Silgram M, Schoumans O F, Walvoort D J J, Anthony S G, Groenendijk P, Stromqvist J, Bouraoui F, Arheimer B, Kapetanaki M, Lo Porto A, Mårtensson K
ADAS UK Ltd., Wergs Road, Wolverhampton, UK.
J Environ Monit. 2009 Mar;11(3):526-39. doi: 10.1039/b823250d. Epub 2009 Feb 25.
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.
模型在亚年度时间步长预测养分流失的能力对于评估政策措施非常重要,因为它能够预测水质阈值的趋势和超标频率。亚年度预测还允许评估养分浓度的季节性,这对于确定富营养化状况的敏感性以及管理措施对水质的影响是必要的。亚年度浓度预测与欧盟指令相关,而负荷估计与《奥斯巴公约》规定的将向海洋区域的养分负荷降低50%的目标相关。本文考虑了四个模型(从概念性到完全机理模型)在挪威、英格兰和意大利流域亚年度尺度上预测河流流量、氮和磷浓度及负荷的能力。结果表明,在年度尺度上被认为令人满意的模型性能,在按周或按月审查时可能掩盖了性能上的相当大差异。在大多数情况下,这四个模型表现令人满意,测量值与模型预测之间的不匹配主要归因于输入数据的局限性(挪威流域的土壤;意大利流域的天气)。然而,结果发现模型概念化存在局限性,与一个大湖泊的阻尼和滞后效应有关,导致挪威流域该特征上下游的模型性能存在差异。对于应用于挪威流域的SWAT模型,尽管流量预测合理,但需要识别的参数数量众多,且对该环境缺乏了解,导致河流养分浓度预测不佳。