Professor Dmitri Kavetski

Professor

School of Architecture and Civil Engineering

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD - email supervisor to discuss availability.

One of the main contributions of Dmitri's research work has been the development of Bayesian Total Error Analysis (BATEA) - a comprehensive framework for parameter estimation and probabilistic prediction accounting for data and model uncertainties. BATEA has been used in research and practice, including in the operational seasonal forecasting system of the Australian Bureau of Meteorology. Additional applications have taken place in river system modelling, irrigation modelling and other areas of environmental engineering.

Dmitri's broader interests include mathematical modelling of surface and subsurface hydrological systems, development of numerically robust rainfall-runoff models, and more generally the design of robust and computationally efficient numerical algorithms for environmental model implementation, calibration and prediction.

Dmitri's international collaborations include the Swiss Federal Institute for Aquatic Science and Technology (EAWAG), CEMAGREF (Paris and Lyon, France), US National Center for Atmospheric Research (NCAR), Environmental Hydraulics Institute of Cantabria (Santander, Spain), and other institutions worldwide.

My Research
Career
Publications
Grants and Funding
Supervision
Professional Activities
Contact

Research Interests

Bayesian inference and prediction in hydrology and environmental modelling. Development of novel Bayesian and Monte Carlo techniques for parameter estimation, uncertainty analysis and predictive applications. Areas of application focus on hydrological models and river system models.

Modelling in hydrology and environmental engineering. Selection of governing equations and process representations in hydrological and snow models, including scientifically defensible hypothesis testing. Model development, optimisation and testing.

Applied numerical and statistical analysis in environmental engineering. Design and implementation of accurate, robust and computationally efficient numerical algorithms and software. Solution of nonlinear differential equations, numerical integration, nonlinear optimisation problems, and others. Areas of application have included Richards equation for groundwater simulations, rainfall-runoff models, CO2 geosequestration models, and others.

Appointments

Date	Position	Institution name
2012 - ongoing	Professor of Civil and Environmental Engineering	University of Adelaide
2010 - 2012	Senior Research Fellow	University of Newcastle Australia
2007 - 2010	Research Fellow	University of Newcastle Australia
2004 - 2007	Postdoctoral Research	Princeton University

Awards and Achievements

Date	Type	Title	Institution Name	Country	Amount
2016	Award	Outstanding Publication in Hydrological Modeling	US National Center for Atmospheric Research (NCAR)	United States	-
2014	Award	Research Spotlight Award from American Geophysical Union (top 5% of papers in AGU) for Westra et al (2014)	American Geophysical Union	United States	-
2014	Award	Editors Highlight Award from Water Resources Research (top 5% of papers in WRR) for Evin et al (2014)	Water Resources Research	United States	-
2012	Award	South Australia Young Tall Poppy Science Award	Australian Institute of Policy and Science	Australia	-
2011	Award	Editors’ Choice Award in Water Resources Research	American Geophysical Union	United States	-
2011	Award	Editors’ Citation for Excellence in Refereeing for Water Resources Research	American Geophysical Union	United States	-
2011	Award	2011 Researcher of the Year Award	http://www.newcastle.edu.au	Australia	-
2011	Award	Vice-Chancellor’s Award for Research Excellence	University of Newcastle	Australia	-
2010	Award	Pro Vice-Chancellor’s Award for Research Excellence, Faculty of Engineering and Built Environment	University of Newcastle	Australia	-

Education

Date	Institution name	Country	Title
2006	University of Newcastle Australia	Australia	Doctor of Philosophy in Engineering (Environmental)
2000	University of Newcastle Australia	Australia	Bachelor of Engineering (Environmental)

Journals

Year	Citation
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
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
2023	Dal Molin, M., Kavetski, D., Albert, C., & Fenicia, F. (2023). Exploring Signature-Based Model Calibration for Streamflow Prediction in Ungauged Basins. Water Resources Research, 59(7), 32 pages. DOI
2022	Prieto, C., Le Vine, N., Kavetski, D., Fenicia, F., Scheidegger, A., & Vitolo, C. (2022). An Exploration of Bayesian Identification of Dominant Hydrological Mechanisms in Ungauged Catchments. Water Resources Research, 58(3), 1-28. DOI Scopus4 WoS4
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 Scopus3 WoS3
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
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 Scopus2
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 Scopus4 WoS5
2021	Fenicia, F., & Kavetski, D. (2021). Behind every robust result is a robust method: Perspectives from a case study and publication process in hydrological modelling. Hydrological Processes, 35(8), 9 pages. DOI Scopus4 WoS3
2021	Prieto, C., Kavetski, D., Le Vine, N., Álvarez, C., & Medina, R. (2021). Identification of Dominant Hydrological Mechanisms Using Bayesian Inference, Multiple Statistical Hypothesis Testing, and Flexible Models. Water Resources Research, 57(8), 32 pages. DOI Scopus7 WoS5
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 Scopus5 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 Scopus4 WoS4
2021	Dal Molin, M., Kavetski, D., & Fenicia, F. (2021). SuperflexPy 1.3.0: an open-source Python framework for building, testing, and improving conceptual hydrological models. GEOSCIENTIFIC MODEL DEVELOPMENT, 14(11), 7047-7072. DOI Scopus5 WoS5
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 Scopus11 WoS10
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 Scopus18 WoS19
2019	Prieto, C., Le Vine, N., Kavetski, D., García, E., & Medina, R. (2019). Flow prediction in ungauged catchments using probabilistic random forests regionalization and new statistical adequacy tests. Water Resources Research, 55(5), 4364-4392. DOI Scopus48 WoS46
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 Scopus15 WoS15
2018	Kavetski, D., Fenicia, F., Reichert, P., & Albert, C. (2018). Signature-domain calibration of hydrological models using approximate bayesian computation: theory and comparison to existing applications. Water Resources Research, 54(6), 4059-4083. DOI Scopus30 WoS27
2018	Fenicia, F., Kavetski, D., Reichert, P., & Albert, C. (2018). Signature-domain calibration of hydrological models using approximate bayesian computation: empirical analysis of fundamental properties. Water Resources Research, 54(6), 3958-3987. DOI Scopus29 WoS27
2018	Hostache, R., Chini, M., Giustarini, L., Neal, J., Kavetski, D., Wood, M., . . . Matgen, P. (2018). Near-Real-Time Assimilation of SAR-Derived Flood Maps for Improving Flood Forecasts. Water Resources Research, 54(8), 5516-5535. DOI Scopus76 WoS69
2018	Kavetski, D., Qin, Y., & Kuczera, G. (2018). The Fast and the Robust: Trade-Offs Between Optimization Robustness and Cost in the Calibration of Environmental Models. Water Resources Research, 54(11), 9432-9455. DOI Scopus12 WoS12
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 Scopus31 WoS32
2018	Qin, Y., Kavetski, D., & Kuczera, G. (2018). A robust Gauss-Newton algorithm for the optimization of hydrological models: from standard Gauss-Newton to robust Gauss-Newton. Water Resources Research, 54(11), 9655-9683. DOI Scopus24 WoS25
2018	Qin, Y., Kavetski, D., & Kuczera, G. (2018). A robust Gauss-Newton algorithm for the optimization of hydrological models: benchmarking against industry-standard algorithms. Water Resources Research, 54(11), 9637-9654. DOI Scopus29 WoS24
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 Scopus30 WoS27
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 Scopus22 WoS20
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 Scopus18 WoS20
2018	Henn, B., Clark, M., Kavetski, D., Newman, A., Hughes, M., McGurk, B., & Lundquist, J. (2018). Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range. Journal of Hydrology, 556, 993-1012. DOI Scopus33 WoS34
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 Scopus92 WoS89
2017	Schaefli, B., & Kavetski, D. (2017). Bayesian spectral likelihood for hydrological parameter inference. Water Resources Research, 53(8), 6857-6884. DOI Scopus7 WoS6
2016	Qin, Y., Kuczera, G., & Kavetski, D. (2016). Comparison of Newton-type and SCE optimisation algorithms for the calibration of conceptual hydrological models. Australian Journal of Water Resources, 20(2), 169-176. DOI Scopus8
2016	Henn, B., Clark, M., Kavetski, D., McGurk, B., Painter, T., & Lundquist, J. (2016). Combining snow, streamflow, and precipitation gauge observations to infer basin-mean precipitation. Water Resources Research, 52(11), 8700-8723. DOI Scopus20 WoS20
2016	Giustarini, L., Hostache, R., Kavetski, D., Chini, M., Corato, G., Schlaffer, S., & Matgen, P. (2016). Probabilistic Flood Mapping Using Synthetic Aperture Radar Data. IEEE Transactions on Geoscience and Remote Sensing, 54(12), 6958-6969. DOI Scopus97 WoS88
2016	Hill, M., Kavetski, D., Clark, M., Ye, M., Arabi, M., Lu, D., . . . Mehl, S. (2016). Practical use of computationally frugal model analysis methods. Groundwater, 54(2), 159-170. DOI Scopus137 WoS51 Europe PMC1
2016	Fenicia, F., Kavetski, D., Savenije, H., & Pfister, L. (2016). From spatially variable streamflow to distributed hydrological models: analysis of key modeling decisions. Water Resources Research, 52(2), 954-989. DOI Scopus73 WoS69
2015	Lockart, N., Kavetski, D., & Franks, S. (2015). A new stochastic model for simulating daily solar radiation from sunshine hours. International Journal of Climatology, 35(6), 1090-1106. DOI Scopus13 WoS13
2015	Clark, M., Nijssen, B., Lundquist, J., Kavetski, D., Rupp, D., Woods, R., . . . Marks, D. (2015). A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies. Water Resources Research, 51(4), 2515-2542. DOI Scopus134 WoS43
2015	Clark, M., Nijssen, B., Lundquist, J., Kavetski, D., Rupp, D., Woods, R., . . . Rasmussen, R. (2015). A unified approach for process-based hydrologic modeling: 1. Modeling concept. Water Resources Research, 51(4), 2498-2514. DOI Scopus289 WoS280
2015	Henn, B., Clark, M., Kavetski, D., & Lundquist, J. (2015). Estimating mountain basin-mean precipitation from streamflow using Bayesian inference. Water Resources Research, 51(10), 8012-8033. DOI Scopus38 WoS41
2015	Wrede, S., Fenicia, F., Martínez-Carreras, N., Juilleret, J., Hissler, C., Krein, A., . . . Pfister, L. (2015). Towards more systematic perceptual model development: a case study using 3 Luxembourgish catchments. Hydrological Processes, 29(12), 2731-2750. DOI Scopus70 WoS70
2014	Fenicia, F., Kavetski, D., Savenije, H., Clark, M., Schoups, G., Pfister, L., & Freer, J. (2014). Catchment properties, function, and conceptual model representation: is there a correspondence?. Hydrological Processes, 28(4), 2451-2467. DOI Scopus124 WoS118
2014	Pagano, T., Wood, A., Ramos, M., Cloke, H., Pappenberger, F., Clark, M., . . . Verkade, J. (2014). Challenges of operational river forecasting. Journal of Hydrometeorology, 15(4), 1692-1707. DOI WoS107
2014	Westra, S., Thyer, M., Leonard, M., Kavetski, D., & Lambert, M. (2014). A strategy for diagnosing and interpreting hydrological model nonstationarity. Water Resources Research, 50(6), 5090-5113. DOI Scopus127 WoS119
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 Scopus122 WoS114
2013	Ershadi, A., McCabe, M., Evans, J., Mariethoz, G., & Kavetski, D. (2013). A Bayesian analysis of sensible heat flux estimation: quantifying uncertainty in meteorological forcing to improve model prediction. Water Resources Research, 49(5), 2343-2358. DOI Scopus16 WoS15
2013	van Esse, W., Perrin, C., Booij, M., Augustijn, D., Fenicia, F., Kavetski, D., & Lobligeois, F. (2013). The influence of conceptual model structure on model performance: A comparative study for 237 French catchments. Hydrology and Earth System Sciences, 17(10), 4227-4239. DOI Scopus78 WoS74
2013	Hill, M., Faunt, C., Belcher, W., Sweetkind, D., Tiedeman, C., & Kavetski, D. (2013). Knowledge, transparency, and refutability in groundwater models, an example from the Death Valley regional groundwater flow system. Physics and Chemistry of the Earth (Print), 64, 105-116. DOI Scopus11 WoS11
2013	Evin, G., Kavetski, D., Thyer, M., & Kuczera, G. (2013). Pitfalls and improvements in the joint inference of heteroscedasticity and autocorrelation in hydrological model calibration. Water Resources Research, 49(7), 4518-4524. DOI Scopus87 WoS81
2012	Clark, M., Kavetski, D., & Fenicia, F. (2012). Reply to comment by K. Beven et al. on "Pursuing the method of multiple working hypotheses for hydrological modelling". Water Resources Research, 48(11), 1-7. DOI Scopus24 WoS26
2012	Lockhart, N., Kavetski, D., & Franks, S. (2012). On the role of soil moisture in daytime evolution of temperatures. Hydrological Processes, online(26), 1-9. DOI Scopus10 WoS9
2012	Fenicia, F., Pfister, L., Kavetski, D., Matgen, P., Iffly, J., Hoffmann, L., & Uijlenhoet, R. (2012). Microwave links for rainfall estimation in an urban environment: Insights from an experimental setup in Luxembourg-City. Journal of Hydrology, 464, 69-78. DOI Scopus36 WoS30
2011	Renard, B., Kavetski, D., Leblois, E., Thyer, M., Kuczera, G., & Franks, S. (2011). Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation. Water Resources Research, 47(11), 1-21. DOI Scopus175 WoS162
2011	McMillan, H., Jackson, B., Clark, M., Kavetski, D., & Woods, R. (2011). Rainfall uncertainty in hydrological modelling: An evaluation of multiplicative error models. Journal of Hydrology, 400(1-2), 83-94. DOI Scopus177 WoS164
2011	Clark, M., McMillan, H., Collins, D., Kavetski, D., & Woods, R. (2011). Hydrological field data from a modeller's perspective: Part 2: process-based evaluation of model hypotheses. Hydrological Processes, 25(4), 523-543. DOI Scopus96 WoS92
2011	Clark, M., Hendrikx, J., Slater, A., Kavetski, D., Anderson, B., Cullen, N., . . . Woods, R. (2011). Representing spatial variability of snow water equivalent in hydrologic and land-surface models: a review. Water Resources Research, 47(7), 1-25. DOI Scopus230 WoS332
2011	Kavetski, D., Fenicia, F., & Clark, M. (2011). Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: insights from an experimental catchment. Water Resources Research, 47(5), 1-25. DOI Scopus80 WoS100
2011	Clark, M., Kavetski, D., & Fenicia, F. (2011). Pursuing the method of multiple working hypotheses for hydrological modeling. Water Resources Research, 47(9), 1-16. DOI Scopus387 WoS251
2011	Kavetski, D., & Fenicia, F. (2011). Elements of a flexible approach for conceptual hydrological modeling: 2. Application and experimental insights. Water Resources Research, 47(11), 1-19. DOI Scopus67 WoS55
2011	Fenicia, F., Kavetski, D., & Savenije, H. (2011). Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development. Water Resources Research, 47(11), 1-13. DOI Scopus241 WoS241
2011	Thyer, M., Leonard, M., Kavetski, D., Need, S., & Renard, B. (2011). The open source RFortran library for accessing R from Fortran, with applications in environmental modelling. Environmental Modelling & Software, 26(2), 219-234. DOI Scopus15 WoS13
2011	Kavetski, D., & Clark, M. (2011). Numerical troubles in conceptual hydrology: approximations, absurdities and impact on hypothesis testing. Hydrological Processes, 25(4), 661-670. DOI Scopus56 WoS53
2010	Franks, S. W., Kavetski, D., & Lockart, N. (2010). Reply to the comment of Cai et al. on the paper "on the recent warming in the Murray-Darling Basin: Land surface interactions misunderstood" by Lockart et al.. Geophysical Research Letters, 37(10), 1 page. DOI Scopus2 WoS2
2010	Kuczera, G., Renard, B., Thyer, M., & Kavetski, D. (2010). There are no hydrological monsters, just models and observations with large uncertainties!. Hydrological Sciences Journal-Journal des Sciences Hydrologiques, 55(6), 980-991. DOI Scopus63 WoS61
2010	Kuczera, G., Kavetski, D., Renard, B., & Thyer, M. (2010). A limited memory acceleration strategy for MCMC sampling in hierarchical Bayesian calibration of hydrological models. Water Resources Research, 46(7), 1-6. DOI Scopus30 WoS32
2010	Renard, B., Kavetski, D., Kuczera, G., Thyer, M., & Franks, S. (2010). Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors. Water Resources Research, 46(5), 1-22. DOI Scopus582 WoS501
2010	Kavetski, D., & Clark, M. (2010). Ancient numerical daemons of conceptual hydrological modeling 2. Impact of time stepping schemes on model analysis and prediction. Water Resources Research, 46(10), 1-27. DOI Scopus131 WoS123
2010	Clark, M., & Kavetski, D. (2010). Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes. Water Resources Research, 46(10), 1-23. DOI Scopus123 WoS210
2010	Fenicia, F., Wrede, S., Kavetski, D., Pfister, L., Hoffmann, L., Savenije, H., & McDonnell, J. (2010). Assessing the impact of mixing assumptions on the estimation of streamwater mean residence time. Hydrological Processes, 24(12), 1730-1741. DOI Scopus72 WoS71
2009	Nordbotten, J., Kavetski, D., Celia, M., & Bachu, S. (2009). Model for CO₂ leakage including multiple geological layers and multiple leaky wells. Environmental Science & Technology, 43(3), 743-749. DOI Scopus183 WoS168 Europe PMC11
2009	Lockart, N., Kavetski, D., & Franks, S. (2009). On the recent warming in the Murray-Darling Basin: land surface interactions misunderstood. Geophysical Research Letters, 36(24), 1-6. DOI Scopus31 WoS29
2009	Renard, B., Kavetski, D., & Kuczera, G. (2009). Comment on "An integrated hydrologic Bayesian multimodel combination framework: confronting input, parameter, and model structural uncertainty in hydrologic prediction" by Newsha K. Ajami et al.. Water Resources Research, 45(3), W03603-1-W03603-10. DOI Scopus17 WoS14
2009	Thyer, M., Renard, B., Kavetski, D., Kuczera, G., Franks, S., & Srikanthan, S. (2009). Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis. Water Resources Research, 45(12), 1-22. DOI Scopus297 WoS267
2008	Viswanathan, H., Pawar, R., Stauffer, P., Kaszuba, J., Carey, W., Olsen, S., . . . Guthrie, G. (2008). Development of a hybrid process and system model for the assessment of wellbore leakage at a geologic CO₂ sequestration site. Environmental Science & Technology, 42(19), 7280-7286. DOI Scopus124 WoS116 Europe PMC7
2007	Kavetski, D., & Kaszuba, J. (2007). Model smoothing strategies to remove microscale discontinuities and spurious secondary optima in objective functions in hydrological calibration. Water Resources Research, 43(3), 1-9. DOI Scopus83 WoS76
2006	Kuczera, G., Kavetski, D., Franks, S., & Thyer, M. (2006). Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters. Journal of Hydrology, 331(1-2), 161-177. DOI Scopus277 WoS244
2006	Kavetski, D., Kuczera, G., & Franks, S. W. (2006). Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory. Water Resources Research, 42(3), 9 pages. DOI Scopus468 WoS521
2006	Kavetski, D., Kuczera, G., & Franks, S. W. (2006). Bayesian analysis of input uncertainty in hydrological modeling: 2. Application. Water Resources Research, 42(3), 10 pages. DOI Scopus219 WoS53
2006	Kavetski, D., Kuczera, G., & Franks, S. W. (2006). Calibration of conceptual hydrological models revisited: 1. Overcoming numerical artefacts. Journal of Hydrology, 320(1-2), 173-186. DOI Scopus96 WoS92
2006	Kavetski, D., Kuczera, G., & Franks, S. W. (2006). Calibration of conceptual hydrological models revisited: 2. Improving optimisation and analysis. Journal of Hydrology, 320(1-2), 187-201. DOI Scopus56 WoS52
2004	Kavetski, D., Binning, P., & Sloan, S. W. (2004). Truncation error and stability analysis of iterative and non-iterative Thomas-Gladwell methods for first-order non-linear differential equations. International Journal for Numerical Methods in Engineering, 60(12), 2031-2043. DOI Scopus15 WoS13
2003	Kavetski, D., Kuczera, G., & Franks, S. W. (2003). Semidistributed hydrological modeling: A "saturation path" perspective on TOPMODEL and VIC. Water Resources Research, 39(9), 8 pages. DOI Scopus52 WoS51
2002	Kavetski, D., Binning, P., & Sloan, S. W. (2002). Noniterative time stepping schemes with adaptive truncation error control for the solution of Richards equation. Water Resources Research, 38(10), 29-1-29-10. DOI Scopus49 WoS49
2002	Kavetski, D., Binning, P., & Sloan, S. W. (2002). Adaptive backward Euler time stepping with truncation error control for numerical modelling of unsaturated fluid flow. International Journal for Numerical Methods in Engineering, 53(6), 1301-1322. DOI Scopus85 WoS69
2001	Kavetski, D., Binning, P., & Sloan, S. W. (2001). Adaptive time stepping and error control in a mass conservative numerical solution of the mixed form of Richards equation. Advances in Water Resources, 24(6), 595-605. DOI Scopus99 WoS86
-	Puma, M. J., Celia, M. A., Rodriguez-Iturbe, I., Nordbotten, J. M., Guswa, A. J., & Kavetski, D. (n.d.). Effects of Spatial Heterogeneity in Rainfall and Vegetation Type on Soil Moisture and Evapotranspiration.
-	Gibbs, M. S., McInerney, D., Humphrey, G., Thyer, M. A., Maier, H. R., Dandy, G. C., & Kavetski, D. (n.d.). State Updating and Calibration Period Selection to Improve Dynamic Monthly Streamflow Forecasts for a Wetland Management Application. DOI
-	Woldemeskel, F., McInerney, D., Lerat, J., Thyer, M., Kavetski, D., Shin, D., . . . Kuczera, G. (n.d.). Evaluating residual error approaches for post-processing monthly and seasonal streamflow forecasts. DOI
-	Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (n.d.). A flexible approach for evaluating the value of probabilistic forecasts for different decision types and risk averse decision-makers. DOI
-	Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (n.d.). Supplementary material to "Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts". DOI
-	Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (n.d.). Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts. DOI
-	Thyer, M., McInerney, D., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N., & Kuczera, G. (n.d.). Seamless subseasonal probabilistic streamflow forecasting: MuTHRE lets you have your cake and eat it too. DOI

Book Chapters

Year	Citation
2018	Kavetski, D. (2018). Parameter estimation and predictive uncertainty quantification in hydrological modelling. In Q. Duan, F. Pappenberger, A. Wood, H. L. Cloke, & J. C. Schaake (Eds.), Handbook of hydrometeorological ensemble forecasting (pp. 481-522). Berlin, Heidelberg: Springer. DOI Scopus3
2016	Kuczera, G., Kavetski, D., Renard, B., & Thyer, M. (2016). Bayesian Methods. In V. Singh (Ed.), Handbook of Applied Hydrology, Second Edition (Second ed., pp. 10 pages). New York, USA: McGraw-Hill.
2003	Kavetski, D., Franks, S. W., & Kuczera, G. (2003). Confronting Input Uncertainty in Environmental Modelling. In Q. Duan, H. V. Gupta, S. Sorooshian, A. N. Rousseau, & R. Turcotte (Eds.), Calibration of Watershed Models (pp. 49-68). American Geophysical Union.

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.
2020	Kuczera, G., Kavetski, D., Franks, S., & Thyer, M. (2020). Characterizing model error in conceptual rainfall-runoff models using storm-dependent parameters. In MODSIM 2005 - International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Proceedings (pp. 2925-2931).
2015	Lerat, J., Pickett-Heaps, C., Shin, D., Zhou, S., Feikema, P., Khan, U., . . . Kavetski, D. (2015). Dynamic streamflow forecasts within an uncertainty framework for 100 catchments in Australia. In The Art and Science of Water - 36th Hydrology and Water Resources Symposium, HWRS 2015 (pp. 1396-1403). online: Engineers Australia. Scopus5
2015	Qin, Y., Kuczera, G., & Kavetski, D. (2015). Revisiting the calibration of conceptual hydrological models using Newton-type optimization algorithms. In The Art and Science of Water - 36th Hydrology and Water Resources Symposium, HWRS 2015 (pp. 766-774). Online: Engineers Australia.
2015	Newman, A., Kuczera, G., & Kavetski, D. (2015). Application of particle filtering methods to a conceptual rainfall-runoff model. In The Art and Science of Water - 36th Hydrology and Water Resources Symposium, HWRS 2015 (pp. 266-273). Australia: 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.
2013	Qin, Y., Kuczera, G., & Kavetski, D. (2013). A Robust Gauss-Newton Algorithm and Its Application to the Calibration of Conceptual Rainfall-runoff Models. In W. Zhaoyin, J. H. W. Lee, G. Jizhang, & C. Shuyou (Eds.), PROCEEDINGS OF THE 35TH IAHR WORLD CONGRESS, VOLS I AND II (pp. 4521-4529). Int Assoc Hydro Environm Engn & Res, Chengdu, PEOPLES R CHINA: TSINGHUA UNIV.
2013	Qin, Y., Kuczera, G., & Kavetski, D. (2013). A robust Gauss-Newton algorithm and its application to the calibration of conceptual rainfall-runoff hydrological model. In Proceedings of 35th IAHR World Congress 2013 (pp. 1-10). China: Tsinghua University Press Beijing.
2012	Westra, S., Thyer, M., Leonard, M., Kavetski, D., & Lambert, M. (2012). Diagnosing non-stationary behaviour in a hydrological model. In Proceedings of the 34th Hydrology & Water Resources Symposium, HWRS 2012 (pp. 256-264). Australia: Engineers Australia.
2012	Newman, A., Kuczera, G., & Kavetski, D. (2012). Towards a recursive bayesian total error analysis framework. In Proceedings of the 34th Hydrology & Water Resources Symposium, HWRS 2012 (pp. 265-273). Australia: Engineers Australia.
2011	Clark, M., Kavetski, D., Fenicia, F., & McMillan, H. (2011). The quest for physically realistic streamflow forecasting models. In J. Sims, L. Merrin, R. Ackland, & N. Herron (Eds.), WIRADA (2012) Water Information Research and Development Alliance: Science Symposium Proceedings (pp. 209-215). Australia: Bureau of Meteorology and CSIRO.
2011	Kavetski, D., Renard, B., Evin, G., Thyer, M., Newman, A., & Kuczera, G. (2011). Uncertainties in flood forecasting: A Bayesian total error perspective. In J. Sims, L. Merrin, R. Ackland, & N. Herron (Eds.), WIRADA (2012) Water Information Research and Development Alliance: Science Symposium Proceedings (pp. 93-98). Australia: Bureau of Meteorology and CSIRO.
2011	Micevski, T., Lerat, J., Kavetski, D., Thyer, M., & Kuczera, G. (2011). Exploring the utility of multi-response calibration in river system modelling. In Proceedings of the 19th MODSIM (pp. 3889-3895). Australia: The Modelling and Simulation Society of Australia and NZ. Scopus5 WoS4
2011	Kavetski, D., Evin, G., Clark, M., Thyer, M., Kuczera, G., Renard, B., . . . Tuteja, N. (2011). Battling hydrological monsters: Insights into numerical approximations, data uncertainty and structural errors. In Proceedings of the 34th IAHR World Congress (pp. 1411-1418). Australia: Engineers Australia. Scopus1
2011	Thyer, M., Renard, B., Kavetski, D., Kuczera, G., & Clark, M. (2011). Improving hydrological model predictions by incorporating rating curve uncertainty. In Proceedings of the 34th IAHR World Congress (pp. 1546-1553). Australia: Engineers Australia. Scopus3
2011	Lockart, N., Kavetski, D., & Franks, S. (2011). Hydro-climatological variability in the Murray-Darling Basin. In S. Franks, E. Boegh, E. Blyth, D. Hannah, & K. Yilmaz (Eds.), IAHS-AISH Publication Vol. 344 (pp. 105-111). Melbourne, AUSTRALIA: INT ASSOC HYDROLOGICAL SCIENCES.
2009	Renard, B., Leblois, E., Kuczera, G., Kavetski, D., Thyer, M., & Franks, S. (2009). Characterizing errors in areal rainfall estimates: application to uncertainty quantification and decomposition in hydrologic modelling. In Proceedings of H2009, the 32nd Hydrology and Water Resources Symposium (pp. 505-516). Australia: Engineers Australia.
2009	Thyer, M., Renard, B., Kavetski, D., & Kuczera, G. (2009). Impact of runoff measurement error models on the quantification of predictive uncertainty in rainfall-runoff models. In Interfacing modelling and simulation with mathematical and computational sciences : 18th IMACS World Congress, MODSIM09, Cairns, Australia 13-17 July 2009 : proceedings (pp. 3414-3420). Christchurch: Modelling and Simulation Society of Australia and New Zealand. Scopus3 WoS2
2009	Thyer, M. A., Renard, B., Kavetski, D., & Kuczera, G. (2009). Impact of runoff measurement error models on the quantification of predictive uncertainty in rainfall-runoff models. In 18th World IMACS Congress and MODSIM 2009 - International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, Proceedings (pp. 3414-3420). Scopus4
2008	Renard, B., Kuczera, G., Kavetski, D., Thyer, M., & Franks, S. (2008). Bayesian Total Error Analysis for hydrologic models: Quantifying uncertainties arising from input, output and structural errors. In 31st Hydrology and Water Resources Symposium (pp. 608-619). Modbury, SA: Engineers Australia.
2008	Thyer, M., Renard, B., Kavetski, D., Kuczera, G., & Srikanthan, S. (2008). Investigating the impact of predicitive uncertainity in rainfall-runoff modelling on storage reliability estimates using Bayesian total error analysis. In R. Babcock, & R. Walton (Eds.), Proceedings of the World Environmental and Water Resources Congress Vol. 316 (pp. 0 pages). USA: American Society of Civil Engineers (ASCE). DOI Scopus1
2008	Kavetski, D., Thyer, M., Renard, B., Kuczera, G., Franks, S., & Srikanthan, S. (2008). Scrutinizing parameter consistency and predictive uncertainty in rainfall-runoff models using Bayesian total error analysis. In R. Babcock, & R. Walton (Eds.), Proceedings of the World Environmental and Water Resources Congress 2008 Vol. 316 (pp. 0 pages). USA: American Society of Civil Engineers (ASCE). DOI Scopus1
2007	Kuczera, G., Kavetski, D., Renard, B., & Thyer, M. (2007). Bayesian total error analysis for hydrologic models: Markov chain Monte Carlo methods to evaluate the posterior distribution. In MODSIM 2007 International Congress on Modelling and Simulation (pp. 2466-2472). Christchurch: Modelling and Simulation Society of Australia and New Zealand. Scopus7 WoS3
2007	Renard, B., Thyer, M., Kuczera, G., & Kavetski, D. (2007). Bayesian total error analysis for hydrologic models: sensitivity to error models. In MODSIM 2007 International Congress on Modelling and Simulation (pp. 2473-2489). Christchurch: Modelling and Simulation Society of Australia and New Zealand,. Scopus5 WoS4
2007	Thyer, M., Renard, B., Kavetski, D., Kuczera, G., & Srikanthan, R. (2007). Bayesian total error analysis for hydrological models: preliminary evaluation using multi-site catchment rainfall data. In International Congress on Modelling and Simulation 2007 (pp. 2459-2465). Christchurch: Modelling and Simulation Society of Australia and New Zealand. Scopus5 WoS3
2007	Kavetski, D., Kuczera, G., Thyer, M., & Renard, B. (2007). Multistart Newton-type optimisation methods for the calibration of conceptual hydrological models. In MODSIM 2007 International Congress on Modelling and Simulation (pp. 2513-2519). Modelling and Simulation Society of Australia and New Zealand: Christchurch. Scopus9 WoS8
2007	Celia, M. A., Nordbotten, J. M., Gasda, S. E., Kavetski, D., & Bachu, S. (2007). Geological storage as a carbon mitigation option. In GEOCHIMICA ET COSMOCHIMICA ACTA Vol. 71 (pp. A153). Cologne, GERMANY: PERGAMON-ELSEVIER SCIENCE LTD. WoS1
2007	Kavetski, D., Peters, C., Celia, M., & Lindquist, B. (2007). Upscaling reaction rate laws in geochemical reactive transport using pore-scale network models. In GEOCHIMICA ET COSMOCHIMICA ACTA Vol. 71 (pp. A470). Cologne, GERMANY: PERGAMON-ELSEVIER SCIENCE LTD. WoS2
2005	Kuczera, G., Kavetski, D., Franks, S., & Thyer, M. (2005). Characterizing model error in conceptual rainfall-runoff models using storm-dependent parameters. In MODSIM 2005 International Congress on Modelling and Simulation (pp. 2925-2931). Canberra, Australia: Modelling and Simulation Society of Australia and New Zealand. Scopus2 WoS1
2000	Kavetski, D., Franks, S., & Kuczera, G. (2000). Calibration of hydrologic models: The role of input errors. In Computational methods in water resources - Volume 1 - Computational methods for subsurface flow and transport (pp. 503-510). Scopus2
2000	Kavetski, D., Binning, P., & Sloan, S. (2000). Automatic time stepping with error control for numerical solution of nonlinear PDEs: 2. Application to Richards equation. In Computational methods in water resources - Volume 2 - Computational methods,surface water systems and hydrology (pp. 693-700).
2000	Binning, P., Kavetski, D., & Sloan, S. (2000). Automatic time stepping with error control for numerical solution of nonlinear PDEs: 1. Algorithm development. In Computational methods in water resources - Volume 2 - Computational methods,surface water systems and hydrology (pp. 685-692). Scopus1

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).
2011	Tuteja, N. K., Shin, D., Laugesen, R., Khan, U., Shao, Q., Wang, E., . . . Le, B. (2011). Experimental evaluation of the dynamic seasonal streamflow forecasting approach. Melbourne, Victoria: Commonwealth of Australia (Bureau of Meteorology).

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

Software

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

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
-	Thyer, M., & Kavetski, D. (n.d.). Advances in improving streamflow predictions, with applications in forecasting. DOI
-	Thyer, M., McInerney, D., Kavetski, D., Kuczera, G., & Lerat, J. (n.d.). Improving probabilistic prediction of daily streamflow. DOI

Research Funding

Grants
Year	Project	Chief Investigators	Funding Body	Amount
2019-2021	Delivering robust hydrological predictions for Australia’s water resource challenges	Thyer, Kavetski, Maier, Westra, Simmons, Jakeman, Croke, Gupta	Australian Research Council (ARC) Discovery Project	$381k
2018-2020	Subseasonal streamflow forecasting	Thyer and Kavetski	Australian Bureau of Meteorology	$426k
2014-2017	A robust integrated streamflow forecasting framework for Australian water information and management agencies	Kavetski, Thyer, Kuczera, Tuteja, Shin, Seed, Lerat, Tibaldi, Clark, Wood	Australian Research Council (ARC) Linkage Project	$270k
2011-2013	The development of IWWS operating rules project	Kuczera, Kavetski	Water Corporation of Western Australia (WCWA)	$468k
2011-2013	Robust optimization of urban drought security for an uncertain climate	Kuczera, Kavetski, Kiem	National Climate Change Adaptation Research Facility (NCCARF), Australia	$217k
2010-2012	Robust streamflow prediction by improving the identification of hydrological model structure	Kavetski, Kuczera, Thyer, Franks	Australian Research Council (ARC) Discovery Project	$240k
2010-2013	An integrated modelling approach for the efficient management of irrigated landscapes	Kuczera, Kavetski, Thyer, Franks, Selle, Githui, Thayalakumaran	Australian Research Council (ARC) Linkage Project	$185k
2010-2012	Adapting Bayesian Total Error Analysis to river systems modelling	Kuczera, Thyer, Kavetski	CSIRO, Flagship Project	$200k
2010-2011	Supply of Bayesian Total Error Analysis	Kuczera, Thyer, Kavetski	Australian Bureau of Meteorology	$125k
2010-2011	Improving flood forecasting via robust handling of data and model uncertainties in hydrologic predictions	Thyer, Kavetski, Kuczera, Franks, Renard, Andreassian, Perrin, Lang, Sauquet	Australian Department of Innovation, Industry, Science and Research (DIISR)	$20k
2008-2010	Urban water systems project	Kuczera, Thyer, Rodriguez, Kavetski	eWater CRC, Core project	$1,911k
2007-2011	Research Fellowship grant	Kavetski	University of Newcastle, Australia	$491k

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

Editorial Boards

Date Role Editorial Board Name Institution Country
2010 - ongoing Associate Editor Water Resources Research American Geophysical Union United States

Date	Role	Editorial Board Name	Institution	Country
2010 - ongoing	Associate Editor	Water Resources Research	American Geophysical Union	United States

Position: Professor
Phone: 83131710
Email: dmitri.kavetski@adelaide.edu.au
Fax: 83134359
Campus: North Terrace
Building: Engineering North, floor 1
Org Unit: Environmental Engineering