Description
Rohini Kumar, Andreas Musolff, Daniel Graeber
This plenary focuses on feedback loops between data and models, highlighting their significant potential for advancing the IP as a unique hub for innovative freshwater resource analysis, both now and in the future. We explore these feedback loops from three approaches that we are using in the IP work: deductive, inductive, and a combined approach.
- Deductively, we test existing theories on data, such as ecological hypotheses on the links between nutrients and ecosystem functioning.
- Inductively, we identify patterns within data to generate new hypotheses, such as the effects of catchment land use or climate on nutrient export.
- In combined approaches, we employ algorithmic water quality models that integrate inductive pattern recognition with deductive testing.
We will showcase examples of these approaches, discussing their strengths and limitations, and aim to foster open communication among colleagues on the interconnections between models and data across disciplinary boundaries.
