44 citations as recorded by crossref.

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2. GIS and SBF for estimating groundwater recharge of a mountainous basin in the Wu River watershed, Taiwan H. YEH et al. https://doi.org/10.1007/s12040-014-0420-5
3. Quantifying watershed‐scale groundwater loading and in‐stream fate of nitrate using high‐frequency water quality data M. Miller et al. https://doi.org/10.1002/2015WR017753
4. Parameter sensitivity of automated baseflow separation for snowmelt‐dominated watersheds and new filtering procedure for determining end of snowmelt period D. Voutchkova et al. https://doi.org/10.1002/hyp.13369
5. The importance of base flow in sustaining surface water flow in the Upper Colorado River Basin M. Miller et al. https://doi.org/10.1002/2015WR017963
6. Enhanced baseflow separation in rural catchments: event-specific calibration of recursive digital filters with tracer-derived data F. Helfer et al. https://doi.org/10.5194/hess-29-6959-2025
7. Streamflow-base flow ratio in a lowland area of North-Eastern Romania I. Minea https://doi.org/10.1134/S0097807817040121
8. Comparison of Baseflow Separation Methods in the German Low Mountain Range M. Kissel & B. Schmalz https://doi.org/10.3390/w12061740
9. Investigating the Effects of Land Use Change on Subsurface, Surface, and Atmospheric Branches of the Hydrologic Cycle in Central Argentina S. Pal et al. https://doi.org/10.1029/2021WR029704
10. Application of multi-method approach to assess groundwater–surface water interactions, for catchment management T. Madlala et al. https://doi.org/10.1007/s13762-018-1819-3
11. Base flow simulation using a physically based subsurface model – The case of a tropical basin in the Western Ghats, India P. George & M. Sekhar https://doi.org/10.1016/j.jhydrol.2022.128451
12. Estimation of flow regime for a spatially varied Himalayan watershed using improved multi-site calibration of the Soil and Water Assessment Tool (SWAT) model M. Hasan & S. Pradhanang https://doi.org/10.1007/s12665-017-7134-3
13. Neural network river forecasting through baseflow separation and binary-coded swarm optimization R. Taormina et al. https://doi.org/10.1016/j.jhydrol.2015.08.008
14. Evaluating the transferability of monthly water balance models under changing climate conditions Ž. Topalović et al. https://doi.org/10.1080/02626667.2020.1725238
15. Catchment clustering in Taiwan through comparative assessment of baseflow separation methods H. Chen & H. Yeh https://doi.org/10.1016/j.ejrh.2026.103438
16. Detecting and attributing the changes in baseflow in China’s Loess Plateau X. Yan et al. https://doi.org/10.1016/j.jhydrol.2022.128957
17. On the structural limitations of recursive digital filters for base flow estimation C. Su et al. https://doi.org/10.1002/2015WR018067
18. Hydrograph separation method and baseflow separation using Chapman Method – A case study in Peusangan Watershed I. Ramli et al. https://doi.org/10.1088/1755-1315/314/1/012026
19. Assessing Efficacy of Baseflow Separation Techniques in a Himalayan River Basin, Northern India S. Bhardwaj et al. https://doi.org/10.1007/s40710-024-00680-z
20. Probability-Based Propagation Characteristics from Meteorological to Hydrological Drought and Their Dynamics in the Wei River Basin, China M. Du et al. https://doi.org/10.3390/w16141999
21. Antibiotic transport requires a renewed focus on baseflow as a critical non-point source pathway H. Xie et al. https://doi.org/10.1016/j.envpol.2025.126355
22. Modelling triazines in the valley of the River Cauca, Colombia, using the annualized agricultural non-point source pollution model M. Villamizar & C. Brown https://doi.org/10.1016/j.agwat.2016.06.010
23. Groundwater recharge study based on hydrological data and hydrological modelling in a South American volcanic aquifer M. Melati et al. https://doi.org/10.1016/j.crte.2019.06.001
24. Can the two-parameter recursive digital filter baseflow separation method really be calibrated by the conductivity mass balance method? W. Yang et al. https://doi.org/10.5194/hess-25-1747-2021
25. Using natural tracers and calibrated analytical filter to highlight baseflow contribution to mountainous Mediterranean rivers in a context of climate change P. Guisiano et al. https://doi.org/10.1016/j.jhydrol.2024.131842
26. Contribution of nonpoint source pollution from baseflow of a typical agriculture-intensive basin in northern China T. Guan et al. https://doi.org/10.1016/j.envres.2022.113589
27. Base-flow segmentation and character analysis of the Huangfuchuan Basin in the middle reaches of the Yellow River, China Y. Zhang et al. https://doi.org/10.3389/fenvs.2022.831122
28. Untangling harvest‐streamflow responses in foothills conifer forests: Nexus of teleconnections, summer‐dominated precipitation, and storage A. Goodbrand et al. https://doi.org/10.1002/hyp.14479
29. Assessment of agricultural watershed water budget considering upstream water budget against reservoir discharge and agricultural water supply S. Kim et al. https://doi.org/10.1016/j.agwat.2025.109587
30. Assessing the suitability of hydrometric data for trend analysis: The ‘FlowScreen’ package for R J. Dierauer et al. https://doi.org/10.1080/07011784.2017.1290553
31. Driving Factors of the Hydrological Response of a Tropical Watershed: The Ankavia River Basin in Madagascar Z. Ramahaimandimby et al. https://doi.org/10.3390/w15122237
32. Changes to rainfall, snowfall, and runoff events during the autumn–winter transition in the Rocky Mountains of North America P. Whitfield & K. Shook https://doi.org/10.1080/07011784.2019.1685910
33. Understanding event runoff coefficient variability across Australia using the hydroEvents R package C. Wasko & D. Guo https://doi.org/10.1002/hyp.14563
34. Relative contribution of land use change and climate variability on discharge of upper Mara River, Kenya H. Mwangi et al. https://doi.org/10.1016/j.ejrh.2015.12.059
35. Bayesian chemistry-assisted hydrograph separation (BACH) and nutrient load partitioning from monthly stream phosphorus and nitrogen concentrations S. Woodward & R. Stenger https://doi.org/10.1007/s00477-018-1612-3
36. Technical note: Analytical sensitivity analysis and uncertainty estimation of baseflow index calculated by a two-component hydrograph separation method with conductivity as a tracer W. Yang et al. https://doi.org/10.5194/hess-23-1103-2019
37. Hydrograph separation using tracers and digital filters to quantify runoff components in a semi‐arid mesoscale catchment A. Saraiva Okello et al. https://doi.org/10.1002/hyp.11491
38. Temporal variations in baseflow for the Little River experimental watershed in South Georgia, USA D. Bosch et al. https://doi.org/10.1016/j.ejrh.2017.02.002
39. Technical note: How physically based is hydrograph separation by recursive digital filtering? K. Eckhardt https://doi.org/10.5194/hess-27-495-2023
40. Spatiotemporal Evaluation of Simulated Evapotranspiration and Streamflow over Texas Using the WRF‐Hydro‐RAPID Modeling Framework P. Lin et al. https://doi.org/10.1111/1752-1688.12585
41. Small island watershed morphometric and hydrological characteristics in Ambon Region, Maluku Province B. Latuamury et al. https://doi.org/10.1088/1755-1315/800/1/012047
42. Impact-Based Critical Areal Rainfall for Early Flood Warning: A Case Study of Zhulong River Watershed in the Upper Reaches of the Xiong’an New Area L. Si et al. https://doi.org/10.3390/atmos14010113
43. Investigation of hydrological processes and the impacts of Acacia mearnsii plantations on groundwater in secondary aquifers: Case study at the two-stream research catchment, South Africa C. Ngubo et al. https://doi.org/10.1016/j.ejrh.2022.101018
44. Comparison of scenario‐neutral approaches for estimation of climate change impacts on flood characteristics L. Keller et al. https://doi.org/10.1002/hyp.13341