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A dynamic mass balance model for phosphorus fluxes and concentrations in coastal areas

机译:沿海地区磷通量和浓度的动态质量平衡模型

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This paper presents a general, process-based mass balance model (CoastMab) for total phosphorus (TP) in defined coastal areas (at the ecosystem scale). The model is based on ordinary differential equations and calculates inflow, outflow and internal fluxes on a monthly basis. It consists of four compartments: surface water, deep water, erosion/transportation areas for fine sediments and accumulation areas for fine sediments. The separation between surface water and deep water is not done based on water temperature, but on sedimen-tological criteria instead (from the theoretical wave base). There are algorithms for all major internal TP fluxes (sedimentation, resuspension, diffusion, mixing and burial). Validations were performed using data from 21 different Baltic coastal areas. The results show that the model predicts monthly TP in water and chlorophyll a very well (generally within the uncertainty bands of the empirical data). The model has also been put through sensitivity tests, which show that the most important factor regulating the predictions of the model is generally the TP concentration in the sea beyond the coast. The model is simple to apply, since all driving variables may be accessed from maps or monitoring programs. The driving variables include coastal area, section area (between the defined coastal area and the adjacent sea), mean and maximum depths, latitude (used to predict water temperatures, stratification and mixing), salinity and TP concentration in the sea. Many of the model structures are general and could be used for areas other than those included in this study, e.g., for open coasts, estuaries or tidal coasts, as well as for other substances than phosphorus.
机译:本文提出了一个通用的,基于过程的质量平衡模型(CoastMab),用于确定沿海地区(在生态系统范围内)的总磷(TP)。该模型基于常微分方程,并每月计算流入,流出和内部通量。它由四个部分组成:地表水,深水,细小沉积物的侵蚀/运输区域和细小沉积物的聚集区域。地表水和深水之间的分离不是基于水温,而是根据沉积学标准(根据理论波基)。有用于所有主要内部TP通量的算法(沉降,重悬浮,扩散,混合和掩埋)。使用来自21个不同波罗的海沿海地区的数据进行了验证。结果表明,该模型预测水和叶绿素的每月总磷非常好(通常在经验数据的不确定范围内)。该模型还经过敏感性测试,表明调节模型预测的最重要因素通常是沿海以外海域的TP浓度。该模型易于应用,因为可以从地图或监视程序访问所有驾驶变量。驱动变量包括沿海地区,断面面积(在定义的沿海地区和相邻海之间),平均和最大深度,纬度(用于预测水温,分层和混合),盐度和海洋中的TP浓度。许多模型结构是通用的,可以用于本研究以外的区域,例如,开阔海岸,河口或潮汐海岸,以及除磷以外的其他物质。

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