49 citations as recorded by crossref.

1. Comparison of three daily rainfall-runoff models with multiple regression analysis for catchment parameters in Biobío, Chile N. Flores et al. https://doi.org/10.1080/02626667.2025.2563596
2. SWAT-Based Streamflow Estimation and Its Responses to Climate Change in the Kadongjia River Watershed, Southern Tibet R. Sun et al. https://doi.org/10.1175/JHM-D-12-0159.1
3. Towards closure relations in the Representative Elementary Watershed (REW) framework containing observable parameters: Relations for Hortonian overland flow E. Vannametee et al. https://doi.org/10.1016/j.advwatres.2012.03.029
4. A review of regionalisation for continuous streamflow simulation Y. He et al. https://doi.org/10.5194/hess-15-3539-2011
5. Calibration of the semi-distributed PDM rainfall–runoff model in the Upper Lee catchment, UK I. Pechlivanidis et al. https://doi.org/10.1016/j.jhydrol.2010.03.022
6. Runoff prediction in ungauged catchments in Norway: comparison of regionalization approaches X. Yang et al. https://doi.org/10.2166/nh.2017.071
7. Impact of the number of donor catchments and the efficiency threshold on regionalization performance of hydrological models W. Qi et al. https://doi.org/10.1016/j.jhydrol.2021.126680
8. Data-driven scale extrapolation: estimating yearly discharge for a large region by small sub-basins L. Gong https://doi.org/10.5194/hess-18-343-2014
9. Sensitivity analyses of landscape attributes on flow prediction in data-poor Semliki watershed J. Kileshye Onema & A. Taigbenu https://doi.org/10.1016/j.pce.2011.07.082
10. Review of Regionalized Parameters for Watershed Hydrological Models under Changing Environment 帅. 李 https://doi.org/10.12677/JWRR.2014.36069
11. Regionalization of catchment hydrological model parameters for global water resources simulations W. Qi et al. https://doi.org/10.2166/nh.2022.118
12. Impact attribution: exploring the contribution of climate change to recent trends in hydrological processes—an editorial introduction F. Hattermann & V. Krysanova https://doi.org/10.1007/s10584-024-03804-4
13. Current awareness https://doi.org/10.1002/hyp.5604
14. Regionalization study of a conceptual hydrological model in Dongjiang basin, south China X. Jin et al. https://doi.org/10.1016/j.quaint.2008.08.006
15. Regionalization of stage-discharge rating curves for hydrodynamic modeling in ungauged basins K. Jafarzadegan & H. Moradkhani https://doi.org/10.1016/j.jhydrol.2020.125165
16. Hydrological Modeling in a Changing Environment: Issues and Challenges 崇. 许 https://doi.org/10.12677/JWRR.2013.22013
17. Regionalization methods for PUB: a comprehensive review of progress after the PUB decade X. Yang et al. https://doi.org/10.2166/nh.2023.027
18. Estimating Selected Parameters for the XAJ Model under Multicollinearity among Watershed Characteristics B. Weimin & L. Qian https://doi.org/10.1061/(ASCE)HE.1943-5584.0000415
19. Application of parameter estimation and regionalization methodologies to ungauged basins of the Upper Blue Nile River Basin, Ethiopia U. Kim & J. Kaluarachchi https://doi.org/10.1016/j.jhydrol.2008.08.016
20. Discharge Estimation for an Ungauged Inland River in an Arid Area Related to Anthropogenic Activities: A Case Study of Heihe River Basin, Northwestern China S. Liu et al. https://doi.org/10.1155/2016/6716501
21. Review and Assessment of Interaction between Watershed Hydrology and Society System 生. 郭 https://doi.org/10.12677/JWRR.2016.51001
22. Attribution assessment of hydrological trends and extremes to climate change for Northern high latitude catchments in Norway X. Yang & S. Huang https://doi.org/10.1007/s10584-023-03615-z
23. Application of Xin'anjiang Model in the flow prediction of ungauged small- and medium-sized catchments in the middle and lower reaches of the Yangtze River Basin G. Junfu et al. https://doi.org/10.18307/2021.0223
24. Using spot flow measurements in a regionalized hydrological model to improve the low flow statistical estimations of rivers: The case of Réunion Island N. Folton https://doi.org/10.1016/j.ejrh.2024.101730
25. Improving regional low-flow modeling in ungauged French catchments using the SMASH platform: A comparative assessment of grid-based parsimonious GR hydrological models and ANN-based regionalization strategies T. de Fournas et al. https://doi.org/10.1016/j.ejrh.2026.103629
26. Regionalisation of the parameters of a hydrological model: Comparison of linear regression models with artificial neural nets G. Heuvelmans et al. https://doi.org/10.1016/j.jhydrol.2005.07.030
27. Quantifying the distribution of tracer discharge from boreal catchments under transient flow using the kinematic pathway approach S. Soltani & V. Cvetkovic https://doi.org/10.1002/2016WR020326
28. Review on Regional Water Resources Assessment Models under Stationary and Changing Climate C. Xu & V. Singh https://doi.org/10.1007/s11269-004-9130-0
29. Hydrologic response to climatic variability in a Great Lakes Watershed: A case study with the SWAT model K. Wu & C. Johnston https://doi.org/10.1016/j.jhydrol.2007.01.030
30. Streamflow prediction in ungauged basins by regressive regionalization: a case study in Huai River Basin, China J. Song et al. https://doi.org/10.2166/nh.2015.155
31. Transferability of regionalization methods under changing climate X. Yang et al. https://doi.org/10.1016/j.jhydrol.2018.10.030
32. Regionalization of hydrological modeling for predicting streamflow in ungauged catchments: A comprehensive review Y. Guo et al. https://doi.org/10.1002/wat2.1487
33. Comparison of four regionalisation methods for a distributed hydrological model J. Götzinger & A. Bárdossy https://doi.org/10.1016/j.jhydrol.2006.09.008
34. An Integrated Modelling Approach for Flood Simulation in the Urbanized Qinhuai River Basin, China R. Li et al. https://doi.org/10.1007/s11269-020-02614-4
35. Regionalization study of a conceptual hydrological model in the Donjiang Basin J. Xiao-li et al. https://doi.org/10.18307/2008.0609
36. Classification and flow prediction in a data-scarce watershed of the equatorial Nile region J. Kileshye Onema et al. https://doi.org/10.5194/hess-16-1435-2012
37. Dependence of regionalization methods on the complexity of hydrological models in multiple climatic regions X. Yang et al. https://doi.org/10.1016/j.jhydrol.2019.124357
38. Predicting runoff in ungauged UK catchments H. Lee et al. https://doi.org/10.1680/wama.2006.159.2.129
39. Improving the flood forecasting capability of the Xinanjiang model for small- and medium-sized ungauged catchments in South China J. Gong et al. https://doi.org/10.1007/s11069-021-04531-0
40. Hydrological Response to Climate Change in Beijiang River Basin Based on the SWAT Model S. Lirong & Z. Jianyun https://doi.org/10.1016/j.proeng.2012.01.713
41. Transferability of Conceptual Hydrological Models Across Temporal Resolutions: Approach and Application M. Jie et al. https://doi.org/10.1007/s11269-017-1874-4
42. Regionalisation for lake level simulation – the case of Lake Tana in the Upper Blue Nile, Ethiopia T. Rientjes et al. https://doi.org/10.5194/hess-15-1167-2011
43. A comparison of simple and complex versions of the Xinanjiang hydrological model in predicting runoff in ungauged basins P. Bai et al. https://doi.org/10.2166/nh.2016.094
44. Evaluation of hydrological response to extreme climate variability using SWAT model: application to the Fuhe basin of Poyang Lake watershed, China J. Lu et al. https://doi.org/10.2166/nh.2016.115
45. Characterizing the groundwater storage–discharge relationship of small catchments in China H. Yan et al. https://doi.org/10.2166/nh.2022.023
46. Application of the Regression-Augmented Regionalization Approach for BTOP Model in Ungauged Basins Y. Zhu et al. https://doi.org/10.3390/w13162294
47. Global water-balance modelling with WASMOD-M: Parameter estimation and regionalisation E. Widén-Nilsson et al. https://doi.org/10.1016/j.jhydrol.2007.04.002
48. Runoff and sediment yield modeling in data-sparse catchments in the Garehsoo River basin, northern Iran M. Golshan et al. https://doi.org/10.1007/s12665-020-09084-2
49. Regional water balance modelling using flow-duration curves with observational uncertainties I. Westerberg et al. https://doi.org/10.5194/hess-18-2993-2014