Model Benchmarks For Coastal Lagoons


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To promote reliable, real-time management of coastal lagoons, increasingly sophisticated numerical models have been developed within the DITTY project (WP4). While models are diverse in design and scope, i.e. watershed, fluid-dynamics, biogeochemical, all have the same fundamental goal, i.e. to account realistically for the processes that drive the dynamic behaviour in coastal lagoons so that their status may ultimately be predicted and the effects of mitigation actions be properly evaluated, resulting on a series of good management practices that increase the sustainability of these fragile ecosystems.

The intent of WP5 (Intercomparison analysis) is to establish a standard set of input parameters and numerical “experiments” to be performed by various existing models so that independent results could be meaningfully compared and evaluated, having in mind the diversity of approach and systems (watershed, lagoon, adjacent coastal area). Furthermore, though comparison, conceptual weakness could be identified and targeted for further exploration by the DITTY partners as a whole. In this report (D16) , that follows D15 in which we described summarised and analysed the employed models in the DITTY community, we have carried out several intercomparison exercises taking into account the diversity of the model employed.

Model intercomparison techniques have been developing over the years in a number of environmental research communities (Røed et al., 1995; Hackett et al., 1995; Proctor, 1997 and 2002; Cramer and Field, 1999; Denning et al., 1999; Orr, 1999; Skogen and Moll, 2000; Beckers et al., 2002; Davies et al., 2002; Caputo et al., 2003; Smith et al., 2004; Delhez et al., 2004). For example, Smith et al. (2002) developed a distributed model intercomparison project (DMIP) to compare simulation of distributed hydrologic models to investigate several issues, such as: nature and impact of spatial variability of basin physical characteristics and forcings, optimal level of basin disaggregation to captures essential spatial variability, nature of error propagation through distributed models. Concerning hydrodynamic models, Beckers et al. (2002) carried out an intercomparison exercise on several water circulation models applied to the Mediterranean Sea using the same forcing. The results show that no model performed better than the others and that there was a similar correlation between model characteristics and modeller’s skill in terms of results. Intercomparison analysis concerning biogeochemical models are more scarce, for example a limited exercise was carried out by Skogen and Moll (2000) concerning the primary production of the North Sea using two ecological models. Both models gave similar results on the annual mean primary production, its variability and the influence of the river inputs.

As already stated, the goals of an intercomparison exercise are always the same. However, the processes we are interested in assess through the developed models are quite different and the requests in terms of data input, forcing variables, validation data, as well as calibration and sensitivity analysis are not completely similar. As we are concerned with three fundamentally different realms of modelling (watershed, hydrodynamic, biogeochemical modelling), we have decided to structure the document in three separate sections.

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