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Eutrophication model for Lake Washington (USA) Part I. Model description and sensitivity analysis

机译:华盛顿湖(美国)的富营养化模型第一部分。模型描述和敏感性分析

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Complex environmental models are often criticized as being difficult to analyze and poorly identifiable due to their nonlinearities and/or their large number of parameters relative to data availability. Others consider overparameterized models to be useful, especially for predicting system dynamics beyond the conditions for which the model was calibrated. In this paper, we present a complex eutrophication model that has been developed to simulate plankton dynamics in Lake Washington, USA. Because this model is to be used for testing alternative managerial schemes, the inclusion of multiple elemental cycles (org. C, N, P, Si, 0) and multiple functional phytoplankton (diatoms, green algae and cyanobacteria) and zooplankton (copepods and cladocerans) groups was deemed necessary. The model also takes into account recent advances in stoichiometric nutrient recycling theory, and the zooplankton grazing term was reformulated to include algal food quality effects on zooplankton assimilation efficiency. The physical structure of the model is simple and consists of two spatial compartments representing the lake epilimnion and hypolimnion. Global sensitivity analysis showed background light attenuation, the maximum phytoplankton growth rate, the phytoplankton basal metabolic rate, the zooplankton maximum grazing rate and the grazing half saturation constant have the greatest impact on model behavior. Phytoplankton phosphorus stoichiometry (maximum and minimum internal concentrations, maximum uptake rate) interacts with these parameters and determines the plankton dynamics (epilimnetic and hypolimnetic phytoplankton biomass, proportion of cyanobacteria and total zooplankton biomass). Sensitivity analysis of the model forcing functions indicated the importance of both external and internal loading for simulating epilimnetic and hypolimnetic plankton dynamics. These results will be used to calibrate the model, to reproduce present chemical and biological properties of Lake Washington and to test this lake's potential response to different external nutrient loading scenarios. (c) 2005 Elsevier B.V. All rights reserved.
机译:复杂的环境模型经常因其非线性和/或相对于数据可用性的大量参数而难以分析且难以识别。其他人则认为过参数化的模型很有用,尤其是在超出模型校准条件的情况下预测系统动态时。在本文中,我们提出了一个复杂的富营养化模型,该模型已经开发出来,可以模拟美国华盛顿湖中的浮游生物动力学。由于此模型将用于测试替代管理计划,因此包含多个元素周期(有机碳,氮,磷,硅,0)和多功能浮游植物(硅藻,绿藻和蓝藻)和浮游动物(足脚类动物和锁骨鱼类) )组被认为是必要的。该模型还考虑到化学计量养分循环理论的最新进展,对浮游动物的放牧术语进行了重新表述,以包括藻类食物质量对浮游动物吸收效率的影响。该模型的物理结构很简单,由代表湖泊上层和下层的两个空间部分组成。全局敏感性分析显示背景光衰减,最大浮游植物生长速率,浮游植物基础代谢速率,浮游动物最大放牧速率和放牧半饱和常数对模型行为的影响最大。浮游植物的磷化学计量(最大和最小内部浓度,最大吸收率)与这些参数相互作用,并确定浮游生物动力学(浮游和低速浮游植物生物量,蓝藻比例和浮游动物总生物量)。对模型强迫函数的敏感性分析表明,外部和内部载荷对于模拟上层和下层浮游生物动力学的重要性。这些结果将用于校准模型,再现华盛顿湖目前的化学和生物学特性,并测试该湖对不同外部养分负荷情况的潜在响应。 (c)2005 Elsevier B.V.保留所有权利。

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