Extreme rainfall estimation at ungauged sites: Comparison between region-of-influence approach of regional analysis and spatial interpolation technique

Reliable estimation of design extreme rainfall at an ungauged site is regarded to be an important task in engineering hydrology. This study compares two approaches of extreme rainfall estimation at ungauged locations: region-of-influence (ROI) approach of regional estimation and interpolation-based at-site estimation in a low-lying country where the density of rainfall measurements is relatively low. Both approaches incorporate generalized extreme value (GEV) based index-flood estimation procedure in which the growth factor is used as the means of comparison. The geographical proximity based ROI scheme is assessed for its suitability in ungauged cases whereas popular interpolation techniquesinverse distance weighting (IDW) and krigingare examined to find an appropriate model for the same purpose. The estimation of index is required in the index-flood method to get a complete frequency curve at ungauged locations. This study also compares several interpolation approaches in this regard. Annual maximum daily rainfall data at 34 stations located in Bangladesh have been used to assess the performance. The successful evaluation of homogeneity test and the unbounded characteristics of frequency model prove the appropriateness of the ROI scheme in ungauged conditions. The ordinary kriging (OK) is found to be superior to the IDW method in terms of cross-validation error measures. The estimates of index rainfall obtained by OK with or without anisotropy produce very similar results, although a slight improvement is achieved when an anisotropic semi-variogram in east direction is used. Regarding comparison between OK and ROI, both methods show a similar performance, indicating that both can be used for ungauged estimation. The overall results suggest that the spatial information about rainfall is an important factor in terms of formation of governing character of extreme rainfall in a low-lying region like Bangladesh.