Assessment of surface water quality of the Ceyhan River basin, Turkey

Nitrogen Budget and Statistical Entropy Analysis of the Tiber River Catchment, a Highly Anthropized Environment

Modern farming causes a decline in the recycling of the soil’s inorganic matter due to losses by leaching, runoff, or infiltration into the groundwater. The Soil System Budget approach was applied to evaluate the net N budget at the catchment and sub-catchment levels of the Tiber River (central Italy) in order to establish the causes for different N budgets among the sub-catchments. Statistical Entropy Analysis (SEA) was used to evaluate the N efficiency of the Tiber River and its sub-catchments, providing information on the dispersion of different N forms in the environment. The total N inputs exceeded the total outputs, showing a low N retention (15.8%) at the catchment level, although some sub-catchments showed higher N retention values. The Utilized Agricultural Area was important in the determination of the N balance, as it was linked to zoo- and agricultural activities, although the Random Forest analysis showed that the importance ranking changed with the land use. The low N retention of the Tiber catchment was due to the soil characteristics (Cambisols and Leptosols), loads from atmospheric deposition, biological fixation, and the livestock industry. The SEA simulations showed a reduction of the N released into the atmosphere and groundwater compartments from 34% to 6% through a reduction of the N loads by 50%.

Multivariate Statistical Analysis of Water Quality and Trophic State in an Artificial Dam Reservoir

Paldang Reservoir, located in the Han River basin in South Korea, is used for drinking water, fishing, irrigation, recreation, and hydroelectric power. Therefore, the water quality of the reservoir is of great importance. The main objectives of this study were to evaluate spatial and seasonal variations of surface water quality in the reservoir using multivariate statistical techniques (MSTs) along with the Trophic State Index (TSI) and Trophic State Index deviation (TSID). The empirical relationships among nutrients (total phosphorus, TP; total nitrogen, TN), chlorophyll-a (CHL-a), and annual variations of water quality parameters were also determined. To this end, 12 water quality parameters were monitored monthly at five sites along the reservoir from 1996 to 2019. Most of the parameters (all except pH, dissolved oxygen (DO), and total coliform bacteria (TCB)) showed significant spatial variations, indicating an influence of anthropogenic activities. Principal component analysis combined with factor analysis (PCA/FA) suggested that the parameters responsible for water quality variations were primarily correlated with nutrients and organic matter (anthropogenic), suspended solids (both natural and anthropogenic), and ionic concentrations (both natural and anthropogenic). Stepwise spatial discriminant analysis (DA) identified water temperature (WT), DO, electrical conductivity (EC), chemical oxygen demand (COD), the ratio of biological oxygen demand (BOD) to COD (BOD/COD), TN, TN:TP, and TCB as the parameters responsible for variations among sites, and seasonal stepwise DA identified WT, BOD, and total suspended solids (TSS) as the parameters responsible for variations among seasons. COD has increased (R2 = 0.63, p < 0.01) in the reservoir since 1996, suggesting that nonbiodegradable organic loading to the water body is rising. The empirical regression models of CHL-a-TP (R2 = 0.45) and CHL-a-TN (R2 = 0.27) indicated that TP better explained algal growth than TN. The mean TSI values for TP, CHL-a, and Secchi depth (SD) indicated a eutrophic state of the reservoir for all seasons and sites. Analysis of TSID suggested that blue-green algae dominated the algal community in the reservoir. The present results show that a significant increase in algal chlorophyll occurs during spring in the reservoir. Our findings may facilitate the management of Paldang Reservoir.

Spatiotemporal Variation Characteristics of Water Pollution and the Cause of Pollution Formation in a Heavily Polluted River in the Upper Hai River

Blackening and odorization of heavily polluted rivers has become a serious concern and threat to ecological and human health. This paper aims to gain a deeper understanding of changes in water pollution and the cause of pollution formation in a heavily polluted river in the upper Hai River. In this study, comprehensive water quality index (CWQI) and multivariate statistical techniques (MSTs) were applied to assess the spatiotemporal variation characteristics of water pollution and to identify potential pollution sources. The seasonal Mann–Kendall (SMK) test and the SMK test of flow-adjusted concentrations were effectively used to explore the temporal variation trends of major pollutants and the causes of their formation. Data of 15 water quality parameters were analyzed during 1980–2018 at 19 monitoring sites in the mainstream and major tributaries of the Xinxiang Section of the Wei River (XSWR). The results showed that the rivers were seriously polluted from 1991 to 2009, but the water quality improved after 2010. Nineteen sampling sites were divided into a low pollution region and a high pollution region. In the flood season, the pollution sources were mainly domestic sewage, industrial wastewater, agricultural runoff, biochemical pollution, and natural sources. In the nonflood season, the pollution sources were mainly domestic sewage and industrial wastewater. In recent years, the water quality of seriously polluted river has generally improved, mainly due to reductions in pollutant discharge from point sources and nonpoint sources.

Use of multivariate statistical methods to analyze the monitoring of surface water quality in the Doce River basin, Minas Gerais, Brazil

The objective of the present study was to evaluate the water quality data in the Minas Gerais portion of the Doce River basin in order to analyze the current monitoring network by identifying the main variables to be maintained in the network, their possible sources of pollution, and the best sampling frequency. Multivariate statistical techniques (factor analysis/principal components analysis, FA/PCA and cluster analysis, CA) complemented by the analysis of violation of the framing classes were used for this purpose. Water quality variables common to 64 monitoring sites were analyzed for the base period from 2010 to 2017. The water quality variables were analyzed considering the different monitoring campaigns: (a) partial campaigns; (b) total campaigns; and (c) monthly campaigns. It was identified from the FA/PCA results, that, when the partial campaign data were analyzed, the variables selected represent the high susceptibility that the basin presents to erosion and the release of domestic effluents in its water bodies. When the data of total campaigns were evaluated, representative variables of the contamination by heavy metals from industrial and mining activities were included. Therefore, the analysis of violation of the framing classes made possible to identify five critical variables: thermotolerant coliforms, dissolved iron, total phosphorus, and total manganese, which reinforced the results obtained in FA/PCA. Based on the results of the analyses, it was recommended to include variables associated with heavy metal contamination in the partial campaigns, prioritizing the dissolved iron and total manganese, as well as total chloride sampling only for the total campaigns. The evaluated data from the monthly campaigns, the CA showed that although the quarterly monitoring frequency is satisfactory, the monthly monitoring is more appropriate for the monitoring of water quality in the Minas Gerais portion of the Doce River basin.

Assessment of surface water quality status of the Aby Lagoon System in the Western Region of Ghana

The pollution status of the Tendo Lagoon, the upstream section of the Aby Lagoon System, was investigated. The water temperature, pH, turbidity, dissolved oxygen (DO), electrical conductivity (EC), nitrates (NO₃^-), and phosphate (PO₄^3-) levels were evaluated using samples taken during the wet and dry seasons to assess the variabilities in water quality in the area. The water quality data was subjected to paired t-test, One-way ANOVA, Factor Analysis, Cluster analysis (CA) as well as a Water Quality Index (WQI) evaluation using the Canadian Council of Ministers of the Environment (CCME) model. The paired sample t-test confirmed that the surface water quality varies significantly between the wet and dry season samples (p < 0.05) except for phosphate loads which may be contributed largely by year-round municipal waste discharges. The results of the ANOVA showed that the variation of the water quality parameters among sampling stations was not statistically significant except for turbidity which was relatively higher in the upstream sections where the Tano River enters the lagoon. The results of FA indicated that three significant factors–relating to the degradation of organic materials, suspended solids (turbidity) and nutrients- accounted for 73.65% of spatio-temporal variations in the water quality. The CA showed that the eight sampling stations can be grouped into four distinct clusters based on their water quality. The source of pollution in the demarcated sections of the Aby Lagoon was concluded to be largely due to the result of localized anthropogenic inputs of domestic waste and sediments carried from the upstream in the Tano River. An evaluation of the CCME WQI for the sampling stations revealed that all the sampling stations showed marginal water quality relative to the target water quality range recommended by the Water Resources Commission (WRC) of Ghana for domestic use and protection of aquatic life. Monitoring programs were recommended with effective management measures instituted and implemented for the sustainability of the lagoon and the Tano River Basin.

Studies on the Spatiotemporal Variability of River Water Quality and Its Relationships with Soil and Precipitation: A Case Study of the Mun River Basin in Thailand

Human activities can affect soil nutrients, thereby influencing river water quality. The spatial pattern of precipitation also impacts distributions of water quality. In this paper, we employed a method that combines point survey, soil, and water quality data to analyze the spatial relationships between precipitation, soil nutrient and water quality in the basin on the basis of field surveys and laboratory analysis. The ordinary kriging method was applied to interpolate the precipitation and soil data, and the spatial pattern was analyzed. The water samples on the main stream and soil samples in the field were collected during both the dry and rainy seasons to analyze the water quality and soil nutrients. The results indicate: (1) The water quality in the dry season is better than that in the rainy season, the water quality in the upper reaches is better than that in the lower reaches, and agricultural activity is the direct source of water pollution. (2) The precipitation in the rainy and dry seasons is differente and the dilution effect of precipitation on pollutant concentrations and transport of water flow affect the spatial distribution of water quality. (3) There is a significant difference in the spatial pattern of soil nutrients between the dry and rainy seasons, and the soil nutrient content and the surface runoff directly affect the water quality. Soil nutrients are affected by human activities, and they potentially act as nonpoint source (NPS) pollution in this river basin. To improve the water quality, suitable agriculture measures need to be implemented.

Micro- and mesoplastics in Northeast Levantine coast of Turkey: The preliminary results from surface samples

The determination of the microplastic distribution will be beneficial as a measure of the potential effects on the environment. The Mediterranean Sea had a high risk of pollution as it was enclosed by highly populated and industrialized countries. Here, we determined the level of micro- and mesoplastic pollution in Iskenderun and Mersin Bays, located in the Northeastern Levantine coast of Turkey. The average level of both micro- and mesoplastic was determined to be 0.376 item/m² at seven stations. The highest level was determined in Mersin Bay at the mouth of the Seyhan river (Station no. 7, with 906 items), and the lowest level was found in Station no. 4 in Iskenderun Bay (78 items). As a result of this study, it was determined that the microplastic pollution level in the Mediterranean coast of Turkey was similar to the other regions of the Mediterranean Sea.

River water quality assessment using environmentric techniques: case study of Jakara River Basin

Jakara River Basin has been extensively studied to assess the overall water quality and to identify the major variables responsible for water quality variations in the basin. A total of 27 sampling points were selected in the riverine network of the Upper Jakara River Basin. Water samples were collected in triplicate and analyzed for physicochemical variables. Pearson product-moment correlation analysis was conducted to evaluate the relationship of water quality parameters and revealed a significant relationship between salinity, conductivity with dissolved solids (DS) and 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), and nitrogen in form of ammonia (NH4). Partial correlation analysis (r p) results showed that there is a strong relationship between salinity and turbidity (r p=0.930, p=0.001) and BOD5 and COD (r p=0.839, p=0.001) controlling for the linear effects of conductivity and NH4, respectively. Principal component analysis and or factor analysis was used to investigate the origin of each water quality parameter in the Jakara Basin and identified three major factors explaining 68.11 % of the total variance in water quality. The major variations are related to anthropogenic activities (irrigation agricultural, construction activities, clearing of land, and domestic waste disposal) and natural processes (erosion of river bank and runoff). Discriminant analysis (DA) was applied on the dataset to maximize the similarities between group relative to within-group variance of the parameters. DA provided better results with great discriminatory ability using eight variables (DO, BOD5, COD, SS, NH4, conductivity, salinity, and DS) as the most statistically significantly responsible for surface water quality variation in the area. The present study, however, makes several noteworthy contributions to the existing knowledge on the spatial variations of surface water quality and is believed to serve as a baseline data for further studies. Future research should therefore concentrate on the investigation of temporal variations of water quality in the basin.

Physical and chemical characteristics of water from the hydrographic basin of the Poxim River, Sergipe State, Brazil

The Poxim River is one of Sergipe State's major waterways. It supplies water to the State capital, Aracaju, but is threatened by urban and agricultural developments that compromise both the quantity and the quality of the water. This has direct impacts on the daily lives of the region's population. In this work, a multivariate analytical approach was used to investigate the physical and chemical characteristics of the water in the river basin. Four sampling campaigns were undertaken, in November 2005, and in February, May, and September 2006, at 15 sites distributed along the Poxim. The parameters analyzed were conductivity, turbidity, color, total dissolved solids, dissolved oxygen, alkalinity, hardness, chlorophyll-a, and nutrients (total phosphorus, dissolved orthophosphate, nitrite, nitrate, ammoniacal nitrogen, and total nitrogen). Dissolved oxygen contents were very low in the Poxim-Açu River (1.0-2.8), the Poxim River (1.6-4.6), and the estuarine region (1.7-5.1), due to the dumping of wastes and discharges of domestic and industrial effluents containing organic matter into fluvial and estuarine regions of the Poxim. Factor analysis identified five components that were indicative of the quality of the water, and that explained 81.73 % of the total variance.

Temporal aspects of surface water quality variation using robust statistical tools

Robust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and analyzed for their physicochemical constituents. Discriminant analysis (DA) provided better results with great discriminatory ability by using five parameters with (P < 0.05) for dry season affording more than 96% correct assignation and used five and six parameters for forward and backward stepwise in wet season data with P-value (P < 0.05) affording 68.20% and 82%, respectively. Partial correlation results revealed that there are strong (r(p) = 0.829) and moderate (r(p) = 0.614) relationships between five-day biochemical oxygen demand (BOD(5)) and chemical oxygen demand (COD), total solids (TS) and dissolved solids (DS) controlling for the linear effect of nitrogen in the form of ammonia (NH(3)) and conductivity for dry and wet seasons, respectively. Multiple linear regression identified the contribution of each variable with significant values r = 0.988, R(2) = 0.976 and r = 0.970, R(2) = 0.942 (P < 0.05) for dry and wet seasons, respectively. Repeated measure t-test confirmed that the surface water quality varies significantly between the seasons with significant value P < 0.05.

Spatial-temporal variation of surface water quality in the downstream region of the Jakara River, north-western Nigeria: A statistical approach

The pollution status of the downstream section of the Jakara River was investigated. Dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), chemical oxygen demand (COD), suspended solids (SS), pH, conductivity, salinity, temperature, nitrogen in the form of ammonia (NH(3)), turbidity, dissolved solids (DS), total solids (TS), nitrates (NO(3)), chloride (Cl) and phosphates (PO(3-)(4)) were evaluated, using both dry and wet season samples, as a measure of variation in surface water quality in the area. The results obtained from the analyses were correlated using Pearson's correlation matrix, principal component analysis (PCA) and paired sample t-tests. Positive correlations were observed for BOD(5), NH(3), COD, and SS, turbidity, conductivity, salinity, DS, TS for dry and wet seasons, respectively. PCA was used to investigate the origin of each water quality parameter, and yielded 5 varimax factors for each of dry and wet seasons, with 70.7 % and 83.1 % total variance, respectively. A paired sample t-test confirmed that the surface water quality varies significantly between dry and wet season samples (P < 0.01). The source of pollution in the area was concluded to be of anthropogenic origin in the dry season and natural origins in the wet season.