Towards learning universal, regional, and local hydrological behaviors via machine le... | RTCL.TV
Channel: STEM RTCL TV
Date: 2023-06-11

### Keywords ###
#CAMELSdataset #Traditionalmodels #singleLSTM #Regionalrainfallrunoff #hydrologicalsciences #LSTMmodel #rainfallrunoffmodeling #RTCLTV #shorts

### Article Attribution ###
Title: Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets
Authors: F. Kratzert, D. Klotz, G. Shalev, G. Klambauer, S. Hochreiter ,and G. Nearing
Publisher: Copernicus Publications
DOI: 10.5194/hess-23-5089-2019
DOAJ URL: https://doaj.org/article/d4b86c11360f4a4bbd79086d63bb3229
Source URL: https://www.hydrol-earth-syst-sci.net/23/5089/2019/hess-23-5089-2019.pdf



### Image Attribution ###
We used stable diffusion to programmatically generate the background images. Viewer discretion is advised.

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### Video Timestamps ###
0:00:00 - Summary 
0:00:24 - Title 
0:00:29 - End