scholarly journals Danube water quality and assessment on ecotourism in the biosphere reserve ‘Bačko Podunavlje’ in Serbia

2020 ◽  
Vol 20 (4) ◽  
pp. 1215-1228
Author(s):  
Sanja Obradović ◽  
Milana Pantelić ◽  
Vladimir Stojanović ◽  
Aleksandra Tešin ◽  
Dragan Dolinaj
Keyword(s):  
Water Quality ◽  
Ecological Status ◽  
Biosphere Reserve ◽  
Surface Water Quality ◽  
Principal Component ◽  
Quality Parameters ◽  
Danube River ◽  
Multivariate Statistical ◽  
Limit Values ◽  
Starting Point

Abstract ‘Bačko Podunavlje’ represents one of the largest and the best-preserved wetland areas of the upper Danube. Water quality is crucial for nature in protected areas and ecotourism. The paper is based on data for the period 1992–2016. Using multivariate statistical analysis, water quality was defined. One-factor analysis of variations is the starting point for the analysis of time variables (annual and monthly analysis). The principal component analysis (PCA) of the ten quality parameters is in the three factors that determine the greatest impact on the change in water quality. Results revealed the satisfactory ecological status of the Danube River in these sections (Bezdan and Bogojevo) and there is no threat that the biodiversity of this area is endangered by poor water quality, which fully justifies the possibilities for intensive development of ecotourism in the biosphere reserve. Suspended solids are the only parameter that exceeds the allowed limit values in a larger number of measurements, especially in the summer period of the year. Other analyzed water quality parameters range within the allowed limit values for the second class of surface water quality based on the Law on Waters (Republic of Serbia) and in accordance with the Water Quality Classification Criteria of ICPDR.

scholarly journals Multivariate Monitoring of Surface Water Quality: Physico-Chemical, Microbiological and 3D Fluorescence Characterization

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1673
Author(s):  
Claude Daou ◽  
Mervat El Hoz ◽  
Amine Kassouf ◽  
Bernard Legube
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Anthropogenic Activities ◽  
Surface Water Quality ◽  
Principal Component ◽  
Specific Weight ◽  
Quality Parameters ◽  
Primary Objective ◽  
Fluorescence Excitation ◽  
Fluorescence Characteristics

The primary objective of this study is to explore a water quality database on two Mediterranean rivers (the Kadisha-Abou Ali and El Jaouz rivers—located in north Lebanon), considering their physicochemical, microbiological and fluorescence characteristics. Principal Component Analysis (PCA) was applied to the matrix gathering physicochemical and microbiological data while the Common Components and Specific Weight Analysis (CCSWA) or ComDim was used for fluorescence excitation-emission matrices (EEMs). This approach provided complementary and valuable information regarding water quality in such complex ecosystem. As highlighted by the PCA and ComDim scores, the Kadisha-Abou Ali River is highly influenced by anthropogenic activities because its watershed districts are intensively populated. This influence reveals the implication of organic and bacteriological parameters. To the contrary, the El Jaouz watershed is less inhabited and is characterized by mineral parameters, which determines its water quality. This work highlighted the relationship between fluorescence EEMs and major water quality parameters, enabling the selection of reliable water quality indicators for the studied rivers. The proposed methodology can surely be generalized to the monitoring of surface water quality in other rivers. Each customized water quality fingerprint should constantly be inspected in order to account for any emerging pollution.

scholarly journals Application of multivariate statistical techniques in the water quality assessment of Danube river, Serbia

2015 ◽  
Vol 41 (4) ◽  
pp. 96-103 ◽  
Author(s):  
Danijela Voza ◽  
Milovan Vukovic ◽  
Ljiljana Takic ◽  
Djordje Nikolic ◽  
Ivana Mladenovic-Ranisavljevic
Keyword(s):  
Water Quality ◽  
Water Quality Management ◽  
Surface Water Quality ◽  
Principal Component ◽  
Water Quality Assessment ◽  
Water Quality Monitoring ◽  
Danube River ◽  
Multivariate Techniques ◽  
Data Set ◽  
Political Issue

AbstractThe aim of this article is to evaluate the quality of the Danube River in its course through Serbia as well as to demonstrate the possibilities for using three statistical methods: Principal Component Analysis (PCA), Factor Analysis (FA) and Cluster Analysis (CA) in the surface water quality management. Given that the Danube is an important trans-boundary river, thorough water quality monitoring by sampling at different distances during shorter and longer periods of time is not only ecological, but also a political issue. Monitoring was carried out at monthly intervals from January to December 2011, at 17 sampling sites. The obtained data set was treated by multivariate techniques in order, firstly, to identify the similarities and differences between sampling periods and locations, secondly, to recognize variables that affect the temporal and spatial water quality changes and thirdly, to present the anthropogenic impact on water quality parameters.

scholarly journals Long-Term Trends in Water Quality Indices in the Lower Danube and Tributaries in Romania (1996–2017)

2021 ◽  
Vol 18 (4) ◽  
pp. 1665
Author(s):  
Rodica-Mihaela Frîncu
Keyword(s):  
Water Quality ◽  
Biosphere Reserve ◽  
Principal Component ◽  
River Basin Management ◽  
Danube River ◽  
Quality Indices ◽  
Ecological Value ◽  
Water Quality Indices ◽  
Long Term Trends

The Danube River is the second longest in Europe and its water quality is important for the communities relying on it, but also for supporting biodiversity in the Danube Delta Biosphere Reserve, a site with high ecological value. This paper presents a methodology for assessing water quality and long-term trends based on water quality indices (WQI), calculated using the weighted arithmetic method, for 15 monitoring stations in the Lower Danube and Danube tributaries in Romania, based on annual means of 10 parameters for the period 1996–2017. A trend analysis is carried out to see how WQIs evolved during the studied period at each station. Principal component analysis (PCA) is applied on sub-indices to highlight which parameters have the highest contributions to WQI values, and to identify correlations between parameters. Factor analysis is used to highlight differences between locations. The results show that water quality has improved significantly at most stations during the studied period, but pollution is higher in some Romanian tributaries than in the Danube. The parameters with the highest contribution to WQI are ammonium and total phosphorus, suggesting the need to continue improving wastewater treatment in the studied area. The methodology and the results of the study may be very useful instruments for specialists and decision makers in updating river basin management plans and prioritising intervention measures.

scholarly journals EVALUATING SURFACE WATER QUALITY AND WATER MONITORING PARAMETERS IN THE TIEN RIVER, VIETNAMESE MEKONG DELTA

2021 ◽  
Vol 83 (3) ◽  
pp. 29-36
Author(s):  
Thanh Giao Nguyen ◽  
Vo Quang Minh
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Monitoring Program ◽  
Oxygen Demand ◽  
Surface Water Quality ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Water Monitoring ◽  
Water Quality Parameters

The study aimed to evaluate the surface water quality of the Tien River and identify water quality parameters to be monitored using the water quality monitoring data in the period of 2011 - 2019. The water samples were collected at five locations from Tan Chau to Cho Moi districts, An Giang province for three times per year (i.e., in March, June, and September). Water quality parameters included temperature (oC), pH, dissolved oxygen (DO), total suspended solids (TSS), nitrate (NO3--N), orthophosphate (PO43--P), biological oxygen demand (BOD), and coliforms. These parameter results were compared with the national technical regulation on surface water quality QCVN 08-MT: 2015/BTNMT, column A1. Principal component analysis (PCA) was used to identify the sources of pollution and the main factors affecting water quality. The results of this study showed that DO concentration was lower and TSS, BOD, PO43--P, coliforms concentrations in the Tien river exceeded QCVN 08-MT: 2015/BTNMT, column A1. pH, temperature, and NO3--N values were in accordance with the permitted regulation. The water monitoring parameters were seasonally fluctuated. DO, BOD, TSS, and coliforms concentrations were higher in the rainy season whereas NO3--N and PO43--P were higher in the dry season. The PCA results illustrated that pH, TSS, DO, BOD, PO43--P and coliforms should be included in the monitoring program. Other indicators such as temperature and NO3--N could be considered excluded from the program to save costs. 

scholarly journals Interpretation of the results of surface water quality applying multivariate analysis

2015 ◽  
Vol 69 (1) ◽  
pp. 29-36 ◽  
Author(s):  
Borko Matijevic ◽  
Djendji Vastag ◽  
Milena Becelic-Tomin ◽  
Bozo Dalmacija ◽  
Suzana Apostolov
Keyword(s):  
Water Quality ◽  
Statistical Analysis ◽  
Surface Water ◽  
Ecological Status ◽  
Surface Water Quality ◽  
Water Bodies ◽  
Chemical Parameters ◽  
Multivariate Statistical ◽  
Surface Water Bodies ◽  
The Given

Monitoring of surface water, through the analysis of physical-chemical and chemical parameters is a very important factor in the control of water quality and the health of living beings. Surface water quality is largely determined by the nature (atmospherics) and anthropogenic processes (discharge of municipal and industrial waste water). The results of monitoring of surface water are usually too expensive and difficult for correct interpreting, due to the spatial and temporal variations in water quality. By applying Multivariate statistical analysis can achieve significant reductions of the ampleness of the available data and the better interpretation of the obtained results about the quality and ecological status/potential of water. In this paper, were analyzed selected results of the analysis of surface water in AP Vojvodina in 2011 year by using multivariate statistical analysis (cluster analysis and principal components analysis). These techniques allow the interpretation of the results of the monitoring program of investigated surface water bodies and simultaneous identification of registered influence and potential sources of pollution on the quality of the given water bodies. With both methods applied and the division of water bodies tested in the same manner at the origin (natural and artificial) and on the basis of territorial belonging monitoring stations (Banat and Backa). Individual variations are discussed in corresponding differences in individual measuring stations in relation to others. Application of the given method, a grouping of the examined indicators of water quality in the following factors: hydro-chemical factor, ecological factor, the factor point pollution and diffusion. The obtained results confirm the initial hypothesis that the use of different statistical methods can identify the main factors that have an impact on the ecological status and ecological potential of water bodies and to improve the existing monitoring. In addition, analysis of the extracted surface water bodies where it is necessary to implement simultaneous monitoring of the biological quality elements to determine whether chemical parameters ensure the functioning of ecosystems.

scholarly journals Water Quality Parameters and Monitoring Soft Surface Water Quality Using Statistical Approaches

2021 ◽  
Author(s):  
Romana Drasovean ◽  
Gabriel Murariu
Keyword(s):  
Water Quality ◽  
Correlation Coefficients ◽  
Surface Water Quality ◽  
Life Forms ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Danube River ◽  
Soft Surface ◽  
The Matrix ◽  
External Causes

Water is the matrix of life and is indispensable on Earth. Water has a multitude of applications and all known life forms depend on it. Therefore, water quality is important for all of us. Water quality can be represented by a set of physical, chemical, biological and bacteriological characteristics. These parameters allow water to be classified in multiple categories leading to its use for a specific purpose. This chapter establishes the connections between external causes and their effect on water quality parameters. In order to provide information on water quality, different Water Quality Index (WQI) models can be used. In order to study the association between water quality parameters, several correlation coefficients have been developed. For a coherent statistical approach, we have used Pearson and Spearman correlations. In order to exemplify the manner in which WQI can be calculated and interpreted, we used a series of data from our previous work, consisting of 13 parameters measured for water samples taken from the Danube River, from Galati City area, Romania.

scholarly journals Assessment of Water Quality for Aquaculture in Hau River, Mekong Delta, Vietnam Using Multivariate Statistical Analysis

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3307
Author(s):  
Fridah Gacheri Mutea ◽  
Howard Kasigwa Nelson ◽  
Hoa Van Au ◽  
Truong Giang Huynh ◽  
Ut Ngoc Vu
Keyword(s):  
Water Quality ◽  
Principal Component ◽  
Quality Parameters ◽  
Point Sources ◽  
Water Quality Parameters ◽  
Soluble Solids ◽  
Accumulation Factor ◽  
Multivariate Statistical ◽  
Aquaculture Production

The deterioration signs of water quality in the Hau River are apparent. The present study analyzed the surface water quality of the Hau River using multivariate statistical techniques, including principal component analysis (PCA) and Cluster Analysis (CA). Eleven water quality parameters were analyzed at 19 different sites in An Giang and Can Tho Provinces for 12 months from January to December 2019. The findings show high levels of Biological Oxygen Demand (BOD), Total Soluble Solids (TSS), and total coliform, all year round. The PCA revealed that all the water quality parameters influenced the water quality of the Hau River, hence the relevance for water sample scrutiny. The dendrogram of similarity between sampling sites showed a maximum similarity of 95.6%. The Accumulation Factor (AF) trend showed that the concentrations/values of TSS, BOD, and phosphate (PO43−) in the downstream were 1.29, 1.53, and 1.52 times, respectively, greater than the upstream levels. Despite most of the parameters analyzed supporting aquaculture production, caution is needed in the regulation of pollution point sources to undertake sustainable aquaculture production.

Hydrochemical Assessment Of Jhilmila Lake, Kanchanpur, Nepal

2021 ◽  
Vol 14 (14) ◽  
pp. 124-131
Author(s):  
Khadka Bahadur Pal ◽  
Kiran Bishwakarma ◽  
Tarka Bahadur Chalaune ◽  
Durga Upadhaya ◽  
Tark Raj Joshi ◽  
...  
Keyword(s):  
Water Quality ◽  
Sustainable Management ◽  
Principal Component ◽  
Organic Pollution ◽  
Quality Parameters ◽  
Standard Test ◽  
Total Hardness ◽  
Test Procedures ◽  
Multivariate Statistical ◽  
Wetland Ecosystems

Freshwater contamination remains a challenging issue for the sustainable management of wetland ecosystems. This study aims to evaluate the water quality of Jhilmila Lake, Kanchanpur, Nepal by adopting standard test procedures, geochemical indices, and multivariate statistical analysis. The surface water samples were collected during the postmonsoon season in 2018 to assess the hydrochemical parameters such as pH, electrical conductivity (EC), total dissolved solids (TDS) and dissolved oxygen (DO), ammonium (NH4+ ), sodium (Na+), potassium (K+), calcium (Ca2+), magnesium (Mg2+), chloride (Cl-), sulphate (SO42-), nitrate (NO3-), phosphate (PO43-), bicarbonate (HCO3-) and total hardness (TH). The EC ranged from 162-190 µS/cm while TDS was 87-101 mg/L. The concentration of DO in the lake was in the range of 4.77-6.21 mg/L, indicated mild organic pollution. Moreover, the results revealed the moderate alkaline nature of water with the pattern of average ionic dominance of Ca2+>Na+>Mg2+ >K+>NH4+ for cations, and HCO3˗> Cl-> SO42- > NO3- > PO43- for anions. The principal component analysis demonstrated four major components indicating the association of EC, TDS, Ca2+, Mg2+, and HCO3- ; Na+ , PO43- and SO42-; NO3- and K+ ; and Cl- for PC1, PC2, PC3, and PC4, respectively exhibiting both the geogenic and anthropic origin. Overall, the Jhilmila Lake was less polluted, and all the measured water quality parameters were found within permissible limits in terms of drinking purposes. The findings of this study could help for the sustainable management of the lake by providing better insights into the water quality and hydrochemistry of the lake.

scholarly journals Water Quality Assessment of Porsuk River, Turkey

2010 ◽  
Vol 7 (2) ◽  
pp. 593-599 ◽  
Author(s):  
Suheyla Yerel
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Surface Water ◽  
Surface Water Quality ◽  
Principal Component ◽  
Statistical Techniques ◽  
Multivariate Statistical Techniques ◽  
Multivariate Statistical ◽  
Porsuk River

The surface water quality of Porsuk River in Turkey was evaluated by using the multivariate statistical techniques including principal component analysis, factor analysis and cluster analysis. When principal component analysis and factor analysis as applied to the surface water quality data obtain from the eleven different observation stations, three factors were determined, which were responsible from the 66.88% of total variance of the surface water quality in Porsuk River. Cluster analysis grouped eleven observation stations into two clusters under the similarity of surface water quality parameters. Based on the locations of the observation stations and variable concentrations at these stations, it was concluded that urban, industrial and agricultural discharge strongly affected east part of the region. Finally, this study shows that the usefulness of multivariate statistical techniques for analysis and interpretation of datasets and determination pollution factors for river water quality management.

scholarly journals Effects of Multi-Dike Protection Systems on Surface Water Quality in the Vietnamese Mekong Delta

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1010 ◽  
Author(s):  
Huynh Vuong Thu Minh ◽  
Masaaki Kurasaki ◽  
Tran Van Ty ◽  
Dat Quoc Tran ◽  
Kieu Ngoc Le ◽  
...  
Keyword(s):  
Water Quality ◽  
Surface Water ◽  
Water Samples ◽  
Mekong Delta ◽  
Surface Water Quality ◽  
Quality Parameters ◽  
Flood Hazards ◽  
Water Control ◽  
Multivariate Statistical ◽  
Protection Systems

The Vietnamese Mekong Delta (VMD) is one of the largest rice-growing areas in Vietnam, and exports a huge amount of rice products to destinations around the world. Multi-dike protection systems have been built to prevent flooding, and have supported agricultural intensification since the early 1990s. Semi-dike and full-dike systems have been used to grow double and triple rice, respectively. Only a small number of studies have been conducted to evaluate the water quality in the VMD. This study aimed to analyze the spatiotemporal variation of water quality inside the dike-protected area. Surface water samples were collected in the dry and wet seasons at 35 locations. We used multivariate statistical analyses to examine various water quality parameters. The mean concentrations of COD, NH4+, NO3−, PO43−, EC, and turbidity were significantly higher in water samples inside the full-dike system than in water samples from outside the full-dike systems and inside the semi-dike systems in both seasons. High concentrations of PO43− were detected in most of the primary canals along which residential, tourist areas and local markets were settled. However, NO3− was mainly found to be higher in secondary canals, where chemical fertilizers were used for rice intensification inside the dike system. Water control infrastructures are useful for preventing flood hazards. However, this has an adverse effect on maintaining water quality in the study area.

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