Ha-Sun Hwang

610 total citations
9 papers, 517 citations indexed

About

Ha-Sun Hwang is a scholar working on Water Science and Technology, Environmental Chemistry and Environmental Engineering. According to data from OpenAlex, Ha-Sun Hwang has authored 9 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Water Science and Technology, 3 papers in Environmental Chemistry and 2 papers in Environmental Engineering. Recurrent topics in Ha-Sun Hwang's work include Hydrology and Watershed Management Studies (5 papers), Water Quality and Pollution Assessment (3 papers) and Soil and Water Nutrient Dynamics (3 papers). Ha-Sun Hwang is often cited by papers focused on Hydrology and Watershed Management Studies (5 papers), Water Quality and Pollution Assessment (3 papers) and Soil and Water Nutrient Dynamics (3 papers). Ha-Sun Hwang collaborates with scholars based in South Korea, United Kingdom and United States. Ha-Sun Hwang's co-authors include Sang‐Woo Lee, Hyun-Chan Sung, Soon‐Jin Hwang, Bernie Engel, Jane Frankenberger, Ji‐Hong Jeon, Sungjun Lee, Yongseok Kim, Kwang‐Sik Yoon and Kyoung Jae Lim and has published in prestigious journals such as Landscape and Urban Planning, Water and Paddy and Water Environment.

In The Last Decade

Ha-Sun Hwang

9 papers receiving 491 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ha-Sun Hwang South Korea	4	397	192	164	146	70	9	517
Jiao Ding China	5	405 1.0×	183 1.0×	119 0.7×	125 0.9×	147 2.1×	5	582
Guoce Xu China	9	520 1.3×	213 1.1×	156 1.0×	183 1.3×	141 2.0×	18	733
Qiuzhi Peng China	8	408 1.0×	186 1.0×	136 0.8×	156 1.1×	164 2.3×	21	656
Tammy Newcomer-Johnson United States	11	277 0.7×	205 1.1×	229 1.4×	141 1.0×	211 3.0×	20	641
Lan Fu China	6	438 1.1×	209 1.1×	124 0.8×	133 0.9×	178 2.5×	9	656
Leora Nanus United States	15	225 0.6×	184 1.0×	156 1.0×	178 1.2×	80 1.1×	24	625
Kristen L. Underwood United States	14	248 0.6×	217 1.1×	102 0.6×	86 0.6×	138 2.0×	38	508
Elliott Kellner United States	15	279 0.7×	109 0.6×	159 1.0×	111 0.8×	134 1.9×	28	422
Renhua Yan China	13	307 0.8×	166 0.9×	71 0.4×	163 1.1×	41 0.6×	27	451
David Brito Portugal	15	259 0.7×	172 0.9×	98 0.6×	105 0.7×	104 1.5×	30	493

Countries citing papers authored by Ha-Sun Hwang

Since Specialization

Citations

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

Fields of papers citing papers by Ha-Sun Hwang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ha-Sun Hwang. 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 Ha-Sun Hwang. The network helps show where Ha-Sun Hwang may publish in the future.

Co-authorship network of co-authors of Ha-Sun Hwang

This figure shows the co-authorship network connecting the top 25 collaborators of Ha-Sun Hwang. A scholar is included among the top collaborators of Ha-Sun Hwang 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 Ha-Sun Hwang. Ha-Sun Hwang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Hwang, Ha-Sun, et al.. (2018). Analysis of the Difference of Flow Duration Curve according to the Cumulative Variation of the Daily Average Flow in Unit Watershed for TPLCs. Journal of The Korean Society of Agricultural Engineers. 60(6). 97–109. 1 indexed citations

2.

Hwang, Ha-Sun, et al.. (2016). Development of Desktop-Based LDC Evaluation System for Effectiveness TMDLs. Journal of The Korean Society of Agricultural Engineers. 58(4). 67–74. 2 indexed citations

3.

Engel, Bernie, et al.. (2015). A Web-Based Tool to Estimate Pollutant Loading Using LOADEST. Water. 7(9). 4858–4868. 29 indexed citations

4.

Hwang, Ha-Sun, et al.. (2015). Study on Estimation and Application of Discharge Coefficient about Nonpoint Source Pollutants using Watershed Model. Journal of Korean Neuropsychiatric Association. 31(6). 653–664. 3 indexed citations

5.

Park, Youn Shik, et al.. (2015). Evaluation of Regression Models in LOADEST to Estimate Suspended Solid Load in Hangang Waterbody. Journal of The Korean Society of Agricultural Engineers. 57(2). 37–45. 2 indexed citations

6.

Hwang, Ha-Sun, et al.. (2014). Evaluation and Application of CLUE-S Model for Spatio-Temporal Analysis of Future Land use Change in Total Water Pollution Load Management System. Journal of Korean Neuropsychiatric Association. 30(4). 418–428. 4 indexed citations

7.

Lee, Sang‐Woo, et al.. (2009). Landscape ecological approach to the relationships of land use patterns in watersheds to water quality characteristics. Landscape and Urban Planning. 92(2). 80–89. 453 indexed citations

8.

Lee, Sang‐Woo, et al.. (2008). The effects of spatial variability of land use on stream water quality in a costal watershed. Paddy and Water Environment. 6(3). 275–284. 21 indexed citations

9.

Jeon, Ji‐Hong, et al.. (2003). Water Quality Model Development for Loading Estimates from Paddy Field. Journal of Ecology and Environment. 36(3). 344–355. 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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