EGU22-11027
https://doi.org/10.5194/egusphere-egu22-11027
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Enhancing global hydrological models with local knowledge to support Nexus analyses

David Haro Monteagudo1, Andrea Momblanch2, Peter Burek3, Taher Kahil3, Joaquín Andreu4, Javier Paredes-Arquiola4, Abel Solera4, and Santiago Beguería5
David Haro Monteagudo et al.
  • 1Geography and Environment, University of Aberdeen, Aberdeen, UK
  • 2Cranfield Water Science Institute, Cranfield University, Cranfield, UK
  • 3International Institute for Applied Systems Analysis, Laxenburg, Austria
  • 4Instituto de Ingeniería del Agua y Medio Ambiente, Universitat Politècnica de València, Valencia, Spain
  • 5Estación Experimental de Aula Dei, Consejo Superior de Investigaciones Científicas, Zaragoza, Spain

Over recent decades major advances have been made in global hydrological modelling underpinned by progress in high-resolution data availability, as well as in computational and data storage capabilities. These advances have provided hydrologists with opportunities to develop high-resolution large-scale hydrological models (LHMs) designed to represent and study the global hydrological cycle. However, with the aim of answering relevant questions for water resources policy and management, LHMs have recently been used in a number of regional applications. This has been enabled by their increasing spatial resolution which makes it possible to zoom-in on specific regions, essentially removing the barriers between global and regional models.

Notwithstanding their growing sophistication, the current generation of LHMs still fall short in their ability to represent dynamic trade-offs in the water-food-energy-environment nexus, and water competition between upstream and downstream users. These limitations hinder the ability of LHMs to provide reliable insights at any scale other than the global, leaving the task of incorporating human water management activities within these models as one of the grand challenges for the hydrologic research community.

Catchment-scale water management models (CWMMs) adopt a holistic systems approach to comprehensively address water availability, use, infrastructure, and policy aspects within multi-sectoral water allocation. The coupling of these models with LHMs can enhance their representation of human interventions in the natural water cycle (e.g., management of reservoirs, intra- and inter-basin water transfers) and improve the accuracy of water demand estimations such as irrigation requirements by including irrigation schemes. The inclusion of this local knowledge into LHMs’ modelling process can, therefore, increase their capacity to support rigorous nexus analyses to inform water policy and management decisions.

This work represents the preliminary outcome of a project with the overall research objective of developing and providing a “proof-of-concept” to explore and design an approach for integrating CWMMs with LHMs, and to assess its potential and limitations to enhance the quality of information LHMs provide at regional scale. This work will present the initial efforts to compare the outcomes of LHMs from the Inter-Sectoral Impact Model Intercomparison Project and the CWMM AQUATOOL in the Ebro River basin, a heavily managed catchment in Spain with multiple competing water uses. This comparison will provide an estimate of the capacity of LHMs to provide useful information for decision making, as well as to identify knowledge gaps to be filled with management models.

How to cite: Haro Monteagudo, D., Momblanch, A., Burek, P., Kahil, T., Andreu, J., Paredes-Arquiola, J., Solera, A., and Beguería, S.: Enhancing global hydrological models with local knowledge to support Nexus analyses, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-11027, https://doi.org/10.5194/egusphere-egu22-11027, 2022.