11 citations as recorded by crossref.

1. Beyond Deterministic Forecasts: A Scoping Review of Probabilistic Uncertainty Quantification in Short-to-Seasonal Hydrological Prediction D. De León Pérez et al. https://doi.org/10.3390/w17202932
2. Propagation and future projection of dry-wet abrupt alternation through the hydrological cycle using a GCM-VIC modeling framework S. Liu et al. https://doi.org/10.1016/j.ejrh.2026.103631
3. Improving Flood Control Optimal Operation of River-Type Cascade Reservoirs through Coupling with 1D Hydrodynamic Model L. Yao et al. https://doi.org/10.1007/s11269-025-04116-7
4. Probabilistic Prediction of Concrete Compressive Strength Using Copula Functions: A Novel Framework for Uncertainty Quantification C. Zhang et al. https://doi.org/10.3390/buildings16040754
5. Demonstrating almost half of cotton fiber quality variation is attributed to climate change using a hybrid machine learning-enabled approach X. Li et al. https://doi.org/10.1016/j.eja.2024.127426
6. Evolution of Data-Driven Flood Forecasting: Trends, Technologies, and Gaps—A Systematic Mapping Study B. Kuhaneswaran et al. https://doi.org/10.3390/w17152281
7. Coupled dominant factors analysis, dual attention deep learning, and uncertainty quantification for long-term pan evaporation ensemble prediction in the Wuding River Basin, China Z. Cui et al. https://doi.org/10.1016/j.ejrh.2026.103323
8. Calibration of Ensemble Forecasts for Extreme Rainfall Using Bayesian Model Averaging: A Comparative Review of Gaussian and Gamma Distributions D. Faidah et al. https://doi.org/10.3390/su18126121
9. Integration of deterministic initialization, real-time updating and probabilistic postprocessing in hydrological forecasting for enhancing flood risk reduction H. Zhang et al. https://doi.org/10.1016/j.jhydrol.2025.134725
10. Risk analysis of real-time reservoir scheduling decisions based on probabilistic inflow process forecasting Z. Cui et al. https://doi.org/10.1016/j.eswa.2025.130836
11. Coupling Machine Learning and Physically Based Hydrological Models for Reservoir-Based Streamflow Forecasting B. Jia & W. Fang https://doi.org/10.3390/rs17132314