Trends In Surface Water Quality Research Articles

Artificial Neural Network (ANN)-Based Water Quality Index (WQI) for Assessing Spatiotemporal Trends in Surface Water Quality—A Case Study of South African River Basins

Artificial neural networks (ANNs) are powerful data-oriented “black-box” algorithms capable of assessing and delineating linear and multifaceted non-linear correlations between the dependent and explanatory variables. Through the years, neural networks have proven to be effective and robust analytical techniques for establishing artificial intelligence-based tools for modelling, estimating, and projecting spatial and temporal variations in water bodies. Accordingly, ANN-based algorithms gained increased attention and have emerged as practical alternatives to traditional approaches for hydro-chemical analysis. ANNs are among the widely used computer systems for modelling surface water quality. Considering their wide recognition, resilience, flexibility, and accuracy, the current study employs a neural network-based methodology to construct a novel water quality index (WQI) model suitable for analysing South African rivers. The feed-forward, back-propagated multilayered perceptron model has three parallel-distributed neuron layers interconnected with seventy weighted links orientated laterally from left to right. First, the input layer includes thirteen neuro-nodes symbolising thirteen explanatory variables, including NH3, Ca, Cl, Chl-a, EC, F CaCO3, Mg, Mn, NO3, pH, SO4, and turbidity (NTU). Second, the hidden layer consists of eleven neuro-nodes accountable for computational tasks. Lastly, the output layer features one neuron responsible for conveying network outcomes using a single-digit WQI rating extending from zero to one hundred, where zero represents substandard water quality and one hundred denotes exceptional water quality. The AI-based model was developed using water quality data obtained from six monitoring locations within four drainage basins under the management of the Umgeni Water Board in the KwaZulu-Natal Province of South Africa. The dataset comprises 416 samples randomly divided into training, testing, and validation sets using a proportional split of 70:15:15%. The Broyden–Fletcher–Goldfarb–Shanno (BFGS) technique was utilised to conduct backpropagation training and adjust synapse weights. The dependent variables are the WQI scores from the universal water quality index (UWQI) model developed specifically for South African river basins. The ANN demonstrated enhanced efficiency through an overall correlation coefficient (R) of 0.985. Furthermore, the neural network attained R-values of 0.987, 0.992, and 0.977 for the training, testing, and validation intervals. The ANN model achieved a Nash–Sutcliffe efficiency (NSE) value of 0.974 and coefficient of determination (R2) of 0.970. Sensitivity analysis provided additional validation of the preparedness and computational competence of the ANN model. The typical target-to-output error tolerance for the ANN model is 0.242, demonstrating an adequate predictive ability to deliver results comparable with the target UWQI, having the lowest and highest index ratings of 75.995 and 94.420, respectively. Accordingly, the three-layer neural network is scientifically sound, with index values and water quality evaluations corresponding to the UWQI results. The current research project seeks to document the processes used and the outcomes obtained.

Long-term trends in surface water quality of China's seven major basins based on water quality identification index and big data analysis

Long-term trends in surface water quality of China's seven major basins based on water quality identification index and big data analysis

Long-Term Study of Monitoring History and Change Trends in Surface Water Quality in China

To investigate the monitoring history and long-term change trends in surface water quality in China since the reform and opening up, the history of surface water environment monitoring is summarized, including monitoring scope, monitoring methods, and technical requirements. Temporal and spatial patterns of surface water quality in China were analyzed based on the monitoring results. In the past 40 years, the monitoring targets for surface water quality have been continuously improved, the frequency of monitoring has become more science-based, and the monitoring indicators are now comprehensive. Overall, the temporal change trend in surface water quality has followed a “fluctuating changes stage—rapid deterioration stage—fluctuations stalemate stage—rapid improvement stage” pattern. However, the current regional surface water quality is still in a polluted status, and there is a gap between surface water quality status and the goal of building a well-off society. At present, China’s surface water pollution is prone to high numbers of incidents and the treatment of surface water pollution has entered a crucial stage. The potential for the continuous reduction of major pollutant discharges has become more challenging, and the marginal cost for pollution control has increased. It is very difficult to comprehensively solve the outstanding water environment problems. In addition to strengthening the existing work on surface water quality control, it is also necessary to strengthen the work of risk identification, early warning, and regulation implementation of the surface water environment. During the 14th year plan period (2021–2025), the overall planning on water resources, water ecology, and water quality will be implemented, and beautiful rivers and lakes will be created.

Surface water quality assessment based on the Integrated Water Quality Index in the Maozhou River basin, Guangdong, China

Rivers are a vital component of both urban and rural aquatic ecosystems, and the rapidly increasing pollution in rivers severely threatens the security of these ecosystems. In this study, the surface water quality in the Maozhou River basin, Guangdong Province, China, was assessed from 2018 to 2020 using multivariate statistical techniques and the Integrated Water Quality Index (IWQI). In addition, spatial trends in surface water quality were studied using a geographic information system. The results indicated that the water quality in 82.17% of the studied section met the Class V standard for surface water quality, with IWQI values ranging from 12.157 to 3.650. The surface water quality was clustered into eight groups and further divided into unsuitable (low quality) and suitable (acceptable quality) according to standard surface water quality thresholds (China in Environmental quality standards for surface water, 2002). Four groups (G1, G2, G3, and G4) were classified as unsuitable, because they fell short of the Class V standard for surface water quality. In these groups, industrial sewage, endogenous pollution, domestic sewage, and rainfall runoff, were the primary sources of pollution, and the main background pollutants for the water quality target of the functional zones were COD, NH3-N, TP, and LAS. The other four groups were classified as suitable. In these groups, endogenous pollution and rainfall runoff were the primary sources of pollution, and the main background pollutants for the water quality target of the functional zones were NH3-N and TP. Among them, NH3-N and LAS were recognized as responsive and sensitive to the surface water quality and spatio-temporal variability. Owing to pollution treatment and management measures undertaken by the Chinese government, the black-odorous water in the Maozhou River basin has disappeared, and the water quality in the Maozhou River basin has been maintained at the “medium and good” level. However, the surface water quality in the estuary region and the southwest tributary in the basin requires further improvement. This calls for further efforts to improve surface water quality and to properly deal with various sources of pollution in the watershed. This combined method has proved to be effective for surface water quality evaluation and management at river or basin scales. The results of this work are expected to provide a scientific foundation for aquatic ecosystem management and planning.

A reduction in mining and industrial effluents in the Blesbokspruit Ramsar wetland, South Africa: Has the quality of the surface water in the wetland improved?

The Blesbokspruit Wetland, 40 km southeast of Johannesburg, South Africa, was listed as a Ramsar Wetland of International Importance in 1986. Following discharges of mine-waters in the mid-1990s, the wetland no longer complied with the Ramsar criteria. This paper reports on historical trends in surface water quality of the Blesbokspruit, as a step towards restoration to Ramsar status. Monthly water quality data (SO 4 , Na, Cl and Mg concentrations, pH and EC values), from January 2000 to December 2011, were obtained from Rand Water for sites at: the stream inflow, just after the discharge point of pumped underground mine-water from Grootvlei mine, and the stream outflow point. The major ions were grouped into two distinct time-variation patterns (SO 4 -Mg) and (Na-Cl). Despite extensive reports that the wetland had an acid mine drainage problem, the pH values over an 11-year period were constrained within a range of 6.7 to 8.8. In 2011, following the cessation of underground mine-water pumping operations, mineralisation of the Blesbokspruit showed a large stepwise reduction, in contrast to a slowly decreasing trend over the previous 10 years, in both the SO 4 -Mg and Na-Cl groups, and EC. The stepwise reduction suggests that the pulping plant within the paper mill, a major source of Na-Cl rich effluent, had ceased operations coincidentally with the cessation of underground water discharges. This contradicts previous findings that underground mine-water discharge was the principal contributor to contamination of the Blesbokspruit Wetland. So, while the Blesbokspruit may have had a high mineralisation problem, this was not simply an acid mine drainage problem, but a combination of the effects of mining and industry. Keywords : acid mine drainage, underground mine-water, Blesbokspruit, Montreux Record, Grootvlei Mine, water quality, circumneutral, Ramsar

A bootstrap method for estimating uncertainty of water quality trends

Estimation of the direction and magnitude of trends in surface water quality remains a problem of great scientific and practical interest. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method was recently introduced as an exploratory data analysis tool to provide flexible and robust estimates of water quality trends. This paper enhances the WRTDS method through the introduction of the WRTDS Bootstrap Test (WBT), an extension of WRTDS that quantifies the uncertainty in WRTDS-estimates of water quality trends and offers various ways to visualize and communicate these uncertainties. Monte Carlo experiments are applied to estimate the Type I error probabilities for this method. WBT is compared to other water-quality trend-testing methods appropriate for data sets of one to three decades in length with sampling frequencies of 6–24 observations per year. The software to conduct the test is in the EGRETci R-package.

Assessment of surface water chloride and conductivity trends in areas of unconventional oil and gas development-Why existing national data sets cannot tell us what we would like to know

Heightened concern regarding the potential effects of unconventional oil and gas development on regional water quality has emerged, but the few studies on this topic are limited in geographic scope. Here we evaluate the potential utility of national and publicly available water-quality data sets for addressing questions regarding unconventional oil and gas development. We used existing U.S. Geological Survey and U.S. Environmental Protection Agency data sets to increase understanding of the spatial distribution of unconventional oil and gas development in the U.S. and broadly assess surface water quality trends in these areas. Based on sample size limitations, we were able to estimate trends in specific conductance (SC) and chloride (Cl−) from 1970 to 2010 in 16% (n = 155) of the watersheds with unconventional oil and gas resources. We assessed these trends relative to spatiotemporal distributions of hydraulically fractured wells. Results from this limited analysis suggest no consistent and widespread trends in surface water quality for SC and Cl− in areas with increasing unconventional oil and gas development and highlight limitations of existing national databases for addressing questions regarding unconventional oil and gas development and water quality.

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Water quality degradation is often a severe consequence of rapid economic expansion in developing countries. Methods to assess spatial-temporal patterns and trends in water quality are essential for guiding adaptive management efforts aimed at water quality remediation. Temporal and spatial patterns of surface water quality were investigated for 54 monitoring sites in the Wen-Rui Tang River watershed of eastern China to identify such patterns in water quality occurring across a rural-suburban-urban interface. Twenty physical and chemical water quality parameters were analyzed in surface waters collected once every 4-8 weeks from 2000 to 2010. Temporal and spatial variations among water quality parameters were assessed between seasons (wet/dry) and among major land use zones (urban/suburban/rural). Factor analysis was used to identify parameters that were important in assessing seasonal and spatial variations in water quality. Results revealed that parameters related to organic pollutants (dissolved oxygen (DO), chemical oxygen demand (manganese) (COD(Mn)), and 5-day biochemical oxygen demand (BOD₅)), nutrients (ammonia nitrogen (NH₄ ⁺-N), total nitrogen (TN), total phosphorus (TP)), and salt concentration (electrical conductivity (EC)) were the most important parameters contributing to water quality variation. Collectively, they explained 70.9 % of the total variance. A trend study using the seasonal Kendall test revealed reductions in COD(Mn), BOD₅, NH₄ ⁺-N, petrol, V-phen, and EC concentrations over the 11-year study period. Cluster analysis was employed to evaluate variation among 14 sampling sites representative of dominant land use categories and indicated three, three, and four clusters based on organic, nutrient, and salt water quality characteristics, respectively. Factors that are typically responsible for water quality degradation (including population, topography, and land use) showed no strong correlation with water quality trends implying considerable point source inputs in the watershed. The results of this study help inform ongoing water quality remediation efforts by documenting trends in water quality across various land use zones.

Characterisation and Description of Surface Water Quality in the Threatened Urban Wetlands around the City of Colombo

Colombo is a city surrounded by a large and interconnected system of natural wetlands. These wetlands which have historically provided a range of water services to the city are now believed to be threatened by degradation due to the recent changes in the urbanization patterns and urban lifestyle in Colombo. This paper presents a study on the current state and recent trends in surface water quality in a selected segment of these wetlands. The study was carried out as a part of a broader multidisciplinary research. The paper consists of a historical analysis of trends in surface water quality parameters and situation analysis of short term spatial and temporal water quality variation in the study area. The research identified that water quality parameters indicating domestic wastewater related pollution showed an increasing trend during the study period. BOD, Phosphates and Fecal Coliform were recorded in levels exceeding the accepted ambient water quality standards. Concentrations of several heavy metals were also above the ambient water quality standards. A distinct difference was observed in water quality between peripheral areas and internal water ways of the wetland. All evidence directs towards severe water quality degradation in the wetland dominated by domestic waste discharges and scattered solid waste dumps. This condition may lead to a nutrient enrichment of the wetland and cause biological and physical responses that may affect adversely on the water services provided. Key words: Water Quality; Urban Wetlands; Wetland Nutrient Enrichment; Water Services; Urban Water Pollution DOI: http://dx.doi.org/10.3126/jowe.v5i0.2831 J Wet Eco 2011 (5): 10-19

Trends in surface-water quality of an intermittent cold-desert stream

Understanding the complex relationships among land use, geology, and climate in semiarid watersheds is essential to restoring degraded riparian areas and improving water quality. Muddy Creek in south-central Wyoming has been listed as impaired since 1996 by the US Environmental Protection Agency due to unstable stream channels and degraded riparian habitat. Water quality data collected from 1985 to 2006 were used to determine trends in surface-water quality. Flow analyses identified reductions in percents of flow duration intervals between the impaired stream9s upper and lower boundary monitoring sites and in hydrograph peaks between pre- and post-best management practice (BMP) implementation. Following BMP implementation, reductions in specific conductivity, total dissolved solids, and turbidity among years were observed in the impaired stream section. Linking water quality improvements to specific BMPs is difficult; however results strongly suggest that positive trends are correlated to BMPs that stabilized stream channels and improved the condition of riparian areas. Naturally erosive conditions in the basin along with anthropogenic impacts elevate the importance of BMP implementation and a long-term monitoring program. Both are needed to evaluate the effectiveness of improvement efforts and to help resource managers develop practical watershed improvement management strategies so that optimum conditions in Muddy Creek basin can be achieved.

Trends in surface-water quality of an intermittent cold-desert stream

Understanding the complex relationships among land use, geology, and climate in semiarid watersheds is essential to restoring degraded riparian areas and improving water quality. Muddy Creek in south-central Wyoming has been listed as impaired since 1996 by the US Environmental Protection Agency due to unstable stream channels and degraded riparian habitat. Water quality data collected from 1985 to 2006 were used to determine trends in surface-water quality. Flow analyses identified reductions in percents of flow duration intervals between the impaired stream9s upper and lower boundary monitoring sites and in hydrograph peaks between pre- and post-best management practice (BMP) implementation. Following BMP implementation, reductions in specific conductivity, total dissolved solids, and turbidity among years were observed in the impaired stream section. Linking water quality improvements to specific BMPs is difficult; however results strongly suggest that positive trends are correlated to BMPs that stabilized stream channels and improved the condition of riparian areas. Naturally erosive conditions in the basin along with anthropogenic impacts elevate the importance of BMP implementation and a long-term monitoring program. Both are needed to evaluate the effectiveness of improvement efforts and to help resource managers develop practical watershed improvement management strategies so that optimum conditions in Muddy Creek basin can be achieved.

Long-term Trends in Surface Water Quality of Five Lakes in Japan

Since 1983, the Ministry of the Environment of Japan has conducted nation-wide acid deposition surveys. To investigate the effects of acid deposition on surface water, we used the nonparametric Mann–Kendall test to find temporal trends in pH, alkalinity, and electrical conductivity (EC) in more than 10 years of data collected from five lakes and their catchments (Lake Kuttara: northernmost; Lake Kamakita: near Tokyo; Lake Ijira: central; Lake Banryu: western; and Lake Unagiike: southernmost). The pH of Lake Ijira water has declined slightly since the mid-1990s, corresponding with the downward trends seen in the pH and alkalinity of the river water flowing into the lake. There were significant upward trends in the EC of both the lake and stream water; the same trends were also found for \( {\text{NO}}^{ - }_{3} \) concentrations. These trends show evidence of acidification due to atmospheric deposition, and this is the first such finding in Japan based on significant long-term trends. Lake Ijira is located about 40 km north of the Chukyo industrial area near Nagoya. The annual depositions of H+, nss-\( {\text{SO}}^{{2 - }}_{4} \), and \( {\text{NO}}^{ - }_{3} \) in Lake Ijira were among the highest of all deposition monitoring sites, suggesting that this is the main cause of the significant acidification observed in Lake Ijira. No significant trends suggesting acidification were observed in any of the other lake catchments in spite of the significant upward trends in EC. Upward trends in pH and alkalinity at Lake Banryu and upward trends in alkalinity at Lake Kamakita were detected, but no change in pH or alkalinity at Lake Kuttara and Lake Unagiike was observed.

Integrated modelling of climate change impacts on water resources and quality in a lowland catchment: River Kennet, UK

An integrated approach to climate change impact assessment is explored by linking established models of regional climate (SDSM), water resources (CATCHMOD) and water quality (INCA) within a single framework. A case study of the River Kennet illustrates how the system can be used to investigate aspects of climate change uncertainty, deployable water resources, and water quality dynamics in upper and lower reaches of the drainage network. The results confirm the large uncertainty in climate change scenarios and freshwater impacts due to the choice of general circulation model (GCM). This uncertainty is shown to be greatest during summer months as evidenced by large variations between GCM-derived projections of future low river flows, deployable yield from groundwater, severity of nutrient flushing episodes, and long-term trends in surface water quality. Other impacts arising from agricultural land-use reform or delivery of EU Water Framework Directive objectives under climate change could be evaluated using the same framework.

STATISTICAL METHODS AND SAMPLING DESIGN FOR ESTIMATING STEP TRENDS IN SURFACE‐WATER QUALITY1

ABSTRACT: This paper addresses two components of the problem of estimating the magnitude of step trends in surface water quality. The first is finding a robust estimator appropriate to the data characteristics expected in water‐quality time series. The Hodges‐Lehmann class of estimators is found to be robust in comparison to other nonparametric and moment‐based estimators. A seasonal Hodges‐Lehmann estimator is developed and shown to have desirable properties. Second, the effectiveness of various sampling strategies are examined using Monte Carlo simulation coupled with application of this estimator. The simulation is based on a large set of total phosphorus data from the Potomac River. To assure that the simulated records have realistic properties, the data are modeled in a multiplicative fashion incorporating flow, hysteresis, seasonal, and noise components. The results demonstrate the importance of balancing the length of the two sampling periods and balancing the number of data values between the two periods. The inefficiency of sampling at frequencies much in excess of 12 samples per year is demonstrated. Rotational sampling designs are discussed, and efficient designs, at least for this river and constituent, are shown to involve more than one year of active sampling at frequencies of about 12 per year.