Articles | Volume 29, issue 12
https://doi.org/10.5194/hess-29-2633-2025
https://doi.org/10.5194/hess-29-2633-2025
Research article
 | 
26 Jun 2025
Research article |  | 26 Jun 2025

Assessing the value of high-resolution data and parameter transferability across temporal scales in hydrological modeling: a case study in northern China

Mahmut Tudaji, Yi Nan, and Fuqiang Tian

Related authors

Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025,https://doi.org/10.5194/hess-29-1919-2025, 2025
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Assessing the adequacy of traditional hydrological models for climate change impact studies: a case for long short-term memory (LSTM) neural networks
Jean-Luc Martel, François Brissette, Richard Arsenault, Richard Turcotte, Mariana Castañeda-Gonzalez, William Armstrong, Edouard Mailhot, Jasmine Pelletier-Dumont, Gabriel Rondeau-Genesse, and Louis-Philippe Caron
Hydrol. Earth Syst. Sci., 29, 2811–2836, https://doi.org/10.5194/hess-29-2811-2025,https://doi.org/10.5194/hess-29-2811-2025, 2025
Short summary
Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?
Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 29, 2361–2375, https://doi.org/10.5194/hess-29-2361-2025,https://doi.org/10.5194/hess-29-2361-2025, 2025
Short summary
CONCN: a high-resolution, integrated surface water–groundwater ParFlow modeling platform of continental China
Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci., 29, 2201–2218, https://doi.org/10.5194/hess-29-2201-2025,https://doi.org/10.5194/hess-29-2201-2025, 2025
Short summary
Evaluating the effects of topography and land use change on hydrological signatures: a comparative study of two adjacent watersheds
Haifan Liu, Haochen Yan, and Mingfu Guan
Hydrol. Earth Syst. Sci., 29, 2109–2132, https://doi.org/10.5194/hess-29-2109-2025,https://doi.org/10.5194/hess-29-2109-2025, 2025
Short summary
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci., 29, 1981–2002, https://doi.org/10.5194/hess-29-1981-2025,https://doi.org/10.5194/hess-29-1981-2025, 2025
Short summary

Cited articles

Addisie, M. B., Ayele, G. K., Hailu, N., Langendoen, E. J., Tilahun, S. A., Schmitter, P., Parlange, J. Y., and Steenhuis, T. S.: Connecting hillslope and runoff generation processes in the Ethiopian Highlands: The Ene-Chilala watershed, J. Hydrol. Hydromech., 68, 313–327, https://doi.org/10.2478/johh-2020-0015, 2020. 
Cunge, J. A.: On The Subject Of A Flood Propagation Computation Method (Musklngum Method), J. Hydraul. Res., 7, 205–230, https://doi.org/10.1080/00221686909500264, 1969. 
Domrös, M. and Peng, G.: The climate of China, Springer Berlin, Heidelberg, VIII, 361 pp., https://doi.org/10.1007/978-3-642-73333-8, 2012. 
Dunne, T., Moore, T., and Taylor, C.: Recognition and prediction of runoff-producing zones in humid regions, Hydrol. Sci. Bull, 20, 305–327, 1975. 
Eriksson, D., Bindel, D., and Shoemaker, C. A: pySOT and POAP: An event-driven asynchronous framework for surrogate optimization, arXiv [preprint], https://doi.org/10.48550/arXiv.1908.00420, 2019. 
Short summary
We assessed the value of high-resolution data and parameter transferability across temporal scales based on seven catchments in northern China. We found that higher-resolution data do not always improve model performance, questioning the need for such data. Model parameters are transferable across different data resolutions but not across computational time steps. It is recommended to utilize a smaller computational time step when building hydrological models even without high-resolution data.
Share