Application of artificial intelligence models for the prediction of standardized precipitation evapotranspiration index (SPEI) at Langat River Basin, Malaysia
| Autor: | K. F. Fung, Y. W. Soh, Chai Hoon Koo, Yuk Feng Huang |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
geography
geography.geographical_feature_category Index (economics) Coefficient of determination 010504 meteorology & atmospheric sciences Mean squared error Scale (ratio) 0208 environmental biotechnology Drainage basin Forestry 02 engineering and technology Horticulture 01 natural sciences 020801 environmental engineering Computer Science Applications Evapotranspiration Statistics Environmental science Precipitation Agronomy and Crop Science Nash–Sutcliffe model efficiency coefficient 0105 earth and related environmental sciences |
| Zdroj: | Computers and Electronics in Agriculture. 144:164-173 |
| ISSN: | 0168-1699 |
| Popis: | Drought forecasting is a vital for mitigating the impact of drought events on the economy, tourism, agriculture and water resource systems. This paper adopts the proposed Wavelet-ARIMA-ANN (WAANN) model and the latest Wavelet-Adaptive Neuro-Fuzzy Inference System (WANFIS) model to predict the Standardized Precipitation Evapotranspiration Index (SPEI) at the Langat River Basin for different time scales (1-month, 3-months and 6-months). Model input data pre-processing with wavelet decomposition for improving the performance of the models was carried out apriori. The historical SPEI from 1976 to 2007 were used in the WAANN and WANFIS models for predicting the SPEI for the test period from 2008 to 2015. The Adjusted Coefficient of Determination (R2adj), Root-Mean-Square-Error (RMSE), Mean Absolute Error (MAE), Willmott's Index of Agreement (d) and the Nash-Sutcliffe Coefficient of Efficiency (E) were used to assess the models. It was found that the prediction accuracy of the two models improved with time scale length. For the prediction of SPEI-1 (1-month), the errors associated with both models were considered relatively high. Based on the performance measures and graphical plots, the WAANN model is better for the prediction of SPEI-3 and SPEI-6. The WANFIS model had satisfactory prediction of the mid-term drought forecasting for all stations. The WAANN model developed in this study however, gives better accuracy for both, the short-term and mid-term drought forecasting. |
| Databáze: | OpenAIRE |
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