21 citations as recorded by crossref.

1. Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales G. Baroni et al. https://doi.org/10.5194/hess-21-2301-2017
2. Understanding the role of hydrologic model structures on evapotranspiration-driven sensitivity D. Jayathilake & T. Smith https://doi.org/10.1080/02626667.2020.1754421
3. Evaluation of Sensible Heat Flux and Evapotranspiration Estimates Using a Surface Layer Scintillometer and a Large Weighing Lysimeter J. Moorhead et al. https://doi.org/10.3390/s17102350
4. Runoff characteristics and its sensitivity to climate factors in the Weihe River Basin from 2006 to 2018 C. Wu et al. https://doi.org/10.1007/s40333-022-0109-6
5. Hydrologic model calibration using remotely sensed soil moisture and discharge measurements: The impact on predictions at gauged and ungauged locations Y. Li et al. https://doi.org/10.1016/j.jhydrol.2018.01.013
6. Identification of Hydrologic Models, Optimized Parameters, and Rainfall Inputs Consistent with In Situ Streamflow and Rainfall and Remotely Sensed Soil Moisture A. Wright et al. https://doi.org/10.1175/JHM-D-17-0240.1
7. Interacting Effects of Precipitation and Potential Evapotranspiration Biases on Hydrological Modeling J. Wang et al. https://doi.org/10.1029/2022WR033323
8. Are temporary stream observations useful for calibrating a lumped hydrological model? M. Scheller et al. https://doi.org/10.1016/j.jhydrol.2024.130686
9. Which Potential Evapotranspiration Formula to Use in Hydrological Modeling World‐Wide? R. Pimentel et al. https://doi.org/10.1029/2022WR033447
10. Evaluation of three gridded potential evapotranspiration datasets for streamflow simulation in three inland river basins in the arid Hexi Corridor, Northwest China C. Wang et al. https://doi.org/10.1016/j.ejrh.2022.101234
11. Informing hydrogeological models with remotely sensed evapotranspiration S. Gelsinari et al. https://doi.org/10.3389/frwa.2022.932641
12. Uncertainty assessment of potential evapotranspiration in arid areas, as estimated by the Penman-Monteith method D. Hua et al. https://doi.org/10.1007/s40333-020-0093-7
13. Comparison between dynamic and static sensitivity analysis approaches for impact assessment of different potential evapotranspiration methods on hydrological models performance R. Nonki et al. https://doi.org/10.1175/JHM-D-20-0192.1
14. Season‐based rainfall–runoff modelling using the probability‐distributed model (PDM) for large basins in southeastern Brazil R. Zhang et al. https://doi.org/10.1002/hyp.13154
15. Evaluation of Potential Evapotranspiration Based on CMADS Reanalysis Dataset over China Y. Tian et al. https://doi.org/10.3390/w10091126
16. The divergence between potential and actual evapotranspiration: An insight from climate, water, and vegetation change Y. Liu et al. https://doi.org/10.1016/j.scitotenv.2021.150648
17. Assessment of multi-source satellite products using hydrological modelling approach A. Mahanta et al. https://doi.org/10.1016/j.pce.2023.103507
18. Hydrological insights: Comparative analysis of gridded potential evapotranspiration products for hydrological simulations and drought assessment M. Abdallah et al. https://doi.org/10.1016/j.ejrh.2024.102113
19. Assessment of the Influences of Different Potential Evapotranspiration Inputs on the Performance of Monthly Hydrological Models under Different Climatic Conditions P. Bai et al. https://doi.org/10.1175/JHM-D-15-0202.1
20. Identifying the Influence of Systematic Errors in Potential Evapotranspiration on Rainfall–Runoff Models D. Jayathilake & T. Smith https://doi.org/10.1061/(ASCE)HE.1943-5584.0002157
21. Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques A. Wright et al. https://doi.org/10.1002/2017WR020442