TY  - CONF
AU  - Mustafa, Syed M. T.
AU  - Ala-Aho, Pertti
AU  - Marttila, Hannu
AU  - Huysmans, Marijke
AU  - Comte, Jean-Christophe
AU  - Shamsudduha, Mohammad
AU  - Ghysels, Gert
AU  - Schilling, Oliver S.
AU  - Hoffmann, Richard
AU  - Rossi, Pekka M.
AU  - Avellan, Tamara
AU  - Haghighi, Ali Torabi
AU  - Peeters, Luk
AU  - Pulido-Velazquez, Manuel
AU  - Larocque, Marie
AU  - Loon, Anne Van
AU  - Ferré, Ty Paul Andrew
AU  - Brunner, Philip
AU  - Hendricks-Franssen, Harrie-Jan
AU  - Klöve, Björn
TI  - Making water models more inclusive and interdisciplinary to underpin sustainable development
M1  - FZJ-2023-02489
PY  - 2023
AB  - Reliable predictions of water systems’ response to external pressures and ongoing changes arehighly important to ensure informed decision-making to support sustainable water resourcesmanagement for human use and the functioning of healthy ecosystems. Recent strongdevelopment of numerical models offers a potential to understand and forecast water systemsunder anthropogenic and climatic influences to provide information for decision-making, processunderstanding of the ‘unseen’ part of the water cycle and hazard risk analysis. However, thereliability of numerical model predictions is strongly influenced by various sources ofuncertainties, 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 thereliability and accuracy of numerical water model predictions considering explicitly stakeholders'needs and, thereby, better serving the society. Six highlighted principles are: (i) clearly defining theobjectives 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, conceptualmodel structure and measurement/information error; (v) translating the results to concrete andunderstandable 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 andimprove 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.
T2  - EGU2023
CY  - 23 Apr 2023 - 28 Apr 2023, Vienna (Germany)
Y2  - 23 Apr 2023 - 28 Apr 2023
M2  - Vienna, Germany
LB  - PUB:(DE-HGF)24
DO  - DOI:10.5194/egusphere-egu23-16122
UR  - https://juser.fz-juelich.de/record/1008817
ER  -