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|Title:||Subannual Models for Catchment Management: Evaluating Model Performance on Three European Catchments|
|Authors:||SILGRAM M.; SCHOUMANS O.; WALVOORT D.; ANTHONY .; GROENENDIJK P.; STROMQVIST J.; BOURAOUI Faycal; ARHEIMER B.; KAPETANAKI M.; LO PORTO A.; MARTENSSON K.|
|Citation:||JOURNAL OF ENVIRONMENTAL MONITORING vol. 11 no. 3 p. 526-539|
|Publisher:||ROYAL SOC CHEMISTRY|
|Type:||Articles in periodicals and books|
|Abstract:||Models¿ abilities to predict nutrient losses at subannual timesteps is highly significant for evaluating policy measures, as it enables trends and the frequency of exceedance of water quality thresholds to be predicted. Subannual predictions also permit assessments of seasonality in nutrient concentrations, which are necessary to determine susceptibility to eutrophic conditions and the impact of management practices on water quality. Predictions of subannual concentrations are pertinent to EC Directives, whereas load estimates are relevant to the 50% target reduction in nutrient loading to the maritime area under OSPAR. This article considers the ability of four models (ranging from conceptual to fully mechanistic), to predict river flows, concentrations and loads of nitrogen and phosphorus on a subannual basis in catchments in Norway, England, and Italy. Results demonstrate that model performance deemed satisfactory on an annual basis may conceal considerable divergence in performance when scrutinised on a weekly or monthly basis. In most cases the four models performed satisfactorily, and mismatches between measurements and model predictions were primarily ascribed to the limitations in input data (soils in the Norwegian catchment; weather in the Italian catchment). However, results identified limitations in model conceptualisation associated with the damping and lagging effect of a large lake leading to contrasts in model performance upstream and downstream of this feature in the Norwegian catchment. For SWAT applied to the Norwegian catchment, although flow predictions were reasonable, the large number of parameters requiring identification, and the lack of familiarity with this environment, led to poor predictions of river nutrient concentrations.|
|JRC Institute:||Sustainable Resources|
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