Search

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. [ABSTRACT FROM AUTHOR]

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]

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]

Purpose: The purpose of this paper is to propose an enhanced conceptual model for the integrated public service (IPS) functionality of the European interoperability framework (EIF). The enhanced model incorporates co-creation within the three stages of the IPS cycle. While co-creation can provide innovative routes to overcome interoperability challenges, how co-creation can be a part of the EIF has not been tackled before (Casiano Flores, et al., 2021). Design/methodology/approach: A preferred Reporting Items for systematic reviews and meta-analyses scoping literature review was used to develop the model and identify decisive aspects of co-creation, service users and service providers. Next, a purposive snowball sampling of grey literature comprising primarily of official documentation produced by the European Union was then undertaken to further inform the central argument. Finally, the subsequent validation of the model and derived conclusions was undertaken both internally and externally by peers and experts. Findings: Relationships between key sets of actors during co-creation are bi-directional. Furthermore, different sets of actors are, in turn, service providers and service users depending on the service provided and the stage in the public service cycle under consideration. Understanding these bi-directional interrelationships can help improve public services provided by governmental actors through collaboration with users. Originality/value: Most public service delivery models see relationships between key stakeholders as unidirectional and one-dimensional. By contrast, this study proposes a shift in paradigm where IPS users are not passive actors and mere consumers of services but instead are key stakeholders actively participating in IPS provision. [ABSTRACT FROM AUTHOR]

Mobile government enhances public sector activities by using mobile technologies, such as handheld devices, smartphones, and laptops that promise anytime, anywhere services. Mobile government solutions are successful if many users adopt them. For this reason, the determinant factors of adoption are extremely important. Despite many studies conducted by various researchers in the field of mobile government adoption, most have focused on technology or e-government adoption models as their basis. To fill this gap, the paper collects possible driving factors, grouped into key factors, for mobile government adoption. The systematic literature review, which included 54 journal articles, led to the identification of 12 key factors affecting mobile government adoption, comprising 87 components. Some of these replicate previously identified factors in technology and e-government adoption models, yet the literature presented us with new specifics in mobile and government, such as the benefits that mobility brings and the influence of trust on adoption. [ABSTRACT FROM AUTHOR]