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Heavy rainfall in East 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 characterise 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 thousand 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 three 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 East Africa and the African Great Lakes region. [ABSTRACT FROM AUTHOR]

On September 28,2018, a 7.5 magnitude earthquake struck the island of Sulawesi, Indonesia. The epicentre was the provincial capital of Palu, located on a bay on the island’s northwest coast. The quake triggered a tsunami that swept 10-meter tall waves of seawater and swamped the city. The combination of the earthquake, tsunami, soil liquefaction and landslides claimed well over 2000 lives, destroyed homes, buildings, infrastructures and farmland in several districts. Recognizing the need to relocate settlements from the liquefaction-prone areas, the Indonesian government developed the Master Plan for Recovery and Reconstruction for Central Sulawesi through the EARR and SWIP projects. Indra and Planetek Italia contributed to the implementation of this plan with a batch of EO-based services. The main information provided was related to terrain deformation mapping (before the earthquake)followed by the update of terrain information mapping (in the months immediately after the earthquake)and reconstruction monitoring with Very High Resolution images. The collaboration went on with a capacity-building workshop and aknowledge transfer activity held in Jakarta in June 2019 regarding the technical aspects of the delivered products and training sessions for local users to teach them to use the Geohazards Exploitation Platform (GEP) of ESA. [ABSTRACT FROM AUTHOR]

The analysis of remote sensing data to assess geohazards is being improved by web-based platforms and collaborative projects, such as the Geohazard Exploitation Platform (GEP) of the European Space Agency (ESA). This paper presents the evaluation of a surface velocity map that is generated by this platform. The map was produced through an unsupervised Multi-temporal InSAR (MTI) analysis applying the Parallel-SBAS (P-SBAS) algorithm to 25 ENVISAT satellite images from the South of Spain that were acquired between 2003 and 2008. This analysis was carried out using a service implemented in the GEP called "SBAS InSAR". Thanks to the map that was generated by the SBAS InSAR service, we identified processes not documented so far; provided new monitoring data in places affected by known ground instabilities; defined the area affected by these instabilities; and, studied a case where GEP could have been able to help in the forecast of a slope movement reactivation. This amply demonstrates the reliability and usefulness of the GEP, and shows how web-based platforms may enhance the capacity to identify, monitor, and assess hazards that are associated to geological processes. [ABSTRACT FROM AUTHOR]