Unravelling user requirements for climate services to support water allocation decisions in a drought prone region in Spain

The development of climate services to address water-related challenges is rapidly progressing. Users’ engagement and adequate interaction between climate service providers and climate service consumers are recognized factors favouring climate services uptake among and the tracking and evaluation of their socio-economic benefits. Under the framework of the H2020 CLINT project, this research presents a preliminary analysis of user requirements in the Douro River Basin (Spain) to develop a climate service prototype, enhanced with artificial intelligence (AI), and intended to assist in the water allocation process; thereby improving drought adaptation. Participatory modelling is applied to explore the full decision-making process among competing needs, namely the allocation of water resources to environmental flows and irrigation. The research focuses on how different actors use historical and forecast hydrometeorological information to inform drought early warning and water use planning (e.g. user-inspired drought indicators), understanding how uncertainty influences decisions, the role of other types of information in the decision-making process, and the differing perceptions of droughts and drought impacts. These assessments of local user knowledge and the need for enhancements are key inputs to further develop and evaluate AI-enhanced climate service in the following stages of the CLINT project.