Mehr et al. (2026) Meteorological drought modeling using recurrent neural network and long short-term memory

Identification

• Journal: Elsevier eBooks
• Year: 2026
• Date: 2026-01-01
• Authors: Ali Danandeh Mehr, Hiba Alkubaisi, Rifat Tur
• DOI: 10.1016/b978-0-443-34205-9.00020-2

Research Groups

• Civil Engineering Department, Antalya Bilim University, Antalya, Türkiye
• Electrical and Computer Engineering Program, Institute of Postgraduate Education, Antalya Bilim University, Antalya, Türkiye
• Civil Engineering Department, Akdeniz University, Antalya, Türkiye

Short Summary

This study focuses on modeling meteorological droughts using advanced machine learning techniques, specifically Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks, to enhance drought monitoring and prediction capabilities.

Objective

• To develop and apply Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) models for the effective modeling and forecasting of meteorological droughts.

Study Configuration

• Spatial Scale: Not specified in the provided excerpt.
• Temporal Scale: Time series analysis for drought dynamics, specific resolution (e.g., daily, monthly) not detailed.

Methodology and Data

• Models used: Recurrent Neural Networks (RNNs), Long Short-Term Memory (LSTM).
• Data sources: Meteorological data, specifically precipitation (rainfall or snowfall). Specific data sources (e.g., satellite, observation, reanalysis) are not detailed in the excerpt.

Main Results

• The provided text is an introductory chapter and does not contain the main results of the study.

Contributions

• The application of advanced deep learning models, specifically Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM) networks, for meteorological drought modeling and prediction, contributing to improved water management and socioeconomic stability.

Funding

• Not specified in the provided excerpt.

Citation

@article{Mehr2026Meteorological,
  author = {Mehr, Ali Danandeh and Alkubaisi, Hiba and Tur, Rifat},
  title = {Meteorological drought modeling using recurrent neural network and long short-term memory},
  journal = {Elsevier eBooks},
  year = {2026},
  doi = {10.1016/b978-0-443-34205-9.00020-2},
  url = {https://doi.org/10.1016/b978-0-443-34205-9.00020-2}
}