Statistical validity of water quality time series in urban watersheds

ABSTRACT The water resources quality continuous monitoring is a complex activity. It generates extensive databases with time series of many variables and monitoring points that require the application of statistical methods for the information extraction. The application of statistical methods for frequency analysis of time series is linked to attending of the basic assumptions of randomness, homogeneity, independence, and stationarity. However, despite its importance, the verification of these assumptions in water quality literature is unusual. Therefore, the present study tests the Upper Iguaçu basin water quality time series against the mentioned hypotheses. Rejection was observed in 15%, 26%, 51% e 31% for randomness, homogeneity, independence, and stationarity, respectively. The results evidenced the strong relation between monitoring strategy, data assessment and meeting of basic statistical assumptions for the analysis of water quality time series. Even with the existence of possible solutions for addressing those issues, the standard monitoring strategies, with irregular frequencies and lack of representativeness in relation to other periods, beyond commercial, act as an obstacle to their implementation.

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Supplementary material to "Evaluation of statistical methods for quantifying fractal scaling in water quality time series with irregular sampling"

10.5194/hess-2017-315-supplement ◽

2017 ◽

Author(s):

Qian Zhang ◽

Ciaran J. Harman ◽

James W. Kirchner

Keyword(s):

Water Quality ◽

Time Series ◽

Statistical Methods ◽

Irregular Sampling ◽

Fractal Scaling ◽

Supplementary Material

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Review of “Evaluation of statistical methods for quantifying fractal scaling in water quality time series with irregular sampling”

10.5194/hess-2017-315-rc2 ◽

2017 ◽

Author(s):

Anonymous

Keyword(s):

Water Quality ◽

Time Series ◽

Statistical Methods ◽

Irregular Sampling ◽

Fractal Scaling

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Time-series model, statistical methods, and software documentation for R–QWTREND—An R package for analyzing trends in stream-water quality

Open-File Report ◽

10.3133/ofr20201014 ◽

2020 ◽

Author(s):

Aldo V. Vecchia ◽

Rochelle A. Nustad

Keyword(s):

Water Quality ◽

Time Series ◽

Statistical Methods ◽

Stream Water ◽

R Package ◽

Time Series Model ◽

Stream Water Quality ◽

Software Documentation

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Methods for Processing and Summarizing Time-Series Temperature Data Collected as Part of the National Water-Quality Assessment Program Studies on the Effects of Urbanization on Stream Ecosystems

Data Series ◽

10.3133/ds330 ◽

2008 ◽

Author(s):

Thomas F. Cuffney ◽

Robin A. Brightbill

Keyword(s):

Water Quality ◽

Time Series ◽

Quality Assessment ◽

Water Quality Assessment ◽

Temperature Data ◽

Stream Ecosystems ◽

Assessment Program ◽

National Water

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Applying Probabilistic Water Quality Standards in River Basin Water Quality Optimization Models

Water Quality Research Journal ◽

10.2166/wqrj.1974.004 ◽

1974 ◽

Vol 9 (1) ◽

pp. 25-29

Author(s):

M. B. Bayer

Keyword(s):

Water Quality ◽

River Basin ◽

Treatment Plant ◽

Oxygen Demand ◽

Minimum Cost ◽

Water Quality Standards ◽

Quality Optimization ◽

Basin Water ◽

Do Concentration ◽

Water Quality Models

Abstract This paper describes a method of applying probabilistic DO (dissolved oxygen) and BOD (biochemical oxygen demand) standards in river basin water quality models. Maximum likelihood estimators for the DO and BOD concentrations variances for each reach are used to obtain a lower bound for BOD so that the probability of violating specified DO and BOD standards is less than Θ per cent in any reach. These boundary values for DO and BOD concentrations are incorporated into a nonlinear water quality optimization model for finding the minimum cost set of wastewater treatment plant efficiencies required to meet DO and BOD standards. The method also provides the minimum DO concentration and the maximum BOD concentration which may be expected to occur 1-Θ of the time for any reach.

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Optimization of Regional Water Quality Monitoring Strategies

Water Science & Technology ◽

10.2166/wst.1987.0251 ◽

1987 ◽

Vol 19 (5-6) ◽

pp. 721-727 ◽

Cited By ~ 4

Author(s):

J. Pintér ◽

L. Somlyódy

Keyword(s):

Water Quality ◽

Water Quality Management ◽

Water Quality Monitoring ◽

Primary Objective ◽

Lake Balaton ◽

Monitoring Networks ◽

Monitoring Strategies ◽

Time Period ◽

Computational Aspects ◽

Indicator Model

A conceptual framework is presented for optimizing the operation of regional monitoring networks which assist water quality management. The primary objective of the studied network is to determine the annual nutrient load carried into a lake by its tributaries. Following the description of the basic (single time–period, single water quality indicator) model, several extension possibilities and computational aspects are highlighted. The suggested methodology is illustrated by a numerical example, concerning the surveillance system on the tributaries of Lake Balaton (Hungary).

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Algae Migration Characteristics in Fresh Water Red Tide

Water Science & Technology ◽

10.2166/wst.1993.0162 ◽

1993 ◽

Vol 28 (7) ◽

pp. 197-201 ◽

Cited By ~ 1

Author(s):

Dunchun Wang ◽

Isao Somiya ◽

Shigeo Fujii

Keyword(s):

Water Quality ◽

Time Series ◽

Fresh Water ◽

Field Data ◽

Field Survey ◽

Red Tide ◽

Bottom Layer ◽

Total Biomass ◽

Quality Indices ◽

Vertical Distributions

To understand the algae migration characteristics in the fresh water red tide, we performed a field survey in the Shorenji Reservoir located in Nabari City, Japan. From the analysis of the field data, it is found that the patterns of vertical distributions of the indices representing biomass are very different in the morning and the afternoon. Since some water quality indices have reverse fluctuations between the surface and the bottom layer in respect of the time series changes and the total biomass of the vertical water column is relatively constant, it is concluded that vertical and daily biomass variation of red tide alga is caused by its daily migration, that is the movement from the bottom layer to the surface in the morning and the reverse movement in the afternoon.

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Assessment of Automatically Monitored Water Levels and Water Quality Indicators in Rivers with Different Hydromorphological Conditions and Pollution Levels in Greece

Hydrology ◽

10.3390/hydrology8020086 ◽

2021 ◽

Vol 8 (2) ◽

pp. 86

Author(s):

Angeliki Mentzafou ◽

George Varlas ◽

Anastasios Papadopoulos ◽

Georgios Poulis ◽

Elias Dimitriou

Keyword(s):

Water Quality ◽

Time Series ◽

Quality Indicators ◽

High Frequency ◽

Automatic Monitoring ◽

Water Levels ◽

High Temporal Resolution ◽

Water Quality Indicators ◽

Pollution Levels ◽

Riverine Ecosystems

Water resources, especially riverine ecosystems, are globally under qualitative and quantitative degradation due to human-imposed pressures. High-temporal-resolution data obtained from automatic stations can provide insights into the processes that link catchment hydrology and streamwater chemistry. The scope of this paper was to investigate the statistical behavior of high-frequency measurements at sites with known hydromorphological and pollution pressures. For this purpose, hourly time series of water levels and key water quality indicators (temperature, electric conductivity, and dissolved oxygen concentrations) collected from four automatic monitoring stations under different hydromorphological conditions and pollution pressures were statistically elaborated. Based on the results, the hydromorphological conditions and pollution pressures of each station were confirmed to be reflected in the results of the statistical analysis performed. It was proven that the comparative use of the statistics and patterns of the water level and quality high-frequency time series could be used in the interpretation of the current site status as well as allowing the detection of possible changes. This approach can be used as a tool for the definition of thresholds, and will contribute to the design of management and restoration measures for the most impacted areas.

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