An Overview of Methods to Identify and Manage Uncertainty for Modelling Problems in the Water–Environment–Agriculture Cross-Sector

Conference paper
Part of the Mathematics for Industry book series (MFI, volume 28)

Abstract

Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclectic treatment in these circumstances, some of it being more qualitative and empirical. Here, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.

Keywords

Mathematics-for-Industry Water resources Uncertainty assessment Uncertainty quantification 

Notes

Acknowledgements

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA-0003525. The article is a contribution to the NSF-funded National Socio-Environmental Synthesis Center project on Effective core practices for model-based integrated water resources management.

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© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Australian National UniversityCanberraAustralia
  2. 2.Sandia National LaboratoriesAlbuquerqueUSA

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