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001008817 0247_ $$2doi$$a10.5194/egusphere-egu23-16122
001008817 037__ $$aFZJ-2023-02489
001008817 041__ $$aEnglish
001008817 1001_ $$0P:(DE-HGF)0$$aMustafa, Syed M. T.$$b0$$eCorresponding author
001008817 1112_ $$aEGU2023$$cVienna$$d2023-04-23 - 2023-04-28$$gEGU2023$$wGermany
001008817 245__ $$aMaking water models more inclusive and interdisciplinary to underpin sustainable development
001008817 260__ $$c2023
001008817 3367_ $$033$$2EndNote$$aConference Paper
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001008817 520__ $$aReliable predictions of water systems’ response to external pressures and ongoing changes arehighly important to ensure informed decision-making to support sustainable water resourcesmanagement for human use and the functioning of healthy ecosystems. Recent strongdevelopment of numerical models offers a potential to understand and forecast water systemsunder anthropogenic and climatic influences to provide information for decision-making, processunderstanding of the ‘unseen’ part of the water cycle and hazard risk analysis. However, thereliability of numerical model predictions is strongly influenced by various sources ofuncertainties, data qualities and assumptions, and often lacks stakeholders' point-of-view. A new,improved approach is needed and in this paper, we present six basic principles to improve thereliability and accuracy of numerical water model predictions considering explicitly stakeholders'needs and, thereby, better serving the society. Six highlighted principles are: (i) clearly defining theobjectives and the purpose of the model, sustaining them during the entire modelling process; (ii)incorporating expert and local community knowledge through stakeholders' feedback; (iii)implementing a multi-model approach in which a range of conceptualizations are explored ; (iv)considering and representing the uncertainties arising from model inputs, parameters, conceptualmodel structure and measurement/information error; (v) translating the results to concrete andunderstandable strategies that policymakers can use for their informed decision-making; and (vi)long term capacity building and monitoring data collection to reduce knowledge gaps, test andimprove predictions. We argue that implementing these six principles reduces uncertainties,improves the predictive capacity of the numerical water models, and ensures informed decision-making to support sustainable water resources management and thereby serve society better.
001008817 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
001008817 536__ $$0G:(EU-Grant)858375$$aWATERAGRI - WATER RETENTION AND NUTRIENT RECYCLING IN SOILS AND STREAMS FOR IMPROVED AGRICULTURAL PRODUCTION (858375)$$c858375$$fH2020-SFS-2019-2$$x1
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001008817 7001_ $$00000-0002-1855-5405$$aAla-Aho, Pertti$$b1
001008817 7001_ $$00000-0002-9744-2483$$aMarttila, Hannu$$b2
001008817 7001_ $$0P:(DE-HGF)0$$aHuysmans, Marijke$$b3
001008817 7001_ $$00000-0002-5129-8391$$aComte, Jean-Christophe$$b4
001008817 7001_ $$0P:(DE-HGF)0$$aShamsudduha, Mohammad$$b5
001008817 7001_ $$0P:(DE-HGF)0$$aGhysels, Gert$$b6
001008817 7001_ $$00000-0003-3840-7087$$aSchilling, Oliver S.$$b7
001008817 7001_ $$0P:(DE-Juel1)188813$$aHoffmann, Richard$$b8
001008817 7001_ $$0P:(DE-HGF)0$$aRossi, Pekka M.$$b9
001008817 7001_ $$0P:(DE-HGF)0$$aAvellan, Tamara$$b10
001008817 7001_ $$00000-0002-5157-0156$$aHaghighi, Ali Torabi$$b11
001008817 7001_ $$00000-0002-1776-3173$$aPeeters, Luk$$b12
001008817 7001_ $$00000-0001-7009-6130$$aPulido-Velazquez, Manuel$$b13
001008817 7001_ $$00000-0001-9906-3535$$aLarocque, Marie$$b14
001008817 7001_ $$00000-0003-2308-0392$$aLoon, Anne Van$$b15
001008817 7001_ $$0P:(DE-HGF)0$$aFerré, Ty Paul Andrew$$b16
001008817 7001_ $$00000-0001-6304-6274$$aBrunner, Philip$$b17
001008817 7001_ $$0P:(DE-Juel1)138662$$aHendricks-Franssen, Harrie-Jan$$b18$$ufzj
001008817 7001_ $$0P:(DE-HGF)0$$aKlöve, Björn$$b19
001008817 773__ $$a10.5194/egusphere-egu23-16122
001008817 8564_ $$uhttps://doi.org/10.5194/egusphere-egu23-16122
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001008817 9141_ $$y2023
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