused material, economic, environmental and human losses in several locations around the world. Flood forecasting is particularly relevant in urban environments, where most of the population is concentrated. The cities are in permanent growth and development, which is usually faster than the development of the municipal drainage system. It is necessary to develop and evaluate methods to generate land cover maps and digital terrain models, which are required as input data for hydrological applications. Deep learning techniques compose the state-of-the-art to generate land cover and 3D maps.

Iremos solicitar aos professores do PPGTA que liberem os alunos para participar das disciplinas nos períodos que existam conflitos de horários.

As vagas são limitadas a capacidade de nossa sala de aula, assim façam a inscrição com antecedência.

Obrigado,