Dr David McInerney

• 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)

• Journals

  Year	Citation
  2024	McInerney, D., Thyer, M., Kavetski, D., Westra, S., Maier, H. R., Shanafield, M., . . . Leonard, M. (2024). Neglecting hydrological errors can severely impact predictions of water resource system performance. Journal of Hydrology, 634, 130853-1-130853-15. DOI Scopus4
  2024	Thyer, M., Gupta, H., Westra, S., McInerney, D., Maier, H. R., Kavetski, D., . . . Tague, C. (2024). Virtual Hydrological Laboratories: Developing the Next Generation of Conceptual Models to Support Decision Making Under Change. Water Resources Research, 60(4), 1-17. DOI Scopus8
  2023	Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (2023). Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts. Hydrology and Earth System Sciences, 27(4), 873-893. DOI Scopus3
  2023	McInerney, D., Westra, S., Leonard, M., Bennett, B., Thyer, M., & Maier, H. R. (2023). A climate stress testing method for changes in spatially variable rainfall. Journal of Hydrology, 625, Part A, 129876. DOI Scopus5
  2023	Renard, B., McInerney, D., Westra, S., Leonard, M., Kavetski, D., Thyer, M., & Vidal, J. P. (2023). Floods and Heavy Precipitation at the Global Scale: 100-Year Analysis and 180-Year Reconstruction. Journal of Geophysical Research Atmospheres, 128(9), 26 pages. DOI
  2022	Qin, Y., Kavetski, D., Kuczera, G., McInerney, D., Yang, T., & Guo, Y. (2022). Technical Note: Can Gauss‐Newton algorithms outperform stochastic optimization algorithms when calibrating a highly parameterized hydrological model? A case study using SWAT. Water Resources Research, 58(11), 14 pages. DOI Scopus6
  2022	Mcinerney, D., Thyer, M., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N., & Kuczera, G. (2022). Seamless streamflow forecasting at daily to monthly scales: MuTHRE lets you have your cake and eat it too. Hydrology and Earth System Sciences, 26(21), 5669-5683. DOI Scopus6
  2022	Renard, B., Thyer, M., McInerney, D., Kavetski, D., Leonard, M., & Westra, S. (2022). A Hidden Climate Indices Modeling Framework for Multi‐Variable Space‐Time Data. Water Resources Research, 58(2), 1-27. DOI Scopus8 WoS5
  2022	Partington, D., Thyer, M., Shanafield, M., McInerney, D., Westra, S., Maier, H., . . . Kavetski, D. (2022). Predicting wildfire induced changes to runoff: A review and synthesis of modeling approaches. WIREs Water, 9(5), 1-25. DOI Scopus24 WoS3
  2021	Hunter, J., Thyer, M., McInerney, D., & Kavetski, D. (2021). Achieving high-quality probabilistic predictions from hydrological models calibrated with a wide range of objective functions. Journal of Hydrology, 603, 1-22. DOI Scopus16 WoS4
  2021	McInerney, D., Thyer, M., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N., & Kuczera, G. (2021). Improving the reliability of sub‐seasonal forecasts of high and low flows by using a flow‐dependent non‐parametric model. Water Resources Research, 57(11), 16 pages. DOI Scopus15 WoS4
  2020	Lerat, J., Thyer, M., McInerney, D., Kavetski, D., Woldemeskel, F., Pickett-Heaps, C., . . . Feikema, P. (2020). A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data. Journal of Hydrology, 591, 1-15. DOI Scopus21 WoS11
  2020	McInerney, D., Thyer, M., Kavetski, D., Laugesen, R., Tuteja, N., & Kuczera, G. (2020). Multi‐temporal hydrological residual error modelling for seamless sub‐seasonal streamflow forecasting. Water Resources Research, 56(11), 1-33. DOI Scopus35 WoS20
  2020	Schwarzwald, K., Poppick, A., Rugenstein, M., Bloch-Johnson, J., Wang, J., McInerney, D., & Moyer, E. J. (2020). Changes in future precipitation mean and variability across scales. Journal of Climate, 34(7), 1-55. DOI Scopus10 WoS4
  2019	McInerney, D., Kavetski, D., Thyer, M., Lerat, J., & Kuczera, G. (2019). Benefits of explicit treatment of zero flows in probabilistic hydrological modelling of ephemeral catchments. Water Resources Research, 55(12), 11035-11060. DOI Scopus20 WoS16
  2019	Wright, D., Thyer, M. A., Westra, S., Renard, B., & McInerney, D. (2019). A generalised approach for identifying influential data in hydrological modelling. Environmental Modelling and Software, 111, 231-247. DOI Scopus7 WoS4
  2018	McInerney, D., Thyer, M. A., Kavetski, D., Bennett, B., Lerat, J., Gibbs, M., & Kuczera, G. (2018). A simplified approach to produce probabilistic hydrological model predictions. Environmental Modelling & Software, 109, 306-314. DOI Scopus29 WoS20
  2018	Wright, D., Thyer, M., Westra, S., & McInerney, D. (2018). A hybrid framework for quantifying the influence of data in hydrological model calibration. Journal of Hydrology, 561, 211-222. DOI Scopus8 WoS6
  2018	McInerney, D., Thyer, M. A., Kavetski, D., Githui, F., Thayalakumaran, T., Liu, M., & Kuczera, G. (2018). The importance of spatiotemporal variability in irrigation inputs for hydrological modelling of irrigated catchments. Water Resources Research, 54(9), 6792-6821. DOI Scopus25 WoS20
  2018	Woldemeskel, F., McInerney, D., Lerat, J., Thyer, M., Kavetski, D., Shin, D., . . . Kuczera, G. (2018). Evaluating post-processing approaches for monthly and seasonal streamflow forecasts. Hydrology and Earth System Sciences, 22(12), 6257-6278. DOI Scopus41 WoS33
  2018	Gibbs, M. S., McInerney, D., Humphrey, G., Thyer, M. A., Maier, H. R., Dandy, G. C., & Kavetski, D. (2018). State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application. Hydrology and Earth System Sciences, 22(1), 871-887. DOI Scopus37 WoS27
  2017	McInerney, D., Thyer, M., Kavetski, D., Lerat, J., & Kuczera, G. (2017). Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors. Water Resources Research, 53(3), 2199-2239. DOI Scopus116 WoS91
  2016	Payne, J., McInerney, D., Barovich, K., Kirkland, C., Pearson, N., & Hand, M. (2016). Strengths and limitations of zircon Lu-Hf and O isotopes in modelling crustal growth. Lithos, 248-251, 175-192. DOI Scopus114 WoS101
  2016	Poppick, A., McInerney, D., Moyer, E., & Stein, M. (2016). Temperatures in transient climates: improved methods for simulations with evolving temporal covariances. Annals of Applied Statistics, 10(1), 477-505. DOI Scopus16 WoS14
  2016	Huang, W. K., Stein, M. L., McInerney, D. J., Sun, S., & Moyer, E. J. (2016). Estimating changes in temperature extremes from millennial-scale climate simulations using generalized extreme value (GEV) distributions. Advances in Statistical Climatology, Meteorology and Oceanography, 2(1), 79-103. DOI
  2016	Bao, J., McInerney, D., & Stein, M. (2016). A spatial-dependent model for climate emulation. Environmetrics, 27(7), 396-408. DOI Scopus4 WoS3
  2015	Payne, J., Hand, M., Pearson, N., Barovich, K., & McInerney, D. (2015). Crustal thickening and clay: controls on O isotope variation in global magmatism and siliclastic sedimentary rocks. Earth and Planetary Science Letters, 412, 70-76. DOI Scopus33 WoS25
  2014	Glotter, M., Elliott, J., McInerney, D., Best, N., Foster, I., & Moyer, E. (2014). Evaluating the utility of dynamical downscaling in agricultural impacts projections. Proceedings of the National Academy of Sciences of the United States of America, 111(24), 8776-8781. DOI Scopus67 WoS61 Europe PMC7
  2014	Evin, G., Thyer, M., Kavetski, D., McInerney, D., & Kuczera, G. (2014). Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity. Water Resources Research, 50(3), 2350-2375. DOI Scopus141 WoS115
  2014	Castruccio, S., McInerney, D., Stein, M., Crouch, F., Jacob, R., & Moyer, E. (2014). Statistical emulation of climate model projections based on precomputed GCM runs. Journal of Climate, 27(5), 1829-1844. DOI Scopus85 WoS70
  2014	Li, D., Jacobson, A., & McInerney, D. (2014). A reactive-transport model for examining tectonic and climatic controls on chemical weathering and atmospheric CO₂ consumption in granitic regolith. Chemical Geology, 365, 30-42. DOI Scopus52 WoS44
  2013	O'Brien, J., Aherne, S., McCormack, O., Jeffers, M., & McInerney, D. (2013). MRI Features of Bilateral Amyloidosis of Breast. BREAST JOURNAL, 19(3), 338-339. DOI
  2012	McInerney, D., Lempert, R., & Keller, K. (2012). What are robust strategies in the face of uncertain climate threshold responses?. Climatic Change, 112(3-4), 547-568. DOI Scopus106 WoS89
  2012	Hall, J. W., Lempert, R. J., Keller, K., Hackbarth, A., Mijere, C., & McInerney, D. J. (2012). Robust climate policies under uncertainty: a comparison of robust decision making and info-gap methods. Risk Analysis, 32(10), 1657-1672. DOI Scopus222 WoS194 Europe PMC19
  2010	McInerney, D., Teubner, M., & Noye, B. (2010). A second-order analytic solution for oscillatory wind-induced flow in an idealized shallow lake. Computers & Fluids, 39(9), 1500-1509. DOI Scopus1 WoS1
  2008	Keller, K., McInerney, D., & Bradford, D. F. (2008). Carbon dioxide sequestration: how much and when?. Climatic Change, 88(3-4), 267-291. DOI Scopus38 WoS32
  2008	McInerney, D., & Keller, K. (2008). Economically optimal risk reduction strategies in the face of uncertain climate thresholds. Climatic Change, 91(1-2), 29-41. DOI Scopus45 WoS37
  2008	Keller, K., & McInerney, D. (2008). The dynamics of learning about a climate threshold. Climate Dynamics, 30(2-3), 321-332. DOI Scopus33 WoS29
  2008	Baehr, J., McInerney, D., Keller, K., & Marotzke, J. (2008). Optimization of an observing system design for the North Atlantic meridional overturning circulation. Journal of Atmospheric and Oceanic Technology, 25(4), 625-634. DOI Scopus18 WoS14
  2008	McInerney, D., Lynch, M., Donegan, J. F., & Weldon, V. (2008). Mode referencing of an external cavity diode laser for continuous frequency stabilization. OPTICAL ENGINEERING, 47(2), 5 pages. DOI
  2000	McInerney, D., & Noye, B. (2000). A triangular coastal element developed for use in finite difference tidal models. The ANZIAM Journal, 42, C936-C953.
  2000	Noye, B., & McInerney, D. (2000). Numerical study of the stability of some explicit finite-difference methods for oscillatory advection. The ANZIAM Journal, 42(1), C1076-C1096.

• 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. DOI
  2021	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. DOI
  2021	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. DOI
  2021	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. DOI
  2021	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. DOI
  2021	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. DOI
  2021	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.
  2006	Weldon, V., McInerney, D., Phelan, R., Lynch, M., & Donegan, J. (2006). Characteristics of several NIR tuneable diode lasers for spectroscopic based gas sensing: A comparison. In SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY Vol. 63 (pp. 1013-1020). ITALY, Florence: PERGAMON-ELSEVIER SCIENCE LTD. DOI
  1988	MILLER, F. R., MCINERNEY, D., & MILLER, B. E. (1988). GROWTH INTERACTIONS BETWEEN CELLS FROM SEQUENTIAL STAGES OF MOUSE MAMMARY-GLAND FROM NORMAL THROUGH PRENEOPLASIA TO HETEROGENEOUS TUMOR. In PROCEEDINGS OF THE AMERICAN ASSOCIATION FOR CANCER RESEARCH Vol. 29 (pp. 59). AMER ASSOC CANCER RESEARCH.
  1986	MILLER, F. R., MCINERNEY, D., & MILLER, B. E. (1986). DIFFERENTIAL ABILITY OF QUABAIN TO UNCOUPLE NORMAL, PRENEOPLASTIC, AND NEOPLASTIC MOUSE MAMMARY CELLS. In PROCEEDINGS OF THE AMERICAN ASSOCIATION FOR CANCER RESEARCH Vol. 27 (pp. 149). AMER ASSOC CANCER RESEARCH.

• 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. DOI
  2021	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. DOI

• Datasets

  Year	Citation
  -	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). DOI
  -	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

• Software

  Year	Citation
  2017	McInerney, D., Bennett, B. S., Thyer, M., & Kavetski, D. (2017). Interactive Probabilistic Predictions [Computer Software]. http://www.probabilisticpredictions.org/. DOI

• 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). DOI

• 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. DOI

Lecturing

• Engineering Hydrology III (2015-2017)
• Engineering Modelling and Analysis II (2015-2017)

• 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

• Position: ARC Grant-Funded Researcher (B)
• Phone: 83131231
• Email: david.mcinerney@adelaide.edu.au
• Campus: North Terrace
• Building: Engineering North, floor N1
• Org Unit: Environmental Engineering