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Persistence Model, also referred to as Constant Water Level Difference (CWLD)

How does the Persistence Model Predict Water Levels?

This models assumes:

• Water level anomalies build progressively. This is particularly true for bays and estuaries.

• Water level anomaly at the time of forecasts will persist throughout the forecasting period.

In other words, take the difference between the observed water level and harmonic prediction during a past time interval and apply it to forecast over a future time interval.

How is it Different than the ANN?

• Provides a forecast with more moderate differences between observed and predicted for extreme high and low water levels.

• Does not utilize wind observations as a model parameter so is not as optimized as ANN during seasons when wind is responsible for set-up and set-down in bays and estuaries.

• Works well when water level anomaly changes slowly over time.

How is the Persistence Model Applied in this Study?

ANN predictive performance is compared to the persistence model which assumes the water level anomaly at the time of forecast will be constant throughout the forecasting period. ANN predictions tend to have a larger anomaly associated with storm conditions. The persistence model results, when used in conjunction with the ANN predictions, provide a conservative boundary on the range of predictions and associated anomalies that may acually be observed.

The persistence model is considered here as a benchmark but could be used as a simpler yet effective replacement to the harmonic forecasts when the necessary input to the ANN models are not available or when the implementation of ANN models is not possible.

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