STARS4Water aims at improving the understanding of climate-change impacts on water resources availability, and the vulnerabilities for ecosystems, society and economic sectors at river basin scale, providing actionable information to stakeholders. Among the project activities is to define a set of indicators for assessing climate risks and impacts on integrated water resources system.

Within the context of STARS4Water, an indicator is defined as a quantitative measure of a condition in a river basin that is monitored in terms of trends and variability. The complexity of the hydrologic system and its interactions with the meteorological, ecological and socio-economic environment, spanning multiple spatial and temporal scales, make it difficult for river basin managers and stakeholders to assess changes in the system and the effectiveness of countermeasures. Indicators help to manage this complexity by summarizing the behavior of the system. Indicators have therefore become common practice in policy making for climate change adaptation.

To define a coherent set of indicators that will help to monitor, evaluate and assess developments in water resources availability and impacts of climate change, the STARS4Water proposes a three-tiered approach:

• The first tier is a set of indicators that are directly derived from publicly available datasets, e.g. the Copernicus Climate Data Store. Global datasets are projected onto the catchment area of the river basin and the number of future scenarios is reduced. This addresses the need for practical information about expected changes in each of the river basins that was expressed by the stakeholders in many of the river basins, while keeping the technical challenges limited. Because these indicators are directly derived from global datasets, they will, in general, not be as accurate as regional model results. Still, these global indicator projections can give an indication of the relative changes that can be expected in the next decades if no regional model is available. In cases where regional models are available, they can be used as a reference or benchmark.

STARS4Water Tier-1 indicators

• The second tier is aimed at combining the global data sets from tier-1 with auxiliary local data from various sources to yield indicators that are more directly related to water resources management. For example, we can combine potential evaporation and precipitation to calculate evaporation deficit, which is a common indicator for agricultural drought. While the calculation methods for these indicators are initially sketched out in this report, the technical feasibility needs to be evaluated in most cases. The tier-2 indicators also depend on the availability and accuracy of the local data. They are technically more demanding and require more time to develop and validate. Although the tier-2 indicators will be more specific and meet more user needs, they will still be (partly) based on global datasets. The suggested list of tier-2 indicators includes: Precipitation deficit, Agricultural water demand, Industrial and consumer water demand, Low flow occurrence and duration, High flow occurrence and duration, Maximum Snow Water Equivalent.

• To address more specific user needs, we therefore define a third tier of indicators, for which numerical models and machine learning techniques are employed to precisely capture the behavior of the hydrological system in a river basin under current and future conditions. The output in terms of e.g. river flows, reservoir storage or water supply and demand can be used to derive further indicators. The model-derived indicators are the most specific to the river basin hubs and require considerable effort to develop, in close collaboration with the stakeholders.

More information can be found in the following STARS4Water project Deliverable:
Beckers, J. et al (2023): Defining indicators for assessing climate risks. Horizon Europe project STARS4Water. Deliverable D2.1.