61 citations as recorded by crossref.

1. Assessing the cumulative impacts of geographically isolated wetlands on watershed hydrology using the SWAT model coupled with improved wetland modules S. Lee et al. https://doi.org/10.1016/j.jenvman.2018.06.006
2. A watershed model predicts the effects of cover crops on river flows, sediment transport, and nutrient loss to Lake Michigan M. Aboelnour et al. https://doi.org/10.1016/j.jglr.2025.102528
3. Improving model prediction reliability through enhanced representation of wetland soil processes and constrained model auto calibration – A paired watershed study A. Sharifi et al. https://doi.org/10.1016/j.jhydrol.2016.08.022
4. Introgression of rye chromosome arm 1RS enhances climate resilience in German winter wheat Y. Bekele-Reba et al. https://doi.org/10.1007/s00122-026-05314-6
5. A Genome-Wide Association Study Pinpoints Quantitative Trait Genes for Plant Height, Heading Date, Grain Quality, and Yield in Rye (Secale cereale L.) D. Siekmann et al. https://doi.org/10.3389/fpls.2021.718081
6. Combined use of crop yield statistics and remotely sensed products for enhanced simulations of evapotranspiration within an agricultural watershed S. Lee et al. https://doi.org/10.1016/j.agwat.2022.107503
7. Cover Crops and Landscape Position Effects on Nitrogen Dynamics in Plant-Soil-Water Pools G. Singh et al. https://doi.org/10.3390/w11030513
8. Synergistic water quality and soil organic carbon sequestration benefits of winter cover crops X. Zhang et al. https://doi.org/10.1016/j.jenvman.2024.123104
9. Investigating water use over the Choptank River Watershed using a multisatellite data fusion approach L. Sun et al. https://doi.org/10.1002/2017WR020700
10. Modeling riverine dissolved and particulate organic carbon fluxes from two small watersheds in the northeastern United States J. Qi et al. https://doi.org/10.1016/j.envsoft.2019.104601
11. Effects of surface runoff and infiltration partition methods on hydrological modeling: A comparison of four schemes in two watersheds in the Northeastern US J. Qi et al. https://doi.org/10.1016/j.jhydrol.2019.124415
12. Yield Performance and Genotype × Environment Interaction of Elite Rye Germplasm Selected from a Greek Landrace Under Mediterranean Conditions I. Sistanis et al. https://doi.org/10.3390/agronomy16202004
13. Mapping landscape-level hydrological connectivity of headwater wetlands to downstream waters: A catchment modeling approach - Part 2 I. Yeo et al. https://doi.org/10.1016/j.scitotenv.2018.11.237
14. The feasibility of satellite remote sensing and spatial interpolation to estimate cover crop biomass and nitrogen uptake in a small watershed M. Xu et al. https://doi.org/10.2489/jswc.73.6.682
15. Adoption of cover crops in Pennsylvania’s Chesapeake Bay watershed S. Duiker & S. Richards https://doi.org/10.2489/jswc.2023.00080
16. Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model S. Lee et al. https://doi.org/10.5194/hess-22-689-2018
17. Estimating cover crop biomass nitrogen credits with Sentinel‐2 imagery and sites covariates Y. Xia et al. https://doi.org/10.1002/agj2.20525
18. Developing sustainable cropping systems by integrating crop rotation with conservation tillage practices on the Loess Plateau, a long-term imperative Z. Li et al. https://doi.org/10.1016/j.fcr.2018.03.027
19. Integrated environmental modeling for efficient aquifer vulnerability assessment using machine learning W. Jang et al. https://doi.org/10.1016/j.envsoft.2019.104602
20. Spatial Variability of Best Management Practices Effectiveness on Water Quality within the Yazoo River Watershed V. Venishetty et al. https://doi.org/10.3390/hydrology10040092
21. Monitoring irrigation using landsat observations and climate data over regional scales in the Murray-Darling Basin D. Bretreger et al. https://doi.org/10.1016/j.jhydrol.2020.125356
22. Impacts of Watershed Characteristics and Crop Rotations on Winter Cover Crop Nitrate-Nitrogen Uptake Capacity within Agricultural Watersheds in the Chesapeake Bay Region S. Lee et al. https://doi.org/10.1371/journal.pone.0157637
23. Assessing the effectiveness of riparian buffers for reducing organic nitrogen loads in the Coastal Plain of the Chesapeake Bay watershed using a watershed model S. Lee et al. https://doi.org/10.1016/j.jhydrol.2020.124779
24. Utility of Remotely Sensed Evapotranspiration Products to Assess an Improved Model Structure S. Lee et al. https://doi.org/10.3390/su13042375
25. Estimation of base and surface flow using deep neural networks and a hydrologic model in two watersheds of the Chesapeake Bay J. Lee et al. https://doi.org/10.1016/j.jhydrol.2022.128916
26. Assessment of BMPs by Estimating Hydrologic and Water Quality Outputs Using SWAT in Yazoo River Watershed V. Venishetty & P. Parajuli https://doi.org/10.3390/agriculture12040477
27. Winter rye as a cover crop reduces nitrate loss to subsurface drainage as simulated by HERMES R. Malone et al. https://doi.org/10.1016/j.agwat.2017.01.016
28. Different utilisation of residual N from oil radish cover crop by maize or sugar beet, and subsequent winter wheat I. Kühling et al. https://doi.org/10.1016/j.eja.2025.127700
29. Modelling Nitrate Reduction Strategies from Diffuse Sources in the Po River Basin A. Malagó et al. https://doi.org/10.3390/w11051030
30. Modeling sediment diagenesis processes on riverbed to better quantify aquatic carbon fluxes and stocks in a small watershed of the Mid-Atlantic region J. Qi et al. https://doi.org/10.1186/s13021-020-00148-1
31. Breeding progress reduces carbon footprints of wheat and rye L. Riedesel et al. https://doi.org/10.1016/j.jclepro.2022.134326
32. Implications of biofuel-induced changes in land use and crop management on sustainability of agriculture in the Texas High Plains Y. Chen et al. https://doi.org/10.1016/j.biombioe.2018.01.012
33. Cover crops control nitrogen and phosphorus transport from two agricultural watersheds at multiple measurement scales S. Speir et al. https://doi.org/10.1016/j.agee.2021.107765
34. Impacts of winter cover crops on carbon dynamics across terrestrial-aquatic systems under future climate using SWAT-C in an agricultural watershed of the Mid-Atlantic region, USA Y. LEE et al. https://doi.org/10.1016/j.pedsph.2026.07.003
35. Performance of process-based models for simulation of grain N in crop rotations across Europe X. Yin et al. https://doi.org/10.1016/j.agsy.2017.03.005
36. Assessing the suitability of the Soil Vulnerability Index (SVI) on identifying croplands vulnerable to nitrogen loss using the SWAT model S. Lee et al. https://doi.org/10.1016/j.catena.2018.04.021
37. Modeling the impact of winter cover crop on tile drainage and nitrate loss using DSSAT model R. Gupta et al. https://doi.org/10.1016/j.agwat.2022.107862
38. Optimization of conservation practice implementation strategies in the context of stream health M. Herman et al. https://doi.org/10.1016/j.ecoleng.2015.07.011
39. Estimating the effect of winter cover crops on nitrogen leaching using cost-share enrollment data, satellite remote sensing, and Soil and Water Assessment Tool (SWAT) modeling W. Hively et al. https://doi.org/10.2489/jswc.75.3.362
40. Uncertainty assessment of multi-parameter, multi-GCM, and multi-RCP simulations for streamflow and non-floodplain wetland (NFW) water storage S. Lee et al. https://doi.org/10.1016/j.jhydrol.2021.126564
41. Dynamic quantitative trait loci (QTL) for plant height predict biomass yield in hybrid rye (Secale cereale L.) T. Miedaner et al. https://doi.org/10.1016/j.biombioe.2018.04.001
42. Winter cover crops effect on soil moisture and soybean growth and yield under different tillage systems B. Acharya et al. https://doi.org/10.1016/j.still.2019.104430
43. Comparative efficiency of the SWAT model and a deep learning model in estimating nitrate loads at the Tuckahoe creek watershed, Maryland J. Lee et al. https://doi.org/10.1016/j.scitotenv.2024.176256
44. A mechanistic framework for integrated simulation of cereal rye growth, residue decomposition, and soil impacts across a cover crop-residue mulch sequence Z. Wang et al. https://doi.org/10.1016/j.eja.2026.128246
45. Impacts of Global Circulation Model (GCM) bias and WXGEN on Modeling Hydrologic Variables S. Lee et al. https://doi.org/10.3390/w10060764
46. Assessing the Effectiveness of Winter Cover Crops for Controlling Agricultural Nutrient Losses E. Getahun & L. Keefer https://doi.org/10.1111/1752-1688.13058
47. Evaluation of Spatio-Temporal Evapotranspiration Using Satellite-Based Approach and Lysimeter in the Agriculture Dominated Catchment U. Kumar et al. https://doi.org/10.1007/s12524-021-01367-w
48. Quantifying regional effects of best management practices on nutrient losses from agricultural lands V. Roland et al. https://doi.org/10.2489/jswc.2022.00162
49. Evaluation of long-term impact of cereal rye as a winter cover crop in Illinois R. Gupta et al. https://doi.org/10.1016/j.scitotenv.2023.162956
50. Employing Cover Crops and No-Till in Southern Great Plains Cotton Production to Manage Runoff Water Quantity and Quality J. Edwards et al. https://doi.org/10.3390/w17152283
51. Modeling lateral carbon fluxes for agroecosystems in the Mid-Atlantic region: Control factors and importance for carbon budget X. Luo et al. https://doi.org/10.1016/j.scitotenv.2023.169128
52. Flood Risk Reduction from Agricultural Best Management Practices F. Antolini et al. https://doi.org/10.1111/1752-1688.12812
53. Biomass Production with Conservation Practices for Two Iowa Watersheds M. Ha et al. https://doi.org/10.1111/1752-1688.12880
54. Groundwater pollution simulation: A systematic review and bibliometric analysis from 1990 to 2024 S. Xiang et al. https://doi.org/10.1007/s10668-025-06374-2
55. Modeling soil temperature in a temperate region: A comparison between empirical and physically based methods in SWAT J. Qi et al. https://doi.org/10.1016/j.ecoleng.2019.01.017
56. Cover crop termination options and application of remote sensing for evaluating termination efficiency V. Kumar et al. https://doi.org/10.1371/journal.pone.0284529
57. Use of multiple modules and Bayesian Model Averaging to assess structural uncertainty of catchment-scale wetland modeling in a Coastal Plain landscape S. Lee et al. https://doi.org/10.1016/j.jhydrol.2020.124544
58. Coupling terrestrial and aquatic thermal processes for improving stream temperature modeling at the watershed scale J. Qi et al. https://doi.org/10.1016/j.jhydrol.2021.126983
59. Modeling nitrogen fluxes in a tile-drained cropping system in the Midwest using an enhanced SWAT model M. Shahid et al. https://doi.org/10.1016/j.agwat.2026.110225
60. Improving the catchment scale wetland modeling using remotely sensed data S. Lee et al. https://doi.org/10.1016/j.envsoft.2017.11.001
61. Models for predicting nitrate leaching and assessing cover crop mitigation: A systematic review V. Daimonakos et al. https://doi.org/10.1016/j.jenvman.2026.130004