In an increasing hydro-climatic risk context as a result of climate change, this work aims to identify future hydro-hazard hot-spots as a result of climate change across Great Britain. First, flood and drought hazards were defined and selected in a consistent and parallel approach with a threshold method. Then, a nation-wide systematic and robust statistical framework was developed to quantify changes in frequency, magnitude, and duration, and assess time of year for both droughts and floods, and the uncertainty associated with climate model projections. This approach was applied to a spatially coherent statistical database of daily river flows (Future Flows Hydrology) across Great Britain to assess changes between the baseline (1961–1990) and the 2080s (2069–2098). The results showed that hydro-hazard hot-spots are likely to develop along the western coast of England and Wales and across north-eastern Scotland, mainly during the winter (floods) and autumn (droughts) seasons, with a higher increase in drought hazard in terms of magnitude and duration. These results suggest a need for adapting water management policies in light of climate change impact, not only on the magnitude, but also on the timing of hydro-hazard events, and future policy should account for both extremes together, alongside their potential future evolution.

Floods are the most common and widely distributed natural risk, causing over £1 billion of damage per year in the UK as a result of recent events. Climatic projections predict an increase in flood risk; it becomes urgent to assess climate change impact on extreme flows, and evaluate uncertainties related to these projections. This paper aims to assess the changes in extreme runoff for the 1:100 year return period across Great Britain as a result of climate change using the Future Flows Hydrology database. The Generalised Extreme Value (GEV) and Generalised Pareto (GP) models are automatically fitted for 11‐member ensemble flow series available for the baseline and the 2080s. The analysis evaluates the uncertainty related to the Extreme Value (EV) and climate model parameters. Results suggest that GP and GEV give similar runoff estimates and uncertainties. From the baseline to the 2080s, increasing estimate and uncertainties is evident in east England. With the GEV the uncertainty attributed to the climate model parameters is greater than for the GP (around 60% and 40% of the total uncertainty, respectively). This shows that when fitting both EV models, the uncertainty related to their parameters has to be accounted for to assess extreme runoffs.

Climate change will define new living and environmental conditions in many areas in the world, deeply affecting our societies. Public outreach on the impacts of climate change on societies and ecosystems is difficult, yet crucial for fostering mitigation and adaptation strategies. To quantify the climate change and communicate about it in easily-understandable terms, we used the climate classification system of Köppen–Geiger. 84 climate projections bias corrected with two methods were used to calculate Köppen–Geiger climate types at an 8-km resolution for 30-year periods from 1976 to 2099 in France. Moderate changes in climate types are expected in 2035 for approximately 20% of France, regardless of the emission scenario. However, major changes are expected after 2040 under RCP 8.5 for 86% of France, with a massive expansion of the temperate, hot summer with or without dry season, as well as the expansion of temperate climate in mountainous regions. We found that these changes could reach an average transition speed of 7 km·yr ^-1 northwards. These rapid changes will have unprecedented consequences on agriculture, biodiversity, water and energy management, not to mention on societies. Similar changes can be expected in other European countries that share the diverse climatic and topographical conditions found in France.

Floods are a significant issue worldwide with over 1 billion people living in areas of potential flood risk. With climate change these risks are anticipated to increase, but there is great uncertainty associated with future projections, which poses challenges to those making decisions on flood management. Climate change projections which explicitly capture climate model parameters uncertainty are available in the United Kingdom; however, their use by practitioners, rather than researchers, has so far been limited. This paper takes an inclusive approach, working with end users, to answer practitioner relevant questions regarding future climate change influence for flood hazards. The method developed demonstrates the findings across Scotland, United Kingdom and investigates (i) the regional impacts to extreme flows and the associated uncertainty, (ii) the changes in extreme peak flows in terms of frequency, and (iii) the physical and hydroclimatic factors controlling these results. The method used industry standard statistical methods, driven by practitioner requirements, and explicitly includes the statistical uncertainty in the climate and extreme value distribution models in extreme flow estimates. Results are analyzed using hierarchical clustering and decision tree analysis, and the subsequent trends are shown to be constrained by different hydrological, climatic, and physical catchment characteristics. Results suggest that there is a high probability that low return period peak flow events would exceed the baseline extreme high return period event by the 2080s, which has significant implications for future‐proofing infrastructure design. This study provides a practical example and outputs resulting from collaboration between research and industry practices.