Yazar "Boyacioglu, Huelya" seçeneğine göre listele

Listeleniyor 1 - 4 / 4
  • Küçük Resim Yok
    Öğe
    EFFICIENCY OF WATER QUALITY INDEX APPROACH AS AN EVALUATION TOOL
    (Soc Ecological Chemistry & Engineering, 2013) Boyacioglu, Huelya; Gundogdu, Vildan
    This study aimed to demonstrate efficiency of documented index method "universal water quality index-UWQI" to evaluate surface water quality and investigate seasonal and temporal changes, in the case of Gediz River Basin Turkey. UWQI expressed results relative to levels according to criteria specified in European legislation (75-440 EEC). The method produced a unitless number ranging from 1 to 100 and a higher number was indicator of better water quality. Water quality is classified into five classes and index scores between 95-100 represent excellent and lower than 24 represent poor quality. In the study, dissolved oxygen-DO, pH, mercury-Hg, cadmium-Cd, total phosphorus-TP, biochemical oxygen demand-BOD and nitrate nitrogen-NO3-N have been chosen as index determinants. Samples analyzed for these variables were collected from five stations on monthly basis along two years. Based on UWQI classification scheme, water quality at sampling stations had scores below 40 and assigned to "marginal" which is between fair and poor quality class. On the other hand sub-indices of water quality determinants showed seasonal differences for some parameters. Cd concentrations were higher in "high flow" and lower values were observed in "low flow" periods. This was explained by negative impact of urban runoff on water quality. On the other hand DO concentrations were higher in "high flow" period. Under "low flow" conditions water quality at upstream stations (where the industrial density is low) was comparably better than downstream part. The study showed that index approach can be efficient tool to: a) evaluate water quality, b) investigate spatial and seasonal variations and finally, c) extract required information from complex data sets that is understandable by non-technical people.
  • Küçük Resim Yok
    Öğe
    EFFICIENCY OF WATER QUALITY INDEX APPROACH AS AN EVALUATION TOOL
    (Soc Ecological Chemistry & Engineering, 2013) Boyacioglu, Huelya; Gundogdu, Vildan
    This study aimed to demonstrate efficiency of documented index method "universal water quality index-UWQI" to evaluate surface water quality and investigate seasonal and temporal changes, in the case of Gediz River Basin Turkey. UWQI expressed results relative to levels according to criteria specified in European legislation (75-440 EEC). The method produced a unitless number ranging from 1 to 100 and a higher number was indicator of better water quality. Water quality is classified into five classes and index scores between 95-100 represent excellent and lower than 24 represent poor quality. In the study, dissolved oxygen-DO, pH, mercury-Hg, cadmium-Cd, total phosphorus-TP, biochemical oxygen demand-BOD and nitrate nitrogen-NO3-N have been chosen as index determinants. Samples analyzed for these variables were collected from five stations on monthly basis along two years. Based on UWQI classification scheme, water quality at sampling stations had scores below 40 and assigned to "marginal" which is between fair and poor quality class. On the other hand sub-indices of water quality determinants showed seasonal differences for some parameters. Cd concentrations were higher in "high flow" and lower values were observed in "low flow" periods. This was explained by negative impact of urban runoff on water quality. On the other hand DO concentrations were higher in "high flow" period. Under "low flow" conditions water quality at upstream stations (where the industrial density is low) was comparably better than downstream part. The study showed that index approach can be efficient tool to: a) evaluate water quality, b) investigate spatial and seasonal variations and finally, c) extract required information from complex data sets that is understandable by non-technical people.
  • Küçük Resim Yok
    Öğe
    Surface water quality assessment by environmetric methods
    (Springer, 2007) Boyacioglu, Huelya; Boyacioglu, Hayal
    This environmetric study deals with the interpretation of river water monitoring data from the basin of the Buyuk Menderes River and its tributaries in Turkey. Eleven variables were measured to estimate water quality at 17 sampling sites. Factor analysis was applied to explain the correlations between the observations in terms of underlying factors. Results revealed that, water quality was strongly affected from agricultural uses. Cluster analysis was used to classify stations with similar properties and results distinguished three groups of stations. Water quality at downstream of the river was quite different from the other part. It is recommended to involve the environmetric data treatment as a substantial procedure in assessment of water quality data.
  • Küçük Resim Yok
    Öğe
    Utilization of statistics based classification approach to investigate water supply profile of Turkey
    (Springer, 2009) Boyacioglu, Hayal; Boyacioglu, Huelya
    In the paper water supply profile of Turkey was examined. In this scope, the questionnaire survey conducted by Turkish Statistical Institute in 2004 to investigate annual amount of water abstracted to drinking water networks by type of resources in 81 provinces was evaluated. In the questionnaire, sources were grouped under five categories as spring, (artificial) lake, river, reservoir and well. Due to the complex and multivariate characteristics of the data sets, to replace a large collection of variables with a smaller number of factors the statistical method "factor analysis" was performed. Results revealed that, water supply systems in the country were mainly governed by groundwater sources (well and/or spring). However, in the northeastern part of the country, rivers were allocated for drinking water supply. On the other hand, reservoir dependent cities were densely located in Marmara, Central Anatolia and Southeast Anatolia Regions. This study showed that statistics based classification methods assist decision makers to extract information from multidimensional complex data sets representing environmental conditions.