scholarly journals Selected hydrologic and water-quality data, 1997 through 1999, for the Lake Traverse Reservation/Roberts County water-resources investigation in South Dakota

2000 ◽  
Author(s):  
R.F. Thompson
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
South Dakota ◽  
Quality Data ◽  
Water Quality Data

Objectives of a Water Quality Monitoring Programme for the International River Basins in a Developing Country in Southern Africa – Mozambique

1984 ◽  
Vol 16 (5-7) ◽  
pp. 33-39
Author(s):  
S J Hugman
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Industrial Development ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Sample Collection ◽  
Water Quality Data ◽  
Maximum Benefit ◽  
Management And Development ◽  
International Obligations

Mozambique lies on the south-east coast of Africa. Its Independence, in 1975, was particularly difficult and severely disrupted the economy. All its major rivers rise in neighbouring countries and several, in particular those from South Africa and Swaziland, are already heavily used before crossing the border. Since 1977 the National Water Directorate has been responsible for management and development of water resources. The Directorate includes a hydrology department which maintains field-teams throughout the country. Virtually no water quality data are available from before 1972, when irregular sample collection began. Since Independence, sampling has continued but the Directorate has redefined the objectives of the programme to obtain maximum benefit from very limited resources. These objectives were chosen for economic, hydrological and political reasons. The long-term objectives are to provide the data required for agricultural and industrial development projects, to manage and maintain the quality of Mozambique's water resources, and to meet international obligations. In practice, the capacity of the hydrological service is insufficient to meet these objectives. The targets for the existing programme were therefore chosen to satisfy the most important objectives and to be feasible with present resources. The routine programme is being completely operated by technicians who have no more than nine years schooling.

scholarly journals Development of a Universal Water Quality Index (UWQI) for South African River Catchments

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1534 ◽  
Author(s):  
Talent Banda ◽  
Muthukrishnavellaisamy Kumarasamy
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
South African ◽  
Water Quality Index ◽  
Quality Index ◽  
Quality Data ◽  
Index Number ◽  
Sudden Increase ◽  
Water Quality Data ◽  
The Ideal

The assessment of water quality has turned to be an ultimate goal for most water resource and environmental stakeholders, with ever-increasing global consideration. Against this backdrop, various tools and water quality guidelines have been adopted worldwide to govern water quality deterioration and institute the sustainable use of water resources. Water quality impairment is mainly associated with a sudden increase in population and related proceedings, which include urbanization, industrialization and agricultural production, among others. Such socio-economic activities accelerate water contamination and cause pollution stress to the aquatic environment. Scientifically based water quality index (WQI) models are then essentially important to measure the degree of contamination and advise whether specific water resources require restoration and to what extent. Such comprehensive evaluations reflect the integrated impact of adverse parameter concentrations and assist in the prioritization of remedial actions. WQI is a simple, yet intelligible and systematically structured, indexing scale beneficial for communicating water quality data to non-technical individuals, policymakers and, more importantly, water scientists. The index number is normally presented as a relative scale ranging from zero (worst quality) to one hundred (best quality). WQIs simplify and streamline what would otherwise be impractical assignments, thus justifying the efforts of developing water quality indices (WQIs). Generally, WQIs are not designed for broad applications; they are customarily developed for specific watersheds and/or regions, unless different basins share similar attributes and test a comparable range of water quality parameters. Their design and formation are governed by their intended use together with the degree of accuracy required, and such technicalities ultimately define the application boundaries of WQIs. This is perhaps the most demanding scientific need—that is, to establish a universal water quality index (UWQI) that can function in most, if not all, the catchments in South Africa. In cognizance of such a need, this study attempts to provide an index that is not limited to certain application boundaries, with a contribution that is significant not only to the authors, but also to the nation at large. The proposed WQI is based on the weighted arithmetic sum method, with parameters, weight coefficients and sub-index rating curves established through expert opinion in the form of the participation-based Rand Corporation’s Delphi Technique and extracts from the literature. UWQI functions with thirteen explanatory variables, which are NH3, Ca, Cl, Chl-a, EC, F, CaCO3, Mg, Mn, NO3, pH, SO4 and turbidity (NTU). Based on the model validation analysis, UWQI is considered robust and technically stable, with negligible variation from the ideal values. Moreover, the prediction pattern corresponds to the ideal graph with comparable index scores and identical classification grades, which signifies the readiness of the model to appraise water quality status across South African watersheds. The research article intends to substantiate the methods used and document the results achieved.

scholarly journals Deterministic and Stochastic Principles to Convert Discrete Water Quality Data into Continuous Time Series

2021 ◽  
Author(s):  
Danieli Mara Ferreira ◽  
Marcelo Coelho ◽  
Cristovão Vicente Scapulatempo Fernandes ◽  
Eloy Kaviski ◽  
Daniel Henrique Marco Detzel
Keyword(s):  
Water Quality ◽  
Water Resources ◽  
Statistical Characteristics ◽  
Quality Data ◽  
Model Description ◽  
Water Resources Planning ◽  
Concentration Data ◽  
Water Quality Data ◽  
Planning And Management ◽  
Resources Planning

Abstract Limited water quality data is often responsible for incorrect model description and misleading interpretation in water resources planning and management scenarios. This study compares two hybrid strategies to convert discrete concentration data into continuous daily values for one year in different river sections. Model A is based on an autoregressive process, accounting for serial correlation, water quality historical characteristics (mean and standard deviation) and random variability; the second approach (model B) is a regression model, based on the relationship between monitoring flow and concentrations, plus an error term. The generated series (here referred to as synthetic series) are propagated in time and space by a full deterministic model (SihQual), that solves the Saint-Venant and advection-dispersion-reaction equations. Results reveal that both approaches are appropriate to reproduce the variability of biochemical oxygen demand and organic nitrogen concentrations, leading to the conclusion that the combination of deterministic/empirical and stochastic components are compatible. A second outcome arises from the comparison of results in different time scales, supporting the need for further assessment of statistical characteristics of water quality data - which relies on monitoring plans. Nonetheless, the proposed methods are suitable to estimate multiple scenarios of interest in water resources planning and management.

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