International Soil and Water Conservation Research · 2018 · 278 citations · 34 references
Groundwater QualityEnvironmental MonitoringEngineeringWater ContaminationWater Quality MonitoringWater Quality ManagementPearson Correlation IndexWater Quality ForecastingEnvironmental ChemistryMarine PollutionPrincipal Component AnalysisHydrogeologySediment QualitySediment-water InteractionPollution IndicatorsWater QualityGroundwater PollutionEcotoxicologyEnvironmental EngineeringPazarsuyu StreamMultivariate Statistical Methods
Monthly water and sediment samples from four stations along Pazarsuyu Stream (June 2014–May 2015) were analyzed with standard methods, and multivariate statistics and pollution indices (EF, CF, Igeo, PERI) were used to assess spatio‑temporal water quality and sediment metal contamination. Water quality at several stations exceeded national and international criteria, PCA revealed six factors explaining 82.9 % of the variation, sediment metals ranked Fe > Mn > Zn > Pb > Cu > Cr > Co > Cd with Pb showing high enrichment, indicating that the stream can be used for irrigation with caution but requires extensive treatment before domestic use.
The spatio-temporal variations of surface water quality and the level of metal contamination in the sediment of Pazarsuyu Stream were determined by using multivariate statistical techniques and pollution indicators, respectively. The water and sediment samples were collected monthly from four different stations along the Pazarsuyu Stream between June 2014 and May 2015 and analyzed using standard methods. Results were assessed according to national and international water quality criteria and the water quality parameters in some stations were found to be over these criteria levels. The present study showed that statistical techniques such as Pearson Correlation Index (PCI), Principal Component Analysis (PCA), Cluster Analysis (CA), One Way ANOVA need to be used to get better information for the studies on the water quality of surface waters. PCA identified six factors accounting for 82.88% of the total variation in the data. The abundance of sediment heavy metals was in the order of Fe > Mn > Zn > Pb > Cu > Cr > Co > Cd. The heavy metal contamination in the sediments was evaluated by applying the enrichment factor (EF), contamination factor (CF), geoaccumulation index (Igeo) and potential ecological risk index (PERI). Pb was heavily contaminated and has a significant enrichment of contamination according to calculated EF values. Therefore, the stream water can be used for irrigation with precaution but extensive treatment required before using for domestic purposes to prevent adverse public health effects.
34
INDEX OF GEOACCUMULATION IN SEDIMENTS OF THE RHINE RIVER
Gerrit Müller · GeoJournal · 1969 · 4.1K citations