9 citations as recorded by crossref.

1. Uncertainty Quantification of Estimated Ultimate Recovery Prediction in Shale Reservoirs Using Quantile Random Forest with Prediction Interval Calibration S. Ki et al.
2. Integrated Quantile Mapping and Spatial Clustering for Robust Bias Correction of Satellite Precipitation in Data-Sparse Regions G. Al-Rawas et al.
3. Advancing Hydrology through Machine Learning: Insights, Challenges, and Future Directions Using the CAMELS, Caravan, GRDC, CHIRPS, PERSIANN, NLDAS, GLDAS, and GRACE Datasets F. Hasan et al.
4. A hybrid method coupling physical process-driven model with generative deep learning for probabilistic flood forecasting X. Yang et al.
5. Enhancing probabilistic hydrological predictions with mixture density Networks: Accounting for heteroscedasticity and Non-Gaussianity D. Li et al.
6. Development of an integrated global sensitivity analysis strategy for evaluating process sensitivities across single- and multi-models J. Yang et al.
7. Use of regional sensitivity analysis for diagnosing parsimony of models: A water model case study R. Srikanthan et al.
8. Improve streamflow simulations by combining machine learning pre-processing and post-processing Y. Zhang et al.
9. Improving PM2.5 simulations using LSTM: a study on spatiotemporal generalization X. Chen et al.