Rima et al. (2026) Kriging of Generalised Extreme Value Distribution Parameters for Regional Flood Frequency Analysis in New South Wales

Identification

• Journal: Lecture notes in civil engineering
• Year: 2026
• Date: 2026-01-01
• Authors: Laura Rima, Khaled Haddad, Ataur Rahman
• DOI: 10.1007/978-3-032-18708-6_9

Research Groups

School of Engineering, Western Sydney University, Sydney, New South Wales, Australia

Short Summary

This study introduces a novel regional flood frequency analysis (RFFA) approach combining kriging with a parameter regression technique (PRT) and the Generalised Extreme Value (GEV) distribution, demonstrating its feasibility and effectiveness in predicting flood quantiles in New South Wales with median relative errors between 35% and 43%.

Objective

• To develop and validate a new regional flood frequency analysis (RFFA) approach that integrates kriging with a parameter regression technique (PRT) framework, utilizing the Generalised Extreme Value (GEV) distribution, for predicting flood quantiles in New South Wales.

Study Configuration

• Spatial Scale: 88 gauged catchments in New South Wales (NSW), Australia.
• Temporal Scale: Flood quantiles across six annual exceedance probabilities (AEPs): 50%, 20%, 10%, 5%, 2%, and 1%.

Methodology and Data

• Models used: Kriging, Parameter Regression Technique (PRT), Generalised Extreme Value (GEV) distribution. A leave-one-out validation technique was employed for model assessment.
• Data sources: Data from 88 gauged catchments in New South Wales.

Main Results

• The integration of the Generalised Extreme Value (GEV) distribution with geostatistical methods (kriging-PRT) into Regional Flood Frequency Analysis (RFFA) is feasible and effective.
• The kriging-PRT method yielded absolute median relative error (median REr %) values ranging from 35% to 43% across the different annual exceedance probabilities.
• These findings are consistent with other RFFA studies, confirming the reliability of kriging-based approaches in RFFA.

Contributions

• Presents a novel RFFA approach by combining kriging with a parameter regression technique (PRT) framework and the Generalised Extreme Value (GEV) distribution.
• Demonstrates the feasibility and effectiveness of this integrated geostatistical and distributional approach for regional flood frequency analysis.
• Provides validation of kriging-based approaches for RFFA in the context of New South Wales, Australia.

Funding

• Not explicitly mentioned in the provided paper text.

Citation

@article{Rima2026Kriging,
  author = {Rima, Laura and Haddad, Khaled and Rahman, Ataur},
  title = {Kriging of Generalised Extreme Value Distribution Parameters for Regional Flood Frequency Analysis in New South Wales},
  journal = {Lecture notes in civil engineering},
  year = {2026},
  doi = {10.1007/978-3-032-18708-6_9},
  url = {https://doi.org/10.1007/978-3-032-18708-6_9}
}