Abstract
Abstract. Heavy rainfall in eastern Africa between late 2019 and mid 2020 caused devastating floods and landslides throughout the region. These rains drove the levels of Lake Victoria to a record-breaking maximum in the second half of May 2020. The combination of high lake levels, consequent shoreline flooding, and flooding of tributary rivers caused hundreds of casualties and damage to housing, agriculture, and infrastructure in the riparian countries of Uganda, Kenya, and Tanzania. Media and government reports linked the heavy precipitation and floods to anthropogenic climate change, but a formal scientific attribution study has not been carried out so far. In this study, we characterize the spatial extent and impacts of the floods in the Lake Victoria basin and then investigate to what extent human-induced climate change influenced the probability and magnitude of the record-breaking lake levels and associated flooding by applying a multi-model extreme event attribution methodology. Using remote-sensing-based flood mapping tools, we find that more than 29 000 people living within a 50 km radius of the lake shorelines were affected by floods between April and July 2020. Precipitation in the basin was the highest recorded in at least 3 decades, causing lake levels to rise by 1.21 m between late 2019 and mid 2020. The flood, defined as a 6-month rise in lake levels as extreme as that observed in the lead-up to May 2020, is estimated to be a 63-year event in the current climate. Based on observations and climate model simulations, the best estimate is that the event has become more likely by a factor of 1.8 in the current climate compared to a pre-industrial climate and that in the absence of anthropogenic climate change an event with the same return period would have led lake levels to rise by 7 cm less than observed. Nonetheless, uncertainties in the attribution statement are relatively large due to large natural variability and include the possibility of no observed attributable change in the probability of the event (probability ratio, 95 % confidence interval 0.8–15.8) or in the magnitude of lake level rise during an event with the same return period (magnitude change, 95 % confidence interval 0–14 cm). In addition to anthropogenic climate change, other possible drivers of the floods and their impacts include human land and water management, the exposure and vulnerability of settlements and economic activities located in flood-prone areas, and modes of climate variability that modulate seasonal precipitation. The attribution statement could be strengthened by using a larger number of climate model simulations, as well as by quantitatively accounting for non-meteorological drivers of the flood and potential unforced modes of climate variability. By disentangling the role of anthropogenic climate change and natural variability in the high-impact 2020 floods in the Lake Victoria basin, this paper contributes to a better understanding of changing hydrometeorological extremes in eastern Africa and the African Great Lakes region.
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