Dr David McInerney
Research Associate
School of Civil, Environmental and Mining Engineering
Faculty of Engineering, Computer and Mathematical Sciences
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
My research interests involve the use of mathematical and statistical models to improve the understanding and management of physical systems. Areas which my research has focussed on include
- Quantifying uncertainty in hydrological predictions
- Developing statistical models for emulating complex climate models
- Robust decision making with respect to uncertain future climate change
- Hydrodynamic modelling of lakes and flood plains
- Numerical and statistical modelling of geological processes
Check out some of my recent research on the Intelligent Water Decisions Blog and my talk at the 2016 DEWNR NRM Science Conference
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Appointments
Date Position Institution name 2016 - 2016 Principal Hydrologist Government of South Australia, Adelaide 2012 Senior Research Associate University of Adelaide, Adelaide 2007 - 2012 Research Associate University of Chicago, Chicago 2005 - 2007 Postdoctoral Research Scholar Pennsylvania State University, University Park -
Education
Date Institution name Country Title — University of Adelaide, Adelaide Australia PhD — University of Adelaide, Adelaide Australia BSc, Mathematics and Computer Sciences (Honours)
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Journals
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Conference Papers
Year Citation 2014 McInerney, D., Thyer, M., Kavetski, D., & Kuczera, G. (2014). Evaluating different approaches for using the Box-Cox transformation to model heteroscedasticity in residual errors of hydrological models. In Hydrology and Water Resources Symposium 2014, HWRS 2014 - Conference Proceedings (pp. 937-944). online: Engineers Australia. -
Report for External Bodies
Year Citation 2020 McInerney, D. J., Thyer, M., Kavetski, D., & Kuczera, G. (2020). Technical note on producing spatially correlated streamflow forecasts at multiple gauged sites. 2019 McInerney, D. J., Thyer, M. A., & Kavetski, D. (2019). Technical Note on Improving Seamless Streamflow Forecasting using Multi-time scale Hydrological Residual Error Modelling. Australian Bureau of Meteorology. 2018 McInerney, D., Thyer, M. A., & Kavetski, D. (2018). Assessment of DEW Surface Water Team Modelling Approaches. South Australian Department of Environment and Water (DEW). -
Datasets
Year Citation — McInerney, D., Thyer, M., Kavetski, D., Githui, F., Thayalakumaran, T., Liu, M., & Kuczera, G. (n.d.). The importance of Spatiotemporal Variability in irrigation inputs for hydrological modelling of irrigated catchments - Datasets.
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Software
Year Citation 2017 McInerney, D., Bennett, B. S., Thyer, M., & Kavetski, D. (2017). Interactive Probabilistic Predictions [Computer Software]. http://www.probabilisticpredictions.org/.
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Filesets
Year Citation — McInerney, D., Thyer, M., & Kavetski, D. (n.d.). Supporting data for "Benefits of explicit treatment of zero flows in probabilistic hydrological modelling of ephemeral catchments" by McInerney et al. (2019).
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Presentations
Year Citation — McInerney, D. (n.d.). Improving Probabilistic Streamflow Predictions.
— Thyer, M., McInerney, D., Kavetski, D., Kuczera, G., & Lerat, J. (n.d.). Improving probabilistic prediction of daily streamflow.
— Mcinerney, D., Thyer, M., Kavetski, D., & Kuzera, G. (n.d.). Practical guidance on representing uncertainty in hydrological predictions.
Lecturing
- Engineering Hydrology III (2015-2017)
- Engineering Modelling and Analysis II (2015-2017)
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Current Higher Degree by Research Supervision (University of Adelaide)
Date Role Research Topic Program Degree Type Student Load Student Name 2019 Co-Supervisor Improving the value of subseasonal streamflow forecasts for water resource management decisions Doctor of Philosophy Doctorate Part Time Mr Richard Mark Laugesen 2018 Co-Supervisor Influence of Catchment-Scale Characteristics on Residual Model Selection and Parameters Doctor of Philosophy Doctorate Full Time Mr Jason Hunter
Connect With Me
External Profiles