Cluster analysis applied to regional geochemical data: Problems and possibilities

Templ, Matthias; Filzmoser, Peter; Reimann, Clemens

doi:10.1016/j.apgeochem.2008.03.004

Cited by 321 publications

(176 citation statements)

References 31 publications

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“…Cluster analysis is a multivariate statistical technique that can aid in interpreting very large datasets by grouping objects (e.g., sampling sites) with similar characteristics together, and is a common tool used in riverine systems (Bierman et al 2011). While many studies have used cluster analysis techniques to interpret water chemistry data (Alberto et al 2001;Daughney et al 2012;Güler et al 2002;Kim et al 2005;Mavukkandy et al 2014;Najar et al 2012;Pati et al 2014;Shrestha and Kazama 2007;Simeonov et al 2003;Singh et al 2004;Singh et al 2005;Templ et al 2008;Wang et al 2013;Wang et al 2014), none of these studies were conducted as part of a citizen science effort or used data collected by citizen science volunteers. Six variables that had the most data available were used in the cluster analyses.…”

Section: Cluster Analysesmentioning

confidence: 99%

The Wabash Sampling Blitz: A Study on the Effectiveness of Citizen Science

Muenich

Peel²,

Bowling

et al. 2016

CSTP

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||The increasing number of citizen science projects around the world brings the need to evaluate the effectiveness of these projects and to show the applicability of the data they collect. This research describes the Wabash River Sampling Blitz, a volunteer water-quality monitoring program in Central Indiana developed by the Wabash River Enhancement Corporation (WREC). Results indicate that field test strips for nitrate+nitrite-N read by volunteers generally agree with lab-determined values. Orthophosphate results are less transferable owing to low observed concentrations, although the field test strip values from unfiltered samples consistently over-predicted the lab values. Hierarchical cluster analysis (HCA) applied to volunteer-collected data groups sampling sites into meaningful management clusters that can help to identify water-quality priorities across the watershed as a proof of concept for watershed managers. Results of the HCA provide an opportunity for WREC to target future programs, education, and activities by analyzing the data collected by citizen scientists. Overall this study demonstrates how citizen science water quality data can be validated and applied in subsequent watershed management strategies.

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Section: Cluster Analysesmentioning

confidence: 99%

The Wabash Sampling Blitz: A Study on the Effectiveness of Citizen Science

Muenich

Peel²,

Bowling

et al. 2016

CSTP

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“…The results of HCA are presented in a dendrogram, which is constructed using Ward's method (Ward, 1963) with the Euclidean distance as a measure of similarity between the samples. Ward's method is one of the most widespread hierarchical clustering methods for the classification of hydrogeochemical data by using the minimum variance to evaluate the distances between the clusters (Güler et al, 2002;Cloutier et al, 2008;Templ et al, 2008).…”

Section: Resultsmentioning

confidence: 99%

“…The variables below or close to the detection limit (Ag, Be, Bi, Br, Cd, Co, Cr, F, Fe, P, PO 4 , Se, Th and Tl) were excluded from the anal-ysis. The data were standardised by subtracting the sample mean from each variable and dividing the resulting value by the standard deviation (Z score standardisation) prior to multivariate analysis to ensure that each variable was weighted equally (Güler et al, 2002;Cloutier et al, 2008;Templ et al, 2008).…”

Section: Resultsmentioning

confidence: 99%

“…The Baltic Sea is one of the largest brackish water areas in the world (EEA, 1999). Although the low salinity, which varies from 3.0 to 7.0 ‰ in the Gulf of Finland (Alenius et al, 1998;UNEP, 2005;Fagerlund, 2008), does not pose a high risk from seawater intrusion compared to other parts of the world (e.g. Oude Essink, 1999Essink, , 2001Barlow, 2003;Pulido-Leboeuf, 2004;Oude Essink et al, 2010;Rasmussen et al, 2013), the salinity is at a higher level than the drinking water standard, and in the long term it can damage the infrastructure such as the pipeline network.…”

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confidence: 99%

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Confronting the vicinity of the surface water and sea shore in a shallow glaciogenic aquifer in southern Finland

Luoma

Okkonen

Korkka-Niemi

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract. The groundwater in a shallow, unconfined, lowlying coastal aquifer in Santala, southern Finland, was chemically characterised by integrating multivariate statistical approaches, principal component analysis (PCA) and hierarchical cluster analysis (HCA), based on the stable isotopes δ 2 H and δ 18 O, hydrogeochemistry and field monitoring data. PCA and HCA yielded similar results and classified groundwater samples into six distinct groups that revealed the factors controlling temporal and spatial variations in the groundwater geochemistry, such as the geology, anthropogenic sources from human activities, climate and surface water. High temporal variation in groundwater chemistry directly corresponded to precipitation. With an increase in precipitation, KMnO 4 consumption, EC, alkalinity and Ca concentrations also increased in most wells, while Fe, Al, Mn and SO 4 were occasionally increased during spring after the snowmelt under specific geological conditions. The continued increase in NO 3 and metal concentrations in groundwater indicates the potential contamination risk to the aquifer. Stable isotopes of δ 18 O and δ 2 H indicate groundwater recharge directly from meteoric water, with an insignificant contribution from lake water, and no seawater intrusion into the aquifer. Groundwater geochemistry suggests that local seawater intrusion is temporarily able to take place in the sulfate reduction zone along the freshwater and seawater mixed zone in the low-lying coastal area, but the contribution of seawater was found to be very low. The influence of lake water could be observed from higher levels of KMnO 4 consumption in wells near the lake. The integration of PCA and HCA with conventional classification of groundwater types, as well as with the hydrogeochemical data, provided useful tools to identify the vulnerable groundwater areas representing the impacts of both natural and human activities on water quality and the understanding of complex groundwater flow system for the aquifer vulnerability assessment and groundwater management in the future.

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“…The usefulness and successful application of fuzzy clustering to geoscientific data has been demonstrated in several studies, e.g. Bosch et al (2013), Dekkers et al (2014), Hanesch et al (2001) and Templ et al (2008).…”

Section: Introductionmentioning

confidence: 99%

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

Kitzig

Kepic

Kieu

2017

Exploration Geophysics

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Abstract. New drilling, measurement-while-drilling and top-of-hole sensing technologies are being developed to overcome the challenges of exploration for new mineral deposits under deep cover. These methods will provide continuous, near-real time data collection from every drillhole in the future. Consequently, there will be a need for efficient methods of analysing and interpreting this data stream to complement the exploration strategy. We demonstrate the usefulness of cluster analysis for rapid, automated rock mass classification, and the impact of selecting different subsets of the available data on the classification results. Our study shows that only a few measurements are needed to broadly domain the intersected rock mass and highlights the importance of selecting correct input data depending on the purpose of the classification. Our analysis also indicates the potential of identifying textural and rock mechanical properties from petrophysical measurements via cluster analysis.

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Cluster analysis applied to regional geochemical data: Problems and possibilities

Cited by 321 publications

References 31 publications

The Wabash Sampling Blitz: A Study on the Effectiveness of Citizen Science

The Wabash Sampling Blitz: A Study on the Effectiveness of Citizen Science

Confronting the vicinity of the surface water and sea shore in a shallow glaciogenic aquifer in southern Finland

Testing cluster analysis on combined petrophysical and geochemical data for rock mass classification

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