| Year |
Citation |
Score |
| 2020 |
McInerney D, Thyer M, Kavetski D, Laugesen R, Tuteja N, Kuczera G. Multi‐temporal hydrological residual error modelling for seamless sub‐seasonal streamflow forecasting Water Resources Research. DOI: 10.1029/2019Wr026979 |
0.458 |
|
| 2020 |
Lerat J, Thyer M, McInerney D, Kavetski D, Woldemeskel F, Pickett-Heaps C, Shin D, Feikema P. A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data Journal of Hydrology. 591: 125129. DOI: 10.1016/J.Jhydrol.2020.125129 |
0.464 |
|
| 2019 |
McInerney D, Kavetski D, Thyer M, Lerat J, Kuczera G. Benefits of Explicit Treatment of Zero Flows in Probabilistic Hydrological Modeling of Ephemeral Catchments Water Resources Research. 55: 11035-11060. DOI: 10.1029/2018Wr024148 |
0.363 |
|
| 2018 |
Gibbs MS, McInerney D, Humphrey G, Thyer MA, Maier HR, Dandy GC, Kavetski D. State updating and calibration period selection to improve dynamic monthly streamflow forecasts for an environmental flow management application Hydrology and Earth System Sciences. 22: 871-887. DOI: 10.5194/Hess-22-871-2018 |
0.462 |
|
| 2018 |
Woldemeskel F, McInerney D, Lerat J, Thyer M, Kavetski D, Shin D, Tuteja N, Kuczera G. Evaluating post-processing approaches for monthly and seasonal streamflow forecasts Hydrology and Earth System Sciences. 22: 6257-6278. DOI: 10.5194/Hess-22-6257-2018 |
0.419 |
|
| 2018 |
Woldemeskel F, McInerney D, Lerat J, Thyer M, Kavetski D, Shin D, Tuteja N, Kuczera G. Evaluating residual error approaches for post-processing monthly and seasonal streamflow forecasts Hydrology and Earth System Sciences Discussions. 1-40. DOI: 10.5194/Hess-2018-214 |
0.47 |
|
| 2018 |
Qin Y, Kavetski D, Kuczera G. A Robust Gauss‐Newton Algorithm for the Optimization of Hydrological Models: From Standard Gauss‐Newton to Robust Gauss‐Newton Water Resources Research. 54: 9655-9683. DOI: 10.1029/2017Wr022488 |
0.356 |
|
| 2018 |
Kavetski D, Qin Y, Kuczera G. The Fast and the Robust: Trade‐Offs Between Optimization Robustness and Cost in the Calibration of Environmental Models Water Resources Research. 54: 9432-9455. DOI: 10.1029/2017Wr022051 |
0.35 |
|
| 2018 |
McInerney D, Thyer M, Kavetski D, Githui F, Thayalakumaran T, Liu M, Kuczera G. The Importance of Spatiotemporal Variability in Irrigation Inputs for Hydrological Modeling of Irrigated Catchments Water Resources Research. 54: 6792-6821. DOI: 10.1029/2017Wr022049 |
0.417 |
|
| 2018 |
Henn B, Clark MP, Kavetski D, Newman AJ, Hughes M, McGurk B, Lundquist JD. Spatiotemporal patterns of precipitation inferred from streamflow observations across the Sierra Nevada mountain range Journal of Hydrology. 556: 993-1012. DOI: 10.1016/J.Jhydrol.2016.08.009 |
0.373 |
|
| 2018 |
McInerney D, Thyer MA, Kavetski D, Bennett B, Lerat J, Gibbs MS, Kuczera G. A simplified approach to produce probabilistic hydrological model predictions Environmental Modelling and Software. 109: 306-314. DOI: 10.1016/J.Envsoft.2018.07.001 |
0.517 |
|
| 2018 |
Fenicia F, Kavetski D, Reichert P, Albert C. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Empirical Analysis of Fundamental Properties Water Resources Research. 54: 3958-3987. DOI: 10.1002/2017Wr021616 |
0.43 |
|
| 2018 |
Kavetski D, Fenicia F, Reichert P, Albert C. Signature‐Domain Calibration of Hydrological Models Using Approximate Bayesian Computation: Theory and Comparison to Existing Applications Water Resources Research. 54: 4059-4083. DOI: 10.1002/2017Wr020528 |
0.37 |
|
| 2017 |
Gibbs MS, McInerney D, Humphrey G, Thyer MA, Maier HR, Dandy GC, Kavetski D. State Updating and Calibration Period Selection to Improve Dynamic Monthly Streamflow Forecasts for a Wetland Management Application Hydrology and Earth System Sciences Discussions. 1-29. DOI: 10.5194/Hess-2017-381 |
0.46 |
|
| 2017 |
Schaefli B, Kavetski D. Bayesian spectral likelihood for hydrological parameter inference Water Resources Research. 53: 6857-6884. DOI: 10.1002/2016Wr019465 |
0.465 |
|
| 2017 |
McInerney D, Thyer M, Kavetski D, Lerat J, Kuczera G. Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors Water Resources Research. 53: 2199-2239. DOI: 10.1002/2016Wr019168 |
0.44 |
|
| 2016 |
Giustarini L, Hostache R, Kavetski D, Chini M, Corato G, Schlaffer S, Matgen P. Probabilistic Flood Mapping Using Synthetic Aperture Radar Data Ieee Transactions On Geoscience and Remote Sensing. 54: 6958-6969. DOI: 10.1109/Tgrs.2016.2592951 |
0.338 |
|
| 2016 |
Qin Y, Kuczera G, Kavetski D. Comparison of Newton-type and SCE optimisation algorithms for the calibration of conceptual hydrological models Australian Journal of Water Resources. 20: 169-176. DOI: 10.1080/13241583.2017.1298180 |
0.387 |
|
| 2016 |
Henn B, Clark MP, Kavetski D, McGurk B, Painter TH, Lundquist JD. Combining snow, streamflow, and precipitation gauge observations to infer basin-mean precipitation Water Resources Research. 52: 8700-8723. DOI: 10.1002/2015Wr018564 |
0.452 |
|
| 2016 |
Fenicia F, Kavetski D, Savenije HHG, Pfister L. From spatially variable streamflow to distributed hydrological models: analysis of key modeling decisions Water Resources Research. 52: 954-989. DOI: 10.1002/2015Wr017398 |
0.538 |
|
| 2015 |
Hill MC, Kavetski D, Clark M, Ye M, Arabi M, Lu D, Foglia L, Mehl S. Practical Use of Computationally Frugal Model Analysis Methods. Ground Water. PMID 25810333 DOI: 10.1111/Gwat.12330 |
0.476 |
|
| 2015 |
Lockart N, Kavetski D, Franks SW. A new stochastic model for simulating daily solar radiation from sunshine hours International Journal of Climatology. 35: 1090-1106. DOI: 10.1002/Joc.4041 |
0.411 |
|
| 2015 |
Wrede S, Fenicia F, Martínez-Carreras N, Juilleret J, Hissler C, Krein A, Savenije HHG, Uhlenbrook S, Kavetski D, Pfister L. Towards more systematic perceptual model development: a case study using 3 Luxembourgish catchments Hydrological Processes. 29: 2731-2750. DOI: 10.1002/Hyp.10393 |
0.461 |
|
| 2015 |
Clark MP, Nijssen B, Lundquist JD, Kavetski D, Rupp DE, Woods RA, Freer JE, Gutmann ED, Wood AW, Gochis DJ, Rasmussen RM, Tarboton DG, Mahat V, Flerchinger GN, Marks DG. A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies Water Resources Research. 51: 2515-2542. DOI: 10.1002/2015Wr017200 |
0.445 |
|
| 2015 |
Clark MP, Nijssen B, Lundquist JD, Kavetski D, Rupp DE, Woods RA, Freer JE, Gutmann ED, Wood AW, Brekke LD, Arnold JR, Gochis DJ, Rasmussen RM. A unified approach for process-based hydrologic modeling: 1. Modeling concept Water Resources Research. 51: 2498-2514. DOI: 10.1002/2015Wr017198 |
0.515 |
|
| 2015 |
Henn B, Clark MP, Kavetski D, Lundquist JD. Estimating mountain basin-mean precipitation from streamflow using Bayesian inference Water Resources Research. 51: 8012-8033. DOI: 10.1002/2014Wr016736 |
0.483 |
|
| 2014 |
Pagano TC, Wood AW, Ramos M, Cloke HL, Pappenberger F, Clark MP, Cranston M, Kavetski D, Mathevet T, Sorooshian S, Verkade JS. Challenges of Operational River Forecasting Journal of Hydrometeorology. 15: 1692-1707. DOI: 10.1175/Jhm-D-13-0188.1 |
0.379 |
|
| 2014 |
Fenicia F, Kavetski D, Savenije HHG, Clark MP, Schoups G, Pfister L, Freer J. Catchment properties, function, and conceptual model representation: Is there a correspondence? Hydrological Processes. 28: 2451-2467. DOI: 10.1002/Hyp.9726 |
0.366 |
|
| 2014 |
Westra S, Thyer M, Leonard M, Kavetski D, Lambert M. A strategy for diagnosing and interpreting hydrological model nonstationarity Water Resources Research. 50: 5090-5113. DOI: 10.1002/2013Wr014719 |
0.535 |
|
| 2014 |
Evin G, Thyer M, Kavetski D, McInerney D, Kuczera G. Comparison of joint versus postprocessor approaches for hydrological uncertainty estimation accounting for error autocorrelation and heteroscedasticity Water Resources Research. 50: 2350-2375. DOI: 10.1002/2013Wr014185 |
0.502 |
|
| 2013 |
Esse WRv, Perrin C, Booij MJ, Augustijn DCM, Fenicia F, Kavetski D, Lobligeois F. The influence of conceptual model structure on model performance: a comparative study for 237 French catchments Hydrology and Earth System Sciences. 17: 4227-4239. DOI: 10.5194/Hess-17-4227-2013 |
0.49 |
|
| 2013 |
Hill MC, Faunt CC, Belcher WR, Sweetkind DS, Tiedeman CR, Kavetski D. Knowledge, transparency, and refutability in groundwater models, an example from the Death Valley regional groundwater flow system Physics and Chemistry of the Earth. 64: 105-116. DOI: 10.1016/J.Pce.2013.03.006 |
0.496 |
|
| 2013 |
Evin G, Kavetski D, Thyer M, Kuczera G. Pitfalls and improvements in the joint inference of heteroscedasticity and autocorrelation in hydrological model calibration Water Resources Research. 49: 4518-4524. DOI: 10.1002/Wrcr.20284 |
0.522 |
|
| 2013 |
Ershadi A, McCabe MF, Evans JP, Mariethoz G, Kavetski D. A Bayesian analysis of sensible heat flux estimation: Quantifying uncertainty in meteorological forcing to improve model prediction Water Resources Research. 49: 2343-2358. DOI: 10.1002/Wrcr.20231 |
0.362 |
|
| 2012 |
Fenicia F, Pfister L, Kavetski D, Matgen P, Iffly J, Hoffmann L, Uijlenhoet R. Microwave links for rainfall estimation in an urban environment: Insights from an experimental setup in Luxembourg-City Journal of Hydrology. 464: 69-78. DOI: 10.1016/J.Jhydrol.2012.06.047 |
0.432 |
|
| 2011 |
Kavetski D, Fenicia F. Elements of a flexible approach for conceptual hydrological modeling : 2. Application and experimental insights Water Resources Research. 47. DOI: 10.1029/2011Wr010748 |
0.518 |
|
| 2011 |
Clark MP, Hendrikx J, Slater AG, Kavetski D, Anderson B, Cullen NJ, Kerr T, Örn Hreinsson E, Woods RA. Representing spatial variability of snow water equivalent in hydrologic and land-surface models: A review Water Resources Research. 47. DOI: 10.1029/2011Wr010745 |
0.387 |
|
| 2011 |
Renard B, Kavetski D, Leblois E, Thyer M, Kuczera G, Franks SW. Toward a reliable decomposition of predictive uncertainty in hydrological modeling: Characterizing rainfall errors using conditional simulation Water Resources Research. 47: 1-21. DOI: 10.1029/2011Wr010643 |
0.518 |
|
| 2011 |
Fenicia F, Kavetski D, Savenije HHG. Elements of a flexible approach for conceptual hydrological modeling : 1. Motivation and theoretical development Water Resources Research. 47. DOI: 10.1029/2010Wr010174 |
0.484 |
|
| 2011 |
Clark MP, Kavetski D, Fenicia F. Pursuing the method of multiple working hypotheses for hydrological modeling Water Resources Research. 47. DOI: 10.1029/2010Wr009827 |
0.48 |
|
| 2011 |
Kavetski D, Fenicia F, Clark MP. Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment Water Resources Research. 47. DOI: 10.1029/2010Wr009525 |
0.484 |
|
| 2011 |
McMillan H, Jackson B, Clark M, Kavetski D, Woods R. Rainfall uncertainty in hydrological modelling: An evaluation of multiplicative error models Journal of Hydrology. 400: 83-94. DOI: 10.1016/J.Jhydrol.2011.01.026 |
0.498 |
|
| 2011 |
Clark MP, McMillan HK, Collins DBG, Kavetski D, Woods RA. Hydrological field data from a modeller's perspective: Part 2: Process-based evaluation of model hypotheses Hydrological Processes. 25: 523-543. DOI: 10.1002/Hyp.7902 |
0.487 |
|
| 2010 |
Kuczera G, Renard B, Thyer M, Kavetski D. There are no hydrological monsters, just models and observations with large uncertainties! Hydrological Sciences Journal-Journal Des Sciences Hydrologiques. 55: 980-991. DOI: 10.1080/02626667.2010.504677 |
0.512 |
|
| 2010 |
Kuczera G, Kavetski D, Renard B, Thyer M. A limited-memory acceleration strategy for MCMC sampling in hierarchical Bayesian calibration of hydrological models. Water Resources Research. 46. DOI: 10.1029/2009Wr008985 |
0.489 |
|
| 2010 |
Kavetski D, Clark MP. Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction Water Resources Research. 46. DOI: 10.1029/2009Wr008896 |
0.529 |
|
| 2010 |
Clark MP, Kavetski D. Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes Water Resources Research. 46. DOI: 10.1029/2009Wr008894 |
0.504 |
|
| 2010 |
Renard B, Kavetski D, Kuczera G, Thyer M, Franks SW. Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors Water Resources Research. 46: 1-22. DOI: 10.1029/2009Wr008328 |
0.493 |
|
| 2010 |
Fenicia F, Wrede S, Kavetski D, Pfister L, Hoffmann L, Savenije HHG, McDonnell JJ. Assessing the impact of mixing assumptions on the estimation of streamwater mean residence time Hydrological Processes. 24: 1730-1741. DOI: 10.1002/Hyp.7595 |
0.47 |
|
| 2009 |
Nordbotten JM, Kavetski D, Celia MA, Bachu S. Model for CO2 leakage including multiple geological layers and multiple leaky wells. Environmental Science & Technology. 43: 743-9. PMID 19245011 DOI: 10.1021/Es801135V |
0.318 |
|
| 2009 |
Thyer M, Renard B, Kavetski D, Kuczera G, Franks SW, Srikanthan S. Critical evaluation of parameter consistency and predictive uncertainty in hydrological modeling: A case study using Bayesian total error analysis Water Resources Research. 45: 1-22. DOI: 10.1029/2008Wr006825 |
0.526 |
|
| 2009 |
Renard B, Kavetski D, Kuczera G. 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. DOI: 10.1029/2007Wr006538 |
0.356 |
|
| 2008 |
Viswanathan HS, Pawar RJ, Stauffer PH, Kaszuba JP, Carey JW, Olsen SC, Keating GN, Kavetski D, Guthrie GD. Development of a hybrid process and system model for the assessment of wellbore leakage at a geologic CO2 sequestration site. Environmental Science & Technology. 42: 7280-6. PMID 18939559 DOI: 10.1021/Es800417X |
0.32 |
|
| 2007 |
Kavetski D, Kuczera G. Model smoothing strategies to remove microscale discontinuities and spurious secondary optima in objective functions in hydrological calibration Water Resources Research. 43. DOI: 10.1029/2006Wr005195 |
0.464 |
|
| 2006 |
Kavetski D, Kuczera G, Franks SW. Bayesian analysis of input uncertainty in hydrological modeling: 2. Application Water Resources Research. 42: 1-10. DOI: 10.1029/2005Wr004376 |
0.539 |
|
| 2006 |
Kavetski D, Kuczera G, Franks SW. Bayesian analysis of input uncertainty in hydrological modeling: 1. Theory Water Resources Research. 42: 1-9. DOI: 10.1029/2005Wr004368 |
0.546 |
|
| 2006 |
Kuczera G, Kavetski D, Franks S, Thyer M. Towards a Bayesian total error analysis of conceptual rainfall-runoff models: Characterising model error using storm-dependent parameters Journal of Hydrology. 331: 161-177. DOI: 10.1016/J.Jhydrol.2006.05.010 |
0.556 |
|
| 2006 |
Kavetski D, Kuczera G, Franks SW. Calibration of conceptual hydrological models revisited: 2. Improving optimisation and analysis Journal of Hydrology. 320: 187-201. DOI: 10.1016/J.Jhydrol.2005.07.013 |
0.502 |
|
| 2006 |
Kavetski D, Kuczera G, Franks SW. Calibration of conceptual hydrological models revisited: 1. Overcoming numerical artefacts Journal of Hydrology. 320: 173-186. DOI: 10.1016/J.Jhydrol.2005.07.012 |
0.506 |
|
| 2003 |
Kavetski D, Kuczera G, Franks SW. Semidistributed hydrological modeling: A “saturation path” perspective on TOPMODEL and VIC Water Resources Research. 39. DOI: 10.1029/2003Wr002122 |
0.524 |
|
| 2002 |
Kavetski D, Binning PJ, Sloan SW. Noniterative time stepping schemes with adaptive truncation error control for the solution of Richards equation Water Resources Research. 38. DOI: 10.1029/2001Wr000720 |
0.325 |
|
| 2002 |
Kavetski D, Binning PJ, Sloan SW. Adaptive backward Euler time stepping with truncation error control for numerical modelling of unsaturated fluid flow International Journal For Numerical Methods in Engineering. 53: 1301-1322. DOI: 10.1002/Nme.329 |
0.418 |
|
| 2001 |
Kavetski D, Binning P, Sloan SW. Adaptive time stepping and error control in a mass conservative numerical solution of the mixed form of Richards equation Advances in Water Resources. 24: 595-605. DOI: 10.1016/S0309-1708(00)00076-2 |
0.365 |
|
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