4.5 Article

A good-looking catchment can turn into a modeller's nightmare

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TAYLOR & FRANCIS LTD
DOI: 10.1080/02626667.2010.505571

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DAISY; MIKE SHE; nitrate; non-point sources; good modelling practice; failure

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This paper tells a real-life story of a modelling study that in many respects, failed to achieve its objectives. The study was carried out in 2003 as part of a Danish government policy process aiming to identify cost-effective measures to reduce nitrate loads from agricultural diffuse pollution in order to be able to meet Water Framework Directive requirements (of achieving good ecological status in surface water by 2015). To support this process, we established a distributed model that we expected could provide reliable predictions of the impacts of local-scale measures. The distributed model established for the 1312-km(2) Odense Pilot River Basin was based on a combination of two model codes: (a) DAISY, which simulated root zone processes; and (b) MIKE SHE/MIKE 11, which simulated the catchment flow and transport processes in surface water and groundwater using a 500-m horizontal grid and nine subsurface layers. The reliability of the modelling results turned out to be significantly poorer than the expectations. The simulations of catchment discharge were not as good as previous simulations with lumped models, owing to inappropriate conceptualisation of the catchment heterogeneity. Subsequent analysis in a PhD study showed that the dominating nitrate reduction process in the subsurface (where more than 50% of the nitrate disappears) is governed by geological heterogeneity with length scales smaller than the grid size of the numerical model. This poses a severe limitation for predicting the effects of local-scale measures, which was one of the reasons for choosing a distributed modelling approach. The entire modelling process was carried out in a policy context with very short deadlines, few allocated resources, and confusion about the terms of reference and the roles and functions of the actors involved. This context, which is far from the ideal modelling process recommended in protocols for good modelling practice, contributed significantly to the problems experienced.

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