John Doherty

5.7k citations

115 papers · 4.4k indexed · 2 hit papers · h-index 33

Impact in

Environmental Engineering top 0.2%
- Groundwater flow and contamination studies
Water Science and Technology top 0.5%
- Hydrology and Watershed Management Studies

Papers in ⓘ

Environmental Engineering 64
- Groundwater flow and contamination studies 59
Ocean Engineering 37
- Reservoir Engineering and Simulation Methods 26

Co-authors: Matthew Tonkin (6 shared papers)Catherine Moore (8 shared papers)Yaochu Jin (8 shared papers)Handing Wang (6 shared papers)Randall J. Hunt (9 shared papers)Marcus Gallagher (3 shared papers)John M. Johnston (2 shared papers)Steen Christensen (4 shared papers)
Journals: Ground Water (14 papers)Water Resources Research (12 papers)Journal of Hydrology (11 papers)Advances in Water Resources (3 papers)Frontiers in Earth Science (3 papers)
Partner nations: Australia United Kingdom United States

In The Last Decade

John Doherty

105 papers receiving 4.1k citations

Hit Papers

align trajectories log scale

A review of liquid hydrogen aircraft and propulsion technologies 2024 · 89 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2024 International Journal of Hydrogen Energy
2017 IEEE Transactions on Cybernetics

Peers

Countries citing papers authored by John Doherty

Since Specialization

Citations

This map shows the geographic impact of John Doherty'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 John Doherty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Doherty more than expected).

Fields of papers citing papers by John Doherty

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Doherty. 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 John Doherty. The network helps show where John Doherty may publish in the future.

Co-authors

The 25 scholars most cited alongside John Doherty, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John Doherty Line = papers co-authored together John Doherty links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 115 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Ground Water Model Calibration Using Pilot Points and Regularization Ground Water ·John Doherty	2003	367
2	Committee-Based Active Learning for Surrogate-Assisted Particle Swarm Optimization of Expensive Problems IEEE Transactions on Cybernetics ·Handing Wang, Yaochu Jin, John Doherty Hit paper breakdown →	2017	314
3	A hybrid regularized inversion methodology for highly parameterized environmental models Water Resources Research ·Matthew Tonkin, John Doherty	2005	209
4	Role of the calibration process in reducing model predictive error Water Resources Research ·Catherine Moore, John Doherty	2005	207
5	METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL¹ JAWRA Journal of the American Water Resources Association ·John Doherty, John M. Johnston	2003	202
6	Offline Data-Driven Evolutionary Optimization Using Selective Surrogate Ensembles IEEE Transactions on Evolutionary Computation ·Handing Wang, Yaochu Jin, Chaoli Sun, John Doherty	2018	179
7	A short exploration of structural noise Water Resources Research ·John Doherty, David E. Welter	2010	178
8	Parameter estimation and uncertainty analysis for a watershed model Environmental Modelling & Software ·Marcus Gallagher, John Doherty	2006	177
9	Calibration‐constrained Monte Carlo analysis of highly parameterized models using subspace techniques Water Resources Research ·Matthew Tonkin, John Doherty	2009	164
10	Optimization and uncertainty assessment of strongly nonlinear groundwater models with high parameter dimensionality Water Resources Research ·Elizabeth Keating, John Doherty, Jasper A. Vrugt, Qinjun Kang	2010	160
11	Are Models Too Simple? Arguments for Increased Parameterization Ground Water ·Randall J. Hunt, John Doherty, Matthew Tonkin	2007	145
12	The cost of uniqueness in groundwater model calibration Advances in Water Resources ·Catherine Moore, John Doherty	2005	134
13	Two statistics for evaluating parameter identifiability and error reduction Journal of Hydrology ·John Doherty, Randall J. Hunt	2009	131
14	Use of paired simple and complex models to reduce predictive bias and quantify uncertainty Water Resources Research ·John Doherty, Steen Christensen	2011	125
15	Quantifying Data Worth Toward Reducing Predictive Uncertainty Ground Water ·Alyssa Dausman, John Doherty, Christian D. Langevin, Michael C. Sukop	2010	96
16	A review of liquid hydrogen aircraft and propulsion technologies International Journal of Hydrogen Energy ·S. N. Tiwari, Michael J. Pekris, John Doherty Hit paper breakdown →	2024	89
17	Efficient accommodation of local minima in watershed model calibration Journal of Hydrology ·Brian Skahill, John Doherty	2006	79
18	Comparison of hydrologic calibration of HSPF using automatic and manual methods Water Resources Research ·Sang Min Kim, Brian Leslie Benham, Kevin M. Brannan, Rebecca W. Zeckoski, John Doherty	2007	76
19	Octopus-Man: QoS-driven task management for heterogeneous multicores in warehouse-scale computers Vinícius Petrucci, Michael A. Laurenzano, John Doherty, Yunqi Zhang, Daniel Mossé, Jason Mars, Lingjia Tang	2015	76
20	Uncertainty assessment and implications for data acquisition in support of integrated hydrologic models Water Resources Research ·Philip Brunner, John Doherty, Craig T. Simmons	2012	71

About John Doherty

John Doherty is a scholar working on Environmental Engineering, Ocean Engineering, Water Science and Technology, Geophysics and Global and Planetary Change, having authored 115 papers that have together received 4.4k indexed citations. Recurring topics across this work include Groundwater flow and contamination studies (59 papers), Hydrology and Watershed Management Studies (32 papers), Reservoir Engineering and Simulation Methods (26 papers), Geophysical and Geoelectrical Methods (13 papers), Hydraulic Fracturing and Reservoir Analysis (12 papers), Advanced Aircraft Design and Technologies (10 papers), Advanced Multi-Objective Optimization Algorithms (9 papers) and Groundwater and Isotope Geochemistry (9 papers). The work is most often cited by research in Environmental Engineering (2.5k citations), Water Science and Technology (1.7k citations), Geochemistry and Petrology (642 citations), Ocean Engineering (1.2k citations) and Global and Planetary Change (746 citations). John Doherty has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Matthew Tonkin, Catherine Moore, Yaochu Jin, Handing Wang, Randall J. Hunt, Marcus Gallagher, John M. Johnston, Steen Christensen, David E. Welter and Brian Skahill. Their work appears in journals such as Ground Water, Water Resources Research, Journal of Hydrology, Advances in Water Resources and Frontiers in Earth Science.

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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