Assessing the occurrence of annual maximum daily discharge for five of the longest rivers in Africa

Abstract

Widespread flooding in Africa has devastating repercussions on communities, and sometimes leading to loss of life, displacement of populations, and significant damage to infrastructure and agriculture. Despite this, there are limited studies that investigate the behaviour of high time frequency river flows for the major river systems of Africa to inform adaptation and mitigation strategies for improved resilience of society. This paper fills this gap by assessing the occurrence time of annual maximum daily discharge for five of the longest rivers of Africa using a statistical modelling approach. This is the first of such a study covering all of the five longest rivers of Africa in one paper. Annual maximum daily discharge time for each river was modeled by mixtures of von Mises distributions, fitted by a Markov chain Monte Carlo algorithm. Data on mean daily discharge was obtained from the Global Runoff Data Centre database for the Niger, Zambezi, Okavango, Limpopo and Orange rivers in Africa. Estimates were inferred for the location parameter of the major mode, location parameter of the minor mode, concentration parameter of the major mode, concentration parameter of the minor mode, mean time, mean resultant, circular variance, circular skewness, and circular kurtosis. The developed models reveal distinctive temporal patterns of peak discharge events in each river, which can have significant implications for flood management, water resource planning, hydrological modeling, risk assessment and infrastructure design.