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水质趋势检测的视觉技术:双质量曲线和累积和函数。

Visual techniques for the detection of water quality trends: Double-mass curves and cusum functions.

机构信息

University du Québec INRS-Eau, C.P. 7500, G1V 4C7, Sainte-Foy, Québec, Canada.

出版信息

Environ Monit Assess. 1983 Jun;3(2):173-84. doi: 10.1007/BF00398846.

DOI:10.1007/BF00398846
PMID:24258934
Abstract

There is a great need for quantitative techniques to assess changes in water quality related to progressive watershed land-use developments, water-related impoundments or to evaluate the impact of recent sanitation programs. In choosing a physically representative variate for the water quality of the run-off, both concentrations and fluxes of pollutants must be taken into account. The importance of the climatic seasonal and hydrological factors associated with unstable event-related contributions of point and non-point pollution sources of the pollutants has lead us to simultaneously study water-discharge and pollutant flux time-series. The mass-discharge time-series are, in practice, far from being ideal for the application of classical trend analysis: they are relatively short and inaccurate: their distribution, orginating from mixed parent populations is very often highly skewed; they show a high level of serial dependence and the seasonal effects represent a large percentage of the variance, concealing possible long-term trends. Faced with the poor structure of these series which prohibits the use of statistical tests, experiments have been carried out with progressive-regressive inertial techniques, which imply the stationarity of water discharges. The double-mass technique was developed originally as a visual technique, to assess the homogeneity of precipitation records and was extended to study variations in sediment transport in modified watersheds. More recently confidence 'rails' and slope change detection have rendered its use more quantitative. Based on the same inertial principles, the Cumulative Sum (CUSUM) functions allow simultaneous evaluation of the covariability of the two series. An example involving weekly sampled nitrate concentrations and continuously monitored water discharges is developed.

摘要

非常需要定量技术来评估与渐进式流域土地利用开发、与水有关的蓄水或评估最近卫生计划的影响有关的水质变化。在选择径流水质的物理代表性变量时,必须同时考虑污染物的浓度和通量。与不稳定的事件相关的点源和非点源污染的季节性和水文因素的重要性,导致我们同时研究水排放量和污染物通量时间序列。在实践中,质量排放量时间序列远非经典趋势分析应用的理想选择:它们相对较短且不准确;它们的分布源自混合的母体种群,通常非常偏斜;它们表现出高水平的序列相关性,季节性效应占方差的很大比例,掩盖了可能的长期趋势。面对这些禁止使用统计检验的序列的不良结构,进行了具有渐进式回归惯性技术的实验,这意味着水排放量的稳定性。双质量技术最初是作为一种视觉技术开发的,用于评估降水记录的同质性,并扩展到研究改良流域中的泥沙输运变化。最近,置信“铁轨”和斜率变化检测使其使用更加定量。基于相同的惯性原理,累积和(CUSUM)函数允许同时评估两个系列的共变。以每周采样的硝酸盐浓度和连续监测的水排放量为例进行了说明。

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引用本文的文献

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Development of a software package for trend detection in temporal series: Application to water and industrial effluent quality data for the St. Lawrence River.开发用于时间序列趋势检测的软件包:在圣劳伦斯河的水质和工业废水质量数据中的应用。
Environ Monit Assess. 1989 Nov;13(2-3):429-41. doi: 10.1007/BF00394243.