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  • Mackay_et_al-2015-Water_Resources_Research

    Rights statement: C2015. American Geophysical Union.All Rights Reserved.

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Digital catchment observatories: a platform for engagement and knowledge exchange between catchment scientists, policy makers, and local communities

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<mark>Journal publication date</mark>06/2015
<mark>Journal</mark>Water Resources Research
Issue number6
Volume51
Number of pages8
Pages (from-to)4815-4822
Publication StatusPublished
Early online date7/06/15
<mark>Original language</mark>English

Abstract

Increasing pressures on the hydrological cycle from our changing planet have led to calls for a refocus of research in the sciences of hydrology and water resources. Opportunities for new and innovative research into these areas are being facilitated by advances in the use of cyberinfrastructure, such as the development of digital catchment observatories. This is enabling research into hydrological issues such as flooding to be approached differently. The ability to combine different sources of data, knowledge, and modeling capabilities from different groups such as scientists, policy makers, and the general public has the potential to provide novel insights into the way individual catchments respond at different temporal and spatial scales. While the potential benefits of the digital catchment observatory are large, this new way of carrying out research into hydrological sciences is likely to prove challenging on many levels. Along with the obvious technical and infrastructural challenges to this work, an important area for consideration is how to enable a digital observatory to work for a range of potential end-users, paving the way for new areas of research through developing a platform effective for engagement and knowledge exchange. Using examples from the recent local-scale hydrological exemplar in the Environmental Virtual Observatory pilot project (http://www.evo-uk.org), this commentary considers a number of issues around the communication between and engagement of different users, the use of local knowledge and uncertainty with cloud-based models, and the potential for decision support and directions for future research.

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C2015. American Geophysical Union.All Rights Reserved.