Comparing conceptual and super ensemble deep learning models for streamflow simulation in data-scarce catchments

Comparing conceptual and super ensemble deep learning models for streamflow simulation in data-scarce catchments

Study Region: Sore and Masha river catchments in Baro Akobo river basin: Ethiopia. Study Focus: This research addresses the challenges associated with conventional data-driven streamflow modelling, which often exhibits inconsistent performance across different variability states. To bridge this gap,...

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Bibliographic Details
Main Authors: Eyob Betru Wegayehu, Fiseha Behulu Muluneh
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Streamflow simulation
Remote sensing
Super ensemble learning
HBV-light model
Ethiopian River basin
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581824000429

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