Cüneyt Güler

Delineation of hydrochemical facies distribution in a regional groundwater system by means of fuzzy c-means clustering

[1] In this paper, classification of a large hydrochemical data set (more than 600 water samples and 11 hydrochemical variables) from southeastern California by fuzzy c-means (FCM) and hierarchical cluster analysis (HCA) clustering techniques is performed and its application to hydrochemical facies delineation is discussed. Results from both FCM and HCA clustering produced cluster centers (prototypes) that can be used to identify the physical and chemical processes creating the variations in the water chemistries. There are several advantages to FCM, and it is concluded that FCM, as an exploratory data analysis technique, is potentially useful in establishing hydrochemical facies distribution and may provide a better tool than HCA for clustering large data sets when overlapping or continuous clusters exist. INDEX TERMS: 1806 Hydrology: Chemistry of fresh water; 1829 Hydrology: Groundwater hydrology; 1831 Hydrology: Groundwater quality; 1871 Hydrology: Surface water quality; KEYWORDS: clustering techniques, fuzzy logic, fuzzy c-means, hydrochemical facies, hydrochemistry inverse modeling

Spatial distribution patterns and temporal trends of heavy-metal concentrations in a petroleum hydrocarbon-contaminated site: Karaduvar coastal aquifer (Mersin, SE Turkey)

The aim of this study was to investigate spatiotemporal variations in groundwater heavy-metal concentrations at the Karaduvar agricultural-industrial district (Mersin, SE Turkey), where parts of the underlying coastal aquifer has been polluted by petroleum hydrocarbons (PHCs) from diverse sources. The water chemistry data for the present study is comprised of 275 samples collected during 2006–2010 from 55 water-supply wells. The samples were analyzed in situ for physical parameters (EC, DO, pH, and temperature) and in the laboratory for As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb and Zn using the ICP-MS method. Box–whisker plots and principal components analysis (PCA) method were employed to determine the seasonal changes occurring in heavy-metal concentrations and to identify source apportionment of pollution parameters in groundwater. During the monitoring period, in many wells, heavy-metal concentrations (except for Cd) exceeded the limit values set by Turkish Water Pollution Control Directive (No: 25687). Results from the PCA suggest that elevated Mn, Fe, Co, Ni and As concentrations may be linked to oxidation–reduction of geogenic Mn/Fe oxyhydroxides in PHC-contaminated parts. The high concentrations of Cu, Mo and probably Cd in background areas result from the agricultural and petrochemical activities conducted in the recent past. At the site, high Pb and Zn concentrations are probably related to agricultural activities in PHC-contaminated areas, whereas Cr can be solely attributed to lithogenic sources. At the Karaduvar site, heavy-metal pollution in groundwater is found to be much more persistent than PHC contamination.

Delineating compositionally different dykes in the Ulukısla basin (Central Anatolia, Turkey) using computer-enhanced multi-spectral remote sensing data

In the Ulukışla basin (Central Anatolia, Turkey) several geological mapping campaigns were carried out using conventional field methods to delineate compositionally different Middle–Upper Eocene dykes. However, complete and correct mapping of these dykes was hampered by rugged terrain, lack of road access, wide spatial dyke distributions with small exposures and diverse weathering of these dykes. For these reasons, Landsat‐5 Thematic Mapper (TM) satellite image of the study area was used to facilitate delineation of the exact boundaries of gabbroic, dioritic and trachytic dykes found in the area. Remotely sensed data were analysed using several image enhancement procedures, including colour composites, band ratios, principal components analysis (PCA), and Crosta technique. Results obtained from all the processes were examined, and it was found that dyke boundaries are best visible in the PCA123 image; RGB 731 colour composite; TM band ratio 5/7, 5/1, 4 combination; and 1457‐PC4 image obtained by Crosta technique. The alteration differences of three dyke groups are enhanced much better in the 1457‐PC4 image obtained by Crosta technique, which highlights the hydroxyl‐bearing minerals as white‐coloured pixels. Using computer‐enhanced multi‐spectral remote sensing data, we were able to map the boundaries and spatial distributions of compositionally different dykes, which otherwise is an overwhelmingly difficult task to achieve using conventional field methods. In similar settings, remote sensing techniques applied in this study may provide an efficient and low‐cost alternative to time‐consuming and physically demanding field‐mapping campaigns.

A review of GIS-integrated statistical techniques for groundwater quality evaluation and protection

Water quality evaluation is critically important for the protection and sustainable management of groundwater resources, which are variably vulnerable to ever-increasing human-induced physical and chemical pressures (e.g., overexploitation and pollution of aquifers) and to climate change/variability. Preceding studies have applied a variety of tools and techniques, ranging from conventional to modern, for characterization of the groundwater quality worldwide. Recently, geographic information system (GIS) technology has been successfully integrated with the advanced statistical/geostatistical methods, providing improved interpretation capabilities for the assessment of the water quality over different spatial scales. This review intends to examine the current standing of the GIS-integrated statistical/geostatistical methods applied in hydrogeochemical studies. In this paper, we focus on applications of the time series modeling, multivariate statistical/geostatistical analyses, and artificial intelligence techniques used for groundwater quality evaluation and aquifer vulnerability assessment. In addition, we provide an overview of salient groundwater quality indices developed over the years and employed for the assessment of groundwater quality across the globe. Then, limitations and research gaps of the past studies are outlined and perspectives of the future research needs are discussed. It is revealed that comprehensive applications of the GIS-integrated advanced statistical methods are generally rare in groundwater quality evaluations. One of the major challenges in future research will be implementing procedures of statistical methods in GIS software to enhance analysis capabilities for both spatial and temporal data (multiple sites/stations and time frames) in a simultaneous manner.

Processes Governing Alkaline Groundwater Chemistry within a Fractured Rock (Ophiolitic Mélange) Aquifer Underlying a Seasonally Inhabited Headwater Area in the Aladağlar Range (Adana, Turkey)

The aim of this study was to investigate natural and anthropogenic processes governing the chemical composition of alkaline groundwater within a fractured rock (ophiolitic melange) aquifer underlying a seasonally inhabited headwater area in the Aladaglar Range (Adana, Turkey). In this aquifer, spatiotemporal patterns of groundwater flow and chemistry were investigated during dry (October 2011) and wet (May 2012) seasons utilizing 25 shallow hand-dug wells. In addition, representative samples of snow, rock, and soil were collected and analyzed to constrain the PHREEQC inverse geochemical models used for simulating water-rock interaction (WRI) processes. Hydrochemistry of the aquifer shows a strong interseasonal variability where Mg–HCO3 and Mg–Ca–HCO3 water types are prevalent, reflecting the influence of ophiolitic and carbonate rocks on local groundwater chemistry. R-mode factor analysis of hydrochemical data hints at geochemical processes taking place in the groundwater system, that is, WRI involving Ca- and Si-bearing phases; WRI involving amorphous oxyhydroxides and clay minerals; WRI involving Mg-bearing phases; and atmospheric/anthropogenic inputs. Results from the PHREEQC modeling suggested that hydrogeochemical evolution is governed by weathering of primary minerals (calcite, chrysotile, forsterite, and chromite), precipitation of secondary minerals (dolomite, quartz, clinochlore, and Fe/Cr oxides), atmospheric/anthropogenic inputs (halite), and seasonal dilution from recharge.