Advancing Climate-Resilient Infrastructure Design in Alabama: A Comparative Assessment of GMLE and L-Moments for IDF Curves using CMIP6
Abstract
Climate change has intensified extreme precipitation patterns, raising questions about the accuracy of traditional methods for constructing Intensity-Duration-Frequency (IDF) curves. However, the performance of Generalized Extreme Value parameter estimation methods across diverse climate zones remains underexplored, particularly for the southeastern United States. The study aims to assess the accuracy of L-moments and Generalized Maximum Likelihood Estimation (GMLE) for estimating the 24-hour precipitation component in IDF curves. This study provides a multi-station, multi-GCM comparison of L-moments and GMLE specifically for Alabama, addressing a gap in region-specific evaluations. The analysis was conducted using the historical simulations from ten Global Climate Models (GCMs), which were downscaled using the Local Constructed Analogs (LOCA) method. The daily precipitation data were extracted from the simulations and used to construct the Partial Duration Series (PDS) of extreme daily rainfall events. The analysis was carried out across fifteen stations across Alabama, and the results were compared with the NOAA Atlas 14 24-hour estimates. Results reveal significant spatial variability: TaiESM1 and GFDL-ESM4 models demonstrated the highest accuracy (mean MAE = 4.24 and 7.67, respectively). The L-moments method outperformed GMLE at 10 of 15 stations, especially for skewed data, with the lowest error at Paint Rock (MAE = 2.09). Conversely, GMLE performed better at stations with normally distributed data but produced greater inter-model dispersion. At Tuscaloosa, some GCM estimates for the 500-year return period reached 58 inches, over four times the NOAA reference (14 inches). The findings have direct practical implications. Employing L-moments with TaiESM1 and GFDL-ESM4 models for inland Alabama provides more reliable estimates for long-return periods critical for major infrastructure design. While coastal stations warrant more cautious approaches due to higher uncertainties (e.g., Dauphin Island, MAE = 26.20). They also support region-specific model selection for non-stationary IDF curves and inform infrastructure design under changing climate conditions.
Publication Title
Earth Systems and Environment
Recommended Citation
Opare, K., Nazari, R., Nikoo, M., Karimi, M., Museru, M., & Heidarian, P. (2026). Advancing Climate-Resilient Infrastructure Design in Alabama: A Comparative Assessment of GMLE and L-Moments for IDF Curves using CMIP6. Earth Systems and Environment, 10 (8), 10915-10933. https://doi.org/10.1007/s41748-026-01200-9
