Daniel J. Goode

37 papers receiving 738 citations

Peers

Daniel J. Goode
Comparison fields: 5 of 61
  • Geochemistry and Petrology 382
  • Environmental Engineering 616
  • Water Science and Technology 204
  • Environmental Chemistry 120
  • Ocean Engineering 117
Replace A.T. Williams with:
A.T. Williams United Kingdom
Thierry Labasque France
Clément Roques Switzerland
Howard W. Reeves United States
Nicholas B. Engdahl United States
M. Bayer-Raich Germany
Jun Kong China
Steven P. Phillips United States
Jingli Shao China
Daniele Pedretti Italy
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Citations per field
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A.T. Williams · 1×
Citations per year

Countries citing papers authored by Daniel J. Goode

Since Specialization
Citations

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

Fields of papers citing papers by Daniel J. Goode

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel J. Goode. 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 Daniel J. Goode. The network helps show where Daniel J. Goode may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel J. Goode, 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 Daniel J. Goode Line = papers co-authored together Daniel J. Goode links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996286
2 199094
3 199854
4 199052
5 201336
6 200835
7 200728
8 201328
9 200926
10 201421
11 201715
12 200915
13 201715
14 199711
15
GROUND-WATER AGE AND ATMOSPHERIC TRACERS: SIMULATION STUDIES AND ANALYSIS OF FIELD DATA FROM THE MIRROR LAKE SITE, NEW HAMPSHIRE
199810
16 201010
17 202010
18 19879
19 20009
20 20239

About Daniel J. Goode

Daniel J. Goode is a scholar working on Environmental Engineering, Geochemistry and Petrology, Water Science and Technology, Mechanical Engineering and Civil and Structural Engineering, having authored 43 papers that have together received 844 indexed citations. Recurring topics across this work include Groundwater flow and contamination studies (37 papers), Groundwater and Isotope Geochemistry (20 papers), Hydraulic Fracturing and Reservoir Analysis (8 papers), Hydrology and Watershed Management Studies (7 papers), Soil and Unsaturated Flow (5 papers), Water Quality and Resources Studies (5 papers), Microbial bioremediation and biosurfactants (4 papers) and Atmospheric and Environmental Gas Dynamics (4 papers). The work is most often cited by research in Geochemistry and Petrology (382 citations), Environmental Engineering (616 citations), Water Science and Technology (204 citations), Environmental Chemistry (120 citations) and Ocean Engineering (117 citations). Daniel J. Goode has collaborated with scholars based in United States, Canada and Jordan. Frequent co-authors include Leonard F. Konikow, Claire R. Tiedeman, Pierre J. Lacombe, Paul A. Hsieh, Thomas E. Imbrigiotta, Allen M. Shapiro, Francis H. Chapelle, Paul M. Bradley, Dennis W. Risser and Charles A. Cravotta. Their work appears in journals such as Ground Water, Water Resources Research, Journal of Contaminant Hydrology, Groundwater Monitoring & Remediation and Hydrological Processes.

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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