David McInerney

2.0k total citations
43 papers, 1.5k citations indexed

About

David McInerney is a scholar working on Global and Planetary Change, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, David McInerney has authored 43 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Global and Planetary Change, 22 papers in Water Science and Technology and 8 papers in Environmental Engineering. Recurrent topics in David McInerney's work include Hydrology and Watershed Management Studies (22 papers), Flood Risk Assessment and Management (19 papers) and Hydrology and Drought Analysis (17 papers). David McInerney is often cited by papers focused on Hydrology and Watershed Management Studies (22 papers), Flood Risk Assessment and Management (19 papers) and Hydrology and Drought Analysis (17 papers). David McInerney collaborates with scholars based in Australia, United States and France. David McInerney's co-authors include Klaus Keller, Mark Thyer, Dmitri Kavetski, Robert J. Lempert, George Kuczera, Andrew Hackbarth, Jim W. Hall, Julien Lerat, Guillaume Évin and E. J. Moyer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Climate and Earth and Planetary Science Letters.

In The Last Decade

David McInerney

41 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David McInerney Australia 21 830 573 380 235 202 43 1.5k
Zhongjing Wang China 24 792 1.0× 872 1.5× 355 0.9× 148 0.6× 511 2.5× 109 1.8k
Sutat Weesakul Thailand 19 1.2k 1.4× 552 1.0× 637 1.7× 456 1.9× 136 0.7× 48 1.8k
Peng Yang China 25 987 1.2× 521 0.9× 238 0.6× 297 1.3× 188 0.9× 79 1.8k
Mohammad Reza Mansouri Daneshvar Iran 21 502 0.6× 142 0.2× 251 0.7× 197 0.8× 50 0.2× 74 1.3k
Sergei Schreider Australia 18 481 0.6× 542 0.9× 173 0.5× 127 0.5× 280 1.4× 60 993
Sumit Das India 22 1.4k 1.7× 1.0k 1.8× 1.2k 3.1× 118 0.5× 132 0.7× 36 2.0k
Roland Barthel Sweden 23 615 0.7× 924 1.6× 607 1.6× 185 0.8× 253 1.3× 55 1.7k
Satiprasad Sahoo India 21 954 1.1× 465 0.8× 852 2.2× 156 0.7× 113 0.6× 63 1.7k
Pedro Martínez‐Santos Spain 24 534 0.6× 871 1.5× 799 2.1× 38 0.2× 618 3.1× 73 1.9k
Alexandra Gemitzi Greece 21 415 0.5× 376 0.7× 513 1.4× 138 0.6× 75 0.4× 56 1.3k

Countries citing papers authored by David McInerney

Since Specialization
Citations

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

Fields of papers citing papers by David McInerney

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David McInerney

This figure shows the co-authorship network connecting the top 25 collaborators of David McInerney. A scholar is included among the top collaborators of David McInerney 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 David McInerney. David McInerney 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.
McInerney, David, Mark Thyer, Dmitri Kavetski, et al.. (2024). Neglecting hydrological errors can severely impact predictions of water resource system performance. Journal of Hydrology. 634. 130853–130853. 6 indexed citations
2.
Thyer, Mark, Hoshin V. Gupta, Seth Westra, et al.. (2024). Virtual Hydrological Laboratories: Developing the Next Generation of Conceptual Models to Support Decision Making Under Change. Water Resources Research. 60(4). 8 indexed citations
3.
Thyer, Mark, et al.. (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. 1 indexed citations
4.
Renard, Benjamin, David McInerney, Seth Westra, et al.. (2023). Floods and Heavy Precipitation at the Global Scale: 100‐Year Analysis and 180‐Year Reconstruction. Journal of Geophysical Research Atmospheres. 128(9).
5.
McInerney, David, Seth Westra, Michael Leonard, et al.. (2023). A climate stress testing method for changes in spatially variable rainfall. Journal of Hydrology. 625. 129876–129876. 6 indexed citations
6.
McInerney, David, Mark Thyer, Dmitri Kavetski, et al.. (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. 7 indexed citations
7.
8.
Partington, Daniel, Mark Thyer, Margaret Shanafield, et al.. (2022). Predicting wildfire induced changes to runoff: A review and synthesis of modeling approaches. Wiley Interdisciplinary Reviews Water. 9(5). 27 indexed citations
9.
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
10.
Renard, Benjamin, Mark Thyer, David McInerney, et al.. (2021). A Hidden Climate Indices Modeling Framework for Multivariable Space‐Time Data. Water Resources Research. 58(1). 4 indexed citations
11.
McInerney, David, et al.. (2020). Multi‐temporal Hydrological Residual Error Modeling for Seamless Subseasonal Streamflow Forecasting. Water Resources Research. 56(11). 33 indexed citations
12.
Lerat, Julien, Mark Thyer, David McInerney, et al.. (2020). A robust approach for calibrating a daily rainfall-runoff model to monthly streamflow data. Journal of Hydrology. 591. 125129–125129. 20 indexed citations
13.
McInerney, David, Dmitri Kavetski, Mark Thyer, Julien Lerat, & George Kuczera. (2019). Benefits of Explicit Treatment of Zero Flows in Probabilistic Hydrological Modeling of Ephemeral Catchments. Water Resources Research. 55(12). 11035–11060. 20 indexed citations
14.
Woldemeskel, Fitsum, David McInerney, Julien Lerat, et al.. (2018). Evaluating residual error approaches for post-processing monthly and seasonal streamflow forecasts. Biogeosciences (European Geosciences Union). 8 indexed citations
15.
Gibbs, Matthew S., David McInerney, Greer B. Humphrey, et al.. (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. 34 indexed citations
16.
McInerney, David, Mark Thyer, Dmitri Kavetski, et al.. (2018). The Importance of Spatiotemporal Variability in Irrigation Inputs for Hydrological Modeling of Irrigated Catchments. Water Resources Research. 54(9). 6792–6821. 28 indexed citations
17.
McInerney, David, Mark Thyer, Dmitri Kavetski, et al.. (2018). A simplified approach to produce probabilistic hydrological model predictions. Environmental Modelling & Software. 109. 306–314. 27 indexed citations
18.
Woldemeskel, Fitsum, David McInerney, Julien Lerat, et al.. (2018). Evaluating post-processing approaches for monthly and seasonal streamflow forecasts. Hydrology and earth system sciences. 22(12). 6257–6278. 39 indexed citations
19.
McInerney, David, Mark Thyer, Dmitri Kavetski, Julien Lerat, & George Kuczera. (2017). Improving probabilistic prediction of daily streamflow by identifying Pareto optimal approaches for modeling heteroscedastic residual errors. Water Resources Research. 53(3). 2199–2239. 112 indexed citations
20.
Gibbs, Matthew S., David McInerney, Greer B. Humphrey, et al.. (2017). State Updating and Calibration Period Selection to Improve Dynamic Monthly Streamflow Forecasts for a Wetland Management Application. 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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