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Population growth and rising economic prosperity combined with alterations of hydroclimatic conditions are expected to pose major challenges for water management policies, particularly in fast-developing economies. Growing energy and food demands will likely trigger major investments in large dam projects, whose performance strongly depends on unknown future conditions in the coming decades. In contrast to traditional impact assessments that focus on climate and socio-economic divers separately, in this work we propose an integrated framework to better understand the nested interdependencies of those drivers across sectors and processes at different scales. We integrate an ensemble of climate projections generated from Representative Concentration Pathways with a large factorial dataset of socio-economic scenarios derived from the Socio-Economic Pathways evaluated using the Global Change Assessment Model (GCAM). As a demonstration, we study the Zambezi River, one of the largest river basins in Africa and a paradigmatic of most basins in developing countries. The four largest dams are mainly operated for hydropower production and irrigation supply, with considerable negative effects on the aquatic ecosystems due to the alteration of the natural flow regime.To assess the robustness of the water-energy-food nexus in the Zambezi River basin against future integrated scenarios of changing socio-economic and climate drivers, we first downscaled climate projections to feed local hydrological models and produce projections of water availability in the basin. In parallel, we spatially and temporally downscaled GCAM outputs via the Tethys software to obtain projections of irrigation demands. Numerical results show that the current management of the system is highly vulnerable to changing conditions, with critical risks of failure in terms of food security due to unreliable irrigation supply. Our framework demonstrates that these critical conditions are mostly generated by global socio-economic drivers, namely the alternative regimes of land-use change taxation, rather than predicted changes in water availability due to climate change. [ABSTRACT FROM AUTHOR]

Between 1980 and 2015, Europe experienced 18% of worldwide weather-related loss events, which accounted for over US$500 billion in damage. Early action triggered by timely information on possible emerging impact has the potential to reduce these losses, playing a substantial role on social and economic development. The importance of the early action systems has been recognized by the seventh global target of the Sendai Framework for disaster risk reduction that urges for the development of impact-informed early warning systems.Despite great advancements in flood forecasting technologies, it remains challenging to produce useful impact-based forecast information in a way to trigger early actions that mitigate risks. Overcoming the challenges to act based on the forecast requires an understanding of the existing forecast tools, and a deeper comprehension of the dynamics between hydrometeorological hazards and impacts. Previous studies have shown spatial and temporal relationships between large-scale climate oscillation and flood risk, flood occurrence and flood losses in Europe. However, little is understood about the skill of these oscillations in forecasting flood losses. Using a database of flood losses (NatCatSERVICE of Munich Re), we examined the skill of large-scale climate oscillation - the El Niño Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the East Atlantic/West Russian pattern (EA/WR) and the East Atlantic Pattern (EA) and the Scandinavian Pattern (SCA) - in forecasting seasonal and sub-regional Flood Losses in Europe. Using multiple linear regression models to analyse relationships between the indices of climate variability and Flood Losses, we found that at the Pan-European level and sub-regional scales, flood losses are linked to the interaction with all five indices of climate oscillation. The largest effect is found in spring between SCA and NAO, in which large-scale Pan-European flood losses are expected to be 26 times more costly (approximately 2500 million euro) than average when the SCA positive interacts with the negative phase of the NAO. At sub-regional scale, the largest effect is found in winter in Eastern Europe between EAWR and NAO, in which large-scale flood losses of approximately 3600 million euro (292 times higher than average) are expected when the SCA positive interacts with the negative phase of the NAO. Since large-scale indices of climate variability can be predicted with longer lead times than weather variables, sub-regional impact-based forecast could be developed for regions where a significant relationship is found between large-scale indices of climate variability and flood losses. [ABSTRACT FROM AUTHOR]

With more than 3500 hydropower dams currently being planned or built around the world, the need for optimal dam planning is more compelling than ever. Current literature efforts are directed towards strategic sizing and siting of dams to maximize economic return and minimize environmental impacts in regime conditions. However, also the initial transient phase of reservoir filling may have substantial environmental and economic implications and, especially in large projects, it can be responsible for critical sectoral conflicts associated to dam development. In this phase, precaution towards downstream impacts requires transiting high percentages of inflow, resulting in multi-years, even decadal, filling transients. Conversely, upstream interests (e.g., hydropower production) favor fast impoundment of water, albeit generating critical periods of minimal streamflow downstream. In this process, hydroclimatic variability plays a key role: if the filling occurs during a dry spell, augmented impacts must be endured by upstream and downstream sectors. The state of global climate teleconnections represents a valuable source of predictability of local hydrometeorological anomalies, which can provide a dual support to dam planning. First, in scheduling a favorable time to start the filling operations based on local effects of long-term climatic oscillations, and second, in designing effective filling strategies adaptive to medium-term hydroclimatic variability. In this work, we consider the case study of the Omo-Turkana basin (Ethiopia-Kenya) to demonstrate the use of seasonal drought forecasts based on multiple climate teleconnections for modulating reservoir filling operations according to the predicted drought conditions, e.g. by transiting higher fractions of the inflow when a drought is forecasted. This case study is in this respect exemplary, because the impacts due to the construction and filling of Gibe III dam and to the current construction of Koysha dam, raised the strong opposition of local communities and international organizations. We run a retrospective analysis of Gibe III filling and compare the impacts of the historical filling strategy to designed alternative strategies, demonstrating the potential to significantly decrease downstream impacts, for instance by successfully maintaining the level of downstream Lake Turkana up to one meter higher than historically observed. Our approach also shows that 2015 was an unfavorable year to begin the filling operations of Gibe III, and significant damage could be avoided by delaying or anticipating the operations by 2-3 years. Finally, we predict that the planned time to start filling the Koysha dam, 2021, occurs at the beginning of a multi-year drought and we issue recommendations on more favorable timings. [ABSTRACT FROM AUTHOR]