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首页> 外文期刊>Environmental Science and Pollution Research >Estimation of the water quality of a large urbanized river as defined by the European WFD: what is the optimal sampling frequency?
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Estimation of the water quality of a large urbanized river as defined by the European WFD: what is the optimal sampling frequency?

机译:欧洲WFD定义的大型城市化河水水质估算:最佳采样频率是多少?

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Assessment of the quality of freshwater bodies is essential to determine the impact of human activities on water resources. The water quality status is estimated by comparing indicators with standard thresholds. Indicators are usually statistical criteria that are calculated on discrete measurements of water quality variables. If the time step of the measured time series is not sufficient to fully capture the variable's variability, the deduced indicator may not reflect the system's functioning. The goal of the present work is to assess, through a hydro-biogeochemical modeling approach, the optimal sampling frequency for an accurate estimation of 6 water quality indicators defined by the European Water Framework Directive (WFD) in a large human-impacted river, which receives large urban effluents (the Seine River across the Paris urban area). The optimal frequency depends on the sampling location and on the monitored variable. For fast varying compounds that originate from urban effluents, such as PO, NH and NO, a sampling time step of one week or less is necessary. To be able to reflect the highly transient character of bloom events, chl a concentrations also require a short monitoring time step. On the contrary, for variables that exert high seasonal variability, as NO and O (2), monthly sampling can be sufficient for an accurate estimation of WFD indicators in locations far enough from major effluents. Integrative water quality variables, such as O (2), can be highly sensitive to hydrological conditions. It would therefore be relevant to assess the quality of water bodies at a seasonal scale rather than at annual or pluri-annual scales. This study points out the possibility to develop smarter monitoring systems by coupling both time adaptative automated monitoring networks and modeling tools used as spatio-temporal interpolators.
机译:对淡水机构质量的评估对于确定人类活动对水资源的影响至关重要。通过比较标准阈值的指标来估算水质状态。指标通常是在离散测量水质变量的统计标准。如果测量时间序列的时间步长不足以完全捕获变量的变化,则推导的指示器可能不会反映系统的功能。目前工作的目标是通过水力生物地球化学建模方法进行评估,最佳采样频率,用于准确估算由欧洲水架指令(WFD)在大型人为河流中定义的6个水质指标,获得大型城市污水(围绕巴黎市区的塞纳河)。最佳频率取决于采样位置和监视变量。对于源自城市流出物的快速变化化合物,例如PO,NH和NO,需要一周或更短的采样时间步长。为了能够反映绽放事件的高瞬态特征,CHL浓度也需要短暂的监控时间步骤。相反,对于发挥高季节变异性的变量,作为NO和O(2),每月采样可以足以准确地估计来自主要污水的地方的粮食计划署指标。整合水质变量,如O(2),对水文条件非常敏感。因此,它与评估季节性规模而不是每年或多年尺度的水体的质量。本研究指出了通过耦合作为时空插值器的时间的适应性自动化监控网络和建模工具来开发更智能的监控系统。

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