Abstract
Summary1. There are increasing demands to predict ecohydrological responses to future changes in catchments but such predictions will be inevitably uncertain because of natural variability and different sources of knowledge (epistemic) uncertainty.2. Policy setting and decision‐making should therefore reflect these inherent uncertainties in both model predictions and potential consequences.3. This is the focus of a U.K. Natural Environment Research Council knowledge exchange project called the Catchment Change Network (CCN). The aim is to bring academics and practitioners together to define Guidelines for Good Practice in incorporating risk and uncertainty into assessments of the impacts of change.4. Here, we assess the development of such Guidelines in the context of having catchment models of everywhere.
Highlights
We assess the development of such Guidelines in the context of having catchment models of everywhere
The biogeochemical processes affecting water quality in surface waters are not that well understood. The impact of those processes on biodiversity and ecological systems is not well understood. Faced with such a range of uncertainties in knowledge and the natural randomness of environmental forcing, there is a real question as to whether the predictions made by models of catchment processes, and the way in which they might change in the future, might be useful in informing management decisions about future investment to effect improvements in water quality and ecological status
We wish to minimise both Type I and Type II errors, but the nature of the epistemic errors in the modelling process means that this is very difficult to achieve securely (Beven, 2010). Such hypothesis testing is well developed within a statistical framework when we can consider that the sources of uncertainty involved are fundamentally random in nature
Summary
1. There are increasing demands to predict ecohydrological responses to future changes in catchments but such predictions will be inevitably uncertain because of natural variability and different sources of knowledge (epistemic) uncertainty. 2. Policy setting and decision-making should reflect these inherent uncertainties in both model predictions and potential consequences. This is the focus of a U.K. Natural Environment Research Council knowledge exchange project called the Catchment Change Network (CCN). The aim is to bring academics and practitioners together to define Guidelines for Good Practice in incorporating risk and uncertainty into assessments of the impacts of change. 4. Here, we assess the development of such Guidelines in the context of having catchment models of everywhere
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