Yilmaz et al. (2026) Fuzzy Logic-Based Drought Index: A Case Study of Goulburn Basin in Victoria, Australia

Identification

• Journal: Lecture notes in civil engineering
• Year: 2026
• Date: 2026-01-01
• Authors: Abdullah Gokhan Yilmaz, Serter Atabay, Monzur Imteaz, Mhamd Saifaldeen Oyounalsoud, Mohamed Abdallah
• DOI: 10.1007/978-3-032-18708-6_8

Research Groups

• Department of Engineering, La Trobe University, Bendigo, VIC, Australia
• Department of Civil Engineering, American University of Sharjah, Sharjah, United Arab Emirates
• Department of Civil and Construction Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia
• Department of Civil Engineering, Karlsruhe Institute of Technology, Karlsruhe, Germany
• Department of Civil and Environmental Engineering, University of Sharjah, Sharjah, United Arab Emirates

Short Summary

This study investigated the effectiveness of Fuzzy Logic (FL)-based drought indices in the Goulburn Basin, Australia, comparing them against conventional indices like SPI, RAI, and SPEI. The results demonstrated that FL-based indices consistently outperformed conventional methods, with even simpler FL models showing high performance for drought management.

Objective

• To study and compare the capability of Fuzzy Logic (FL)-based drought indices with widely used conventional drought indices (i.e., SPI, RAI, and SPEI) in the Goulburn Basin, Victoria, Australia.

Study Configuration

• Spatial Scale: Goulburn Basin, Victoria, Australia
• Temporal Scale: Not explicitly defined in the abstract, but typically involves historical hydro-climatic data for drought analysis.

Methodology and Data

• Models used: Fuzzy Logic (FL) models, Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), Standardized Precipitation Evapotranspiration Index (SPEI).
• Data sources: Hydro-climatic factors including rainfall, maximum temperature, mean temperature, and potential evapotranspiration (PET). Specific data sources (e.g., observation, reanalysis) are not detailed in the abstract.

Main Results

• Fuzzy Logic (FL)-based drought indices demonstrated superiority over the conventional indices (SPI, RAI, SPEI) in the Goulburn Basin.
• The FL-based index incorporating rainfall, maximum temperature, and PET as inputs exhibited the highest performance.
• A simpler FL index, utilizing only rainfall and mean temperature, performed almost as effectively as more complex FL indices.
• Among the conventional indices studied, the Rainfall Anomaly Index (RAI) was identified as the best-performing.
• The study's findings affirm the capability of the FL model for effective drought management.

Contributions

• Provides empirical evidence for the superior performance of Fuzzy Logic-based drought indices compared to established conventional indices (SPI, RAI, SPEI) in the Goulburn Basin, Australia.
• Highlights the potential for developing effective drought management tools using FL models, including simpler configurations that maintain high performance.
• Contributes to the literature by validating FL as a robust approach for drought monitoring and assessment in a specific regional context.

Funding

• Not specified in the provided paper text.

Citation

@article{Yilmaz2026Fuzzy,
  author = {Yilmaz, Abdullah Gokhan and Atabay, Serter and Imteaz, Monzur and Oyounalsoud, Mhamd Saifaldeen and Abdallah, Mohamed},
  title = {Fuzzy Logic-Based Drought Index: A Case Study of Goulburn Basin in Victoria, Australia},
  journal = {Lecture notes in civil engineering},
  year = {2026},
  doi = {10.1007/978-3-032-18708-6_8},
  url = {https://doi.org/10.1007/978-3-032-18708-6_8}
}