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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 techniques—inverse distance weighting (IDW) and kriging—are 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. Maps of growth factors (X10 and X100) derived by inverse distance weighting (IDW) and ordinary kriging (OK) approaches. The observed estimate is indicated by circle relative to the maximum value. [ABSTRACT FROM AUTHOR]

This study investigates the applicability of the region-of-influence (ROI) approach of frequency analysis of extreme rainfall in a monsoon-dominated country and to find the most appropriate scheme of the method. Seven different ROI pooling schemes are examined which differ in their similarly distance measure containing a range of different site descriptors (also known as pooling variables). The site descriptors also include average annual monsoon rainfall (AAMR) which is introduced to assess its suitability in this climatic condition. The ROI schemes are evaluated against traditional regional as well as at-site frequency analysis. The performance of the selected scheme in terms of homogeneity and frequency behaviour is also assessed. In order to determine the performance, the study uses annual maximum rainfall data of 1-day duration at 34 stations in Bangladesh, which has a tropical monsoon climate. It is found that the ROI method of any variants is superior to the traditional geographical approach of regional analysis as well as to the at-site analysis. The AAMR based pooling scheme has provided the best result among the considered ROI schemes. The pooling groups delineated based on AAMR has also passed the homogeneity test and conveyed a desirable frequency behaviour. All results indicate that the AAMR as a pooling variable, i.e. information about monsoon rainfall, should be accommodated to the estimation of extreme rainfall in a monsoon-dominated region. [ABSTRACT FROM AUTHOR]