George Kuczera

9.7k total citations · 1 hit paper
195 papers, 7.5k citations indexed

About

George Kuczera is a scholar working on Global and Planetary Change, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, George Kuczera has authored 195 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 141 papers in Global and Planetary Change, 126 papers in Water Science and Technology and 51 papers in Environmental Engineering. Recurrent topics in George Kuczera's work include Hydrology and Watershed Management Studies (113 papers), Hydrology and Drought Analysis (89 papers) and Flood Risk Assessment and Management (84 papers). George Kuczera is often cited by papers focused on Hydrology and Watershed Management Studies (113 papers), Hydrology and Drought Analysis (89 papers) and Flood Risk Assessment and Management (84 papers). George Kuczera collaborates with scholars based in Australia, United States and China. George Kuczera's co-authors include Stewart W. Franks, Dmitri Kavetski, Mark Thyer, Éric Parent, Peter J Coombes, Anthony S. Kiem, Tom Micevski, Lijie Cui, David McInerney and J. D. Kalma and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Science of The Total Environment and Water Research.

In The Last Decade

George Kuczera

190 papers receiving 6.9k citations

Hit Papers

Monte Carlo assessment of... 1998 2026 2007 2016 1998 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
George Kuczera Australia 44 5.0k 4.8k 2.6k 1.2k 946 195 7.5k
Donald H. Burn Canada 50 5.6k 1.1× 6.6k 1.4× 2.2k 0.9× 1.1k 0.9× 2.1k 2.2× 162 9.5k
David R. Maidment United States 44 4.7k 0.9× 4.0k 0.8× 1.9k 0.7× 951 0.8× 1.2k 1.3× 201 7.7k
K. Beven United Kingdom 26 5.7k 1.1× 3.9k 0.8× 2.8k 1.1× 715 0.6× 836 0.9× 41 6.9k
Henrik Madsen Denmark 42 4.4k 0.9× 5.4k 1.1× 2.1k 0.8× 909 0.8× 2.0k 2.1× 124 7.5k
Okke Batelaan Belgium 50 4.4k 0.9× 4.0k 0.8× 4.2k 1.6× 818 0.7× 949 1.0× 289 8.9k
K. P. Sudheer India 41 3.9k 0.8× 3.3k 0.7× 4.4k 1.7× 645 0.5× 725 0.8× 119 7.0k
Mukand S. Babel Thailand 50 3.2k 0.6× 3.6k 0.7× 1.6k 0.6× 1.2k 1.0× 1.3k 1.4× 205 6.8k
Xu Liang United States 27 5.6k 1.1× 5.2k 1.1× 2.0k 0.8× 497 0.4× 2.6k 2.7× 77 7.9k
Stewart W. Franks Australia 39 5.0k 1.0× 5.1k 1.1× 2.2k 0.9× 543 0.4× 1.7k 1.8× 104 7.3k
Dmitri Kavetski Australia 44 6.1k 1.2× 5.0k 1.0× 3.5k 1.4× 830 0.7× 1.7k 1.8× 112 8.1k

Countries citing papers authored by George Kuczera

Since Specialization
Citations

This map shows the geographic impact of George Kuczera's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by George Kuczera with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George Kuczera more than expected).

Fields of papers citing papers by George Kuczera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by George Kuczera. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by George Kuczera. The network helps show where George Kuczera may publish in the future.

Co-authorship network of co-authors of George Kuczera

This figure shows the co-authorship network connecting the top 25 collaborators of George Kuczera. A scholar is included among the top collaborators of George Kuczera based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with George Kuczera. George Kuczera is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Senanayake, I.P., In‐Young Yeo, & George Kuczera. (2024). Three Decades of Inundation Dynamics in an Australian Dryland Wetland: An Eco-Hydrological Perspective. Remote Sensing. 16(17). 3310–3310. 3 indexed citations
2.
Senanayake, I.P., In‐Young Yeo, & George Kuczera. (2023). A Random Forest-Based Multi-Index Classification (RaFMIC) Approach to Mapping Three-Decadal Inundation Dynamics in Dryland Wetlands Using Google Earth Engine. Remote Sensing. 15(5). 1263–1263. 11 indexed citations
3.
McInerney, David, Mark Thyer, Dmitri Kavetski, et al.. (2021). Improving the Reliability of Sub‐Seasonal Forecasts of High and Low Flows by Using a Flow‐Dependent Nonparametric Model. Water Resources Research. 57(11). 14 indexed citations
4.
Kavetski, Dmitri, et al.. (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. 29 indexed citations
5.
Kavetski, Dmitri, et al.. (2018). A Robust Gauss‐Newton Algorithm for the Optimization of Hydrological Models: Benchmarking Against Industry‐Standard Algorithms. Water Resources Research. 54(11). 9637–9654. 29 indexed citations
6.
Chowdhury, Kamal, et al.. (2017). Development and evaluation of a stochastic daily rainfall model with long-term variability. Hydrology and earth system sciences. 21(12). 6541–6558. 16 indexed citations
7.
Haddad, Khaled, et al.. (2009). Regional flood estimation technique for NSW: application of generalised least squares quantile regression technique. 829. 5 indexed citations
8.
Cui, Lijie & George Kuczera. (2009). Application of Multiobjective Optimization Methods for Urban Water Management: A Case Study for Canberra Water Supply System. 887. 3 indexed citations
9.
Kuczera, George, et al.. (2009). Addressing the shortcomings of water resource simulation models based on network linear programming. 877. 5 indexed citations
10.
Micevski, Tom & George Kuczera. (2008). A General and Practical Bayesian Procedure for Regional and At-site Flood Frequency Analysis. NOVA (University of Newcastle Australia). 363. 1 indexed citations
11.
Thyer, Mark, Andrew Frost, George Kuczera, & R. Srikanthan. (2006). Stochastic Modelling of (Not-so) Long-term Hydrological Data: Current Status and Future Research. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 321. 1 indexed citations
12.
Coombes, Peter J, et al.. (2003). The Impact of Supply and Demand Management Approaches on the Security of Sydney's Water Supply. 3. 6 indexed citations
13.
Coombes, Peter J, et al.. (2003). Development of Stochastic Multisite Rainfall and Urban Water Demand for the Central Coast Region of New South Wales. 2. 3 indexed citations
14.
Coombes, Peter J & George Kuczera. (2003). A Sensitivity Analysis of an Investment Model Used to Determine the Economic Benefits of Rainwater Tanks. 2. 15 indexed citations
15.
Coombes, Peter J, George Kuczera, & J. D. Kalma. (2002). Economic, Water Quantity and Quality Results from a House with a Rainwater Tank in the Inner City. 861. 14 indexed citations
16.
Lambert, Martin F., et al.. (2002). Regionalisation of a High Resolution Point Rainfall Model. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 726. 2 indexed citations
17.
Lambert, Martin F., et al.. (2002). Overcoming the Joint Probability Problem Associated with Initial Loss Estimation in Design Flood Estimation. 70. 4 indexed citations
18.
Coombes, Peter J, George Kuczera, & J. D. Kalma. (2000). A probabilistic behavioural model for simulation of exhouse water demand. 793. 5 indexed citations
19.
Thyer, Mark & George Kuczera. (2000). A New Approach for Modelling Long Term Rainfall Persistence at Multiple Sites. 544. 1 indexed citations
20.
Kuczera, George, Brian P. Williams, Philip John Binning, & Martin F. Lambert. (2000). An education web site for free water engineering software. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 1048. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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