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

Abstract

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 lowlying 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.

Historical Rainfall and Evapotranspiration Changes over Mpologoma Catchment in Uganda

“…As a quality control procedure, the infilling of missing records was done using the Inverse Distance Weighted (IDW) interpolation technique developed by Shepard [66] in equation (1). Due to its robustness, the IDW technique has been applied in several studies [67][68][69][70][71]. e missing rainfall depth/intensity R M at station M for a given period was determined using rainfall values R j at the neighbouring stations q of the same period: 1.…”

Scale-Dependent Reliability of Projected Rainfalls over Bangladesh with the PRECIS Model

“…There are 28 observational stations of BMD within the study area of about 147,000 km 2 . Daily rainfall monitored at all 28 gauges of BMD successfully passed the homogeneity test by various literatures [32][33][34][35]. Notably, for all 28 BMD stations Khan et al [34] found almost straight lines with no breakpoint in the double mass curves and Mahmud et al [35] observed homogenous using Standard Normal Homogeneity test, Von Neumann Ratio test, Buishand Range test and Pettitt test.…”

New hourly extreme precipitation regions and regional annual probability estimates for the UK

“…Further, the ROI approach (e.g., FEH) lacks the physical basis in the pooling of gauges that is provided by specifically accounting for the spatial variability of precipitation extremes and its driving variables. Various studies have reported that using a fixed regions approach to estimate extreme precipitation return levels provides more precise results with smaller errors compared to using ROI, and efficiently reduce random and climatologically irrelevant variations in estimating model parameters and high quantiles (Kyselý et al, 2011;Carreau et al, 2012;Das, 2019). Furthermore, Kyselý et al (2011) reported that using the at-site estimation approach to estimate extreme precipitation may be significantly affected by the inclusion of a single (outlying) observation, where the estimates would be uncertain.…”