Socio-Economic Assessment of Value for Climate Services Case Study, Uganda and Kenya

Abstract

The study re-affirmed that the economy of IGAD region as very vulnerable to climate change. The vulnerability of population to climate change is exacerbated by the structural issues that reinforces poverty, inequality and deprivation in the society, making the poor most impacted. Climate variability, ranging from unpredictable, intense and at times extreme weather events such as droughts, floods and landslides, are on the rise, and a likely trend for years ahead, threatening ecosystems and livelihoods at alarming rates. The region is experiencing increasing frequency and intensity of droughts and floods, putting the livelihoods of many at risks and also testing the legitimacy of national governments as custodian of social services for their citizens. Repeated failed weather inform of prolonged droughts are becoming a regional new normal, a trend that is worrying for poverty alleviation efforts of achieving the national social economic transformation such as ongoing 2030 Sustainable Development Agenda, working towards African Union (AU) agenda 2063, and could reverse the past gains across member states in elimination of hunger and poverty.Kenya and Uganda targeted in this assessment, lose annually on average of US$56.96 million and US$ 113.86 million respectively to natural disasters related damages resulting from droughts, mudslides, and floods among others. In the coming century (2100), Kenya is projected to lose about 7.2% of its GDP (US$ 18.8 billion), while Uganda 6.3% of GDP (US$ 9.5 billions) annually to climate disasters. However, the provision of climate services inform of early warning and decision advisory in production system would significantly reduce the levels of these losses across all sectors. For examples:Economically, improvements of climate services has been linked to: 1) Agricultural sector (avoidance of crop losses from unsuitable weather; timing of crop protection, planning and harvesting; increased farm production and scales; more efficient scheduling of the use of agricultural machinery, minimization of drought relief costs. In air transport (aviation), reduced fuel consumption through route planning, improved scheduling of flight arrival and departures; minimization of airline costs from aircraft diversions; minimization of search and rescue costs; reduction of accidents and emission; saving in passenger times, materials and working times (airport maintenance).In marine transport (reduction of accidents and environmental damages, fuel savings, more efficient rescue operations). In oil prospecting (avoidance of unnecessary shutdown of offshore oil and gas operations; more efficient planning of energy production and diversity). In energy sector (Prediction of power demands, power failure reduction, savings in material and working times (maintenance), energy savings). In construction sector (potential to eliminate serious construction problems a priori (risk control system). In flood/humanitarian protection (savings in human lives and property, more efficient rescue operations.Socially: prot...