Accurate flood quantile estimation at ungauged sites is essential in water resource planning and flood risk management. Regional Flood Frequency Analysis (RFFA) based on the L-moment framework offers a robust and computationally efficient approach for estimating flood quantiles, particularly in data-scarce or ungauged catchments. Recent studies highlight the advantages of LH moments (i.e. higher-order probability-weighted moments), which provide enhanced sensitivity to distributional tails and improve the representation of extreme flood events. This paper assesses the influence of Koppen-Geiger climatic zones (i.e. arid, temperate, and tropical) on design flood estimation for ungauged rivers of peninsular India. The Conventional Index Flood method is compared with a recently proposed RFFA approach tailored for general peak discharge distribution datasets within the LH-moment framework, treating climatic zones as homogeneous regions. Results indicate higher heterogeneity in the arid zone, while the tropical zone is relatively homogeneous. Regional goodness-of-fit tests identify the GEV and GLO distributions as suitable regional distributions for the arid region, whereas the GLO distribution is more appropriate for the tropical region. The findings support improved flood risk assessment and infrastructure design and contribute to the development of more reliable, climate-sensitive flood management strategies.