--- title: Sectoral Climate Impact Indicators layout: layouts/skeleton.mustache breadcrumb: - title: Home path: / - title: sectoral climate impact indicators path: /Sectoral-Climate-Impact-Indicators --- {{#markdown}} ![Haweswater Reservoir in Cumbria - 1995 vs 2010 © Jay Murphy](haweswater-reservoir-compare.png "Haweswater Reservoir in Cumbria - 1995 vs 2010 © Jay Murphy") Image: Haweswater Reservoir in Cumbria, UK - 1995 vs 2010. Source: Jay Murphy ## What are Sectoral Climate Impact Indicators and what do they mean? Sectoral Climate Impact Indicators (SCIIs) are hydro-meteorological metrics that represent some key features useful for the water sector. In EDgE, they mainly summarise the state of the river, for example droughts or flood magnitude. While they are linked to the climate, they need to be calculated by hydrological models because there is often a delay between rainfall events and river flow. **Further info:** EDgE is working with stakeholders to identify which SCIIs are the most useful to make decisions, and prioritise those for delivery within the project. Their inclusion also depends on the ability of our modelling chain to be able to calculate them accurately. For example, water temperature is an important variable for some sectors like energy production or environmental protection, but is not currently included in our models and so will not be provided in this phase of the project. In addition to SCIIs, EDgE is also providing climate-related time series that are useful for more technical analyses to be done, for example the Potential Evapotranspiration which is used to calculate irrigation needs or to drive hydrological models. ## How are the Sectoral Impact Indicators calculated? Within the EDgE domain, three state-of-the-art hydrologic/land-surface models have been set-up: mHM, NOAH-MP, and VIC, at a spatial resolution of 5 km. All these models use a common set of meteorological forcings (i.e the weather information) and land surface characteristics (i.e the type of soil, geology and vegetation) to parameterise the model components. The outputs of these models are then used to generate Sectoral Climate Impact Indicators (SCIIs) and other climate-related variables at time scales ranging from daily to monthly to seasonal and longer time scales. {{/markdown}}