EGU25-13900, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-13900
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Assumptions in global irrigation modelling are mostly pragmatic, not empirical
Seth Nathaniel Linga1, Carmen Aguiló1, Joshua Larsen1, Michela Massimi2, Nanxin Wei1, and Arnald Puy1
Seth Nathaniel Linga et al.
  • 1School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, United Kingdom
  • 2School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh EH8 9JX, United Kingdom

Mathematical models are idealised representations of real-world processes and must balance the specific characteristics of the object of study with simplifications to ensure usability. In other words: they have to rely on both empirical (backed by data and research) and pragmatic (designed to facilitate computation, abstractions) assumptions. However, we do not know how many of the assumptions embedded in global irrigation models (GIM) fall into each category. Given that pragmatic assumptions are more flexible and can be replaced, changed or removed, this knowledge gap constrains our ability to delineate the uncertainties in these models and assess how reliable their results are. 

To tackle this issue, we used sensitivity auditing, a framework for evaluating both quantitative and qualitative assumptions. We systematically analysed 50 documents of nine GIMs and extracted all the assumptions that underpin the simulation of global irrigation water withdrawals. We grouped them into relevant facets of irrigation (climate, crop, soil moisture, irrigation practices, and water source) and classified each assumption as pragmatical or empirical in nature using a philosophy of science perspective.

Our analysis reveals that irrigation models are largely guided by pragmatic considerations. Of approximately 100 identified assumptions, over 70% lack empirical support, with most idealising farmer behaviour. Moreover, 40% of these pragmatic claims are common to at least two models, suggesting that modellers tend to follow each other's assumptions, irrespective of their empirical validity.

The widespread reliance on pragmatic assumptions in GIMs suggests that their uncertainty space is much larger than previously thought, provided that pragmatic assumptions are potentially changeable without jeopardising the representational capacity of the model. The effect that changing pragmatic assumptions has on the output of GIMs deserves further exploration. Our findings underscore the need to appraise the uncertainty in model assumptions to foster transparency and improve the epistemic role and utility of GIMs in society.

How to cite: Linga, S. N., Aguiló, C., Larsen, J., Massimi, M., Wei, N., and Puy, A.: Assumptions in global irrigation modelling are mostly pragmatic, not empirical, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13900, https://doi.org/10.5194/egusphere-egu25-13900, 2025.