NI: Enhancing global hydrological models with local knowledge

The assessment of water resources at both the global and regional scales is currently a major concern for scientists and policy makers due to the increasing incidence of water scarcity and extreme water-related hazards affecting the globe in the last 50 years. This concern will become even more relevant should future climate projections for the XXI Century become a reality in the coming years. The hydrological modelling community is aware that there is a need to look at the large-scale fluxes of water but also to consider the use of water at smaller scales. However, much of the work done until this moment on this regard has focused on achieving hyper-resolution of models, while the ability of these new modelling approaches to provide relevant and reliable information to catchment water management has received relatively less attention. This project initiates a collaboration between the large-scale modelling and the catchment modelling communities, aiming to fill a gap whose existence is often recognised but sparsely studied. The overall research objective of this project is to explore and design an approach for integrating Catchment Water Management Models (CWMM) with Large-Scale Hydrological Models (LHM), and to assess its potential and limitations to enhance the quality of information LHMs provide at a regional scale. This project will deliver an integrated programme of knowledge exchange - on selected the CWMM and LHM, AQUATOOL and CWatM respectively, and their capabilities - and research - developing a proof-of-concept to couple both models in the heavily managed, data-rich Ebro River Basin (Spain), in collaboration with three leading institutions on global and regional hydrological modelling. The main project output will be a proof-of-concept of an advanced CWatM model for the Ebro River basin that efficiently couples water management and other human interactions with the hydrological system. The new version of CWatM will allow for a better evaluation of human impacts on water availability, overcoming the current limitations LHMs to faithfully represent regional hydrology. This will translate into substantial progress not only for the hydrological science community, but for the climate and earth system science communities. The outcomes of this project will be the onset of further collaborative research to produce a generalised version of the proof-of-concept which will be applicable to understand and address pressing regional water issues, such as transboundary conflicts, which are traditionally hampered by data securitisation. The generalised version can also serve as a benchmark for the benefits of modelling-based water resources assessment and management in developing countries with low water governance, which may encourage investments in capacity building and data collation to conduct their own analyses, which this partnership can support.