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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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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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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DOI: https://doi.org/10.1007/s00704-020-03438-3