Li‐Chiu Chang

5.8k total citations · 1 hit paper
90 papers, 4.6k citations indexed

About

Li‐Chiu Chang is a scholar working on Environmental Engineering, Global and Planetary Change and Water Science and Technology. According to data from OpenAlex, Li‐Chiu Chang has authored 90 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Environmental Engineering, 35 papers in Global and Planetary Change and 30 papers in Water Science and Technology. Recurrent topics in Li‐Chiu Chang's work include Hydrological Forecasting Using AI (41 papers), Flood Risk Assessment and Management (32 papers) and Hydrology and Watershed Management Studies (25 papers). Li‐Chiu Chang is often cited by papers focused on Hydrological Forecasting Using AI (41 papers), Flood Risk Assessment and Management (32 papers) and Hydrology and Watershed Management Studies (25 papers). Li‐Chiu Chang collaborates with scholars based in Taiwan, United States and China. Li‐Chiu Chang's co-authors include Fi‐John Chang, I-Feng Kao, Yanlai Zhou, Chi‐Chuan Yeh, Yen‐Ming Chiang, Li Chen, Pin-An Chen, Kuo‐Wei Wang, Edwin E. Herricks and Yong‐Huang Lin and has published in prestigious journals such as Nature Communications, Applied Physics Letters and Journal of Applied Physics.

In The Last Decade

Li‐Chiu Chang

89 papers receiving 4.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Exploring a Long Short-Term Memory based Encoder-Decoder framework for multi-step-ahead flood forecasting

2020 297 citations Yanlai Zhou, Li‐Chiu Chang et al. Journal of Hydrology profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Li‐Chiu Chang Taiwan	40	2.4k	1.9k	1.6k	997	680	90	4.6k
Ali Najah Ahmed Malaysia	51	4.6k 1.9×	3.2k 1.7×	2.3k 1.4×	830 0.8×	1.0k 1.5×	326	9.1k
Yanlai Zhou China	32	1.3k 0.5×	1.8k 0.9×	1.2k 0.8×	1.0k 1.0×	368 0.5×	102	3.4k
Dimitri Solomatine Netherlands	48	3.9k 1.6×	4.1k 2.2×	3.6k 2.2×	881 0.9×	1.1k 1.6×	199	8.3k
Mohammad Zounemat‐Kermani Iran	42	3.1k 1.3×	2.3k 1.2×	1.8k 1.1×	350 0.4×	716 1.1×	154	5.7k
Vladan Babovic Singapore	39	1.9k 0.8×	1.6k 0.9×	1.6k 1.0×	489 0.5×	383 0.6×	104	4.0k
Salim Heddam Algeria	39	2.5k 1.1×	2.1k 1.1×	1.1k 0.7×	284 0.3×	410 0.6×	175	4.4k
Barbara Minsker United States	33	1.5k 0.6×	917 0.5×	540 0.3×	1.6k 1.6×	1.0k 1.5×	142	3.7k
Vahid Nourani Iran	52	6.0k 2.5×	4.7k 2.5×	3.7k 2.3×	666 0.7×	979 1.4×	298	9.8k
K. P. Sudheer India	41	4.4k 1.9×	3.9k 2.1×	3.3k 2.0×	645 0.6×	726 1.1×	119	7.0k
Bryan A. Tolson Canada	29	1.5k 0.6×	2.2k 1.2×	1.5k 0.9×	950 1.0×	801 1.2×	94	4.0k

Countries citing papers authored by Li‐Chiu Chang

Since Specialization

Citations

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

Fields of papers citing papers by Li‐Chiu Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Li‐Chiu Chang. 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 Li‐Chiu Chang. The network helps show where Li‐Chiu Chang may publish in the future.

Co-authorship network of co-authors of Li‐Chiu Chang

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

All Works

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20 of 20 papers shown

Chang, Li‐Chiu, et al.. (2025). Flood resilience through hybrid deep learning: Advanced forecasting for Taipei's urban drainage system. Journal of Environmental Management. 379. 124835–124835. 7 indexed citations

Jang, Cheng‐Shin, Shih‐Kai Chen, & Li‐Chiu Chang. (2025). Evaluation of groundwater vulnerability to nitrate-nitrogen by using probability-based modssified DRASTIC models with source and attenuation factors. Journal of Hydrology. 655. 132951–132951. 2 indexed citations

Wang, Sheng‐Wei, et al.. (2025). A case study on the application of a data-driven (XGBoost) approach on the environmental and socio-economic perspectives of agricultural groundwater management. Agricultural Water Management. 318. 109729–109729. 2 indexed citations

Sun, Wei, et al.. (2025). Advanced groundwater level forecasting with hybrid deep learning model: Tackling water challenges in Taiwan’s largest alluvial fan. Journal of Hydrology. 655. 132887–132887. 5 indexed citations

Hsu, Chia-Yu, et al.. (2025). A CNN-transformer framework for air quality forecasting to support aeolian dust management in river basins. Advanced Engineering Informatics. 68. 103758–103758. 1 indexed citations

Zhou, Yanlai, et al.. (2024). Methane degassing in global river reservoirs and its impacts on carbon budgets and sustainable water management. The Science of The Total Environment. 957. 177623–177623. 1 indexed citations

Sun, Wei, Li‐Chiu Chang, & Fi‐John Chang. (2024). Deep dive into predictive excellence: Transformer's impact on groundwater level prediction. Journal of Hydrology. 636. 131250–131250. 21 indexed citations

Chang, Li‐Chiu, et al.. (2024). Advancing climate-resilient flood mitigation: Utilizing transformer-LSTM for water level forecasting at pumping stations. The Science of The Total Environment. 927. 172246–172246. 29 indexed citations

Chang, Li‐Chiu, et al.. (2023). A flood Impact-Based forecasting system by fuzzy inference techniques. Journal of Hydrology. 625. 130117–130117. 9 indexed citations

10.

Chang, Li‐Chiu, et al.. (2023). High-spatiotemporal-resolution PM2.5 forecasting by hybrid deep learning models with ensembled massive heterogeneous monitoring data. Journal of Cleaner Production. 433. 139825–139825. 9 indexed citations

11.

Sun, Wei, et al.. (2023). Watershed groundwater level multistep ahead forecasts by fusing convolutional-based autoencoder and LSTM models. Journal of Environmental Management. 351. 119789–119789. 13 indexed citations

12.

Chang, Li‐Chiu, et al.. (2020). Explore Regional PM2.5 Features and Compositions Causing Health Effects in Taiwan. Environmental Management. 67(1). 176–191. 53 indexed citations

13.

Chang, Li‐Chiu, et al.. (2020). Self-organizing maps of typhoon tracks allow for flood forecasts up to two days in advance. Nature Communications. 11(1). 1983–1983. 53 indexed citations

14.

Zhou, Yanlai, Li‐Chiu Chang, & Fi‐John Chang. (2019). Explore a Multivariate Bayesian Uncertainty Processor driven by artificial neural networks for probabilistic PM2.5 forecasting. The Science of The Total Environment. 711. 134792–134792. 28 indexed citations

15.

Chang, Fi‐John, et al.. (2017). Conservation of groundwater from over-exploitation—Scientific analyses for groundwater resources management. The Science of The Total Environment. 598. 828–838. 49 indexed citations

16.

Chang, Fi‐John, Pin-An Chen, Li‐Chiu Chang, & Yu-Hsuan Tsai. (2016). Estimating spatio-temporal dynamics of stream total phosphate concentration by soft computing techniques. The Science of The Total Environment. 562. 228–236. 25 indexed citations

17.

Chang, Li‐Chiu, et al.. (2013). Online multistep-ahead inundation depth forecasts by recurrent NARX networks. Hydrology and earth system sciences. 17(3). 935–945. 56 indexed citations

18.

Chiang, Yi‐Ming, et al.. (2011). Auto-control of pumping operations in sewerage systems by rule-based fuzzy neural networks. Hydrology and earth system sciences. 15(1). 185–196. 38 indexed citations

19.

Chang, Li‐Chiu, et al.. (2009). Forecasting of ozone episode days by cost-sensitive neural network methods. The Science of The Total Environment. 407(6). 2124–2135. 48 indexed citations

20.

Chang, Li‐Chiu, et al.. (1999). COMPARISON OF INTEGRATED ARTIFICIAL NEURAL NETWORK WITH TIME SERIES MODELING FOR FLOOD FORECAST. 17(2). 37–50. 7 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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