scholarly journals Effect of rainfall seasonality and land use on the water quality of the paraíba do sul river

2021 ◽  
Vol 29 ◽  
pp. 211-228
Author(s):  
Dayane Andrade da Silva Bourguignon ◽  
Micael de Souza Fraga ◽  
Gustavo Bastos Lyra ◽  
Roberto Avelino Cecílio ◽  
Marcel Carvalho Abreu
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Water Quality Index ◽  
Quality Index ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Paraíba Do Sul River ◽  
Dry And Rainy Seasons

Monitoring water quality is important for the suitable management of water resources. Therefore, this study aims to assess the main water quality parameters and the National Sanitation Foundation-Water Quality Index (WQINSF) of four locations on the Paraíba do Sul River basin, in the state of Rio de Janeiro, influenced by different land use and land cover, and in the dry and rainy seasons. The following quality parameters were evaluated: total phosphorus (TP), nitrate (NO3-), dissolved oxygen (DO), potential of hydrogen (pH), turbidity (Turb), thermotolerant coliforms (Col), total dissolved solids (TDS), biochemical oxygen demand (BOD), water temperature (Twater) and air temperature (Tair). Statistical differences (p < 0.05) were observed between the dry and rainy seasons for the parameters: TP, Col, Turb, TDS, Twater, Tair, NO3-, DO, and WQINSF. The concentration of rainfall was effective in water quality parameters behavior. WQINSF was lower in the rainy season and possibly the runoff was the major cause of water quality degradation. Land use and land cover influenced the concentration of DO and Col and, consequently, WQINSF. Despite statistical differences, in most cases, the Paraíba do Sul River basin lies in medium water quality index according to the classification of the National Water and Sanitation Agency (ANA).

scholarly journals Implementation of Machine Learning Methods for Monitoring and Predicting Water Quality Parameters

2020 ◽  
Vol 11 (2) ◽  
pp. 9285-9295 ◽  
Keyword(s):  
Machine Learning ◽  
Water Quality ◽  
River Basin ◽  
Water Quality Index ◽  
Quality Index ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Quality Data ◽  
Learning Tools ◽  
Water Quality Data

The importance of good water quality for human use and consumption can never be underestimated, and its quality is determined through effective monitoring of the water quality index. Different approaches have been employed in the treatment and monitoring of water quality parameters (WQP). Presently, water quality is carried out through laboratory experiments, which requires costly reagents, skilled labor, and consumes time. Thereby making it necessary to search for an alternative method. Recently, machine learning tools have been successfully implemented in the monitoring, estimation, and predictions of river water quality index to provide an alternative solution to the limitations of laboratory analytical methods. In this study, the potentials of one of the machine learning tools (artificial neural network) were explored in the predictions and estimation of the Kelantan River basin. Water quality data collected from the 14 stations of the River basin was used for modeling and predicting (WQP). As for WQP analysis, the results obtained from this study show that the best prediction was obtained from the prediction of pH. The low kurtosis values of pH indicate that the appearance of outliers give a negative impact on the performance. As for WQP analysis for each station, we found that the WQP prediction in station 1, 2, and 3 give the good results. This is related to the available data of those stations that are more than the available data in other stations, except station 8.

scholarly journals Assessment of coastal surface water quality for irrigation purpose

2020 ◽  
Vol 15 (4) ◽  
pp. 960-972
Author(s):  
M. F. Serder ◽  
M. S. Islam ◽  
M. R. Hasan ◽  
M. S. Yeasmin ◽  
M. G. Mostafa
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Water Type ◽  
Post Monsoon ◽  
Irrigation Purpose

Abstract The study aimed to assess the coastal surface water quality for irrigation purposes through the analysis of the water samples of some selected estuaries, rivers, and ponds. The analysis results showed that the mean value of typical water quality parameters like electrical conductivity (EC), total dissolved solids (TDS), sodium (Na+), and chloride (Cl−) ions exceeded the permissible limit of the Department of Environment (DoE), Bangladesh 2010, and FAO, 1985 for the pre- and post-monsoon seasons. The Piper diagram indicated a Na-Cl water type, especially during the pre- and post-monsoon seasons. The water quality parameters in the areas showed a higher amount than the standard permissible limits, indicating that the quality is deteriorating. The water quality index values for domestic uses showed very poorly to unsuitable in most of the surface waters except pond water, especially during the pre- and post-monsoon periods. The surface water quality index for irrigation purpose usages was found to be high and/ or severely restricted (score: 0–55) during the pre- and post-monsoon seasons. The study observed that due to saline water intrusion, the water quality deterioration started from post-monsoon and reached its highest level during the pre-monsoon season, which gradually depreciates the water quality in coastal watersheds of Bangladesh.

scholarly journals Extracting the spatio-temporal linkages between land use/land cover and water quality parameters using spatio-temporal weighted regression

2018 ◽  
Vol 53 (4) ◽  
pp. 205-218
Author(s):  
Farid Karimipour ◽  
Arash Madadi ◽  
Mohammad Hosein Bashough
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
Temporal Variations ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Spatial And Temporal Variations ◽  
Weighted Regression ◽  
Land Use Land Cover ◽  
Spatio Temporal

Abstract Studies in water quality management have indicated significant relationships between land use/land cover (LULC) variables and water quality parameters. Thus, understanding this linkage is essential in protecting and developing water resources. This article extends the conventional geographical weighted regression (GWR) to a temporal version in order to take both spatial and temporal variations of such linkages into account, which has been ignored by many of the previous efforts. The approach has been evaluated for total nitrates and nitrites' concentration as the case study. For this, observations of 45 water quality sampling stations were examined in a time interval of 20 years (1992–2011), and the linkages between LULC variables and NO2 + NO3 concentration were extracted through Pearson correlation coefficient as a global regression model, the conventional geographic weighted regression, and the proposed spatio-temporal weighted regression (STWR). Comparing the results based on two global criteria of goodness-of-fitness (R2) and residual sum of squares (RSS) verifies that the simultaneous consideration of spatial and temporal variations by STWR substantially improves the results.

scholarly journals Water quality index as a tool for wetland restoration

Water Policy ◽  
2017 ◽  
Vol 19 (3) ◽  
pp. 390-403 ◽  
Author(s):  
Nitin Bassi ◽  
M. Dinesh Kumar
Keyword(s):  
Water Quality ◽  
Water Quality Index ◽  
Urban Areas ◽  
Quality Index ◽  
Action Plan ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Bodies ◽  
Water Quality Parameters ◽  
Anthropogenic Pressures

Worldwide, wetlands are subjected to increasing anthropogenic pressures resulting in loss of their hydrological and ecological functions. Such impacts are more pronounced in the case of wetlands in urban areas which are exposed to land use changes and increased economic activities. In many Indian cities, natural water bodies such as lakes are heavily polluted due to runoff from farmlands in urban and peri-urban areas and discharge of untreated domestic and industrial wastewater. The major constraint for restoring such water bodies is difficulty in devising a concrete action plan for analysing different sets of water quality parameters. Hence, a water quality index (WQI), which is a tool to analyse large amounts of data on different water quality parameters, is computed for one of the biggest natural lakes in the metropolitan city of Delhi. The mean WQI of the lake was estimated to be 46.27, which indicates a high level of water pollution. The paper discusses how these findings can be used for informing policies on management of wetlands. The paper also suggests establishment of a community based water quality monitoring and surveillance system, backed by infrastructural support from the State, in order to restore the wetlands in urban areas.

scholarly journals Spatiotemporal Analysis of Surface Water Quality in Dong Thap Province, Vietnam Using Water Quality Index and Statistical Approaches

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 336
Author(s):  
Nguyen Thanh Giao ◽  
Phan Kim Anh ◽  
Huynh Thi Hong Nhien
Keyword(s):  
Water Pollution ◽  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
E Coli

The study was conducted to spatiotemporally analyze the quality, location and critical water variables influencing water quality using water monitoring data from the Department of Environment and Natural Resources, Dong Thap province in 2019. The water quality parameters including turbidity, pH, temperature, dissolved oxygen (DO), total suspended solids (TSS), biological oxygen demand (BOD), chemical oxygen demand (COD), nitrite (N-NO2−), nitrate (N-NO3−), ammonium (N-NH4+), total nitrogen (TN), orthophosphate (P-PO43−), chloride (Cl−), oil and grease, sulfate (SO42−), coliforms, and Escherichia coli (E. coli) were collected at 58 locations with the frequency of four times per year (February, May, August, and November). These parameters were compared with national technical regulation on surface water quality—QCVN 08-MT: 2015/BTNMT. Water quality index (WQI) was calculated and spatially presented by geographical information system (GIS) tool. Pearson correlation analysis, cluster analysis (CA), and principal component analysis (PCA) were used to evaluate the correlation among water quality parameters, group and reduce the sampling sites, and identify key parameters and potential water pollution sources. The results showed that TSS, BOD, COD, N-NH4+, P-PO43−, coliforms, and E. coli were the significant concerns impairing the water quality. Water quality was assessed from poor to medium levels by WQI analysis. CA suggested that the current monitoring locations could be reduced from 58 sites to 43 sites which can be saved the total monitoring budget up to 25.85%. PCA showed that temperature, pH, TSS, DO, BOD, COD, N-NH4+, N-NO2−, TN, P-PO43−, coliforms, and E. coli were the key water parameters influencing water quality in Dong Thap province’s canals and rivers; thus, these parameters should be monitored annually. The water pollution sources were possibly hydrological conditions, water runoff, riverbank erosion, domestic and urban activities, and industrial and agricultural discharges. Significantly, the municipal and agricultural wastes could be decisive factors to the change of surface water quality in the study area. Further studies need to focus on identifying sources of water pollution for implementing appropriate water management strategies.

A study of spatial and water quality index during dry and rainy seasons at Kelantan River Basin, Peninsular Malaysia

2021 ◽  
Vol 14 (2) ◽  
Author(s):  
Khairul Nizam Abdul Maulud ◽  
Arniza Fitri ◽  
Wan Hanna Melini Wan Mohtar ◽  
Wan Shafrina Wan Mohd Jaafar ◽  
Nur Zukrina Zuhairi ◽  
...  
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Water Quality Index ◽  
Quality Index ◽  
Peninsular Malaysia ◽  
Kelantan River Basin ◽  
Dry And Rainy Seasons

scholarly journals Surface Water Pollution Risk From Vietnam Water Quality Index (VN-WQI) in the Ca Mau City, Mekong Delta

2021 ◽  
Vol 20 (4) ◽  
Author(s):  
Nguyen Ngan Ha ◽  
Tran Thi Thu Huong ◽  
Pham The Vinh ◽  
Tran Thi Van
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Quality Index ◽  
Quality Index ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Sentinel 2

This paper presents the study of integrating the remote sensing technology with in-situ ground observation for assessing the status of water quality in Ca Mau city through the Vietnam Water Quality Index (VN-WQI). The Sentinel-2 image and in-situ surface water samples were collected on 20 February 2020 for this study. The sample results were then specified by samples’ coordination. Besides, Sentinel-2 imaging was processed by radiometric and atmospheric correction, geometric registration, and extracted pixel spectral values from the sample locations. The multiple linear regressions of seven water quality parameters including BOD5, COD, NH4, PO4, TSS, pH, Coliform with surface water’s pixel spectral values from the satellite images were calculated and used to simulate water quality parameters on the satellite image. They were integrated into the VN-WQI to estimate, classify, and evaluate the general surface water quality of the Ca Mau city. The results show that there is a regressive correlation between measured data and image spectral values, and the simulation also well fits with the data with an acceptable error. The surface water quality of Ca Mau city is heavily polluted with almost all water quality parameters recognized at B1 to above B2 level according to the QCVN08-MT:2015/BTNMT. In terms of VN-WQI, the results also illustrate the low quality of surface water and heavy pollution only used for water transportation, not for domestic use. This approach can be a powerful method in spatially monitoring water quality and supporting environment management.

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