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  5. An Adaptable Integrated Modelling Platform to Support Rapidly Evolving Agricultural and Environmental Policy

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Preprint
en
2023

An Adaptable Integrated Modelling Platform to Support Rapidly Evolving Agricultural and Environmental Policy

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0 Files

en
2023
DOI: 10.2139/ssrn.4408349

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Laurence Jones
Laurence Jones

UK Centre for Ecology & Hydrology

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Paula A. Harrison
Kate Beauchamp
Joe Cooper
+24 more

Abstract

The utility of integrated models for informing policy has been criticised due to limited stakeholder engagement, model opaqueness, inadequate transparency in assumptions, lack of model flexibility and lack of communication of uncertainty that, together, lead to a lack of trust in model outputs. We present the ERAMMP Integrated Modelling Platform (IMP) for supporting the development of “business-critical” policies focused on agriculture, land-use and natural resource management. We demonstrate how the long-term (>5 years), iterative, two-way and continuously evolving participatory process led to the co-creation of the IMP with government, building trust and understanding in a complex integrated model. This is supported by a customisable modelling framework that is sufficiently flexible to adapt to changing policy needs in near real-time. We discuss how these attributes have facilitated cultural change within Welsh Government where the IMP is being actively used to explore, test and iterate policy design prior to final implementation.

How to cite this publication

Paula A. Harrison, Kate Beauchamp, Joe Cooper, Ian A. Dickie, Alice Fitch, Richard Gooday, Michael Hollaway, Ian Holman, Merryn Hunt, Laurence Jones, Thomas Mondain‐Monval, Daniel Sandars, G. Siriwardena, Fiona M. Seaton, Simon M. Smart, Amy Thomas, Bede West, Freya Whittaker, Edward Carnell, Robert Matthews, Sophie Neupauer, Vadim Saraev, Jens Scheffler, Philip Trembath, Massimo Vieno, Adrian Williams, R. W. Dunford (2023). An Adaptable Integrated Modelling Platform to Support Rapidly Evolving Agricultural and Environmental Policy. , DOI: https://doi.org/10.2139/ssrn.4408349.

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Publication Details

Type

Preprint

Year

2023

Authors

27

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.2139/ssrn.4408349

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