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Long term and high frequency monitoring of beam attenuation coefficient as a proxy for suspended particulate inorganic matter: use in the calibration of a sediment resuspension model

机译:光束衰减系数的长期和高频监测作为悬浮颗粒无机物质的代理:用于沉积物重新悬浮模型的校准

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The concentration of suspended particulate matter (SPM) is important for water quality in lakes and reservoirs. High concentration of SPM will affect the light climate for phytoplankton and reduce the quality of drinking water supplies (GAUTHIER et al. 2003). The light extinction coefficient of water (Kd) is an important factor when estimating the underwater light climate. Light extinction in water is caused by yellow substance, phytoplankton, SPM, and the properties of pure water. Suspended particulate matter can further be divided into suspended particulate inorganic matter (SPIM) and suspended particulate organic matter (SPOM). The SPIM fraction affects Kd due to its light scattering properties (PIERSON et al. 2003). The amount of SPM in lakes is related to wind speed (SOMLYODY & KONCSOS 1991), internal seiches (PIERSON & WEYHENMEYER 1994, MAN et al. 1997), bioturbation (SCHEFFER et al. 2003), and transport from discharging rivers (BLOESCH 1994, MARKENSTEN & PIERSON 2003). Many numerical models predicting SPM in lakes have included the effect of wind speed (BLOESCH 1994, TEETER et al. 2001), but only rarely has it been combined with the effect of river flow (MARKENSTEN & PIERSON 2003). We used underwater beam attenuation coefficient measurements collected at frequent intervals to calculate and verify the performance of a wind-speed and river-flow driven SPIM model (MARKENSTEN & PIERSON 2003). We tested the performance of this model using 24 months of measured beam attenuation data, as compared to the initial testing of the model, which was made using only 3 months of data ( MARKENSTEN & PIERSON 2003).
机译:悬浮颗粒物质(SPM)的浓度对于湖泊和储层中的水质是重要的。高浓度的SPM将影响浮游植物的轻质气候,降低饮用水的质量(Gauthier等,2003)。光消光系数(KD)是估计水下光气候时的重要因素。水中的光线消光是由黄色物质,浮游植物,SPM和纯水的性质引起的。悬浮的颗粒物可以进一步分为悬浮的颗粒状无机物质(Spim)和悬浮的颗粒状有机物(SPOM)。由于其光散射特性(Pierson等,2003),Spim级别会影响KD。湖泊中的SPM数量与风速有关(Somlyody&Koncsos 1991),内部Seiches(Pierson&Weyhenmeyer 1994,Man等人1997),Bioturnation(Scheffer等,2003),以及从排放河流的运输(Blosech 1994 ,Markensten和Pierson 2003)。预测湖泊中SPM的许多数值模型包括风速(Bloesch 1994,Teeter等,2001)的效果,但只有很少与河流流量的影响(Markensten&Pierson 2003)结合。我们使用以频繁的间隔收集的水下光束衰减系数测量来计算和验证风速和河流驱动的SPIM模型的性能(Markensten和Pierson 2003)。我们使用24个月的测量光束衰减数据测试了该模型的性能,与模型的初始测试相比,使用仅3个月的数据(Markensten和Pierson 2003)进行。

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