Management scenarios of the Grand Ethiopian Renaissance Dam and their impacts under recent and future climates

Close to the border with Sudan, Ethiopia is currently building the largest hydroelectric power plant in Africa with a storage volume corresponding to approximately 1.5 years of the mean discharges of the Blue Nile. This endeavor is controversially debated in the public and the scientific literature. Contributing to this discussion, by shading some light on climate change issues, an eco-hydrological model, equipped with a reservoir module, was applied to investigate downstream hydrological impacts during filling and regular operation, the latter considering climate change projected by an ensemble of 10 global and regional climate models. Our results show that at the earliest after 20 months, the dam could produce hydroelectric power. Full supply level may be reached after four years or not at all, depending on filling policies and assumptions of seepage rates. Under recent hydro-climatic conditions, the dam may produce 13 TWh −a , which is below the envisaged target of 15.7 TWh −a . The ensemble mean suggests slightly increasing hydropower production in the future. Almost independently of the operation rules, the highly variable discharge regime will be significantly altered to a regime with almost equal flows each month. Achieving a win-win situation for all riparian countries requires a high level of cooperation in managing the Eastern Nile water resources

Multimodel assessment of flood characteristics in four large river basins at global warming of 1.5, 2.0 and 3.0 K above the pre-industrial level

This study assesses the flood characteristics (timing, magnitude and frequency) in the pre-industrial and historical periods, and analyzes climate change impacts on floods at the warming levels of 1.5, 2.0 and 3.0 K above the pre-industrial level in four large river basins as required by the Paris agreement. Three well-established hydrological models (HMs) were forced with bias-corrected outputs from four global climate models (GCMs) for the pre-industrial, historical and future periods until 2100. The long pre-industrial and historical periods were subdivided into multiple 31-year subperiods to investigate the natural variability. The mean flood characteristics in the pre-industrial period were derived from the large ensemble based on all GCMs, HMs and 31-year subperiods, and compared to the ensemble means in the historical and future periods. In general, the variance of simulated flood characteristics is quite large in the pre-industrial and historical periods. Mostly GCMs and HMs contribute to the variance, especially for flood timing and magnitude, while the selection of 31-year subperiods is an important source of variance for flood frequency. The comparison between the ensemble means shows that there are already some changes in flood characteristics between the pre-industrial and historical periods. There is a clear shift towards earlier flooding for the Rhine (1.5 K scenario) and Upper Mississippi (3.0 K scenario). The flood magnitudes show a substantial increase in the Rhine and Upper Yellow only under the 3.0 K scenario. The floods are projected to occur more frequently in the Rhine under the 1.5 and 2.0 K scenarios, and less frequently in the Upper Mississippi under all scenarios

Spatial-Explicit Climate Change Vulnerability Assessments Based on Impact Chains. Findings from a Case Study in Burundi

Climate change vulnerability assessments are an essential instrument to identify regions most vulnerable to adverse impacts of climate change and to determine appropriate adaptation measures. Vulnerability assessments directly support countries in developing adaptation plans and in identifying possible measures to reduce adverse consequences of changing climate conditions. Against this background, this paper describes a vulnerability assessment using an integrated and participatory approach that builds on standardized working steps of previously developed ‘Vulnerability Sourcebook’ guidelines. The backbone of this approach is impact chains as a conceptual model of cause–effect relationships as well as a structured selection of indicators according to the three main components of vulnerability, namely exposure, sensitivity and adaptive capacity. We illustrate our approach by reporting the results of a vulnerability assessment conducted in Burundi focusing on climate change impacts on water and soil resources. Our work covers two analysis scales: a national assessment with the aim to identify climate change ‘hotspot regions’ through vulnerability mapping; and a local assessment aiming at identifying local-specific drivers of vulnerability and appropriate adaptation measures. Referring to this vulnerability assessment in Burundi, we discuss the potentials and constraints of the approach. We stress the need to involve stakeholders in every step of the assessment and to communicate limitations and uncertainties of the applied methods, indicators and maps in order to increase the comprehension of the approach and the acceptance of the results by different stakeholders. The study proved the practical usability of the approach at the national level by the selection of three particularly vulnerable areas. The results at a local scale supported the identification of adaption measures through intensive engagement of local rural populations

Improving the Accuracy of Hydrodynamic Simulations in Data Scarce Environments Using Bayesian Model Averaging: A Case Study of the Inner Niger Delta, Mali, West Africa

In this paper, the study area was the Inner Niger Delta (IND) in Mali, West Africa. The IND is threatened by climate change, increasing irrigation, and dam operations. 2D hydrodynamic modelling was used to simulate water levels, discharge, and inundation extent in the IND. Three different digital elevation models (DEM) (SRTM, MERIT, and a DEM derived from satellite images were used as a source of elevation data. Six different models were created, with different sources of elevation data and different downstream boundary conditions. Given that the performance of the models varies according to the location in the IND, the variable under consideration and the performance criteria, Bayesian Model Averaging (BMA) was used to assess the relative performance of each of the six models. The BMA weights, along with deterministic performance measures, such as the Nash Sutcliffe coefficient (NS) and the Pearson’s correlation coefficient (r), provide quantitative evidence as to which model is the best when simulating a particular hydraulic variable at a particular location. After the models were combined with BMA, both discharge and water levels could be simulated with reasonable precision (NS > 0.8). The results of this work can contribute to the more efficient management of water resources in the IND

Effects of model calibration on hydrological and water resources management simulations under climate change in a semi-arid watershed

Semi-arid regions are known for erratic precipitation patterns with significant effects on the hydrological cycle and water resources availability. High temporal and spatial variation in precipitation causes large variability in runoff over short durations. Due to low soil water storage capacity, base flow is often missing and rivers fall dry for long periods. Because of its climatic characteristics, the semi-arid north-eastern region of Brazil is prone to droughts. To counter these, reservoirs were built to ensure water supply during dry months. This paper describes problems and solutions when calibrating and validating the eco-hydrological model SWIM for semi-arid regions on the example of the Pajeú watershed in north-eastern Brazil. The model was calibrated to river discharge data before the year 1983, with no or little effects of water management, applying a simple and an enhanced approach. Uncertainties result mainly from the meteorological data and observed river discharges. After model calibration water management was included in the simulations. Observed and simulated reservoir volumes and river discharges are compared. The calibrated and validated models were used to simulate the impacts of climate change on hydrological processes and water resources management using data of two representative concentration pathways (RCP) and five earth system models (ESM). The differences in changes in natural and managed mean discharges are negligible ( 5%) under RCP2.6 for the ESM ensemble mean. In semi-arid catchments, the enhanced approach should be preferred, because in addition to discharge, a second variable, here evapotranspiration, is considered for model validation. © 2020, The Author(s)

a comparative experimental and numerical study of baroclinic wave dynamics

The differentially heated rotating annulus is a widely studied tabletop-size laboratory model of the general mid-latitude atmospheric circulation. The two most relevant factors of cyclogenesis, namely rotation and meridional temperature gradient are quite well captured in this simple arrangement. The radial temperature difference in the cylindrical tank and its rotation rate can be set so that the isothermal surfaces in the bulk tilt, leading to the formation of baroclinic waves. The signatures of these waves at the free water surface have been analyzed via infrared thermography in a wide range of rotation rates (keeping the radial temperature difference constant) and under different initial conditions. In parallel to the laboratory experiments, five groups of the MetStröm collaboration have conducted numerical simulations in the same parameter regime using different approaches and solvers, and applying different initial conditions and perturbations. The experimentally and numerically obtained baroclinic wave patterns have been evaluated and compared in terms of their dominant wave modes, spatio-temporal variance properties and drift rates. Thus certain “benchmarks” have been created that can later be used as test cases for atmospheric numerical model validation

Targeting Mental Models of Climate Change Risk to Facilitate Climate Action - Lagos Data Brief

This report summarises the background and topline findings from the Lagos case study of the Targeting Mental models of Climate change risk to facilitate Climate Action (MECCA) project. The research was conducted between 2019 and 2022 with the aim of integrating natural and social science expertise to develop an understanding of the bio-physical risks posed to Lagos by ongoing changes in the climate, how climate change and the associated risks are understood by Lagos residents, and how risk perceptions relate to people’s actions

Low-cost adaptation options to support green growth in agriculture, water resources, and coastal zones

The regional climate as it is now and in the future will put pressure on investments in sub-Saharan Africa in water resource management, fisheries, and other crop and livestock production systems. Changes in oceanic characteristics across the Atlantic Ocean will result in remarkable vulnerability of coastal ecology, littorals, and mangroves in the middle of the twenty-first century and beyond. In line with the countries' objectives of creating a green economy that allows reduced greenhouse gas emissions, improved resource efficiency, and prevention of biodiversity loss, we identify the most pressing needs for adaptation and the best adaptation choices that are also clean and affordable. According to empirical data from the field and customized model simulation designs, the cost of these adaptation measures will likely decrease and benefit sustainable green growth in agriculture, water resource management, and coastal ecosystems, as hydroclimatic hazards such as pluviometric and thermal extremes become more common in West Africa. Most of these adaptation options are local and need to be scaled up and operationalized for sustainable development. Governmental sovereign wealth funds, investments from the private sector, and funding from global climate funds can be used to operationalize these adaptation measures. Effective legislation, knowledge transfer, and pertinent collaborations are necessary for their success

Low-cost adaptation options to support green growth in agriculture, water resources, and coastal zones

The regional climate as it is now and in the future will put pressure on investments in sub-Saharan Africa in water resource management, fisheries, and other crop and livestock production systems. Changes in oceanic characteristics across the Atlantic Ocean will result in remarkable vulnerability of coastal ecology, littorals, and mangroves in the middle of the twenty-first century and beyond. In line with the countries' objectives of creating a green economy that allows reduced greenhouse gas emissions, improved resource efficiency, and prevention of biodiversity loss, we identify the most pressing needs for adaptation and the best adaptation choices that are also clean and affordable. According to empirical data from the field and customized model simulation designs, the cost of these adaptation measures will likely decrease and benefit sustainable green growth in agriculture, water resource management, and coastal ecosystems, as hydroclimatic hazards such as pluviometric and thermal extremes become more common in West Africa. Most of these adaptation options are local and need to be scaled up and operationalized for sustainable development. Governmental sovereign wealth funds, investments from the private sector, and funding from global climate funds can be used to operationalize these adaptation measures. Effective legislation, knowledge transfer, and pertinent collaborations are necessary for their success

The DBOX Corpus Collection of Spoken Human-Human and Human-Machine Dialogues

This paper describes the data collection and annotation carried out within the DBOX project ( Eureka project, number E! 7152). This project aims to develop interactive games based on spoken natural language human-computer dialogues, in 3 European languages: English, German and French. We collect the DBOX data continuously. We first start with human-human Wizard of Oz experiments to collect human-human data in order to model natural human dialogue behaviour, for better understanding of phenomena of human interactions and predicting interlocutors actions, and then replace the human Wizard by an increasingly advanced dialogue system, using evaluation data for system improvement. The designed dialogue system relies on a Question-Answering (QA) approach, but showing truly interactive gaming behaviour, e.g., by providing feedback, managing turns and contact, producing social signals and acts, e.g., encouraging vs. downplaying, polite vs. rude, positive vs. negative attitude towards players or their actions, etc. The DBOX dialogue corpus has required substantial investment. We expect it to have a great impact on the rest of the project. The DBOX project consortium will continue to maintain the corpus and to take an interest in its growth, e.g., expand to other languages. The resulting corpus will be publicly released