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Continuous measurement of nitrate concentration in a highlyudevent-responsive agricultural catchment in south-west ofudFrance: is the gain of information useful?

机译:连续测量硝酸盐浓度 ud西南的事件响应型农业流域法国:获取信息有用吗?

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摘要

A nitrate sensor has been set up to measure every 10 min the nitrate signal in a stream draining a small agricultural catchment dominated by fertilized crops during a 2-year study period (2006–2008) in the south-west of France. An in situ sampling protocol using automatic sampler to monitor flood events have been used to assume a point-to-point calibration of the sensor values. The nitrate concentration exhibits nonsystematic concentration and dilution effects during flood events. We demonstrate that the calibrated nitrate sensor signal gathered from the outlet is considered to be a continuous signal using the Nyquist–Shannon sampling theorem. The objectives of this study are to quantify the errors generated by a typical infrequent sampling protocol and to design appropriate sampling strategy according to the sampling objectives. Nitrate concentration signal and flow data are numerically sampled to simulate common sampling frequencies. The total fluxes calculated from the simulated samples are compared with the reference value computed on the continuous signal. Uncertainties are increasing as sampling intervals increase; the method that is not using continuous discharge to compute nitrate fluxes bring larger uncertainty. The dispersion and bias computed for each sampling interval are used to evaluate the uncertainty during each hydrological period. High underestimation is made during flood periods when high-concentration period is overlooked. On the contrary, high sampling frequencies (from 3 h to 1 day) lead to a systematic overestimation (bias around 3%): highest concentrations are overweighted by the interpolation of the concentration in such case. The in situ sampling protocol generates less than 1% of load estimation error and sample highest concentration peaks. We consider useful such newly emerging field technologies to assess short-term variations of water quality parameters, to minimize the number of samples to be analysed and to assess the quality state of the stream at any time.
机译:在法国西南部为期2年的研究期间(2006年至2008年),已经建立了硝酸盐传感器,用于每10分钟测量一次排水量中每10分钟的硝酸盐信号,该溪水排泄了以施肥作物为主的小农业集水区。使用自动采样器监视洪水事件的原位采样协议已被用来假设传感器值的点对点校准。洪水期间硝酸盐浓度表现出非系统性的浓度和稀释作用。我们证明,使用Nyquist–Shannon采样定理,从出口收集的校准硝酸盐传感器信号被认为是连续信号。这项研究的目的是量化由典型的不频繁采样协议产生的误差,并根据采样目标设计适当的采样策略。对硝酸盐浓度信号和流量数据进行数字采样,以模拟常见的采样频率。将模拟样本计算出的总通量与连续信号计算出的参考值进行比较。随着采样间隔的增加,不确定性也在增加。不使用连续放电计算硝酸盐通量的方法带来较大的不确定性。针对每个采样间隔计算的离散度和偏差用于评估每个水文期间的不确定性。在高浓度时期被忽视的洪水时期,高估了。相反,高采样频率(从3小时到1天)会导致系统的高估(偏差大约为3%):在这种情况下,最高浓度会被浓度插值法加权。原位采样协议产生的负载估计误差小于1%,并且样品的最高浓度峰值较高。我们认为这种有用的新兴现场技术可用于评估水质参数的短期变化,最大程度地减少要分析的样本数量并随时评估水流的质量状态。

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