Dr David McInerney
ARC Grant-Funded Researcher (B)
School of Architecture and Civil Engineering
Faculty of Sciences, Engineering and Technology
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 - ongoing 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 2021 Partington, D., Thyer, M., Shanafield, M., McInerney, D., Westra, S., Maier, H., . . . Kavetski, D. (2021). Modelling hydrological change due to wildfires. In Proceedings of the 24th International Congress on Modelling and Simulation (MODSIM2021) (pp. 582-587). Canberra, ACT, Australia: Modelling and Simulation Society of Australia and New Zealand.
DOI2021 Kavetski, D., McInerney, D., Hunter, J., & Thyer, M. (2021). Recent learnings towards achieving high quality probabilistic predictions in practical applications of hydrological models. In R. W. Vervoort, A. A. Voinov, J. P. Evans, & L. Marshall (Eds.), MODSIM2021, 24th International Congress on Modelling and Simulation. (pp. 526-532). Canberra, ACT, Australia: Modelling and Simulation Society of Australia and New Zealand.
DOI2021 McInerney, D., Thyer, M., Kavetski, D., Laugesen, R., Woldemsekel, F., Tuteja, N., & Kuczera, G. (2021). Improving sub-seasonal streamflow forecasts across flow regimes. In MODSIM2021, 24th International Congress on Modelling and Simulation. (pp. 616-622). Canberra, ACT, Australia: Modelling and Simulation Society of Australia and New Zealand.
DOI2021 Thyer, M., McInerney, D., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N., & Kuczera, G. (2021). Advances in subseasonal streamflow forecasting: An overview. In R. W. Vervoort, A. A. Voinov, J. P. Evans, & L. Marshall (Eds.), MODSIM2021, 24th International Congress on Modelling and Simulation. (pp. 623-629). Canberra, ACT, Australia: Modelling and Simulation Society of Australia and New Zealand.
DOI2021 Lerat, J., Kavetski, D., McInerney, D., & Thyer, M. (2021). A method to calibrate daily rainfall-runoff models to monthly streamflow data. In MODSIM2021, 24th International Congress on Modelling and Simulation. (pp. 533-539). Canberra, ACT, Australia: Modelling and Simulation Society of Australia and New Zealand.
DOI2021 Thyer, M., McInerney, D., Kavetski, D., & Hunter, J. (2021). Practical approaches to produce high-quality probabilistic predictions and improve risk-based design making. In Proceedings of the Hydrology and Water Resources Symposium (HWRS 2021) (pp. 612-625). virtual online: Engineers Australia. 2021 McInerney, D., Thyer, M., Kavetski, D., Laugesen, R., Tuteja, N., & Kuczera, G. (2021). The MuTHRE Model for High Quality Sub-seasonal Streamflow Forecasts. In Proceedings of the Hydrology and Water Resources Symposium (HWRS 2021) (pp. 444-452). Online: Engineers Australia. 2021 Kavetski, D., McInerney, D., Thyer, M., Lerat, J., & Kuczera, G. (2021). Probabilistic streamflow prediction and uncertainty estimation in ephemeral catchments. In Proceedings of the Hydrology and Water Resources Symposium (HWRS 2021) (pp. 482-496). Adelaide, Australia: Engineers Australia. 2021 Hunter, J., Thyer, M., McInerney, D., & Kavetski, D. (2021). High-quality probabilistic predictions for existing hydrological models with common objective functions. In Proceedings of the Hydrology and Water Resources Symposium (HWRS 2021) (pp. 626-639). Adelaide, Australia: Engineers Australia.
DOI2021 Kavetski, D., Lerat, J., McInerney, D., & Thyer, M. (2021). Can a daily rainfall-runoff model be successfully calibrated to monthly streamflow data?. In Proceedings of the Hydrology and Water Resources Symposium (HWRS 2021) (pp. 806-817). virtual online: Engineers Australia. 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. -
Conference Items
Year Citation 2023 McInerney, D., Wu, T. T., Weinhouse, G., Wallace, B., & Devlin, J. (2023). NEXT-NIGHT DISRUPTED SLEEP PREDICTION FROM CLINICIAN NOTES USING WEAKLY SUPERVISED LEARNING MODELS. Poster session presented at the meeting of CRITICAL CARE MEDICINE. CA, San Francisco: LIPPINCOTT WILLIAMS & WILKINS. 2023 Wu, T. T., McInerney, D., Weinhouse, G., Wallace, B., & Devlin, J. (2023). PREDICTORS OF ICU CLINICIAN DOCUMENTATION OF DISRUPTED SLEEP IN CRITICALLY ILL MEDICAL ADULTS. Poster session presented at the meeting of CRITICAL CARE MEDICINE. CA, San Francisco: LIPPINCOTT WILLIAMS & WILKINS. 2022 Thyer, M., Hunter, J., McInerney, D., & Kavetski, D. (2022). High-quality probabilistic predictions for existing hydrological models with common objective functions. Poster session presented at the meeting of Abstracts of the EGU General Assembly 2022. Vienna, Austria & Online: Copernicus GmbH.
DOI2021 Leigh, R., Knowling, M., Westra, S., Bennett, B., Zecchin, A., Maier, H., . . . Devanand, A. (2021). A multi-modelling framework to stress-test water resource systems under change. Poster session presented at the meeting of 24th International Congress on Modelling and Simulation (MODSIM2021) Book of Abstracts. Sydney, Australia: Modelling and Simulation Society of Australia and New Zealand Inc.. -
Report for External Bodies
Year Citation 2022 Westra, S., Leigh, R., Knowling, M., Beh, E., Devanand, A., Thyer, M., . . . McInerney, D. (2022). Assessment of current and future water security in the Barossa and Eden Valleys. 2021 McInerney, D., Thyer, M., Kavetski, D., & Kuczera, G. (2021). Technical note on producing spatially correlated daily streamflow forecasts at semi-gauged sites. 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). -
Internet Publications
Year Citation - Thyer, M., McInerney, D., Kavetski, D., Kuczera, G., Lerat, J., Tuteja, N., . . . Shin, D. (n.d.). Seasonal Streamflow Forecasting for Water Management: Advances and Opportunities.
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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.
DOI- McInerney, D., Thyer, M., & Kavetski, D. (n.d.). Supporting data for "Improving the reliability of sub-seasonal forecasts of high and low flows by using a flow-dependent non-parametric model" by McInerney et al. (2021).
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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., Thyer, M., Kavetski, D., & Kuzera, G. (n.d.). Practical guidance on representing uncertainty in hydrological predictions.
DOI- McInerney, D. (n.d.). Improving Probabilistic Streamflow Predictions.
DOI- Thyer, M., McInerney, D., Kavetski, D., Kuczera, G., & Lerat, J. (n.d.). Improving probabilistic prediction of daily streamflow.
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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
Connect With Me
External Profiles