Jonathan Mackay

Dr Jonathan Mackay

Hydrological modeller
BGS Keyworth


Jon is a hydrological modeller with expertise in modelling land surface and subsurface hydrological processes, particularly in cold regions where strong climate-crysophere-hydrosphere coupling influences catchment water cycling (e.g. Mackay et al., 2018; Mackay et al., 2019). His research aims to improve our understanding of water resource change due to environmental pressures (e.g. climate and land use change) through developing and applying hydrological models to regions vulnerable to these changes. His research spans a range of geographical settings in countries including the UK, Philippines, India, Africa, Iceland and Peru. He is particularly interested in the world’s so called ‘water towers’ (mountains) where water cycling and resource availability are influenced by interactions between surface hydrology, groundwater and melt from snow and glaciers. These are also some of the most vulnerable regions to global climate change. Jon has a track record of using the models he develops to produce state-of-the-art hydrological projections over seasonal (Mackay et al., 2015) to decadal timescales (Prudhomme et al., 2013; Mackay et al., 2019). Underpinning his science is an expertise in quantifying model uncertainty (Mackay et al., 2015; Marchant et al., 2016; Mackay et al., 2019) so that more robust and informative model projections can be delivered to stakeholders and end users.

Jonathan Mackay’s Biography

  •  2011 – ongoing : Hydrological Modeller, BGS Keyworth.
  •  2015 –2019 : PhD. Twenty-first century glacial and hydrological change in the Virkisjökull Glacier Observatory, Iceland. University of Birmingham.
  •  2009 –2010 : MSc with Distinction, Hydrology and Water Resource Management, Imperial College London.
  •  2006 –2009 : BSc (Hons) 1st Class, Environmental Science, Lancaster University.

Research interests

  • Modelling water cycles across hydrological interfaces e.g. cryosphere->hydrosphere
  • Impact of climate change on water cycling and availability
  • Hydrological model simplification and hypothesis testing
  • Better quantification of model projection uncertainty

Current projects and collaborations

  • RAHU: Water security and climate change adaptation in Peruvian glacier-fed river basins
  • Hydro-JULES
  • PhiGO: Philippines Groundwater Outlook
  • Hydrological Outlook: a multi-partner collaboration providing 3-month ahead forecasts of groundwater levels and river flows for the UK


  • van Dijk, W M, Densmore, A, Jackson, C R, Mackay, J D, Joshi, S, Sinha, R, Shekhar, S, and Gupta, S. 2019. Spatial variation of groundwater response to multiple drivers in a depleting alluvial aquifer system, northwestern India. Progress in Physical Geography, Preeprint.
  • Mackay, J D, Barrand, N E, Hannah, D M, Krause, S, Jackson, C R, Everest, J, and Aðalgeirsdóttir, G, Black, A R. 2019. Future evolution and uncertainty of river flow regime change in a deglaciating river basin. Hydrology and earth system science, 23, 1833-1865.
  • Mackay, J D, Barrand, N E, Hannah, D M, Krause, S, Jackson, C R, Everest, J, and Aðalgeirsdóttir, G. 2018. Glacio-hydrological melt and run-off modelling: application of a limits of acceptability framework for model comparison and selection. The cryosphere, 12, 2175-2210.
  • Marchant, B, Mackay, J D, and Bloomfield, J. 2016. Quantifying uncertainty in predictions of groundwater levels using formal likelihood methods. Journal of hydrology, 540, 699-711.
  • Mackay, J D, Jackson, C R, Brookshaw, A, Scaife, A A, Cook, J, and Ward, R S. 2015. Seasonal forecasting of groundwater levels in principal aquifers of the United Kingdom. Journal of hydrology, 530, 815-828.
  • Mackay, J D, Jackson, C R, and Wang, L. 2014. A lumped conceptual model to simulate groundwater level time-series. Environmental modelling and software, 61, 229-245.
  • Prudhomme, C, Haxton, T, Crooks, S, Jackson, C, Barkwith, A, Williamson, J, Kelvin, J, Mackay, J D, Wang, L, Young, A, and Watts, G. 2013. Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain. Earth system science data, 5 (1), 101-107.

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