Dmitri Kavetski

Prof Dmitri Kavetski

Professor

School of Civil Engineering and Construction

College of Engineering and Information 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.

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.

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

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 -

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)

Year Citation
2026 Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (2026). Software library to quantify the value of forecasts for decision-making: Case study on sensitivity to damages. Environmental Modelling and Software, 196, 12 pages.
DOI
2025 Fenicia, F., Prieto, C., & Kavetski, D. (2025). A historical perspective on modelling the relationship between catchment wetness and streamflow response. Hydrological Sciences Journal, 70(13), 2258-2277.
DOI
2024 Volpi, E., Grimaldi, S., Aghakouchak, A., Castellarin, A., Chebana, F., Papalexiou, S. M., . . . Sharma, A. (2024). The legacy of STAHY: milestones, achievements, challenges, and open problems in statistical hydrology. Hydrological Sciences Journal, 69(14), 1-37.
DOI Scopus11 WoS10
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 Scopus7 WoS7
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 Scopus12 WoS11
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 Scopus5 WoS5
2023 Renard, B., McInerney, D., Westra, S., Leonard, M., Kavetski, D., Thyer, M., & Vidal, J. (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 Scopus1 WoS1
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 Scopus9 WoS9
2022 Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (2022). Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts.
DOI
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 Scopus9 WoS8
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 Scopus21 WoS20
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 Scopus30 WoS29
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 Scopus7 WoS7
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 Scopus8 WoS8
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 Scopus7 WoS7
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 Scopus20 WoS19
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 Scopus18 WoS15
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 Scopus17 WoS15
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 Scopus15 WoS13
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 Scopus22 WoS19
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 Scopus39 WoS37
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 Scopus87 WoS78
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 WoS20
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 Scopus110 WoS103
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 Scopus18 WoS18
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 Scopus45 WoS45
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 Scopus30 WoS30
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 Scopus32 WoS27
2018 Woldemeskel, F., McInerney, D., Lerat, J., Thyer, M., Kavetski, D., Shin, D., . . . Kuczera, G. (2018). Evaluating residual error approaches for post-processing monthly and seasonal streamflow forecasts.
DOI
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 Scopus43 WoS41
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 Scopus44 WoS43
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 Scopus27 WoS25
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 Scopus31 WoS29
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 WoS33
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 Scopus40 WoS40
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 Scopus120 WoS114
2017 Gibbs, M. S., McInerney, D., Humphrey, G., Thyer, M. A., Maier, H. R., Dandy, G. C., & Kavetski, D. (2017). State Updating and Calibration Period Selection to Improve Dynamic Monthly Streamflow Forecasts for a Wetland Management Application.
DOI
2017 Schaefli, B., & Kavetski, D. (2017). Bayesian spectral likelihood for hydrological parameter inference. Water Resources Research, 53(8), 6857-6884.
DOI Scopus9 WoS8
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 WoS8
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 Scopus25 WoS25
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 Scopus131 WoS120
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 Scopus145 WoS55 Europe PMC2
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 Scopus86 WoS82
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 Scopus179 WoS74
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 Scopus366 WoS342
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 Scopus43 WoS44
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 Scopus81 WoS79
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 Scopus149 WoS140
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 WoS130
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 Scopus150 WoS138
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 Scopus142 WoS130
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 Scopus18 WoS17
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 Scopus102 WoS100
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 Scopus100 WoS94
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 Scopus28 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 Scopus14 WoS12
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 Scopus41 WoS36
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 Scopus196 WoS180
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 Scopus205 WoS194
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 Scopus100 WoS97
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 Scopus302 WoS398
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 Scopus92 WoS114
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 Scopus443 WoS307
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 Scopus77 WoS65
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 Scopus289 WoS286
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 Scopus16 WoS14
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 Scopus62 WoS58
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 Scopus69 WoS67
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 WoS24
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 Scopus700 WoS596
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 Scopus142 WoS131
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 Scopus141 WoS225
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 Scopus79 WoS78
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 Scopus207 WoS190 Europe PMC21
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 Scopus32 WoS30
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 Scopus19 WoS16
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 Scopus326 WoS295
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 Scopus149 WoS134 Europe PMC16
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 Scopus92 WoS86
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 Scopus294 WoS261
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 Scopus519 WoS557
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 Scopus233 WoS76
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 Scopus108 WoS104
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 Scopus57 WoS54
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 Scopus16 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), SWC81-SWC88.
DOI Scopus60 WoS61
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), 29-29-10.
DOI Scopus52 WoS52
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 Scopus89 WoS73
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 Scopus109 WoS94

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 Scopus6
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.

Year Citation
2024 You, L., Kavetski, D., & Lambert, M. (2024). Third-order Polynomial Normal Transform in extreme rainfall modelling: Application to Australian sites. In Hydrology and Water Resources Symposium Hwrs 2024 (pp. 687-690).
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 Scopus1
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.
Scopus8 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 WoS9
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. N., Franks, S. W., & 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. N., Binning, P., & Sloan, S. W. (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. N., & Sloan, S. W. (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

Year Citation
2023 Thyer, M., McInerney, D., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N., & Kuczera, G. (2023). Seamless subseasonal probabilistic streamflow forecasting: MuTHRE lets you have your cake and eat it too. Poster session presented at the meeting of Abstracts of the European Geosciences Union General Assembly (EGU 2023). Vienna, Austria & Online: Copernicus GmbH.
DOI
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
2022 Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (2022). A flexible approach for evaluating the value of probabilistic forecasts for different decision types and risk averse decision-makers. Poster session presented at the meeting of Unknown Conference.
DOI
- Thyer, M., Gupta, H., Westra, S., McInerney, D., Maier, H., Kavetski, D., . . . Tague, C. (n.d.). Virtual Hydrological Laboratories: Developing the next generation of conceptual models to support decision-making under change. Poster session presented at the meeting of Unknown Conference.
DOI

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).

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

Year Citation
2022 Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (2022). 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.). Supporting data for "Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts" by Laugesen et.al. (2023).
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
- 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
- Laugesen, R., Thyer, M., McInerney, D., & Kavetski, D. (n.d.). Supporting data for "Software library to quantify the value of forecasts for decision-making: Case study on sensitivity to damages" by Laugesen et al. (2025).
DOI

Year Citation
2017 McInerney, D., Bennett, B. S., Thyer, M., & Kavetski, D. (2017). Interactive Probabilistic Predictions [Computer Software]. http://www.probabilisticpredictions.org/.
DOI
- McInerney, D., Westra, S., Leonard, M., Kavetski, D., Thyer, M., & Maier, H. (n.d.). Code and data for 'Tailored Calibration of Stochastic Weather Generators for Enhanced Hydrological System Evaluation' by McInerney et al [Computer Software].
DOI

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

Year Citation
- Thyer, M., Kavetski, D., & McInerney, D. (n.d.). Introduction to Evaluating Probabilistic Predictions.
DOI
- Thyer, M., Kavetski, D., McInerney, D., & Renard, B. (n.d.). Introduction to Residual Diagnostics.
DOI
- Thyer, M., Kavetski, D., McInerney, D., & Hunter, J. (n.d.). Guidance on Enhancing Probabilistic Predictions.
DOI
- Thyer, M., McInerney, D., Kavetski, D., Laugesen, R., & Tuteja, N. (n.d.). Do you want high quality subseasonal streamflow forecasts? Ask MuTHRE! vEGU 2021 Conference Presentation.
DOI
- Thyer, M., Hunter, J., McInerney, D., & Kavetski, D. (n.d.). High-quality probabilistic predictions for existing hydrological models with common objective functions: EGU2022 Conference Presentation.
DOI
- Thyer, M., McInerney, D., Kavetski, D., Westra, S., Maier, H., Shanafield, M., . . . Leonard, M. (n.d.). Neglecting hydrological errors can severely impact predictions of water resource system performance.
DOI

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

Year Citation
2022 McInerney, D., Thyer, M., Kavetski, D., Laugesen, R., Woldemeskel, F., Tuteja, N., & Kuczera, G. (2022). Seamless streamflow model provides forecasts at all scales from daily to monthly and matches the performance of non-seamless monthly model.
DOI
2016 Puma, M. J., Celia, M. A., Rodriguez-Iturbe, I., Nordbotten, J. M., Guswa, A. J., & Kavetski, D. (2016). Effects of Spatial Heterogeneity in Rainfall and Vegetation Type on Soil
Moisture and Evapotranspiration.

Research Funding

Year Project Chief Investigators Funding Body Amount
Grants
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

 

Date Role Research Topic Program Degree Type Student Load Student Name
2023 Principal Supervisor A Unified Calibration Framework of Statistical Weather Generators for Climate Risk Assessment Doctor of Philosophy Doctorate Full Time Miss Ling-Wan You
2023 Principal Supervisor A Unified Calibration Framework of Statistical Weather Generators for Climate Risk Assessment Doctor of Philosophy Doctorate Full Time Miss Ling-Wan You
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
2019 Co-Supervisor Improving the value of subseasonal streamflow forecasts for water resource management decisions Doctor of Philosophy Doctorate Full Time Mr Richard Mark Laugesen

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

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