EconPapers    
Economics at your fingertips  
 

Multi-steps drought forecasting in arid and humid climate environments: Development of integrative machine learning model

Masoud Karbasi, Mehdi Jamei, Anurag Malik, Ozgur Kisi and Zaher Mundher Yaseen

Agricultural Water Management, 2023, vol. 281, issue C

Abstract: In the current study, the Standardized Precipitation Evaporation Index (SPEI) was forecasted using a combination of the empirical wavelet transform (EWT), discrete wavelet transforms (DWT), extended Kalman filter (EKF), two models of multilayer perceptrons (MLP), and group method of data handling (GMDH) neural networks. Two synoptic stations of Tabriz (semi-arid climate) and Rasht (humid climate) covering data period (1987–2019) were selected for forecasting. 70% of the data was used for model training and 30% for validation. Three forecasting horizons (1, 3, and 6 months ahead SPEI) were investigated. Autocorrelation function and partial autocorrelation function were used to determine the optimal inputs to the models. The outcomes of the present study showed that in both stations, the combination of machine learning models with two types of wavelet transforms (EWT and DWT) compared to the standalone models improved the performance of the forecasting (correlation coefficient, R = 0.9980, root mean square error, RMSE = 0.0483 for Tabriz Station and R = 0.9988, RMSE = 0.0521 for Rasht Station). A comparison of the EWT and DWT wavelets showed that the EWT had better performance in all forecasting intervals. By raising the forecasting interval from one month to six months, EWT performance was more evident than DWT performance. In 6-month forecasting horizon, the DWT had almost no effect on model performance improvement. In both stations, the combination of the EWT and MLP-EKF model had the best performance in forecasting SPEI drought index.

Keywords: Drought forecasting; Empirical wavelet transform; Extended Kalman filter; Neural Networks; SPEI drought index (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378377423000756
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:agiwat:v:281:y:2023:i:c:s0378377423000756

DOI: 10.1016/j.agwat.2023.108210

Access Statistics for this article

Agricultural Water Management is currently edited by B.E. Clothier, W. Dierickx, J. Oster and D. Wichelns

More articles in Agricultural Water Management from Elsevier
Bibliographic data for series maintained by Catherine Liu ().

 
Page updated 2025-03-19
Handle: RePEc:eee:agiwat:v:281:y:2023:i:c:s0378377423000756