151 citations as recorded by crossref.

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10. Comparison of SWAT and GWLF Model Simulation Performance in Humid South and Semi-Arid North of China Z. Qi et al. 10.3390/w9080567
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14. Evaluating the impacts of soil data on hydrological and nonpoint source pollution prediction L. Chen et al. 10.1016/j.scitotenv.2016.04.107
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24. Evaluation of global land use/land cover products for hydrologic simulation in the Upper Yom River Basin, Thailand C. Chirachawala et al. 10.1016/j.scitotenv.2019.135148
25. Impending Hydrological Regime of Lhasa River as Subjected to Hydraulic Interventions—A SWAT Model Manifestation M. Yasir et al. 10.3390/rs13071382
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32. Developing an integrated PCE-ANOVA-RF method for uncertainty quantification of hydrological model – The Amu Darya River Basin in Central Asia Z. Xu et al. 10.1016/j.jhydrol.2023.129941
33. Improved forest dynamics leads to better hydrological predictions in watershed modeling H. Haas et al. 10.1016/j.scitotenv.2022.153180
34. Improvement of model evaluation by incorporating prediction and measurement uncertainty L. Chen et al. 10.5194/hess-22-4145-2018
35. Simulation of stream flow components in a mountainous catchment in northern Thailand with SWAT, using the ANSELM calibration approach M. Bannwarth et al. 10.1002/hyp.10268
36. Modeling metal-sediment interaction processes: Parameter sensitivity assessment and uncertainty analysis E. Cho et al. 10.1016/j.envsoft.2016.02.026
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43. Hydroclimatic Impact Assessment Using the SWAT Model in India—State of the Art Review S. Dubey et al. 10.3390/su152215779
44. Sensitivity and uncertainty analysis of a surface runoff model using ensemble of artificial rainfall experiments J. Jeřábek & P. Kavka 10.2478/johh-2024-0021
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46. The Rivillas flood of 5–6 November 1997 (Badajoz, Spain) revisited: An approach based on Iber+ modelling J. González-Cao et al. 10.1016/j.jhydrol.2022.127883
47. The comparative study of multi‐site uncertainty evaluation method based on SWAT model J. Zhang et al. 10.1002/hyp.10380
48. A comprehensive study of the effect of GIS data on hydrology and non-point source pollution modeling Z. Shen et al. 10.1016/j.agwat.2012.12.005
49. Predicting Non-Point Source Pollution in Henan Province Using the Diffuse Pollution Estimation with Remote Sensing Model with Enhanced Sensitivity Analysis W. Chen et al. 10.3390/app15052261
50. Uncertainty analysis of a semi-distributed hydrologic model based on a Gaussian Process emulator J. Yang et al. 10.1016/j.envsoft.2017.11.037
51. Assessing model parameters sensitivity and uncertainty of streamflow, sediment, and nutrient transport using SWAT A. Dakhlalla & P. Parajuli 10.1016/j.inpa.2018.08.007
52. The influence of parameter distribution uncertainty on hydrological and sediment modeling: a case study of SWAT model applied to the Daning watershed of the Three Gorges Reservoir Region, China S. Zhenyao et al. 10.1007/s00477-012-0579-8
53. Improving Forecast Skill of Lowland Hydrological Models Using Ensemble Kalman Filter and Unscented Kalman Filter Y. Sun et al. 10.1029/2020WR027468
54. Developing a real-time water quality simulation toolbox using machine learning and application programming interface G. Bang et al. 10.1016/j.jenvman.2025.124719
55. Evaluating uncertainty estimates in distributed hydrological modeling for the Wenjing River watershed in China by GLUE, SUFI-2, and ParaSol methods H. Wu & B. Chen 10.1016/j.ecoleng.2014.05.014
56. Hydrological Modeling of Tributaries of Cantareira System, Southeast Brazil, with the Swat Model L. Pontes et al. 10.1590/1809-4430-eng.agric.v36n6p1037-1049/2016
57. Using site-specific soil samples as a substitution for improved hydrological and nonpoint source predictions L. Chen et al. 10.1007/s11356-016-6789-8
58. Development of an integrated modeling approach for identifying multilevel non-point-source priority management areas at the watershed scale L. Chen et al. 10.1002/2013WR015041
59. Event-based uncertainty assessment of sediment modeling in a data-scarce catchment H. Xie et al. 10.1016/j.catena.2018.10.008
60. Effect of different likelihood measures on parameter conditioning and model uncertainty F. Baig et al. 10.1007/s00477-025-02909-1
61. Quantification of predictive uncertainty with a metamodel: toward more efficient hydrologic simulations V. Tran & J. Kim 10.1007/s00477-019-01703-0
62. The Impact and Application of Smart Grid on Global Energy Delivery M. Koroma & I. Sawaneh 10.34256/ajir20237
63. Evaluation of the number of events’ influence on model performance and uncertainty in urban data-scarce areas based on behavioral parameter ranking method Y. Wu et al. 10.1016/j.jhydrol.2024.131298
64. A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification V. Tran et al. 10.1029/2019WR025727
65. Modeling Non-point Source Phosphorus Load on a Rural Basin with Onsite Wastewater Treatment Systems B. Kibet Kimengich et al. 10.7132/jrcsa.27_1_1
66. The challenges of modelling phosphorus in a headwater catchment: Applying a ‘limits of acceptability’ uncertainty framework to a water quality model M. Hollaway et al. 10.1016/j.jhydrol.2018.01.063
67. Application of hydrological model for assessment of water security using multi-model ensemble of CORDEX-South Asia experiments in a semi-arid river basin of India S. Dubey et al. 10.1016/j.ecoleng.2019.105641
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71. An Interval-Deviation Approach for hydrology and water quality model evaluation within an uncertainty framework L. Chen et al. 10.1016/j.jhydrol.2013.11.043
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73. GLUE algorithm capability in estimating the van Genuchten soil–water characteristic parameters and their uncertainties S. Etminan et al. 10.1007/s10333-021-00886-z
74. Impacts of land use change and climate variations on annual inflow into the Miyun Reservoir, Beijing, China J. Zheng et al. 10.5194/hess-20-1561-2016
75. Automatic calibration of a large-scale sediment model using suspended sediment concentration, water quality, and remote sensing data H. Fagundes et al. 10.1590/2318-0331.241920180127
76. Integrated approach to simulate hydrological responses to land use dynamics and climate change scenarios employing scoring method in upper Narmada basin, India B. Pandey et al. 10.1016/j.jhydrol.2021.126429
77. Quantifying the Uncertainty in Modeled Water Drainage and Nutrient Leaching Fluxes in Forest Ecosystems G. van der Heijden et al. 10.1007/s10021-018-0295-4
78. Towards a more consistent eco-hydrological modelling through multi-objective calibration: a case study in the Andean Vilcanota River basin, Peru C. Fernandez-Palomino et al. 10.1080/02626667.2020.1846740
79. Parameter uncertainty analysis for simulating streamflow in a river catchment of Vietnam D. Khoi & V. Thom 10.1016/j.gecco.2015.10.007
80. Simulating the Hydrological Processes of a Meso-Scale Watershed on the Loess Plateau, China M. Leng et al. 10.3390/w12030878
81. Uncertainty assessment of radar-raingauge merged rainfall estimates in river discharge simulations N. Nanding et al. 10.1016/j.jhydrol.2021.127093
82. Identification of sensitive parameters in daily and monthly hydrological simulations in small to large catchments in Central India A. Singh & S. Jha 10.1016/j.jhydrol.2021.126632
83. Uncertainty and sensitivity assessments of an agricultural–hydrological model (RZWQM2) using the GLUE method M. Sun et al. 10.1016/j.jhydrol.2015.12.045
84. Integrated Geospatial Analysis and Hydrological Modeling for Peak Flow and Volume Simulation in Rwanda R. Mind’je et al. 10.3390/w13202926
85. Uncertainty analysis for integrated water system simulations using GLUE with different acceptability thresholds Y. Zhang et al. 10.1007/s11431-020-1752-0
86. Bayesian uncertainty analysis in hydrological modeling associated with watershed subdivision level: a case study of SLURP model applied to the Xiangxi River watershed, China J. Han et al. 10.1007/s00477-013-0792-0
87. Preliminary Investigation on Coupling MCDA with GLUE to Perform Uncertainty Analysis of a Hydrological Model P. Vallam et al. 10.7763/IJESD.2015.V6.555
88. Streamflow Modelling: A Primer on Applications, Approaches and Challenges D. Bourdin et al. 10.1080/07055900.2012.734276
89. Adapting SWAT hillslope erosion model to predict sediment concentrations and yields in large Basins O. Vigiak et al. 10.1016/j.scitotenv.2015.08.095
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91. Determination of the Hydrological and Morphometric Characteristics Using GIS S. Abd Elrahman & I. Ataalmanan 10.2478/cee-2023-0004
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98. Uncertainties in SWAT extreme flow simulation under climate change X. Zhang et al. 10.1016/j.jhydrol.2014.04.064
99. Effects of hydrologic conditions on SWAT model performance and parameter sensitivity for a small, mixed land use catchment in New Zealand W. Me et al. 10.5194/hess-19-4127-2015
100. Evaluation of Agricultural Water Supply and Selection of Deficient Districts in Yeongsan River Basin of South Korea Considering Supply Priority S. Kim et al. 10.3390/w14030298
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125. Evaluation of Gridded Precipitation Data for Driving SWAT Model in Area Upstream of Three Gorges Reservoir Y. Yang et al. 10.1371/journal.pone.0112725
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