Abstract
Abstract. Estimation of peak flow quantiles in ungauged catchments is a challenge often faced by water professionals in many parts of the world. Approaches to address such problem exist, but widely used techniques such as flood frequency regionalisation is often not subjected to performance evaluation. In this study, the jack-knifing principle is used to assess the performance of the flood frequency regionalisation in the complex and data-scarce River Nile basin by examining the error (regionalisation error) between locally and regionally estimated peak flow quantiles for different return periods (QT). Agglomerative hierarchical clustering based algorithms were used to search for regions with similar hydrological characteristics. Hydrological data employed were from 180 gauged catchments and several physical characteristics in order to regionalise 365 identified catchments. The Generalised Extreme Value (GEV) distribution, selected using L-moment based approach, was used to construct regional growth curves from which peak flow growth factors could be derived and mapped through interpolation. Inside each region, variations in at-site flood frequency distribution were modelled by regression of the mean annual maximum peak flow (MAF) versus catchment area. The results showed that the performance of the regionalisation is heavily dependent on the historical flow record length and the similarity of the hydrological characteristics inside the regions. The flood frequency regionalisation of the River Nile basin can be improved if sufficient flow data of longer record length of at least 40 yr become available.
Highlights
Estimation of the peak flow quantiles is required in many civil and water engineering applications
We used agglomerative hierarchical cluster algorithms to search for homogeneous regions in the complex River Nile basin and regionalised 365 identified catchments into groups of “homogeneous” regions. 180 flow data were used; about 40 % of which have flow record length greater than 30 yr
Several catchment physical characteristics were digitally extracted and used in the clustering process and the regression modelling for estimation of the maximum peak flow (MAF)
Summary
Estimation of the peak flow quantiles (usually referred to as design floods) is required in many civil and water engineering applications. The similarity can be used to estimate (design) peak flows for given return periods at any location in the region. It is obvious that the regional flood frequency estimates improve when that sample is larger and/or more representative of the whole population of site. P. Nyeko-Ogiramoi et al.: An elusive search for regional flood frequency estimates peak flows in the studied region (Chebana and Ouarda, 2009; Lubomır, 2005; Northrop, 2004). There is no consensus on a common objective method for delineating homogeneous regions for the purpose of flood frequency estimation
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