Overall Goal
"Support water resources and soil management through the development of monitoring and predictive/forecast systems based on principles of model transparency, reproducibility, interoperability, fidelity, and flexibility."
There is a great consensus that predictive systems provide cost-effective ways for testing management solutions that balance economic and environmental factors. However, accurate prediction of hydrological and biogeochemical variables remains a major scientific challenge despite decades of research. Major challenges in computational hydrology that work on include model fidelity and reproducibility. Our objective is to develop/improve modelling and sensing systems of water quality to support decision analysis and participatory processes with provincial, national and international stakeholders and policy-makers. We aim also at creating flexible, open-source and interoperable systems that can maximize transdisciplinary research.
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GitHub pages UE-Hydro: github.com/orgs/ue-hydro/repositories Diogo Costa: github.com/DiogoCostaPT?tab=repositories SPOTLIGHT: OpenWQ model:
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Methodological Approach
Our research program explores the continuum between hydrology and biogeochemistry to address questions related to water security, climate change and water resources management. My work aims to support provincial, national and international stakeholders and policy-makers through four primary thrusts:
- Mathematical modelling,
- Monitoring systems and sensors,
- Field/laboratory observations, and
- Applied Research.