Characteristics Of Surface Water Quality Research Articles

Water quality improvement and existing challenges in the Pearl River Basin, China

This study highlights the effectiveness of a national water quality improvement initiative on water quality in the Pearl River Basin. The dynamic characteristics of surface water quality in the Pearl River Basin from 2006 to 2018 were analyzed, and the effects of driving factors, including economy, population, land use, water resources, forestry, industry, energy and animal husbandry on water quality were determined. There was a significant improvement in the overall water quality of the Pearl River basin (except Guangzhou) by controlling the discharge of wastewater pollutants and emphasizing environmental protection of forests and disposal of domestic waste. That is particularly evident from the exponential decrease of GDP normalized ammonium (NH4+-N) and COD concentrations. The modeling of water quality and driving factors indicates water quality in the Pearl River Basin was closely related to industrial pollution control investment, afforested area, innocuous disposal capacity of domestic garbage, vegetable sown area, use of natural gas, ecological water consumption, production of sulfuric acid and mutton yields. The improvement in water quality occurred at a time when GDP was increasing providing evidence that economic development and environmental protection can occur through appropriate environmental investment. It is worth noting that although water quality in Guangzhou has improved, nitrogen pollution resulting from domestic sewage and industrial pollutants remains a severe challenge for water quality in this region.

Comparative Analysis of Regression Models for Remote Sensing-based Water Quality Assessment

The 80-kilometer-long Vembanad Lake in Kerala, India, is a Ramsar site. Eutrophication is deteriorating its water quality and threatening its biodiversity. In this study, satellite imageries of Sentinel 2A and Landsat 8 OLI were utilized to determine its water quality. Various data sets of the water quality parameters viz. pH, Electrical conductivity, TSS, TDS, BOD, DO, chloride etc. are analyzed and interpreted. Regression models were developed on the parameters taken up for water quality analysis. The empirical R2 values of the developed models evidenced the accuracy of the developed mdoels. The findings show that remote sensing images are reliable for analyzing surface water quality characteristics. The comparative analysis of the model developed illustrated the effectiveness of using the imaging systems mentioned above for water quality index estimation through remote sensing.

Multiple Evaluations of the Spatial and Temporal Characteristics of Surface Water Quality in the Typical Area of the Yangtze River Delta of China Using the Water Quality Index and Multivariate Statistical Analysis: A Case Study in Shengzhou City.

Surface water assessments are of critical importance for balancing economic development with the ecological environment in rapidly developing regions. In this research, Shengzhou City, a typical town in the Yangtze River Delta region of China, was chosen to conduct a surface water quality study. As a region with a well-developed water system, monthly water quality monitoring data from eight sampling sites on the major tributaries and the mainstream were selected for six consecutive years from 2013 to 2018, containing seven important water quality indicators (pH, DO, CODMn, CODCr, BOD, NH4+-N, and TP). The comprehensive evaluation method based on the water quality index (WQI) and multivariate statistical analysis methods of cluster analysis (CA) and principal component analysis (PCA) were applied to explore the spatial and temporal changes of water quality in Shengzhou City. The main findings are as follows: (1) spatially, for three main tributaries, Xinchang River had the worst water quality, followed by Changle River, while Huangze River had the best. The water quality of the tributaries had higher volatility than the mainstream. (2) The sampling sites with similar locations had similar water quality characteristics. (3) Seasonally, for the four indicators of DO, CODMn, CODCr, and BOD, the water quality was better in the dry season while, for NH4+-N and TP, water quality was better in the wet season. The low WQI points were more likely to appear in the wet season. (4) The results of WQI assessment showed an improving trend in water quality. (5) Nitrogenous substances and organic matter were the key pollutants in this area. The research results prove that water quality evaluation methods and multivariate statistical methods are effective for the study of regional surface water quality.

Variation Characteristics of Surface Water Quality in China in Recent Years

Based on data from 839 comparable sections (sites) of the national surface water environmental quality monitoring network from 2012 to 2020, the variation tendency of surface water environmental quality over the past nine years was analyzed. The results showed that the environmental quality of surface water in China has continuously improved, the proportion of Grade Ⅰ-Ⅲ water quality increased steadily, and the proportion of inferior Grade Ⅴ water quality decreased in succession. The annual average concentration of ammonia nitrogen, total phosphorus, and permanganate index all showed a decreasing trend annually; compared with those in 2012, the three indicator concentrations respectively declined 75.9%, 48.2%, and 17.5% by 2020. In Guangxi, Hainan, and Ningxia, the proportion of Grade Ⅰ-Ⅲ water quality sections was maintained at 100%, whereas Hubei and Jiangxi showed a consecutive decreasing trend, and the other provinces showed a consecutive increasing trend. In Guangxi, Hainan, Ningxia, Hunan, and Fujian, the proportion of inferior Grade Ⅴ water quality sections remained at 0, and the other provinces showed a decreasing trend yearly. The annual average concentration of total phosphorus in Guangxi and Jiangxi and the permanganate index in Hubei, Hainan, and Liaoning increased annually, whereas that in the other provinces decreased to varying degrees. The proportion of Grade Ⅰ-Ⅲ water quality sections in Ten Major basins showed a fluctuating upward trend. The proportion of inferior Grade Ⅴ water quality in the Zhejiang and Fujian Slice Rivers was maintained at 0, and the other river basins showed a fluctuating and declining trend. The annual average of the main pollution indicators all decreased to varying degrees. In 2020, 53% of 32 important lakes were eutrophic, which increased 12% compared to that in 2012. On the whole, surface water quality has generally improved in China during the past nine years; especially since the 13th Five-Year Plan period, remarkable achievements have been made in the prevention and control of water pollution. However, there are differences among various provinces and basins, the improvement in water environmental quality is unbalanced and uncoordinated, water resources are distributed unevenly, and the eutrophication trend of lakes and reservoirs is not optimistic. In the future, water resources, water environment, and water ecology should be overall managed, and great attention should be focused on precise pollution control and ecological restoration of surface water.

Response of surface water quality characteristics to socio-economic factors in Eastern-Central China.

Following the implementation of the strictest water resource management system in China, it has become increasingly important to understand and improve the surface water quality and the rate at which water function zones reach the water quality standard. Based on the monthly monitoring data from 450 monitoring sites at the provincial borders of 27 provinces in China in 2019, the overall surface water quality at provincial boundaries in China was evaluated. The Canadian Council of Ministers of the Environment-water quality index (CCME-WQI) showed that the provincial boundary water quality exceeded the fair level, and F1 was the most influential factor. Then, 27 factors that directly or indirectly affect the surface water quality were identified, and the indirect influencing factors were integrated into the ecological environmental quality index and human activities quantitative index. Finally, the 27 factors were integrated into six factors, and the relationship between these indicators and CCME-WQI as well as the concentration of influencing elements with respect to regulatory standard limits were analyzed. The proportion of building land was the most significant factor affecting the quality of the aquatic environment in provincial boundaries. In addition, the economic development level, proportion of farmland, and degree of social development were identified as significant influencing factors. The six factors have different degrees of impact on the concentrations of major elements with respect to standard limits. This study basically explores water resource management and offers significant reference and guidelines for the improvement of the quality of surface water at provincial boundaries in China.

Combining hydrochemistry and hydrogen and oxygen stable isotopes to reveal the influence of human activities on surface water quality in Chaohu Lake Basin

The input of pollutants caused by human activities induces the deterioration of surface water quality. To reveal the characteristics of surface water quality in Chaohu Lake Basin and the influence of human activities, the hydrochemistry and stable isotope composition of hydrogen and oxygen in lake water and inflow river water were analyzed. The results show that the hydrochemical type of lake water is the Na–Cl type,while river water is the Na–Cl, Ca–Cl and mixed types. The ion proportional coefficient method and principal component analysis show that surface water is controlled by weathering of evaporated salt rocks and silicate rocks, in which Cl- and SO42- are affected by fertilizers and sewage to some extent. There is a strong correlation between conventional ions and nutrient indexes, which indicates that dissolved ions are affected not only by rock weathering but also by human activities (such as the discharge of domestic sewage or nitrogen-containing wastewater and the use of fertilizers). The stable isotope values of hydrogen and oxygen in surface water are distributed at the lower right portion of the local precipitation line and are close to it, indicating that surface water mainly originates from precipitation. The high value of d-excess values in surface water indicates that evaporation is weak. As pollution indicators, EC, Cl- and NO3- indicates that the Nanfei River, Dianbu River, Shiwuli River and Pai River flow in northwestern of Chaohu Lake Basin through Hefei urban city are severely polluted, NO3- originates from manure and sewage. Rivers flowing through farmland areas are less polluted, and the use of agricultural fertilizer contributes greatly to NO3-.

Characteristics of Surface Water Quality and Diversity of Zoobenthos in Water Bodies, An Giang Province, Vietnam

The use of zoobenthos to evaluate water quality has gained considerable interest due to its low cost and environmental friendliness. This study analyzed water and zoobenthos samples at 13 sites in the water bodies in An Giang province in the rainy season (on March) and dry season (on September) in 2018. The results showed that the surface water was contaminated by organic matters, suspended solids and coliforms. There was occurrence of 28 species of zoobenthos divided into five classes including Oligochaeta, Polychaeta, Insecta, Gastropoda, and Bivalvia in which Bivalvia was the most diverse class accounting for 75%. The densities of zoobenthos in the dry and wet season were from 30 divided into three clusters for the dry season and six clusters for the rainy season indicating seasonal variation of zoobenthos composition possibly due to variance of water and sediment characteristics. The results of Pearson correlation indicated that the composition of zoobenthos was strongly correlated with temperature, pH, N-NH4+ and N-NO3-. Using water quality index (WQI), Shannon-Wiener diversity index (H’) and associated average score per taxon (ASPT) for water quality assessment revealed that water quality ranges from medium (from α to β- mesosaprobe) to heavy pollution (Polysaprobe). There was inconsistency between using physicochemicals and diversity index of zoobenthos for water quality identification leading to the use of zoobenthos for water indication could result in misadjustment of water quality. Further study should investigate the relationship between zoobenthos and water quality in different ecological areas to better indicate role of zoobenthos in quick diagnose water quality.

Characteristics of surface water quality and stable isotopes in Bamen Bay watershed, Hainan Province, China.

Bamen Bay is located at the intersection of the Wenjiao River and Wenchang River in Hainan Province (China), where mangroves have been facing a threat of water quality deterioration. Therefore, it is imperative to study the characteristics of the surface water quality on a watershed scale. Water samples were collected three times from 36 monitoring sites from 2015 to 2016. It was found that nitrate was the main inorganic nitrogen form and all the surface water types were alkaline. Meanwhile, aquaculture water had high content of nitrogen, total phosphorus, chlorophyll a (Chl.a), total organic carbon (TOC), and chemical oxygen demand (COD). Significant spatial and temporal variations were found for most parameters. However, stable isotopes of δD and δ18O indicated that river water mainly originated from atmospheric precipitation and experienced strong evaporation. The water chemistry and isotopes of the Bamen Bay, mangroves, and aquaculture water were initially affected by the mixing of fresh water and seawater, followed by evaporation. The river and reservoir water chemistry were mainly controlled by water–rock interactions and cation exchange as deduced from the ionic relationships and Gibbs plots. These interactions involved the dissolution of calcite-, bicarbonate-, carbonate-, and calcium-containing minerals. Oxidized environments (river, reservoir, and Bamen Bay) were conducive for nitrification, while anaerobic conditions (mangrove and aquaculture water) were beneficial to the reduced nitrogen forms.

Problem identification on surface water quality in the Mun River Basin, Thailand

The largest Mekong River Tributary in Thailand, the Mun River nurtures more than 10 million people, although degradation of its water quality has been reported. This study aims to illustrate spatio-temporal patterns of water quality across the basin. Water quality datasets acquired from field sampling, questionnaires, and long-term monitoring were analyzed. The findings show seven surface water quality characteristics, which were significantly spatiotemporally dependent. During the monsoon, water quality was often found with high coliform bacteria. Salinity problem was substantial, particularly during the early monsoon in the upper northern part. The dry-season water quality was even worse, exhibiting high loadings of organic compounds, coliform bacteria, nutrient, and low dissolved oxygen. This poor water quality was found in Lam Takhong Sub-Basin and the lower basins—including the lower part of the main river, Huai Samran Sub-Basin, and Lam Se Bai Sub-Basin. The degrading water, with a rotten smell and algae bloom, was affecting the quality of supplied water, as reported by the local agencies. Discharge of household wastewater could respond to the poor water quality, exhibiting high BOD and PO43−, whereas agriculture contributes to high N-to-P ratio characteristics. Suggestions on water quality management should focus on solutions for salinity, control of direct discharges of household wastewater, promoting good agricultural practices, and properly disinfecting tap water.

Long-term trends and probability distributions of river water quality variables and their relationships with climate elasticity characteristics.

The statistical characteristics of surface water quality play fundamental roles in climate change-related studies. Climatic drivers will affect surface water quality, and such potential effects will vary between different regions and climate types. Here, we studied the long-term trends and probability distributions of water quality variables (including water temperature, pH, turbidity, DO, C-,N-,P-variables, etc.) and their relationship with climate elasticity, a non-parametric estimator of the sensitivity of the response of water quality to climate drivers, based on three typical watersheds: the Yukon, the Mekong, and the Murray. Significant decreasing trends were observed in the Yukon and Murray watersheds for the majority of water quality variables, except turbidity and filtered nitrate plus nitrite, whereas increasing trends were exhibited by most water quality variables in the Mekong watershed. Compared with the Yukon and Murray watersheds, the probability distributions of most water quality variables and their corresponding percentage change-based elasticity estimator samples are characterized by a heavy-tailed distribution in the Mekong watershed. The precipitation elasticity results are statistically meaningful in the Mekong and Murray watersheds, whereas temperature elasticity is significant in the Yukon watershed. The revealed characteristics of long-term trends and probability distributions pattern of basic water quality variables are helpful for water quality modeling. The findings suggested that the increasing trends, heavy-tailed probability distribution patterns, and the response of water quality to precipitation and temperature, especially in densely populated developing areas, can be modulated by restoration efforts, which will reduce the potential impacts of climatic and non-climatic factors.

Evolution Characteristics of Surface Water Quality Due to Climate Change and LUCC under Scenario Simulations: A Case Study in the Luanhe River Basin.

It is of great significance to study the effects and mechanisms of the key driving forces of surface water quality deterioration—climate change and LUCC (land use and land cover change). The Luanhe River Basin (LRB) in north-eastern China was examined for qualitatively and quantitatively assessing the responses of total nitrogen (TN) and total phosphorus (TP) loads on different climate scenarios and LUCC scenarios. The results show that from 1963 to 2017, the TN and TP loads basically presented a negative correlation with the temperature change (except for winter), while showing a significant positive correlation with the precipitation change. The incidence of TN pollution is sensitive to temperature increase. From 2020 to 2050, the annual average loads of TN and TP were slightly lower than from 1963 to 2017. The contribution of rising temperature was more significant on nutrient loads. Also, the incidence of TN pollution is sensitive to the future climate change. Under LUCC scenarios, the TN and TP loads and pollution incidence increased correspondingly with the decrease of natural land. The evolution characteristics analysis can provide support for the effect and adaptation-strategies study of climate change and LUCC on surface water quality.

Seasonal characteristics of surface water quality in the wastewater catchment system of an urbanizing basin

Vientiane, Lao PDR, has been subject to extensive and ongoing urbanization plans, including development of natural marshes and residentialization of paddy fields into suburban areas, despite natural marshes playing a vital role in treating wastewater from urban areas. Therefore, it is important to understand the current situation regarding the nutrient balance in these natural wastewater treatment systems to predict future conditions and design appropriate measures against water quality deterioration. However, limited data are available in Vientiane on the hydrological characteristics of water and nutrient runoff that flow into marshes through drainage canals. In this study, we conducted a periodic survey of drainage canals and Mak Hiao River in the wastewater catchment system surrounding Vientiane during the rainy and dry seasons. We monitored the discharge of surface water at 21 observation sites and analyzed water quality of nitrogen, phosphorus, and total organic carbon. These observations revealed that the concentrations of dissolved nitrogen and phosphorus were significantly higher at sites in urban areas, followed by sites in the main river basin and those in agricultural areas. Dissolved nitrogen and phosphorus concentrations varied with runoff discharge, especially in urban and river basin sites, with lower concentrations in the rainy season and higher concentrations in the dry season. On the other hand, we found no significant differences between the rainy and dry seasons in nutrient concentrations in the agricultural basin. Finally, we proposed measures to counteract the deterioration of water quality during dry seasons and simulated the impact of these measures.

Influential factors detection for surface water quality with geographical detectors in China

Surface water quality is a matter of serious concern in China. This study quantitatively analyzes the spatial–temporal characteristics of surface water quality among 100 monitoring stations in China during 2015. A geographical detector was used to detect the influential annual and seasonal factors. Surface water quality is primarily controlled by the content of nutrient pollutants and organic pollutants. Natural factors (precipitation, temperature, soil erosion, and terrain) and anthropogenic factors [land use type, population density, and per capita gross domestic product (GDP-per-capita)] were selected as geographical proxies to be tested for their explanatory power for surface water quality. Results indicated that the top three factors influencing the annual mean of nutrient pollutants were the population density, terrain, and precipitation, the explanatory power of which was 0.82, 0.35, and 0.24, respectively. The interactive explanatory power for population density and terrain was 0.88 and for population density and precipitation was 0.87, both exhibiting enhanced interaction relationships. The top three factors influencing the annual mean of organic pollutants were population density, temperature, and basin, the explanatory power of which was 0.46, 0.29, and 0.27, respectively. The interactive explanatory power for population density and basin was 0.80 and for terrain and precipitation was 0.82, both demonstrating a nonlinear enhanced interaction relationship. For seasonal changes, the nutrient pollutants and organic pollutants were both affected by agricultural runoff due to seasonal farming. This study revealed that anthropogenic factors influenced surface water quality two to three times more than natural factors.

Assessment of Seasonal Variation in Water Quality in River Rwizi Using Multivariate Statistical Techniques, Mbarara Municipality, Uganda

Assessment of seasonal variations in surface water quality characteristics is an essential aspect for evaluating water pollution due to both natural and anthropogenic influences on water resources. In this study, temporal variations of water quality in river Rwizi section within Mbarara municipality, Uganda, were assessed using multivariate statistical methods. This river section is a major source of water for the inhabitants of Mbarara municipality. Water samples from five sites were analyzed for physicochemical parameters such as pH, EC, turbidity, temperature, TSS, TDS, alkalinity, salinity, colour, NH3-N, , total hardness, BOD, COD, DO, Ca, Mg, Fe, and Mn. About 50% of sites recorded colour above 800 Pt Co, 60% of sites recorded turbidity above maximum permissible limit of 100 mg/l, attributable to erosion and mineral matter. pH for dry season ranged between 6.5 and 8.5 whereas for rainy season was below 6.0. All study sites recorded total Fe above 0.3 mg/l and Mn below 0.5 mg/l, attributable to chemical weathering of host rock materials as well as from industrial effluent. About 60% of sites recorded COD above 100 mg/l, 40% and 80% of study sites showed BOD above 50 mg/l in dry and rainy seasons respectively. Hardness ranged between 50 and 100 mg/l indicating that the water is moderately soft. Colour, turbidity, alkalinity, TSS, TDS, salinity, pH, hardness, Fe, Mn, NH3-N, BOD, COD, and DO were higher in rainy season, as a result of erosion, discharge of domestic and industrial waste. Mg, Ca, and were higher during dry season due to high evaporation of water from the river. PCA/FA determined that 81.2% of the total variance was explained by the first factor for the dry season and 69.2% for rain season. These results revealed that water pollution resulted primarily from domestic waste water, agricultural runoff and industrial effluents.

Hysico-Chemical Characteristics of Surface Water Quality of Urban Ponds in Thiruvananthapuram District, Kerala

hysico-Chemical Characteristics of Surface Water Quality of Urban Ponds in Thiruvananthapuram District, Kerala

Descriptive Characteristics of Surface Water Quality in Hong Kong by a Self-Organising Map.

In this study, principal component analysis (PCA) and a self-organising map (SOM) were used to analyse a complex dataset obtained from the river water monitoring stations in the Tolo Harbor and Channel Water Control Zone (Hong Kong), covering the period of 2009–2011. PCA was initially applied to identify the principal components (PCs) among the nonlinear and complex surface water quality parameters. SOM followed PCA, and was implemented to analyze the complex relationships and behaviors of the parameters. The results reveal that PCA reduced the multidimensional parameters to four significant PCs which are combinations of the original ones. The positive and inverse relationships of the parameters were shown explicitly by pattern analysis in the component planes. It was found that PCA and SOM are efficient tools to capture and analyze the behavior of multivariable, complex, and nonlinear related surface water quality data.

Evaluation of surface water quality characteristics in Ogun watershed of south western Nigeria using principal component analysis

Utilization of water resources across watersheds in Nigeria has been without commensurate at-tention to protection from degradation at the basin level. One of the strategies in river basin management is effective monitoring and assessment of pollution levels, patterns and identifica-tion of major variables driving such degradation most importantly at the watershed scale. Therefore, it is important to evaluate how critical a quality indicator is in its contribution as well as its spatial extent within and across the entire water basin. Twenty six water quality indicators were assessed in Ogun watershed, Nigeria. The nitrogen forms; TN, NO 3 - and NH 4- N were significantly low in the watershed while TP and PO 4 3- were higher (p<0.05). The BOD 5 and COD were significantly high which explains the low DO observed in the watershed. High levels of Fe, Cd, Pb, Mn as well as E-coli and Fecal Coliform were recorded. Using Principal Component Analysis (PCA), 77% (20 out of 26) of the water quality indicators examined were found to be critical. These explained more than 90% of the observed water quality variation across the watershed. The variable inclusion level showed that these parameters were critical in 70% of the locations across the watershed. The selection of 77% of the parameters investigated by PCA over 70% of the locations revealed high levels of diffused pollution that calls for urgent attention. Keywords : Principal Component Analysis, Ogun watershed, Water Quality, Pollution, Nigeria

Statistical Approach in Determining the Spatial Changes of Surface Water Quality at the Upper Course of Kano River, Nigeria

In this study, statistical techniques were used to evaluate the spatial variation of surface water quality and pollution source apportionment in Kano River, Nigeria. Triplicate water samples were collected from 30 sampling sites along the upper course of Kano River and analyzed for 23 parameters which include dissolved oxygen (DO), 5-day biochemical oxygen demand $$(\hbox {BOD}_{5})$$ , chemical oxygen demand, pH, temperature, salinity, conductivity, dissolved solids, suspended solids, total solids, turbidity, chloride (Cl), ammonia $$(\hbox {NH}_{3})$$ , nitrate $$(\hbox {NO}_{3})$$ , potassium (K), magnesium (Mg), sodium (Na), calcium (Ca), phosphate $$(\hbox {PO}_{4})$$ , iron (Fe), zinc (Zn), Escherichia coliform (E. coli), and total coliform (T. coli). Hierarchical agglomerative cluster analysis grouped the 30 sampling sites into three statistically significant clusters based on similarities of surface water quality characteristics. Principal component and factor analyses (PCA and FA) were used to investigate the source of water quality parameters and to identify three major water pollution sites: high pollution sites, moderate pollution site, and low pollution site which explained more than 65 % of the total variance in water quality. Discriminant analysis provided a better result with great discriminatory ability, pattern recognition, and important data reduction using only seven parameters (DO, $$\hbox {BOD}_{5}$$ , pH, $$\hbox {NH}_{3}$$ , Cl, E. coli, and T. coli) for spatial variation and affording more than 90 % correct cases assignation. Further, one-way analysis of variance (one-way ANOVA) was applied to the three factors obtained from PCA and FA to compare the variation within and between the factors, the result showed significant differences $$(p < 0.05)$$ between the factors. The study provides a new insight into the environmental quality in Kano River for effective surface water quality management and protection.

Surface Water Quality of Chittagong University Campus, Bangladesh

Some important characteristics of surface water quality of Chittagong University campus, Bangladesh were evaluated for use in domestic, industrial, agriculture, recreation and aquaculture purposes. Fifteen water samples were collected and analyzed in the laboratory of the Department of Soil Science of the University of Chittagong. The study revealed that most physical parameters and inorganic elements are not a serious problem for the water bodies of Chittagong University campus. On the basis of sample analysis it can be said that the surface water of Chittagong University campus is suitable for common uses.

Spatial characteristics of surface water quality in the Haicheng River (Liao River basin) in Northeast China

Spatial variations of the water quality in the Haicheng River during April and October 2009 were evaluated for the national monitoring program on water pollution control and treatment in China. The spatial autocorrelation analysis with lower Moran's I values displayed the spatial heterogeneity of the 12 physicochemical parameters among all the sampling sites of the river. The one-way ANOVA showed that all variables at different sampling sites had significant spatial differences (p < 0.01). Based on the similarity of water quality characteristics, cluster analysis grouped the 20 sampling sites into three clusters, related with less polluted, moderately polluted and highly polluted sites. The factor analysis extracted three major factors explaining 76.4 % of the total variance in the water quality data set, i.e., integrated pollution factor, nitrogen pollution factor and physical factor. The results revealed that the river has been severely polluted by organic matter and nitrogen. The major sources leading to water quality deterioration are complex and ascribed to anthropogenic activities, e.g., domestic and industrial wastewater discharges, agricultural runoff, and animal rearing practices. 2013 Springer-Verlag Berlin Heidelberg.