79 citations as recorded by crossref.

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9. Assessment of changes in water conservation capacity under land degradation neutrality effects in a typical watershed of Yellow River Basin, China D. Zuo et al. https://doi.org/10.1016/j.ecolind.2023.110145
10. Impact of Land Use Change on Water Conservation: A Case Study of Zhangjiakou in Yongding River T. Pan et al. https://doi.org/10.3390/su13010022
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13. Assessment of hydrological water balance in Lower Nzoia Sub-catchment using SWAT-model: towards improved water governace in Kenya L. Juma et al. https://doi.org/10.1016/j.heliyon.2022.e09799
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18. Effects of the “Grain for Green” Program on Soil Water Dynamics in the Semi-Arid Grassland of Inner Mongolia, China Z. Zhang et al. https://doi.org/10.3390/w13152034
19. Effects of vegetation restoration on runoff and its components in the mountainous Haihe River Basin Y. Chang et al. https://doi.org/10.1016/j.ejrh.2024.101803
20. Assessing the impact of vegetation changes on water availability in the upper Yellow River Basin, China Y. Wang et al. https://doi.org/10.1016/j.ejrh.2025.102403
21. Baseflow estimation in typical catchments in the Yellow River Basin, China C. Hu et al. https://doi.org/10.2166/ws.2020.338
22. Improving SWAT model performance in the upper Blue Nile Basin using meteorological data integration and subcatchment discretization E. Polanco et al. https://doi.org/10.5194/hess-21-4907-2017
23. Quantifying climate and anthropogenic impacts on runoff using the SWAT model, a Budyko-based approach and empirical methods R. Xu et al. https://doi.org/10.1080/02626667.2023.2218551
24. Precipitation Modulates the Impact of Human Activities on Riverine Food Webs Revealed by Environmental DNA S. Zhang et al. https://doi.org/10.1002/ece3.73713
25. Hydrological evaluation of open-access precipitation data using SWAT at multiple temporal and spatial scales J. Pang et al. https://doi.org/10.5194/hess-24-3603-2020
26. A coupled Hydro–Biogeochemical framework for evaluating lateral loss of soil organic carbon under land-use change at the basin scale G. Zhang et al. https://doi.org/10.1016/j.jenvman.2026.128981
27. Sensitivity of Vegetation Growth to Precipitation in a Typical Afforestation Area in the Loess Plateau: Plant-Water Coupled Modelling D. Wu et al. https://doi.org/10.1016/j.ecolmodel.2020.109128
28. Assessment of an Alternative Climate Product for Hydrological Modeling: A Case Study of the Danjiang River Basin, China Y. Guo et al. https://doi.org/10.3390/w14071105
29. Impacts of land use/cover change on water balance by using the SWAT model in a typical loess hilly watershed of China Z. Liu et al. https://doi.org/10.1016/j.geosus.2022.11.006
30. Analysis of Water Source Conservation Driving Factors Based on Machine Learning Y. Jia et al. https://doi.org/10.3390/su17041713
31. Assessing the Impacts of Future Climate and Land-Use Changes on Streamflow under Multiple Scenarios: A Case Study of the Upper Reaches of the Tarim River in Northwest China Q. Han et al. https://doi.org/10.3390/w16010100
32. Multi-Scale Effect of Land Use Landscape on Basin Streamflow Impacts in Loess Hilly and Gully Region of Loess Plateau: Insights from the Sanchuan River Basin, China Z. Lei et al. https://doi.org/10.3390/su162310781
33. DHRFLUT: A scenario-controlled framework for decoupling runoff responses from land use transitions – a case study in China’s Wei River basin C. Yao et al. https://doi.org/10.1016/j.jhydrol.2026.135092
34. Hydrologic response to land use/cover changes and Pteronia incana shrub invasion in Keiskamma catchment, Eastern Cape Province, South Africa S. Mlamla et al. https://doi.org/10.1080/10106049.2022.2032395
35. Coupling of SWAT and EPIC Models to Investigate the Mutual Feedback Relationship between Vegetation and Soil Erosion, a Case Study in the Huangfuchuan Watershed, China Z. Luo et al. https://doi.org/10.3390/f14040844
36. Spatiotemporal Water Yield Variations and Influencing Factors in the Lhasa River Basin, Tibetan Plateau H. Lu et al. https://doi.org/10.3390/w12051498
37. Quantifying spatiotemporal inconsistencies in runoff responses to forest logging in a subtropical watershed, China Y. Xu et al. https://doi.org/10.1016/j.fecs.2025.100337
38. Disentangling climate effects of greenhouse gas emissions and land cover change on future gross primary productivity in the Yellow River basin, China X. Ru et al. https://doi.org/10.1016/j.jenvman.2025.126026
39. Spatiotemporal variations of water conservation function based on EOF analysis at multi time scales under different ecosystems of Heihe River Basin Q. Wu et al. https://doi.org/10.1016/j.jenvman.2022.116532
40. Climatic and hydrologic controls on net primary production in a semiarid loess watershed F. Zhao et al. https://doi.org/10.1016/j.jhydrol.2018.11.031
41. An investigation into hydrological response to urbanization in the Loess Plateau, China: Does urban expansion only boost flow? C. Yao et al. https://doi.org/10.1016/j.ejrh.2025.102659
42. Attribution Analysis of Runoff Change in Min-Tuo River Basin based on SWAT model simulations, China J. Hu et al. https://doi.org/10.1038/s41598-020-59659-z
43. Determining relative contributions of climate change and multiple human activities to runoff and sediment reduction in the eastern Loess Plateau, China J. Wang et al. https://doi.org/10.1016/j.catena.2023.107376
44. Modeling the effect of LULC change on water quantity and quality in Big Creek Lake Watershed, South Alabama USA E. Eva et al. https://doi.org/10.1016/j.ejrs.2024.03.005
45. Coupling Changes in Runoff and Sediment and Their Relationships with Erosion Energy and Underlying Surface in the Wuding River Basin, China Q. Yang et al. https://doi.org/10.3390/land13040496
46. Land Use Change Impacts on Hydrology in the Nenjiang River Basin, Northeast China F. Li et al. https://doi.org/10.3390/f10060476
47. Unveiling flood-generating mechanisms using circular statistics-based machine learning approach without the need for discharge data during inference Z. Zhang et al. https://doi.org/10.2166/nh.2023.058
48. Impact of the Grain for Green Project on water resources and ecological water stress in the Yanhe River Basin Y. Han et al. https://doi.org/10.1371/journal.pone.0259611
49. Revisiting Biophysical Impacts of Greening on Precipitation Over the Loess Plateau of China Using WRF With Water Vapor Tracers Y. Liu et al. https://doi.org/10.1029/2023GL102809
50. Impact of greenspaces and water bodies on hydrological processes in an urbanizing area: A case study of the Liuxi River Basin in the Pearl River Delta, China N. Wang et al. https://doi.org/10.1016/j.ecolind.2023.111083
51. Investigating the effects of climate and vegetation changes on spatiotemporal variation of baseflow in the Yellow River Basin J. Xu et al. https://doi.org/10.1016/j.jhydrol.2024.132517
52. Impact of global climate change induced variations in reservoir-river systems on fish habitats G. Zhao et al. https://doi.org/10.1038/s41598-026-41555-7
53. Spatio-Temporal Patterns of Land-Use Changes and Conflicts between Cropland and Forest in the Mekong River Basin during 1990–2020 J. Zhai et al. https://doi.org/10.3390/land11060927
54. The Runoff in the Upper Taohe River Basin and Its Responses to Climate Change L. Cheng et al. https://doi.org/10.3390/w14132094
55. Revisiting the application of the SWAT model in arid and semi-arid regions: a selection from 2009 to 2022 A. Rocha et al. https://doi.org/10.1007/s00704-023-04546-6
56. Uncertainty in simulation of land-use change impacts on catchment runoff with multi-timescales based on the comparison of the HSPF and SWAT models Y. Chen et al. https://doi.org/10.1016/j.jhydrol.2019.03.091
57. Total Maximum Daily Load of the Curug Sub-district Segment of The Cirarab River, Indonesia K. Indriyani et al. https://doi.org/10.1051/e3sconf/202020202010
58. Parameter Uncertainty Analysis for Streamflow Simulation Using SWAT Model in Nashe Watershed, Blue Nile River Basin, Ethiopia M. Leta et al. https://doi.org/10.1155/2022/1826942
59. Bivariate frequency analysis of flood and extreme precipitation under changing environment: case study in catchments of the Loess Plateau, China A. Guo et al. https://doi.org/10.1007/s00477-017-1478-9
60. Hydrological effects of change in vegetation components across global catchments Z. Chen et al. https://doi.org/10.1016/j.jhydrol.2020.125775
61. Impact of revegetation and agricultural intensification on water storage variation in the Yellow River Basin Z. Wang et al. https://doi.org/10.1016/j.jhydrol.2024.131218
62. Parameter Uncertainty Analysis of the SWAT Model in a Mountain-Loess Transitional Watershed on the Chinese Loess Plateau F. Zhao et al. https://doi.org/10.3390/w10060690
63. Quantifying the contributions of climate variation, land use change, and engineering measures for dramatic reduction in streamflow and sediment in a typical loess watershed, China P. Sun et al. https://doi.org/10.1016/j.ecoleng.2019.105611
64. Multi-scenario analysis and optimization strategy of ecological security pattern in the Weihe river basin X. Luo et al. https://doi.org/10.1016/j.jenvman.2024.121813
65. Impacts of climate change and fruit tree expansion on key hydrological components at different spatial scales Y. Xu et al. https://doi.org/10.3389/ffgc.2023.1114423
66. Soil Water Analysis Tools (SWAT) hydrology modelling as a basis for spatial planning: a case study in Cimandiri Watershed, West Java Province I. Ridwansyah et al. https://doi.org/10.1088/1755-1315/380/1/012017
67. Crucial role of natural processes in detecting human influence on evapotranspiration by multisource data analysis M. Zhang & X. Yuan https://doi.org/10.1016/j.jhydrol.2019.124350
68. Inversion and Analysis of Water Storage Change in the Loess Plateau under the Background of the Grain for Green Project X. Xie et al. https://doi.org/10.1134/S0097807823601152
69. Hydrological Assessment Using the SWAT Model in the Jundiaí River Basin, Brazil: Calibration, Model Performance, and Land Use Change Impact Analysis L. Moura et al. https://doi.org/10.3390/resources14070112
70. Assessing the response of runoff to climate change and human activities for a typical basin in the Northern Taihang Mountain, China J. Wang et al. https://doi.org/10.1007/s12040-018-0932-5
71. Evaluation and machine learning improvement of global hydrological model-based flood simulations T. Yang et al. https://doi.org/10.1088/1748-9326/ab4d5e
72. A Multivariate and Multistage Streamflow Prediction Model Based on Signal Decomposition Techniques with Deep Learning D. Yan et al. https://doi.org/10.2112/JCOASTRES-D-21-00011.1
73. Is returning farmland to forest an effective measure to reduce phosphorus delivery across distinct spatial scales? W. Wang et al. https://doi.org/10.1016/j.jenvman.2019.109663
74. Long-Term Variation of Runoff Coefficient during Dry and Wet Seasons Due to Climate Change D. Ha et al. https://doi.org/10.3390/w11112411
75. Quantitative impacts of climate change and human activities on runoff in the Huolin River catchment D. Dan et al. https://doi.org/10.2166/wcc.2022.223
76. Changes in water conservation and possible causes in the Yellow River Basin of China during the recent four decades G. Chen et al. https://doi.org/10.1016/j.jhydrol.2024.131314
77. Quantifying Climate and Residual Non-Climatic Contributions to Runoff Reduction in Major Watersheds of the Chinese Loess Plateau X. Yang et al. https://doi.org/10.3390/w18101191
78. Significance of using dynamic land-use data and its threshold in hydrology and water quality simulation models Q. Wang et al. https://doi.org/10.1007/s10661-022-09761-8
79. Impacts of Climate Change and Land-Use Change on Hydrological Extremes in the Jinsha River Basin Q. Chen et al. https://doi.org/10.3390/w11071398