Can geomorphic flood descriptors coupled with machine learning models enhance in quantifying flood risks over data-scarce catchments? Development of a hybrid framework for Ganga basin (India)
Quantifying flood risks through a cascade of hydraulic-cum-hydrodynamic modelling is data-intensive and computationally demanding- a major constraint for economically struggling and data-scarce low and middle-income nations. Under such circumstances, geomorphic flood descriptors (GFDs), that encompa...
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| Veröffentlicht in: | Environmental science and pollution research international 2024-05 |
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| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
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