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Created: | Jun 15, 2022 at 10:36 a.m. | |
Last updated: | Jan 04, 2023 at 11:27 a.m. (Metadata update) | |
Published date: | Jun 22, 2022 at 5:56 a.m. | |
DOI: | 10.4211/hs.8a5d36ac9386418da0fb1c990a797102 | |
Citation: | See how to cite this resource |
Sharing Status: | Published |
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Abstract
Use this Colaboratory workbook (implements an RNN) to assess the simulations of hydrological models. The latest version of this workbook can be found at:
https://drive.google.com/file/d/1vdV01gI5vf_DP2NVMMHtYmhIDhZMvUOe/view?usp=share_link
Along with the workbook, an example data file (data.zip) is also provided. This data file contains three case studies. Set the variable values according to the following for each one of the three case studies of the data.zip.
# LRHM applied to Bakas
DATASTARTROW= 2581
INP= [ 7,13,16,18 ]
TRG= 1
PDT= 0.70
SEQLEN=10
# LRHM applied to Alagonia
DATASTARTROW= 3690
INP= [ 7,13,14,20 ]
TRG= 2
PDT= 0.70
SEQLEN=10
# LRHM applied to Karveliotis
DATASTARTROW= 2553
INP= [ 7,13,14,22 ]
TRG=3
PDT= 0.70
SEQLEN=10
For more information, see [1].
1. E. Rozos, P. Dimitriadis, and V. Bellos, Machine Learning in Assessing the Performance of Hydrological Models, Hydrology, doi:10.3390/hydrology9010005 , 9(1), 5, 2021.
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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