12 citations as recorded by crossref.

1. Projected river water temperatures in Poland under climate change scenarios W. Dong et al. 10.1016/j.ejrh.2025.102368
2. Modeling and mapping sea surface gage height using satellite remote sensing data N. Suwal & Z. Deng 10.1007/s12145-024-01350-2
3. Development of machine learning models for estimation of daily evaporation and mean temperature: a case study in New Delhi, India J. Rajput et al. 10.2166/wpt.2024.144
4. Methods for predicting water temperature in data-scarce areas under different climate regions of China J. Zhang et al. 10.1016/j.watcyc.2025.03.001
5. Enhancing Alaskan wildfire prediction and carbon flux estimation: a two-stage deep learning approach within a process-based model H. Seo & Y. Kim 10.1088/1748-9326/ad8bdc
6. Rising summer river water temperature across Canada: spatial patterns and hydroclimatic controls R. Shrestha et al. 10.1088/1748-9326/ad365f
7. Prediction of daily river water temperatures using an optimized model based on NARX networks J. Sun et al. 10.1016/j.ecolind.2024.111978
8. Long-term daily water temperatures unveil escalating water warming and intensifying heatwaves in the Odra river Basin, Central Europe J. Sun et al. 10.1016/j.gsf.2024.101916
9. A novel method for frequency analysis of high water temperatures using temperature duration curves in a partially regulated watershed M. Khorsandi & S. Déry 10.1016/j.scitotenv.2025.178863
10. An optimized NARX-based model for predicting thermal dynamics and heatwaves in rivers S. Zhu et al. 10.1016/j.scitotenv.2024.171954
11. HydroEcoLSTM: A Python package with graphical user interface for hydro-ecological modeling with long short-term memory neural network T. Nguyen et al. 10.1016/j.ecoinf.2025.102994
12. River water temperature prediction using hybrid machine learning coupled signal decomposition: EWT versus MODWT S. Heddam et al. 10.1016/j.ecoinf.2023.102376