دورية أكاديمية
Drought Forecasting Using Integrated Variational Mode Decomposition and Extreme Gradient Boosting
| العنوان: | Drought Forecasting Using Integrated Variational Mode Decomposition and Extreme Gradient Boosting |
|---|---|
| المؤلفون: | Ömer Ekmekcioğlu |
| المصدر: | Water, Vol 15, Iss 19, p 3413 (2023) |
| بيانات النشر: | MDPI AG, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Hydraulic engineering LCC:Water supply for domestic and industrial purposes |
| مصطلحات موضوعية: | drought forecasting, hydrology, machine learning, Mann–Whitney U test, sc-PDSI, semi-arid climate, Hydraulic engineering, TC1-978, Water supply for domestic and industrial purposes, TD201-500 |
| الوصف: | The current study seeks to conduct time series forecasting of droughts by means of the state-of-the-art XGBoost algorithm. To explore the drought variability in one of the semi-arid regions of Turkey, i.e., Denizli, the self-calibrated Palmer Drought Severity Index (sc-PDSI) values were used and projections were made for different horizons, including short-term (1-month: t + 1), mid-term (3-months: t + 3 and 6-months: t + 6), and long-term (12-months: t + 12) periods. The original sc-PDSI time series was subjected to the partial autocorrelation function to identify the input configurations and, accordingly, one- (t − 1) and two-month (t − 2) lags were used to perform the forecast of the targeted outcomes. This research further incorporated the recently introduced variational mode decomposition (VMD) for signal processing into the predictive model to enhance the accuracy. The proposed model was not only benchmarked with the standalone XGBoost but also with the model generated by its hybridization with the discrete wavelet transform (DWT). The overall results revealed that the VMD-XGBoost model outperformed its counterparts in all lead-time forecasts with NSE values of 0.9778, 0.9405, 0.8476, and 0.6681 for t + 1, t + 3, t + 6, and t + 12, respectively. Transparency of the proposed hybrid model was further ensured by the Mann–Whitney U test, highlighting the results as statistically significant. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2073-4441 |
| العلاقة: | https://www.mdpi.com/2073-4441/15/19/3413Test; https://doaj.org/toc/2073-4441Test |
| DOI: | 10.3390/w15193413 |
| الوصول الحر: | https://doaj.org/article/74f503d0b3d64839aa325f1dbbbe6a8bTest |
| رقم الانضمام: | edsdoj.74f503d0b3d64839aa325f1dbbbe6a8b |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 20734441 |
|---|---|
| DOI: | 10.3390/w15193413 |