Integrated modeling in urban hydrology: reviewing the role of monitoring technology in overcoming the issue of ‘big data’ requirements

Hutchins, Michael G. ORCID: https://orcid.org/0000-0003-3764-5331; McGrane, Scott J.; Miller, James D. ORCID: https://orcid.org/0000-0002-7705-8898; Hagen-Zanker, Alex; Kjeldsen, Thomas R.; Dadson, Simon J.; Rowland, Clare S. ORCID: https://orcid.org/0000-0002-0459-506X. 2017 Integrated modeling in urban hydrology: reviewing the role of monitoring technology in overcoming the issue of ‘big data’ requirements. Wiley Interdisciplinary Reviews: Water, 4 (1). 10.1002/wat2.1177

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Abstract/Summary

Increasingly, the application of models in urban hydrology has undergone a shift toward integrated structures that recognize the interconnected nature of the urban landscape and both the natural and engineered water cycles. Improvements in computational processing during the past few decades have enabled the application of multiple, connected model structures that link previously disparate systems together, incorporating feedbacks and connections. Many applications of integrated models look to assess the impacts of environmental change on physical dynamics and quality of landscapes. Whilst these integrated structures provide a more robust representation of natural dynamics, they often place considerable data requirements on the user, whereby data are required at contrasting spatial and temporal scales which can often transcend multiple disciplines. Concomitantly, our ability to observe complex, natural phenomena at contrasting scales has improved considerably with the advent of increasingly novel monitoring technologies. This has provided a pathway for reducing model uncertainty and improving our confidence in modeled outputs by implementing suitable monitoring regimes. This commentary assesses how component models of an exemplar integrated model have advanced over the past few decades, with a critical focus on the role of monitoring technologies that have enabled better identification of the key physical process. This reduces the uncertainty of processes at contrasting spatial and temporal scales, through a better characterization of feedbacks which then enhances the utility of integrated model applications.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1002/wat2.1177
UKCEH and CEH Sections/Science Areas:	Parr Rees (from October 2014) Reynard
ISSN:	2049-1948
NORA Subject Terms:	Hydrology Data and Information
Date made live:	20 Sep 2016 14:03 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/514202

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