Making water models more inclusive and interdisciplinary to underpin sustainable development
- 1Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands (syed.mustafa@wur.nl)
- 2Water, Energy and Environmental Engineering Research Unit, University of Oulu, Finland
- 3Department of Hydrology and Hydraulic Engineering, Vrije Universiteit Brussel, Belgium
- 4School of Geosciences, University of Aberdeen, Scotland, UK
- 5Department of Geography, University of Sussex, Brighton, UK
- 6Institute for Risk and Disaster Reduction, University College London, London, UK
- 7Hydrogeology, Department of Environmental Sciences, University of Basel, Basel, Switzerland
- 8Department of Water Ressources and Drinking Water, Eawag – Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland
- 9Agrosphere (IBG-3), Forschungszentrum Jülich GmbH, Jülich, Germany
- 10CSIRO Land and Water, Adelaide, Australia
- 11Research Institute of Water and Environmental Engineering (IIAMA), Universitat Politècnica de València, Valencia, Spain
- 12Département des sciences de la Terre et de l’atmosphère, Université du Québec à Montréal, Montréal, Canada
- 13Institute for Environmental Studies, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- 14Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, USA
- 15Center for Hydrogeology and Geothermics (CHYN), University of Neuchâtel, Neuchâtel, Switzerland
- *A full list of authors appears at the end of the abstract
Reliable predictions of water systems’ response to external pressures and ongoing changes are highly important to ensure informed decision-making to support sustainable water resources management for human use and the functioning of healthy ecosystems. Recent strong development of numerical models offers a potential to understand and forecast water systems under anthropogenic and climatic influences to provide information for decision-making, process understanding of the ‘unseen’ part of the water cycle and hazard risk analysis. However, the reliability of numerical model predictions is strongly influenced by various sources of uncertainties, data qualities and assumptions, and often lacks stakeholders' point-of-view. A new, improved approach is needed and in this paper, we present six basic principles to improve the reliability and accuracy of numerical water model predictions considering explicitly stakeholders' needs and, thereby, better serving the society. Six highlighted principles are: (i) clearly defining the objectives and the purpose of the model, sustaining them during the entire modelling process; (ii) incorporating expert and local community knowledge through stakeholders' feedback; (iii) implementing a multi-model approach in which a range of conceptualizations are explored ; (iv) considering and representing the uncertainties arising from model inputs, parameters, conceptual model structure and measurement/information error; (v) translating the results to concrete and understandable strategies that policymakers can use for their informed decision-making; and (vi) long term capacity building and monitoring data collection to reduce knowledge gaps, test and improve predictions. We argue that implementing these six principles reduces uncertainties, improves the predictive capacity of the numerical water models, and ensures informed decision-making to support sustainable water resources management and thereby serve society better.
Pertti Ala-Aho, Hannu Marttila, Marijke Huysmans, Jean-Christophe Comte, Mohammad Shamsudduha, Gert Ghysels, Oliver S. Schilling, Richard Hoffmann, Pekka M. Rossi, Tamara Avellan, Ali Torabi Haghighi, Luk Peeters, Manuel Pulido-Velazquez, Marie Larocque, Anne Van Loon, Ty Paul Andrew Ferré, Philip Brunner, Harrie-Jan Hendricks-Franssen, Victor Bense, Björn Klöve. Victor Bense (Hydrology and Quantitative Water Management Group, Wageningen University & Research, Wageningen, the Netherlands)
How to cite: Mustafa, S. M. T., Ala-Aho, P., Marttila, H., Huysmans, M., Comte, J.-C., Shamsudduha, M., Ghysels, G., Schilling, O. S., Hoffmann, R., Rossi, P. M., Avellan, T., Haghighi, A. T., Peeters, L., Pulido-Velazquez, M., Larocque, M., Loon, A. V., Ferré, T. P. A., Brunner, P., Hendricks-Franssen, H.-J., and Klöve, B. and the Syed M T Mustafa: Making water models more inclusive and interdisciplinary to underpin sustainable development, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16122, https://doi.org/10.5194/egusphere-egu23-16122, 2023.
