Browsing by Author "Heuvelink, Gerard B. M."

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    Going Platinum: The European Journal of Soil Science at 75
    (Wiley, 2024-03-01) Dungait, Jennifer A. J.; Evans, Daniel L.; Farrell, Mark; He, Hailong; Heuvelink, Gerard B. M.; Schmidt, Olaf
    The European Journal of Soil Science (EJSS) is published by Wiley on behalf of the British Society of Soil Science (BSSS) to fulfil its original mission to ‘publish an annual publication’. The Journal for Soil Science published its first issue in March 1949 (Figure 1, left) before a change of name to the European Journal of Soil Science (EJSS) in 1994. The current issue (Volume 75, Issue 2, March-April 2024; Figure 1, right) therefore marks our 75th Anniversary. In this Editorial, we (the Senior Editorial Team of the EJSS; Figure 2) review briefly how the journal has evolved over the last three-quarters of a century and look forward to both the challenges and opportunities that the future holds.
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    Recent insights on uncertainties present in integrated catchment water quality modelling
    (Elsevier, 2018-12-05) Tscheikner-Gratl, Franz; Bellos, Vasilis; Schellart, Alma; Moreno-Rodenas, Antonio; Muthusamy, Manoranjan; Langeveld, Jeroen; Clemens, Francois; Benedetti, Lorenzo; Rico-Ramirez, Miguel Angel; Fernandes de Carvalho, Rita; Breuer, Lutz; Shucksmith, James; Heuvelink, Gerard B. M.; Tait, Simon
    This paper aims to stimulate discussion based on the experiences derived from the QUICS project (Quantifying Uncertainty in Integrated Catchment Studies). First it briefly discusses the current state of knowledge on uncertainties in sub-models of integrated catchment models and the existing frameworks for analysing uncertainty. Furthermore, it compares the relative approaches of both building and calibrating fully integrated models or linking separate sub-models. It also discusses the implications of model linkage on overall uncertainty and how to define an acceptable level of model complexity. This discussion includes, whether we should shift our attention from uncertainties due to linkage, when using linked models, to uncertainties in model structure by necessary simplification or by using more parameters. This discussion attempts to address the question as to whether there is an increase in uncertainty by linking these models or if a compensation effect could take place and that overall uncertainty in key water quality parameters actually decreases. Finally, challenges in the application of uncertainty analysis in integrated catchment water quality modelling, as encountered in this project, are discussed and recommendations for future research areas are highlighted.