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ai4er-cdt / flood_risk_shipston

The purpose of this project is to investigate whether we can establish the effectiveness of natural flood management (NFM) interventions undertaken in the British town of Shipston-on-Stour during 2017 to 2020 from publicly available meteorological data and private data from the river gauge in Shipston.
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Predictions vs Observations analysis notebook #27

Closed herbiebradley closed 3 years ago

herbiebradley commented 4 years ago

Notebook to analyse whether NFM interventions are effective. CSV file is in #flood_data channel.

herbiebradley commented 3 years ago

Just sticking this here since it's a convenient place:

Results for Shipston-only models

Model Validation NSE (2010-2016)
Tuned Vanilla LSTM** 0.8175
Vanilla 1D Conv model 0.4309
WaveNet 0.6975
FilterNet 0.5978
Autoregressive* WaveNet 0.3359
Autoregressive* FilterNet 0.602
Autoregressive* LSTM 0.6925

*Autoregressive here refers to including the previous 365 days of discharge data as an additional feature. **Hyperparameters: 10 layers, 100 hidden units, dropout probability of 0.2, 200 epochs of training.

Temperature and precipitation were the baseline features used in all models. The training set consisted of the data from 1986-2010, and validation set was 2010-2016.