Heechan Han

916 total citations
36 papers, 641 citations indexed

About

Heechan Han is a scholar working on Global and Planetary Change, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, Heechan Han has authored 36 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Global and Planetary Change, 19 papers in Water Science and Technology and 18 papers in Environmental Engineering. Recurrent topics in Heechan Han's work include Flood Risk Assessment and Management (20 papers), Hydrology and Watershed Management Studies (18 papers) and Hydrological Forecasting Using AI (16 papers). Heechan Han is often cited by papers focused on Flood Risk Assessment and Management (20 papers), Hydrology and Watershed Management Studies (18 papers) and Hydrological Forecasting Using AI (16 papers). Heechan Han collaborates with scholars based in South Korea, United States and Brazil. Heechan Han's co-authors include Hung Soo Kim, Ryan R. Morrison, Jungho Kim, Changhyun Choi, Jaewon Jung, Jungwook Kim, Sanghun Lim, Lynn E. Johnson, Rob Cifelli and Haonan Chen and has published in prestigious journals such as The Science of The Total Environment, Journal of Hydrology and Sustainability.

In The Last Decade

Heechan Han

31 papers receiving 623 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Heechan Han South Korea 16 400 371 350 119 56 36 641
N. Sajikumar India 9 359 0.9× 449 1.2× 345 1.0× 59 0.5× 44 0.8× 29 650
Mustafa Al-Mukhtar Iraq 13 264 0.7× 307 0.8× 228 0.7× 75 0.6× 39 0.7× 30 559
Okan Mert Katipoğlu Türkiye 16 379 0.9× 324 0.9× 526 1.5× 96 0.8× 105 1.9× 101 830
Wan Zurina Wan Jaafar Malaysia 16 215 0.5× 233 0.6× 258 0.7× 129 1.1× 43 0.8× 39 552
Hirad Abghari Iran 12 291 0.7× 307 0.8× 460 1.3× 99 0.8× 67 1.2× 23 689
Yutong Chen China 12 281 0.7× 459 1.2× 441 1.3× 65 0.5× 90 1.6× 21 714
Meral Büyükyıldız Türkiye 10 283 0.7× 240 0.6× 230 0.7× 72 0.6× 55 1.0× 31 480
Mehdi Rezaeianzadeh United States 11 334 0.8× 274 0.7× 350 1.0× 52 0.4× 90 1.6× 16 573
Ngoc Duong Vo Vietnam 10 202 0.5× 256 0.7× 291 0.8× 62 0.5× 51 0.9× 24 503
Cheng Yao China 17 339 0.8× 645 1.7× 587 1.7× 195 1.6× 27 0.5× 47 846

Countries citing papers authored by Heechan Han

Since Specialization
Citations

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

Fields of papers citing papers by Heechan Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Heechan Han

This figure shows the co-authorship network connecting the top 25 collaborators of Heechan Han. A scholar is included among the top collaborators of Heechan Han 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 Heechan Han. Heechan Han 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.
2.
Kim, Changju, et al.. (2025). Multi-Hazard Susceptibility Mapping Using Machine Learning Approaches: A Case Study of South Korea. Remote Sensing. 17(10). 1660–1660. 2 indexed citations
3.
Han, Heechan, et al.. (2024). Integrating machine learning for enhanced wildfire severity prediction: A study in the Upper Colorado River basin. The Science of The Total Environment. 952. 175914–175914. 8 indexed citations
4.
Kim, Changju & Heechan Han. (2024). Long-term effects of wildfires on river water quality: a comprehensive review of the variability of water quality in South Korea. Journal of Water and Health. 22(11). 2146–2159.
5.
Han, Heechan, et al.. (2023). Predicting Flood Water Level Using Combined Hybrid Model of Rainfall-Runoff and AI-Based Models. KSCE Journal of Civil Engineering. 28(4). 1580–1593. 4 indexed citations
6.
Han, Heechan, et al.. (2023). Flood risk assessment using an indicator based approach combined with flood risk maps and grid data. Journal of Hydrology. 627. 130396–130396. 15 indexed citations
7.
Han, Heechan, et al.. (2023). Spatiotemporal Evaluation of Satellite-Based Precipitation Products in the Colorado River Basin. Journal of Hydrometeorology. 24(10). 1739–1754. 4 indexed citations
8.
Han, Heechan, et al.. (2023). Development of Heavy Rain Damage Prediction Technique Based on Optimization and Ensemble Method. KSCE Journal of Civil Engineering. 27(5). 2313–2326.
9.
Han, Heechan, et al.. (2023). Application of AI-Based Models for Flood Water Level Forecasting and Flood Risk Classification. KSCE Journal of Civil Engineering. 27(7). 3163–3174. 15 indexed citations
10.
Han, Heechan, et al.. (2023). Machine learning approach for the estimation of missing precipitation data: a case study of South Korea. Water Science & Technology. 88(3). 556–571. 3 indexed citations
11.
Han, Heechan, et al.. (2022). Development of Simple Method for Flood Control Capacity Estimation of Dam in South Korea. Water. 14(9). 1366–1366.
12.
Kim, Jongsung, et al.. (2022). Determining the Risk Level of Heavy Rain Damage by Region in South Korea. Water. 14(2). 219–219. 7 indexed citations
13.
Han, Heechan, et al.. (2022). Improvement of Deep Learning Models for River Water Level Prediction Using Complex Network Method. Water. 14(3). 466–466. 12 indexed citations
14.
Han, Heechan. (2021). Application of sequence to sequence learning based LSTM model (LSTM-s2s) for forecasting dam inflow. Journal of Korea Water Resources Association. 54(3). 157–166. 7 indexed citations
15.
Han, Heechan, Changhyun Choi, Jaewon Jung, & Hung Soo Kim. (2021). Deep Learning with Long Short Term Memory Based Sequence-to-Sequence Model for Rainfall-Runoff Simulation. Water. 13(4). 437–437. 48 indexed citations
16.
Han, Heechan, et al.. (2020). Hydrological impact of Atmospheric River landfall on the Korean Peninsula. Journal of Korea Water Resources Association. 53(11). 1039–1047. 1 indexed citations
17.
18.
19.
Kim, Jungho, et al.. (2018). Modeling the Runoff Reduction Effect of Low Impact Development Installations in an Industrial Area, South Korea. Water. 10(8). 967–967. 18 indexed citations
20.
Han, Heechan, et al.. (2015). Annual Precipitation Reconstruction Based on Tree-ring Data at Seorak. Journal of Korean Neuropsychiatric Association. 31(1). 19–28. 1 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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