14 citations as recorded by crossref.

1. Setting expectations for hydrologic model performance with an ensemble of simple benchmarks W. Knoben https://doi.org/10.1002/hyp.15288
2. Development of a model-agnostic isotope tracer simulator T. Holmes et al. https://doi.org/10.1080/02626667.2025.2556917
3. Advancing objective functions in hydrological modelling: Integrating knowable moments for improved simulation accuracy A. Pizarro & J. Jorquera https://doi.org/10.1016/j.jhydrol.2024.131071
4. Unlocking the potential of stochastic simulation through Bluecat: Enhancing runoff predictions in arid and high‐altitude regions J. Jorquera & A. Pizarro https://doi.org/10.1002/hyp.15046
5. Selecting a conceptual hydrological model using Bayes' factors computed with replica-exchange Hamiltonian Monte Carlo and thermodynamic integration D. Mingo et al. https://doi.org/10.5194/gmd-18-1709-2025
6. Evaluating the parameter sensitivity and impact of hydrologic modeling decisions on flood simulations A. Alexander et al. https://doi.org/10.1016/j.advwatres.2023.104560
7. On the importance of discharge observation uncertainty when interpreting hydrological model performance J. Aerts et al. https://doi.org/10.5194/hess-28-5011-2024
8. Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis (CAMELS-SPAT): streamflow observations, forcing data and geospatial data for hydrologic studies across North America W. Knoben et al. https://doi.org/10.5194/hess-29-5791-2025
9. A flexible, differentiable framework for neural-enhanced hydrological modeling: Design, implementation, and applications with HydroModels.jl X. Jing et al. https://doi.org/10.1016/j.envsoft.2025.106802
10. Multi-station Joint Runoff Forecasting Using Graph Neural Network Coupled with Spatial Connectivity of Hydrological Stations Q. Wang & S. Zhu https://doi.org/10.1007/s11004-024-10167-0
11. Combining uncertainty quantification and entropy-inspired concepts into a single objective function for rainfall-runoff model calibration A. Pizarro et al. https://doi.org/10.5194/hess-29-4913-2025
12. GHydroMod-SIM-DAI v1.0: A new distributed hydrological model capable of dynamically recognizing runoff generation mechanisms and accounting for aboveground and underground anthropogenic impacts Y. Wang et al. https://doi.org/10.1016/j.jhydrol.2025.134184
13. Multivariate calibration can increase simulated discharge uncertainty and model equifinality S. Pool et al. https://doi.org/10.5194/hess-30-2797-2026
14. Symptoms of Performance Degradation During Multi‐Annual Drought: A Large‐Sample, Multi‐Model Study L. Trotter et al. https://doi.org/10.1029/2021WR031845