A predictive modelling tool for assessing climate, land use and hydrological change on reservoir quality.
Ficheiros
Data
2012
Autores
Santos, João Carlos Andrade dos
Lopes, Domingos Manuel Mendes
Trindade, Henrique Manuel da Fonseca
Cabral, João Alexandre
Santos, Mário
Lourenço, José Manuel Martinho
Aranha, José Tadeu Marques
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Resumo
Reservoirs are fundamental for water and energy supply but vulnerable to impacts including climate
change. This paper outlines the steps in the development of a model to predict how climate, land
use and hydrological change could affect the physiochemical and ecological quality of reservoirs in
Portugal’s Douro region. Climatic data will be downscaled for subsequent finer spatial scale models
to develop scenarios and outputs. Field observations and satellite imagery analysis will create dynamic
maps providing data on change in land use and vegetation cover, while Artificial Neural Networks
will determine how climate, land use and vegetation cover change may influence catchment hydrology.
Data from field surveys of biological indicators, greenhouse gas emissions plus additional
research will be applied in the Stochastic Dynamic Methodology, a sequential modelling process
based on statistical parameter estimation, developed to predict and model physiochemical and
ecological changes in reservoirs. This interdisciplinary approach will provide vital modelling tools for
end users essential for water resource management in Portugal and to comply with the EU Water
Framework Directive.
Descrição
Palavras-chave
Portugal , Climate change , Lande use , Hydrology , Reservoir , Predictive modelling
Citação
Hughes, S. J. el al, 2012