A novel approach for predicting the standardised precipitation index considering climatic factors
Drought modelling is essential to managing water resources in arid regions to limit its impacts. Additionally, climate change has a significant effect on the frequency and intensity of drought. This research provides a novel approach to forecasting the standardised precipitation index (SPI 3), consi...
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| Format: | Article |
| Language: | English |
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Wasit University
2022-12-01
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| Series: | Wasit Journal of Engineering Sciences |
| Subjects: | |
| Online Access: | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/382 |
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| author | Mustafa A. Alawsi Salah L. Zubaidi Laith B. Al-badranee |
| author_facet | Mustafa A. Alawsi Salah L. Zubaidi Laith B. Al-badranee |
| author_sort | Mustafa A. Alawsi |
| collection | DOAJ |
| description | Drought modelling is essential to managing water resources in arid regions to limit its impacts. Additionally, climate change has a significant effect on the frequency and intensity of drought. This research provides a novel approach to forecasting the standardised precipitation index (SPI 3), considering several climatic variables by employing hybrid methods including (i.e., data pre-processing represented by normalisation, cleaning (i.e., outliers and Singular Spectrum Analysis), and best model input (i.e., tolerance technique), in addition to, artificial neural network (ANN) combined with particle swarm optimisation (PSO)). The data on climatic factors were applied to build and evaluate the SPI 3 model from 1990 to 2020 for the Al-Kut region. The result revealed that data pre-processing techniques enhance the data quality by increasing the correlation coefficient between independent and dependent variables; and choosing the optimal input model scenario. Also, it was found that the PSO algorithm precisely predicts the parameters of the proposed model. Moreover, the finding confirmed that the supposed methodology precisely simulated the SPI 3 depending on several statistical criteria (i.e., R², RMSE, MAE).
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| format | Article |
| id | doaj-art-e4b1969cf9034d6baafcb2401cdca7f7 |
| institution | Kabale University |
| issn | 2305-6932 2663-1970 |
| language | English |
| publishDate | 2022-12-01 |
| publisher | Wasit University |
| record_format | Article |
| series | Wasit Journal of Engineering Sciences |
| spelling | doaj-art-e4b1969cf9034d6baafcb2401cdca7f72025-08-20T03:45:39ZengWasit UniversityWasit Journal of Engineering Sciences2305-69322663-19702022-12-0110310.31185/ejuow.Vol10.Iss3.382A novel approach for predicting the standardised precipitation index considering climatic factors Mustafa A. Alawsi0Salah L. Zubaidi 1Laith B. Al-badranee 2Wasit University - Engineering CollegeDepartment of Civil Engineering, Wasit UniversityDepartment of Civil Engineering, Wasit UniversityDrought modelling is essential to managing water resources in arid regions to limit its impacts. Additionally, climate change has a significant effect on the frequency and intensity of drought. This research provides a novel approach to forecasting the standardised precipitation index (SPI 3), considering several climatic variables by employing hybrid methods including (i.e., data pre-processing represented by normalisation, cleaning (i.e., outliers and Singular Spectrum Analysis), and best model input (i.e., tolerance technique), in addition to, artificial neural network (ANN) combined with particle swarm optimisation (PSO)). The data on climatic factors were applied to build and evaluate the SPI 3 model from 1990 to 2020 for the Al-Kut region. The result revealed that data pre-processing techniques enhance the data quality by increasing the correlation coefficient between independent and dependent variables; and choosing the optimal input model scenario. Also, it was found that the PSO algorithm precisely predicts the parameters of the proposed model. Moreover, the finding confirmed that the supposed methodology precisely simulated the SPI 3 depending on several statistical criteria (i.e., R², RMSE, MAE). https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/382DroughtSPIANNSSAPSOIraq |
| spellingShingle | Mustafa A. Alawsi Salah L. Zubaidi Laith B. Al-badranee A novel approach for predicting the standardised precipitation index considering climatic factors Wasit Journal of Engineering Sciences Drought SPI ANN SSA PSO Iraq |
| title | A novel approach for predicting the standardised precipitation index considering climatic factors |
| title_full | A novel approach for predicting the standardised precipitation index considering climatic factors |
| title_fullStr | A novel approach for predicting the standardised precipitation index considering climatic factors |
| title_full_unstemmed | A novel approach for predicting the standardised precipitation index considering climatic factors |
| title_short | A novel approach for predicting the standardised precipitation index considering climatic factors |
| title_sort | novel approach for predicting the standardised precipitation index considering climatic factors |
| topic | Drought SPI ANN SSA PSO Iraq |
| url | https://ejuow.uowasit.edu.iq/index.php/ejuow/article/view/382 |
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