Geoethical Groundwater Modelling: Aligning Decision-Support Models with the Scientific Method

Rui Hugman, John Doherty

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Management of groundwater resources is increasingly reliant on numerical simulation. Unfortunately, decision-support modelling is often conducted under the premise that predictive reliability increases with modelling complexity. In truth, while modelling complexity can support quantification of predictive uncertainty, the latter is a function of data availability. Excessive complexity can often erode, rather than enhance, a model’s ability to quantify and reduce the uncertainties of decision-critical predictions by reducing its capacity to assimilate prediction-salient information. We submit that a groundwater model is more productively viewed as a data assimilator for decision-pertinent information than as simulating subsurface processes, even though the latter role (though imperfect) underpins the former. Assimilated data may, or may not, allow rejection of the hypothesis that a certain course of management action will have adverse consequences. Either way, the decision-making process requires that this hypothesis be tested. In the following document, we outline how decision-support environmental modelling can be implemented with the scientific method, and discuss how uncertainties of decision-salient predictions can be addressed with appropriate model complexity so that stakeholder expectations are better aligned with what models can and cannot deliver to the decision-making process.

Original languageEnglish
Title of host publicationAdvances in Science, Technology and Innovation: Theory and Practice for a Sustainable Development
Subtitle of host publicationProceedings of the 1st Congress on Geoethics and Groundwater Management (GEOETH&GWM’20), Porto, Portugal 2020
EditorsManuel Abrunhosa, António Chambel, Silvia Peppoloni, Helder I. Chaminé
Place of PublicationCham, Switzerland
PublisherSpringer Nature
Pages425-428
Number of pages4
ISBN (Electronic)978-3-030-59320-9
ISBN (Print)978-3-030-59319-3
DOIs
Publication statusPublished - 2021
Externally publishedYes
Event1st Congress on Geoethics and Groundwater Management - , Portugal
Duration: 18 May 202022 May 2020
Conference number: 1

Publication series

NameAdvances in Science, Technology and Innovation
ISSN (Print)2522-8714
ISSN (Electronic)2522-8722

Conference

Conference1st Congress on Geoethics and Groundwater Management
Country/TerritoryPortugal
Period18/05/2022/05/20

Keywords

  • Complexity
  • Decision support
  • Modelling
  • Scientific method
  • Uncertainty

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