Picture of  Jim Freer

Jim Freer Visiting Professor

University of Saskatchewan

Research Area(s)

  • Uncertainty Analysis
  • Conceptual modelling
  • Catchment Hydrology
  • Model evaluation
  • Predictive diagnostics
  • Large sample hydrology
  • UAS operations

Academic History

  • PhD, 1998: Hydrology, Lancaster University, Lancaster, United Kingdom
  • BSc, 1990: Environmental Science, Lancaster University, Lancaster, United Kingdom

Background and Interests

Jim is a Visiting Professor of Hydrology at the University of Saskatchewan, an honorary Professor at the University of Bristol, and an editor of HESS. Jim's research interests currently involve:

  1. Understanding uncertainties in environmental modelling problems
  2. Developing and evaluating semi-distributed conceptual hydrological models
  3. Large sample hydrology and the inclusion of human impacts on catchment hydrological modelling

Detailed Description:
My research has been built upon understanding environmental processes, I explore and develop methodologies to understand hillslope and catchment scale hydrological, water quality and erosional processes. This results in a fascinating interplay between observations, data analysis, building conceptual models as hypotheses testing tools and developing frameworks for model evaluation to quantify and formalise our process understanding. In essence to bring these elements together, and what I am known for internationally, is the coupling of innovative conceptual model designs and the development of uncertainty analysis techniques to explore our predictive capability. My research into uncertainty analyses has been world leading in hydrology over the last 10-15 years and has changed the way the science examines predictive computer model performance. My science vision is the exploration of the considerable challenges of how we best conceptualise real world processes whilst recognising the limitations and errors in our observations that both drive and are used to assess model performance. My techniques can be applied generically to many environmental problems. This has enabled me to reflect on the limits of modelling, and pragmatically what types of models and data are useful in determining if our models give good predictions for the right reasons, and how we evaluate that in complex real world systems. 

Previous Experience

  • 2020-present: Visiting Professor of Hydrology, University of Saskatchewan, Canmore, Alberta, CANADA.
  • 2019-present: Honorary Professor of Hydrology, University of Bristol, Bristol, UK.
  • 2012-2019: Professor of Hydrology, University of Bristol, Bristol, UK.
  • 2010-2012: Reader in Hydrology, University of Bristol, Bristol, UK.
  • 2008-2010: Senior Lecturer, University of Bristol, Bristol, UK.
  • 2005-2008: Research Fellow, Lancaster University, Lancaster, UK.
  • 1998-2004: Research Associate, Lancaster University, Lancaster, UK.
  • 1994-1997: Research Associate, College of Forestry, SUNY, Syracuse, USA.
  • 1991-1993: Research Assistant, Lancaster University, Lancaster, UK.

Publications

Jim has authored or co-authored over 110 journal articles since receiving his PhD at Lancaster University in 1998.

  • Lane, R.A., Coxon, G., Freer, J.E., Wagener, T., Johnes, P.J., Bloomfield, J.P., Greene, S., Macleod, C.J.A. and Reaney, S.M. (2019) Benchmarking the predictive capability of hydrological models for river flow and flood peak predictions across over 1000 catchments in Great Britain. Hydrology and Earth System Sciences 23(10), 4011-4032
  • Knoben, W.J.M., Freer, J.E., Fowler, K.J.A., Peel, M.C. and Woods, R.A. (2019) Modular Assessment of Rainfall-Runoff Models Toolbox (MARRMoT) v1.2: an open-source, extendable framework providing implementations of 46 conceptual hydrologic models as continuous state-space formulations. Geoscientific Model Development 12(6), 2463-2480. DOI: 10.5194/gmd-12-2463-2019
  • Schellenberg, B., Richardson, T., Watson, M., Greatwood, C., Clarke, R., Thomas, R., Wood, K., Freer, J., Thomas, H., Liu, E., Salama, F. and Chigna, G. (2019) Remote sensing and identification of volcanic plumes using fixed-wing UAVs over Volcan de Fuego, Guatemala. Journal of Field Robotics 36(7), 1192-1211. DOI: 10.1002/rob.21896
  • Coxon, G., Freer, J., Lane, R., Dunne, T., Knoben, W.J.M., Howden, N.J.K., Quinn, N., Wagener, T. and Woods, R. (2019) DECIPHeR v1: Dynamic fluxEs and ConnectIvity for Predictions of HydRology. Geoscientific Model Development 12(6), 2285-2306
  • Lloyd, C.E.M., Johnes, P.J., Freer, J.E., Carswell, A.M., Jones, J.I., Stirling, M.W., Hodgkinson, R.A., Richmond, C. and Collins, A.L. (2019) Determining the sources of nutrient flux to water in headwater catchments: Examining the speciation balance to inform the targeting of mitigation measures. Science of the Total Environment 648, 1179-1200
  • Knoben, W.J.M., Woods, R.A. and Freer, J.E. (2019) Global bimodal precipitation seasonality: A systematic overview. International Journal of Climatology 39(1), 558-567
  • Nijzink, R.C., Almeida, S., Pechlivanidis, I.G., Capell, R., Gustafssons, D., Arheimer, B., Parajka, J., Freer, J., Han, D., Wagener, T., van Nooijen, R.R.P., Savenije, H.H.G. and Hrachowitz, M. (2018) Constraining Conceptual Hydrological Models With Multiple Information Sources. Water Resources Research 54(10), 8332-8362
  • Lewis, E., Quinn, N., Blenkinsop, S., Fowler, H.J., Freer, J., Tanguy, M., Hitt, O., Coxon, G., Bates, P. and Woods, R. (2018) A rule based quality control method for hourly rainfall data and a 1 km resolution gridded hourly rainfall dataset for Great Britain: CEH-GEAR1hr. Journal of Hydrology 564, 930-943
  • Fowler, K., Coxon, G., Freer, J., Peel, M., Wagener, T., Western, A., Woods, R. and Zhang, L. (2018) Simulating Runoff Under Changing Climatic Conditions: A Framework for Model Improvement. Water Resources Research 54(12), 9812-9832
  • Kiang, J.E., Gazoorian, C., McMillan, H., Coxon, G., Le Coz, J., Westerberg, I.K., Belleville, A., Sevrez, D., Sikorska, A.E., Petersen-Overleir, A., Reitan, T., Freer, J., Renard, B., Mansanarez, V. and Mason, R. (2018) A Comparison of Methods for Streamflow Uncertainty Estimation. Water Resources Research 54(10), 7149-7176
  • Beven, K.J., Almeida, S., Aspinall, W.P., Bates, P.D., Blazkova, S., Borgomeo, E., Freer, J., Goda, K., Hall, J., Phillips, J.C., Simpson, M., Smith, P.J., Stephenson, D.B., Wagener, T., Watson, M. and Wilkins, K.L. (2018) Epistemic uncertainties and natural hazard risk assessment - Part 1: A review of different natural hazard areas. Natural Hazards and Earth System Sciences 18(10), 2741-2768
  • Robins, P.E., Lewis, M.J., Freer, J., Cooper, D.M., Skinner, C.J. and Coulthard, T.J. (2018) Improving estuary models by reducing uncertainties associated with river flows. Estuarine Coastal and Shelf Science 207, 63-73
  • Knoben, W.J.M., Woods, R.A. and Freer, J.E. (2018) A Quantitative Hydrological Climate Classification Evaluated With Independent Streamflow Data. Water Resources Research 54(7), 5088-5109
  • Zischg, A.P., Felder, G., Weingartner, R., Quinn, N., Coxon, G., Neal, J., Freer, J. and Bates, P. 2018. Effects of variability in probable maximum precipitation patterns on flood losses. Hydrology and Earth System Sciences 22(5), 2759-2773
  • Guillod, B.P., Jones, R.G., Dadson, S.J., Coxon, G., Bussi, G., Freer, J., Kay, A.L., Massey, N.R., Sparrow, S.N., Wallom, D.C.H., Allen, M.R. and Hall, J.W. 2018. A large set of potential past, present and future hydro-meteorological time series for the UK. Hydrology and Earth System Sciences 22(1), 611-634
  • Brenner, S., Coxon, G., Howden, N.J.K., Freer, J. and Hartmann, A. 2018. Process-based modelling to evaluate simulated groundwater levels and frequencies in a Chalk catchment in south-western England. Natural Hazards and Earth System Sciences 18(2), 445-461
  • Ockenden, M.C., Tych, W., Beven, K.J., Collins, A.L., Evans, R., Falloon, P.D., Forber, K.J., Hiscock, K.M., Hollaway, M.J., Kahana, R., Macleod, C.J.A., Villamizar, M.L., Wearing, C., Withers, P.J.A., Zhou, J.G., Benskin, C.M.H., Burke, S., Cooper, R.J., Freer, J.E. and Haygarth, P.M. 2017. Prediction of storm transfers and annual loads with data-based mechanistic models using high-frequency data. Hydrology and Earth System Sciences 21(12), 6425-6444