Daniel J. Goode

1.4k total citations
51 papers, 887 citations indexed

About

Daniel J. Goode is a scholar working on Environmental Engineering, Geochemistry and Petrology and Water Science and Technology. According to data from OpenAlex, Daniel J. Goode has authored 51 papers receiving a total of 887 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Environmental Engineering, 28 papers in Geochemistry and Petrology and 18 papers in Water Science and Technology. Recurrent topics in Daniel J. Goode's work include Groundwater flow and contamination studies (43 papers), Groundwater and Isotope Geochemistry (26 papers) and Hydrology and Watershed Management Studies (9 papers). Daniel J. Goode is often cited by papers focused on Groundwater flow and contamination studies (43 papers), Groundwater and Isotope Geochemistry (26 papers) and Hydrology and Watershed Management Studies (9 papers). Daniel J. Goode collaborates with scholars based in United States, Canada and Jordan. Daniel J. Goode's co-authors include Leonard F. Konikow, Claire R. Tiedeman, Paul A. Hsieh, Pierre J. Lacombe, Thomas E. Imbrigiotta, Allen M. Shapiro, Francis H. Chapelle, Paul M. Bradley, Charles A. Cravotta and Dennis W. Risser and has published in prestigious journals such as Water Resources Research, Hydrological Processes and Journal of Arid Environments.

In The Last Decade

Daniel J. Goode

44 papers receiving 773 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel J. Goode United States 15 638 392 237 141 133 51 887
Malcolm S. Field United States 17 805 1.3× 509 1.3× 305 1.3× 81 0.6× 106 0.8× 41 1.3k
Ronit Nativ Israel 24 908 1.4× 493 1.3× 215 0.9× 207 1.5× 134 1.0× 52 1.4k
A.T. Williams United Kingdom 17 380 0.6× 291 0.7× 228 1.0× 89 0.6× 79 0.6× 23 701
John Heathcote United Kingdom 14 556 0.9× 613 1.6× 295 1.2× 124 0.9× 62 0.5× 34 1.1k
Bertel Nilsson Denmark 23 723 1.1× 444 1.1× 475 2.0× 113 0.8× 144 1.1× 57 1.4k
Douglas S. Cherkauer United States 15 674 1.1× 306 0.8× 268 1.1× 209 1.5× 131 1.0× 34 931
Clément Roques Switzerland 17 418 0.7× 221 0.6× 220 0.9× 147 1.0× 90 0.7× 50 817
Howard W. Reeves United States 17 519 0.8× 228 0.6× 373 1.6× 57 0.4× 170 1.3× 55 900
E. Scott Bair United States 13 540 0.8× 228 0.6× 210 0.9× 164 1.2× 185 1.4× 38 726
Kathryn M. Hess United States 9 907 1.4× 316 0.8× 133 0.6× 217 1.5× 192 1.4× 12 1.1k

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-authorship network of co-authors of Daniel J. Goode

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel J. Goode. A scholar is included among the top collaborators of Daniel J. Goode 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 Daniel J. Goode. Daniel J. Goode 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
2.
Shapiro, Allen M., Daniel J. Goode, Thomas E. Imbrigiotta, Michelle M. Lorah, & Claire R. Tiedeman. (2019). The complex spatial distribution of trichloroethene and the probability of NAPL occurrence in the rock matrix of a mudstone aquifer. Journal of Contaminant Hydrology. 223. 103478–103478. 3 indexed citations
3.
Velpuri, Naga Manohar, et al.. (2018). Validation of seven gridded rainfall products for the Jordan, Palestine, and Lebanon region using in situ observations. 2018.
4.
Tiedeman, Claire R., Allen M. Shapiro, Paul A. Hsieh, et al.. (2017). Bioremediation in Fractured Rock: 1. Modeling to Inform Design, Monitoring, and Expectations. Ground Water. 56(2). 300–316. 15 indexed citations
6.
Shapiro, Allen M., Claire R. Tiedeman, Thomas E. Imbrigiotta, et al.. (2017). Bioremediation in Fractured Rock: 2. Mobilization of Chloroethene Compounds from the Rock Matrix. Ground Water. 56(2). 317–336. 14 indexed citations
7.
Goode, Daniel J.. (2016). Map visualization of groundwater withdrawals at the sub-basin scale. Hydrogeology Journal. 24(4). 1057–1065. 4 indexed citations
8.
Goode, Daniel J., Thomas E. Imbrigiotta, & Pierre J. Lacombe. (2014). High-resolution delineation of chlorinated volatile organic compounds in a dipping, fractured mudstone: Depth- and strata-dependent spatial variability from rock-core sampling. Journal of Contaminant Hydrology. 171. 1–11. 21 indexed citations
9.
Révész, Kinga, Barbara Sherwood Lollar, Julie D. Kirshtein, et al.. (2013). Integration of stable carbon isotope, microbial community, dissolved hydrogen gas, and 2HH2O tracer data to assess bioaugmentation for chlorinated ethene degradation in fractured rocks. Journal of Contaminant Hydrology. 156. 62–77. 25 indexed citations
11.
12.
Tiedeman, Claire R., Pierre J. Lacombe, & Daniel J. Goode. (2009). Multiple Well‐Shutdown Tests and Site‐Scale Flow Simulation in Fractured Rocks. Ground Water. 48(3). 401–415. 25 indexed citations
13.
Bradley, Paul M., Pierre J. Lacombe, Thomas E. Imbrigiotta, Francis H. Chapelle, & Daniel J. Goode. (2009). Flowpath Independent Monitoring of Reductive Dechlorination Potential in a Fractured Rock Aquifer. Groundwater Monitoring & Remediation. 29(4). 46–55. 15 indexed citations
14.
Tiedeman, Claire R., Daniel J. Goode, Allen M. Shapiro, et al.. (2008). Multidisciplinary investigation of the fate, transport, and remediation of chlorinated solvents in fractured rocks at the former Naval Air Warfare Center (NAWC): Scientific and management challenges, and strategies for a successful research program. AGUFM. 2008. 2 indexed citations
15.
Révész, Kinga, Allen M. Shapiro, Claire R. Tiedeman, et al.. (2008). Monitoring Natural Biodegradation of TCE in Fractured Sedimentary Rocks Using delta 13C of TCE and its Degradation Products: Estimating Isotopic Fractionation Factor under Field Conditions. AGUFM. 2008. 1 indexed citations
16.
Goode, Daniel J.. (1997). Composite Recovery Type Curves in Normalized Time from Theis’ Exact Solution. Ground Water. 35(4). 672–677. 11 indexed citations
17.
Goode, Daniel J., Paul A. Hsieh, Allen M. Shapiro, Warren W. Wood, & Thomas F. Kraemer. (1993). Concentration history during pumping from a leaky aquifer with stratified initial concentration. Hydraulic Engineering. 29–35. 3 indexed citations
18.
Goode, Daniel J.. (1992). Modeling Transport in Transient Ground‐Water Flow: An Unacknowledged Approximation. Ground Water. 30(2). 257–261. 8 indexed citations
19.
Goode, Daniel J. & Allen M. Shapiro. (1991). Comment on “Flow and tracer transport in a single fracture: A stochastic model and its relation to some field observations” by L. Moreno et al.. Water Resources Research. 27(1). 129–131. 6 indexed citations
20.
Goode, Daniel J. & Leonard F. Konikow. (1990). Apparent dispersion in transient groundwater flow. Water Resources Research. 26(10). 2339–2351. 91 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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