55 citations as recorded by crossref.

1. The Impact of Climate Change on Agricultural Nonpoint Source Pollution in the Sand River Catchment, Limpopo, South Africa T. Chuene et al. https://doi.org/10.3390/w17121818
2. Industrial Assessment Tools of Risks Associated with Wastewater and Water Technologies A. Trubetskaya et al. https://doi.org/10.1021/acsestwater.5c00839
3. Dual-Phase Calibration for Surface–Subsurface Hydrologic Models with Diverse Hydrologic Conditions S. Abbas et al. https://doi.org/10.1061/JHYEFF.HEENG-6479
4. Sensitivity analysis-based multi-objective calibration using machine learning emulators for integral water system models M. Mohan et al. https://doi.org/10.1080/02626667.2026.2674165
5. Sustainable management of urban groundwater in Lahore central business district: Trends, challenges, and economic implications U. Majed et al. https://doi.org/10.1016/j.envc.2025.101368
6. Uncertainty analysis and parameter optimization enhance assessment accuracy in water yield modelling J. Li et al. https://doi.org/10.1016/j.ejrh.2025.103011
7. Copula-Based Bayesian Inference Approaches for Uncertainty Quantification for Hydrological Simulation F. Wang et al. https://doi.org/10.3390/hydrology13020050
8. Disentangling precipitation forcing and parameter uncertainty in a multi-objective surface–subsurface hydrologic modeling framework S. Abbas et al. https://doi.org/10.1016/j.jhydrol.2026.136136
9. Assessing selenium fate and transport in a semi-arid river basin with and without human influence R. Bailey et al. https://doi.org/10.1016/j.watres.2025.123335
10. The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa F. Merk et al. https://doi.org/10.5194/hess-28-5511-2024
11. Quantifying the impact of climate change and land use change on surface-subsurface nutrient dynamics in a Chesapeake Bay watershed system A. Tuladhar et al. https://doi.org/10.1016/j.jenvman.2025.125101
12. Integrating remote sensing data with watershed-scale ecohydrological modeling in diverse forest and agricultural landscapes of the Upper Mississippi River Basin A. Risal et al. https://doi.org/10.1016/j.envsoft.2025.106588
13. Predicting increased diffuse nitrogen loss from compound extreme precipitations and pollution risk assessment J. Hu et al. https://doi.org/10.1016/j.jclepro.2026.148420
14. Spatial optimization of best management practices for agricultural nitrogen nonpoint source control: a review and practical framework Y. Pan et al. https://doi.org/10.48130/nc-0025-0015
15. Surface runoff modeling in the Subarnarekha River basin using SWAT for sustainable water resource management S. Patra et al. https://doi.org/10.1016/j.asr.2026.04.017
16. Towards intelligent microclimate control in cattle housing: A dynamic-balance framework via multi-constraint optimization M. Wang et al. https://doi.org/10.1016/j.atech.2025.101697
17. Return Flow Compensation Reshapes Water Savings and Carbon–Water Synergy in Cold-Region Paddy Systems J. Wang et al. https://doi.org/10.3390/agriculture16091002
18. An Adaptive Process-Wise Fitting Approach for Hydrological Modeling Based on Streamflow and Remote Sensing Evapotranspiration C. Wang et al. https://doi.org/10.3390/w16233446
19. Modeling agro-hydrological surface-subsurface processes in a semi-arid, intensively irrigated river basin S. Abbas et al. https://doi.org/10.1016/j.ejrh.2025.102188
20. Hydrological Stability and Sensitivity Analysis of the Cahaba River Basin: A Combined Review and Simulation Study P. Preetha et al. https://doi.org/10.3390/w18080894
21. Development of an MPE-BMA Ensemble Model for Runoff Prediction Under Future Climate Change Scenarios: A Case Study of the Xiangxi River Basin W. Li et al. https://doi.org/10.3390/su17104714
22. Irrigated-area expansion offsets agricultural water-saving benefits in an arid region: A case study of the Ebinur Lake Basin, China J. Liu et al. https://doi.org/10.1016/j.agwat.2026.110392
23. Streamflow assessment of the lower Godavari river basin using the SWAT model M. Diwakar & K. Vijay https://doi.org/10.1007/s12517-025-12415-x
24. Calibration guide for watershed modeling with distributed groundwater modeling: application for the SWAT+ model S. Abbas et al. https://doi.org/10.1080/02626667.2024.2393414
25. Some Remarks About Forward and Inverse Modelling in Hydrology, Within a General Conceptual Framework M. Giudici https://doi.org/10.3390/hydrology11110189
26. Coupling SWAT+ with machine learning-enhanced ECMWF seasonal forecasts for predicting inflows to Entrepeñas and Buendía reservoirs P. Jimeno-Sáez et al. https://doi.org/10.1016/j.envsoft.2026.107094
27. Rice Irrigation Deficits under Monsoon-Dominated Hydrology: A Water Balance Study of the Bila Catchment, Indonesia R. Asra https://doi.org/10.62321/issn.1000-1298.2025.10.2
28. A surrogate model-based framework for national-scale assessment of climate change impacts and vulnerabilities: A review with applications in the agricultural sector S. Choi et al. https://doi.org/10.15531/KSCCR.2025.16.5.1061
29. Enhancing groundwater representation in SWAT+gwflow with an open-source zonal parameterization and calibration workflow in R J. Rodríguez-Castellanos et al. https://doi.org/10.1016/j.envsoft.2026.107049
30. Assessing improvements in environmental flow estimation through the use of a coupled surface-groundwater model G. Castellanos-Osorio et al. https://doi.org/10.1016/j.gsd.2025.101426
31. Hybrid deep learning-numerical modeling framework for long-term prediction of groundwater discharge and radionuclide transport M. Seong et al. https://doi.org/10.1016/j.jhazmat.2026.141346
32. Modeling sediment yield and assessing conservation measure effectiveness with SWAT+ F. Aghajan Liafu et al. https://doi.org/10.1007/s11629-025-9812-z
33. Assessing Streamflow Response to Climate Change Under Shared Socioeconomic Pathways (SSPs) in the Olifants River Basin, South Africa K. Benti et al. https://doi.org/10.3390/hydrology12090244
34. Uncertainty in modeled eco-hydrologic responses to climate change in Korea mountain wetlands J. Seo & S. Kim https://doi.org/10.1016/j.eti.2026.105003
35. Assessment of the Impact of Spatial Variability on Streamflow Predictions Using High-Resolution Modeling and Parameter Estimation: Case Study of Geumho River Catchment, South Korea B. Kim et al. https://doi.org/10.3390/w16040591
36. Evaluation of precipitation products for small karst catchment hydrological modeling in data-scarce mountainous regions I. Al Khoury et al. https://doi.org/10.1016/j.jhydrol.2024.132131
37. Decoding parameter sensitivities across scales: a Wavelet–Sobol framework for hydrological modelling V. Sai Suswara et al. https://doi.org/10.1016/j.jhydrol.2026.135482
38. Evaluating the continued significance of dam-induced vigorous downstream channel erosion in the context of projected climate change: a case study from Peninsular India J. Sanyal https://doi.org/10.1080/15715124.2024.2423697
39. Reconstruction of pyroclastic density currents emplaced during the April 1993 sub-Plinian eruption of Lascar volcano, northern Chile A. Esquivel et al. https://doi.org/10.1007/s00445-025-01879-0
40. Review of Watershed Hydrology and Mathematical Models S. Sarker & O. Leta https://doi.org/10.3390/eng6060129
41. A process-informed multi-parameter downscaling framework for high-resolution source apportionment of riverine nutrients X. Li et al. https://doi.org/10.1016/j.jhydrol.2026.135644
42. Assessing the necessity of water transfer using SWAT modelling V. Panchabikesan et al. https://doi.org/10.1016/j.dwt.2025.101544
43. Unravelling the hydrologic impact of climate change in the Great Ruaha River Basin, Tanzania E. Mukama et al. https://doi.org/10.1088/2515-7620/ae1ed9
44. Modeling runoff, sediment yield and conservation measures using SWAT in Ajima catchment, Upper Blue Nile Basin, Ethiopia S. Hatiye et al. https://doi.org/10.1038/s41598-025-34617-9
45. The contribution of red clover to nitrate loading in an agricultural watershed Y. Jiang et al. https://doi.org/10.3389/fenvs.2025.1471213
46. A novel spatiotemporal and machine learning framework for sustainable groundwater monitoring and management S. Maqbool et al. https://doi.org/10.1016/j.gsd.2026.101612
47. Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system I. Qurban et al. https://doi.org/10.1016/j.scitotenv.2025.179861
48. Modeling spatial and temporal groundwater recharge dynamics using the newly physically-based coupled model in Tana sub-basin, Ethiopia K. Berhanu et al. https://doi.org/10.1007/s13201-025-02436-y
49. Surface Runoff and Sediment Yield Responses to Land Use and Cover Changes: Implications for Watershed Management in the Gidabo Watershed, Ethiopia D. Dogiso et al. https://doi.org/10.1002/hyp.70245
50. Quantifying Baseflow Changes Due to Irrigation Expansion Using SWAT+gwflow R. Navas et al. https://doi.org/10.3390/w17111680
51. Analysis of SWAT+ model performance: A comparative study using different software and algorithms S. Cecconello et al. https://doi.org/10.1016/j.envsoft.2025.106425
52. Holistic uncertainty quantification and attribution for real-time seasonal streamflow predictions: Insights from input, parameter and initial condition L. Liu et al. https://doi.org/10.1016/j.ejrh.2025.102427
53. An objective-driven framework for hydrological model selection in data-scarce tropical regions: integrating LULC projection and uncertainty analysis E. Adesina & H. Suraj https://doi.org/10.1007/s12517-026-12546-9
54. Enhancing inverse modeling in groundwater systems through machine learning: a comprehensive comparative study J. Chen et al. https://doi.org/10.5194/hess-29-4251-2025
55. Research on attribution and prediction of runoff changes in loess gully areas based on SWAT and machine learning models Y. Zhao et al. https://doi.org/10.1016/j.ecolind.2026.115244