Journal Article
An Uncertainty Approach to Assessment of Climate Change Impacts on the Zambezi River Basin

Many residents of the Zambezi River Valley are dependent on water-related resources. Greenhouse gas (GHG) emissions may cause a significant change to the climate in the Zambezi Basin in the future, but there is much uncertainty about the future climate state. This situation leaves policy makers at a state of urgency to prepare for these changes as well as reduce the impacts of the changes through GHG mitigation strategies. First and foremost, we must better understand the economic sectors most likely impacted and the magnitude of those impacts, given the inherent uncertainty. In this study, we present a suite of models that assess the effects of climate change on water resources for four countries in the Zambezi basin: Malawi, Mozambique, Zambia, and Zimbabwe. We use information from a large ensemble (6800) of climate scenarios for two GHG emission policies which represent a distribution of impacts on water-related sectors, considering emissions uncertainty, climate sensitivity uncertainty, and regional climate uncertainty. Two GHG mitigation scenarios are used to understand the effect of global emissions reduction on the River Basin system out to 2050. Under both climate polices, the majority of the basin will likely be drier, except for a portion in the north around Malawi and northern Zambia. Three Key Performance Indicators are used—flood occurrence, unmet irrigation demand, and hydropower generation—to understand the impact channels of climate change effects on the four countries. We find that floods are likely to be worse in Mozambique, irrigation demands are likely to be unmet in Mozambique and Zimbabwe, and hydropower generation is likely to be reduced in Zambia. We also find that the range of possible impacts is much larger under an unconstrained GHG emissions case than under a strict mitigation strategy, suggesting that GHG mitigation would reduce uncertainties about the future climate state, reducing the risks of extreme changes as compared to the unconstrained emissions case.

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