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Validate dpLGAR using Streamflow #8
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Testing my mass balance with a different threshold: This is with
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This is a threshold of
It looks like the SE threshold is sensitive, this is something to note between versions of LGAR |
For context, this is the mass balance I want to benchmark against with LGAR-C:
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See PR #10 for why our mass balance is now different |
Setting Also, I changed the runoff calculation to this: ponded_depth = ponded_depth_temp
_runoff_ = ponded_depth - infiltration
runoff = torch.clamp(_runoff_, min=0.0) so there is always a runoff grad |
Debugging the updating soil parameters:
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Parameter updates work:
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See PR #11 For more information on parameter updates and training |
First run with the new data:
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There is a small discrepency when using hourly intervals vs 15 min intervals:
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See #15 |
training the model using torchrun: torchrun --nproc_per_node=1 --master_port=47800 dpLGAR/__main__.py ++nproc=1 ++save_name=debug_inplace |
Updates from work today:
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We have to do the following to tune parameters
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