The Effects of Climate Change on Rural-Urban Migration in Sub-Saharan Africa (SSA)—The Cases of Democratic Republic of Congo, Kenya and Niger

Abstract

Water is essential for the existence of living organisms including humans. Water is needed in farms to grow crops, firms and manufacturing industry to produce products and services. This chapter examines water resources availability and management in Sub-Saharan Africa (SSA) in climate change perspective using vector auto-regression (VAR) time series analysis. Water is known to be unevenly distributed among countries and continents around the world, particularly in Sub-Sahara Africa; the water availability varies between member countries and regions in the individual country, water supply systems experience enormous pressure to make water accessible to people in both rural and urban communities. Water security remains to be an integral part of the SSA's effort to achieve food security and supply, halve poverty and eradicate hunger. This chapter more importantly aims to investigate impact of rainfall and temperature issues--that are climate change proxy variables--on water security and people movement in three SubSaharan African countries that are Democratic Republic of Congo, Kenya and Niger. This article assesses some possible causes of migration from rural to urban area using VAR and granger causality tests; this process involves four variables namely Rural Migration 'MR', Urban Migration 'MU', Rainfall 'Rain' and Temperature 'Temp'. The model predicts rainfall and temperature across 10 years and examines how these changes impact water availability and people movement in relevant countries. This study finds that some countries are experiencing water security challenges upon which large numbers migrate to urban areas. The study reveals that variations in rainfall and temperature have compounded people movements from rural areas. It is noted that the agricultural production in SSA have not improved over time and in fact, it has further decreased due to the move away from rural areas by many farmers.

Gendered Vulnerability to Climate Change Impacts in Selected Counties in Kenya

“…The outcome was increase in the workload of women who were left with the burden of tending for families without the men who had migrated. In a similar trend, internal migrations have taken place quite to a large extent in the republics of Kiribati and Tuvalu as a result of induced climate change (Hassan and Tularam 2018). Majority of the people especially women in the Kiribati and Tuvalu rely almost entirely on agricultural-related activities.…”

“…Several agencies including the United Nations have called upon organizations and individual countries to have measures in place to address displacement and migration of people (United Nations 2016). However, despite the calls and efforts of the UN, migrations and displacements of people have been on the increase (Hassan and Tularam 2018).…”

“…Poor land use practices have further exacerbated the continent' problem of soil erosion and desertification (Ngugi et al 2015), further compounding population's vulnerability to extreme climate events such as droughts. It is estimated that climate change is partly responsible for the rural-urban migration in the SSA region, as people flee to towns and cities to pursue alternative livelihoods (Barrios et al 2006;Hassan and Tularam 2018).…”

Water-energy-food nexus in the Great Lakes Region of Africa: Current status and prospects

“…The DRC is located in the GLRA in Central Africa bordered with nine other Sub-Saharan Africa (SSA) countries [Hassan and Tularam 2018]. The country enjoys the fame of being the largest in SSA, having a landmass area coverage of 2.34 million km 2 with vast deposits of natural resources for example; oil, diamonds, copper and cobalt [Hassan and Tularam 2018]. The country serves as Africa's greater water catchment tower having large amount of both groundwater and surface water reservoir respectively [ UNEP 2011].…”

Impact of Solar and Wind Prices on the Integrated Global Electricity Spot and Options Markets: A Time Series Analysis

“…The VAR approach imposes a minimum theoretical demand on the utilised model's structure, and it requires only the variables and the largest number of lags to capture most of the variables' inter-effects. A number of examples of this approach can be found in the literature Hassan and Tularam, 2018;Reza et al, 2017;Wong and El Massah, 2018).…”