Dr Arnald Puy PhD

Dr Arnald Puy

School of Geography, Earth and Environmental Sciences
Associate Professor in Social and Environmental Uncertainties

Contact details

University of Birmingham
B15 2TT

Arnald Puy focuses on understanding and appraising uncertainties in contentious phenomena, especially those related with agriculture, climate and water resources. His research aims at providing insights for sustainability and makes use of mathematical models, uncertainty and sensitivity analysis, post-normal science and ethics of quantification.


  • 2022 – onwards: Associate Professor in Social and Environmental Uncertainties, University of Birmingham.
  • 2020 – 2022: Marie-Sklodowska Curie Global Fellow, Center for the Study of the Sciences and the Humanities, University of Bergen, Norway
  • 2019 – 2020: Marie-Sklodowska Curie Global Fellow, Ecology and Evolutionary Biology Department, Princeton University, USA.
  • 2018 – 2019: Researcher, Centre de Recherches en Archéologie et Patrimoine, Université Libre de Bruxelles, Belgium.
  • 2015 – 2017: Marie Curie Intra-European Fellow, Department of Maritime Civilizations, University of Haifa, Israel.
  • 2014 – 2015: Humboldt Research Fellow, Institute of Geography, University of Cologne, Germany.
  • 2012 – 2014: Postdoctoral Associate, Complexity and Socio-Ecological Dynamics, CSIC, Spain.
  • 2008 – 2012: Predoctoral Student, Faculty of Philosophy, Autonomous University of Barcelona, Spain.

Postgraduate supervision

Arnald Puy’s research cuts across the Humanities and the Sciences and welcomes enquiries from students interested in developing interdisciplinary profiles. He is willing to supervise and mentor students in the following fields:

  • Uncertainty and sensitivity analysis of mathematical models.
  • Appraisal of uncertainties in global climate / water models.
  • Traditional / indigenous knowledge on irrigation.
  • The use of numbers in climate / water research or in any pressing and controversial issue.
  • The use of science for policy-making.
He is also open to suggestions for supervision / mentoring in any other field involving deep uncertainties.

Other activities

Reviewer for Science, Nature Sustainability, Journal of Statistical Software, Geophysical Research Letters, Water Resources Research, Environmental Modeling & Software, Reliability Systems and Engineering Safety, Catena, Land Degradation and Development, among others. 

Arnald Puy has also reviewed for the European Research Council, the National Geographical Society and the Israel Science Foundation.


Recent publications


Saltelli, A, Kuc-Czarnecka, M, Lo Piano, S, János Lórincz, M, Olczyk, M, Puy, A, Reinert, E, Thor Smith, S & van der Sluijs, J 2023, 'Impact assessment culture in the European Union. Time for something new?', Environmental Science and Policy, vol. 142, pp. 99-111. https://doi.org/10.1016/j.envsci.2023.02.005

Di Fiore, M, Kuc-Czarnecka, M, Lo Piano, S, Puy, A & Saltelli, A 2023, 'The Challenge of Quantification: An Interdisciplinary Reading', Minerva, vol. 61, no. 1, pp. 53-70. https://doi.org/10.1007/s11024-022-09481-w

Saltelli, A & Puy, A 2023, 'What can mathematical modelling contribute to a sociology of quantification?', Humanities and Social Sciences Communications, vol. 10, no. 1, 213. https://doi.org/10.1057/s41599-023-01704-z

Puy, A, Becker, W, Lo Piano, S & Saltelli, A 2022, 'A comprehensive comparison of total-order estimators for global sensitivity analysis', International Journal for Uncertainty Quantification, vol. 12, no. 2, pp. 1-18. https://doi.org/10.1615/Int.J.UncertaintyQuantification.2021038133

Piano, SL, Borgonovo, E, Puy, A, Saltelli, A, Walsh, J, Vidoni, D & Savona, R (ed.) 2022, 'Improving the reliability of cohesion policy databases', PLOS One, vol. 17, no. 4, e0266823. https://doi.org/10.1371/journal.pone.0266823

Puy, A, Beneventano, P, Levin, S, Lo Piano, S, Portaluri, T & Saltelli, A 2022, 'Models with higher effective dimensions tend to produce more uncertain estimates', Science Advances, vol. 8, no. 42, eabn9450, pp. eabn9450. https://doi.org/10.1126/sciadv.abn9450

Piano, SL, Sheikholeslami, R, Puy, A & Saltelli, A 2022, 'Unpacking the modelling process via sensitivity auditing', Futures, vol. 144, 103041. https://doi.org/10.1016/j.futures.2022.103041

Puy, A, Saltelli, A, Piano, SL & Levin, SA 2022, 'sensobol: an R package to compute variance-based sensitivity indices', Journal of Statistical Software, vol. 102, no. 5, pp. 1-37. https://doi.org/10.18637/jss.v102.i05

Puy, A, Borgonovo, E, Piano, SL, Levin, SA & Saltelli, A 2021, 'Irrigated areas drive irrigation water withdrawals', Nature Communications, vol. 12, no. 1, 4525. https://doi.org/10.1038/s41467-021-24508-8

Puy, A, Piano, SL & Saltelli, A 2021, 'Is VARS more intuitive and efficient than Sobol’ indices?', Environmental Modelling & Software, vol. 137, 104960. https://doi.org/10.1016/j.envsoft.2021.104960

Razavi, S, Jakeman, A, Saltelli, A, Prieur, C, Iooss, B, Borgonovo, E, Plischke, E, Lo Piano, S, Iwanaga, T, Becker, W, Tarantola, S, Guillaume, JHA, Jakeman, J, Gupta, H, Melillo, N, Rabitti, G, Chabridon, V, Duan, Q, Sun, X, Smith, S, Sheikholeslami, R, Hosseini, N, Asadzadeh, M, Puy, A, Kucherenko, S & Maier, HR 2021, 'The future of sensitivity analysis: an essential discipline for systems modeling and policy support', Environmental Modelling and Software, vol. 137, 104954. https://doi.org/10.1016/j.envsoft.2020.104954


Puy, A, Massimi, M, Lankford, B & Saltelli, A 2023, 'Irrigation modelling needs better epistemology', Nature Reviews Earth & Environment. https://doi.org/10.1038/s43017-023-00459-0

Puy, A, Sheikholeslami, R, Gupta, HV, Hall, JW, Lankford, B, Piano, SL, Meier, J, Pappenberger, F, Porporato, A, Vico, G & Saltelli, A 2022, 'The delusive accuracy of global irrigation water withdrawal estimates', Nature Communications, vol. 13, no. 1, 3183. https://doi.org/10.1038/s41467-022-30731-8


Puy, A, Lankford, B, Meier, J, Kooij, SVD & Saltelli, A 2022, 'Large variations in global irrigation withdrawals caused by uncertain irrigation efficiencies', Environmental Research Letters, vol. 17, no. 4, 044014. https://doi.org/10.1088/1748-9326/ac5768


Puy, A & Saltelli, A 2022 'Mind the hubris in mathematical modeling'. https://doi.org/10.48550/arXiv.2207.12230

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