Won‐Ho Nam

1.7k total citations
108 papers, 1.3k citations indexed

About

Won‐Ho Nam is a scholar working on Water Science and Technology, Global and Planetary Change and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Won‐Ho Nam has authored 108 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Water Science and Technology, 48 papers in Global and Planetary Change and 28 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Won‐Ho Nam's work include Hydrology and Watershed Management Studies (40 papers), Hydrology and Drought Analysis (28 papers) and Climate variability and models (19 papers). Won‐Ho Nam is often cited by papers focused on Hydrology and Watershed Management Studies (40 papers), Hydrology and Drought Analysis (28 papers) and Climate variability and models (19 papers). Won‐Ho Nam collaborates with scholars based in South Korea, United States and China. Won‐Ho Nam's co-authors include Jin‐Yong Choi, Eunmi Hong, Mark Svoboda, Tsegaye Tadesse, Michael J. Hayes, Donald A. Wilhite, Tae‐Gon Kim, Seung‐Hwan Yoo, Min-Won Jang and Nengcheng Chen and has published in prestigious journals such as The Science of The Total Environment, Remote Sensing of Environment and Water Resources Research.

In The Last Decade

Won‐Ho Nam

90 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Won‐Ho Nam South Korea 20 704 504 245 225 182 108 1.3k
Inmaculada Pulido‐Calvo Spain 18 670 1.0× 387 0.8× 132 0.5× 195 0.9× 151 0.8× 49 1.3k
Yufeng Luo China 16 824 1.2× 695 1.4× 103 0.4× 137 0.6× 224 1.2× 45 1.2k
Proloy Deb India 20 536 0.8× 454 0.9× 228 0.9× 73 0.3× 200 1.1× 33 1.1k
Brian Joyce United States 17 397 0.6× 663 1.3× 98 0.4× 399 1.8× 143 0.8× 28 1.1k
Mohsin Hafeez Australia 18 514 0.7× 522 1.0× 63 0.3× 236 1.0× 211 1.2× 48 1.1k
Daniela Anghileri United Kingdom 17 506 0.7× 519 1.0× 89 0.4× 318 1.4× 84 0.5× 30 921
Alireza Gohari Iran 14 418 0.6× 606 1.2× 119 0.5× 391 1.7× 80 0.4× 46 1.1k
Gholamreza Naser Canada 13 944 1.3× 366 0.7× 214 0.9× 127 0.6× 111 0.6× 40 1.4k
Jong Ahn Chun South Korea 21 565 0.8× 589 1.2× 125 0.5× 75 0.3× 116 0.6× 64 1.4k
Gary W. Marek United States 22 821 1.2× 546 1.1× 256 1.0× 134 0.6× 592 3.3× 101 1.4k

Countries citing papers authored by Won‐Ho Nam

Since Specialization
Citations

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

Fields of papers citing papers by Won‐Ho Nam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Won‐Ho Nam. 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 Won‐Ho Nam. The network helps show where Won‐Ho Nam may publish in the future.

Co-authorship network of co-authors of Won‐Ho Nam

This figure shows the co-authorship network connecting the top 25 collaborators of Won‐Ho Nam. A scholar is included among the top collaborators of Won‐Ho Nam 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 Won‐Ho Nam. Won‐Ho Nam 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.
Shen, Yonglin, et al.. (2025). Low-cost video-based air quality estimation system using structured deep learning with selective state space modeling. Environment International. 199. 109496–109496. 4 indexed citations
2.
Zhang, Xiang, Chao Yang, Xihui Gu, et al.. (2025). Disentangling vegetation physiological responses under extreme drought in the Amazon Rainforest: A multispectral remote sensing approach with insights from ET, SIF, and VOD. ISPRS Journal of Photogrammetry and Remote Sensing. 230. 599–615.
3.
Zhang, Xu, Xin Liu, Xiang Zhang, et al.. (2025). A Fusion Strategy for High-Accuracy Multilayer Soil Moisture Downscaling and Mapping. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 17405–17421.
4.
Nam, Won‐Ho, et al.. (2024). A survey on the application of ICTs in automated water level gauges for agricultural reservoirs. Korean Journal of Agricultural Science. 51(2). 217–225.
5.
Zhang, Xiang, Yu Song, Won‐Ho Nam, et al.. (2024). Data fusion of satellite imagery and downscaling for generating highly fine-scale precipitation. Journal of Hydrology. 631. 130665–130665. 19 indexed citations
6.
Zhang, Xiang, Jiangyuan Zeng, Jiabo Yin, et al.. (2024). Impact of drought-induced forest mortality on terrestrial carbon cycle from remote sensing perspective. 2(1). 100057–100057. 6 indexed citations
7.
Nam, Won‐Ho, et al.. (2024). Assessment of agricultural drought status using visible infrared imaging radiometer suite land products. Theoretical and Applied Climatology. 155(7). 6887–6897.
8.
Zhang, Xiang, Won‐Ho Nam, Guoyong Leng, et al.. (2023). Multiple Markov Chains for Categorial Drought Prediction on the U.S. Drought Monitor at Weekly Scale. Journal of Applied Meteorology and Climatology. 62(10). 1415–1435. 1 indexed citations
10.
Zhang, Xiang, Aminjon Gulakhmadov, Yu Song, et al.. (2022). Deep Learning-Based 500 m Spatio-Temporally Continuous Air Temperature Generation by Fusing Multi-Source Data. Remote Sensing. 14(15). 3536–3536. 15 indexed citations
11.
Wang, Siqi, Xiang Zhang, Nengcheng Chen, et al.. (2022). A systematic review and quantitative meta-analysis of the relationships between driving forces and cyanobacterial blooms at global scale. Environmental Research. 216(Pt 3). 114670–114670. 8 indexed citations
12.
Huang, Shuzhe, Xiang Zhang, Nengcheng Chen, et al.. (2022). A Novel Fusion Method for Generating Surface Soil Moisture Data With High Accuracy, High Spatial Resolution, and High Spatio‐Temporal Continuity. Water Resources Research. 58(5). 27 indexed citations
13.
Kim, Ha-Young, et al.. (2021). Estimation of Irrigation Return Flow on Agricultural Watershed in Madun Reservoir. Journal of The Korean Society of Agricultural Engineers. 63(2). 85–96. 4 indexed citations
14.
Lee, Heejin, et al.. (2021). Detection of flash drought using evaporative stress index in South Korea. Journal of Korea Water Resources Association. 54(8). 577–587. 1 indexed citations
15.
Nam, Won‐Ho, et al.. (2020). Impact of climate change on reference evapotranspiration in Egypt. CATENA. 194. 104711–104711. 54 indexed citations
16.
Nam, Won‐Ho, Song Feng, Brian Wardlow, et al.. (2020). Agricultural Drought Assessment in East Asia Using Satellite-Based Indices. Remote Sensing. 12(3). 444–444. 38 indexed citations
17.
Nam, Won‐Ho, et al.. (2020). Spatiotemporal Agricultural Drought Damage and Its Relationship with Hydrometeorological Characteristics of Historical Drought Events for Recent 40 Years. 392–392. 1 indexed citations
18.
Nam, Won‐Ho, et al.. (2019). Satellite-based Evaporative Stress Index (ESI) as an Indicator of Agricultural Drought in North Korea. Journal of The Korean Society of Agricultural Engineers. 61(3). 1–14. 4 indexed citations
19.
Nam, Won‐Ho, et al.. (2018). Flash drought risk assessment over China and Korea using Evaporative Demand Drought Index (EDDI). AGUFM. 2018. 1 indexed citations
20.
Bang, N. D., et al.. (2018). Assessment of the Meteorological Characteristics and Statistical Drought Frequency for the Extreme 2017 Spring Drought Event Across South Korea. Journal of The Korean Society of Agricultural Engineers. 60(4). 37–48. 4 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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