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Seasonal rainfall hindcasting using ensemble multi-stage genetic programming

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Abstract

Rainfall hindcasting is one of the most challenging tasks in the hydrometeorological forecasting community. The current ad hoc data-driven approaches appear to be insufficient for forecasting rainfall. The task becomes more difficult, when the forecasts are over a long period of time. To increase the accuracy of seasonal rainfall hindcasting, this paper introduces an ensemble evolutionary model that integrates two genetic programming techniques: gene expression programming (GEP) and multi-stage genetic programming (MSGP). To demonstrate the development and validation procedures of the new model, the rainfall data from the Antalya meteorology station was used. The model performance was evaluated in terms of different statistical measures and compared with that of the state-of-the-art gradient boosted decision tree (GBT) model developed as a reference model in this study. The performance results during testing showed that the proposed ensemble model has increased the seasonal forecasting accuracy of the GEP and MSGP models up to 30%. The GBT was found comparable to the proposed model during training period; however, it drastically underestimated extreme wet seasons during testing.

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Abbreviations

ACF:

Autocorrelation function

ANN:

Artificial neural networks

DM:

Data mining

EGEP:

Ensemble gene expression programming

EMSGP:

Evolutionary ensemble multi-stage genetic programing

GBT:

Gradient boosted tree

GEP:

Gene expression programming

GP:

Genetic programing

LEM:

Linear ensemble model

MAPE:

Mean absolute percentage of error

MLR:

Multi-variable linear regression

MSGP:

Multi-stage genetic programming

NSE:

Nash-Sutcliff Efficiency

OAM:

Ordinary arithmetic mean

PACF:

Partial autocorrelation function

RMSE:

Root mean squared error

SR:

Seasonal rainfall

SSA:

Singular spectrum analysis

SVM:

Support vector machine

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Acknowledgements

The author appreciates three anonymous reviewers for their constructive comments and Prof. Habib Sadid for his language editing provided on this manuscript.

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Correspondence to Ali Danandeh Mehr.

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Danandeh Mehr, A. Seasonal rainfall hindcasting using ensemble multi-stage genetic programming. Theor Appl Climatol 143, 461–472 (2021). https://doi.org/10.1007/s00704-020-03438-3

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