Cargando…
Super ensemble based streamflow simulation using multi-source remote sensing and ground gauged rainfall data fusion
Traditional data-driven streamflow predictions usually apply a single model with inconsistent performance in different variability conditions. These days model ensembles or merging the benefits of different models without losing the general character of the data are becoming a trend in hydrology. Th...
Autores principales: | Wegayehu, Eyob Betru, Muluneh, Fiseha Behulu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10336834/ https://www.ncbi.nlm.nih.gov/pubmed/37449175 http://dx.doi.org/10.1016/j.heliyon.2023.e17982 |
Ejemplares similares
-
Multivariate Streamflow Simulation Using Hybrid Deep Learning Models
por: Wegayehu, Eyob Betru, et al.
Publicado: (2021) -
Addressing rainfall data selection uncertainty using connections between rainfall and streamflow
por: Levy, Morgan C., et al.
Publicado: (2017) -
Streamflow Prediction in Highly Regulated, Transboundary Watersheds Using Multi‐Basin Modeling and Remote Sensing Imagery
por: Du, Tien L. T., et al.
Publicado: (2022) -
Ensemble streamflow forecasting based on variational mode decomposition and long short term memory
por: Sun, Xiaomei, et al.
Publicado: (2022) -
The Application of SWAT Model and Remotely Sensed Products to Characterize the Dynamic of Streamflow and Snow in a Mountainous Watershed in the High Atlas
por: Taia, Soufiane, et al.
Publicado: (2023)