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751 |
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 14: 3367-3390. 24 S.
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752 |
Machine-learning-constrained projection of bivariate hydrological drought magnitudes and socioeconomic risks over China
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 14: 3305-3326. 22 S.
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753 |
To what extent do flood-inducing storm events change future flood hazards?
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 14: 3161-3190. 30 S.
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754 |
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 13: 3051-3077. 27 S.
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755 |
Quantifying cascading uncertainty in compound flood modeling with linked process-based and machine learning models
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 11: 2531-2553. 23 S.
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756 |
Metamorphic testing of machine learning and conceptual hydrologic models
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 11: 2505-2529. 25 S.
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757 |
Towards understanding the influence of seasons on low-groundwater periods based on explainable machine learning
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 9: 2167-2178. 12 S.
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758 |
Disentangling coastal groundwater level dynamics in a global dataset
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 5: 1215-1249. 35 S.
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759 |
Toward interpretable LSTM-based modeling of hydrological systems
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 4: 945-971. 27 S.
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760 |
A comprehensive study of deep learning for soil moisture prediction
Enthalten in Hydrology and earth system sciences Bd. 28, 2024, Nr. 4: 917-943. 27 S.
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