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
  2022	Renard, B., Thyer, M., McInerney, D., Kavetski, D., Leonard, M., & Westra, S. (2022). A Hidden Climate Indices Modeling Framework for Multivariable Space-Time Data. Water Resources Research, 58(1), 27 pages. DOI Scopus1 WoS1
  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), e1599-1-e1599-25. DOI Scopus1
  2022	Qin, Y., Kavetski, D., Kuczera, G., McInerney, D., Yang, T., & Guo, Y. (2022). 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). DOI
  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
  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 Scopus3 WoS3
  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 Scopus2 WoS3
  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 Scopus9 WoS9
  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 Scopus10 WoS11
  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 Scopus1 WoS1
  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 Scopus11 WoS12
  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 Scopus4 WoS3
  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 Scopus13 WoS14
  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 Scopus7 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 Scopus17 WoS17
  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 Scopus23 WoS25
  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 Scopus24 WoS24
  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 Scopus79 WoS78
  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 Scopus93 WoS93
  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 Scopus14 WoS13
  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 Scopus2 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 Scopus24 WoS24
  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 Scopus56 WoS57 Europe PMC5
  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 Scopus111 WoS102
  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 Scopus61 WoS64
  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 Scopus44 WoS42
  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 Scopus89 WoS87
  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 Scopus188 WoS186 Europe PMC13
  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 Scopus33 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 Scopus44 WoS35
  2008	Keller, K., & McInerney, D. (2008). The dynamics of learning about a climate threshold. Climate Dynamics, 30(2-3), 321-332. DOI Scopus31 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
  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.

• Conference Items

  Year	Citation
  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

• Report for External Bodies

  Year	Citation
  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).

• 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). 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. (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
  	Mcinerney, D., Thyer, M., Kavetski, D., & Kuzera, G. (n.d.). Practical guidance on representing uncertainty in hydrological predictions. 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
  2018	Co-Supervisor	Influence of Catchment-Scale Characteristics on Residual Model Selection and Parameters	Doctor of Philosophy	Doctorate	Part Time	Mr Jason Hunter

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