The hydrochemistry of Mt. Ciremai

2017 ◽  
Author(s):  
Dasapta Erwin Irawan
Keyword(s):  
Cluster Analysis ◽  
Volcanic Rock ◽  
Neutral Type ◽  
Chemical Properties ◽  
Principal Component ◽  
Volcanic Aquifer ◽  
Aquifer System ◽  
Fractured Aquifers ◽  
Groundwater Samples ◽  
Surface Environment

This project was originated from my PhD research project (2005-2009), which has been uploaded for sometime at Figshare.---The Mount Ciremai is a 3072 masl situated in the south of Cirebon. It constitutes of spring zones along its foot slopes with nearly 200 groundwater springs, discharging 10 L/s to 800 L/s of water. The spring zone is fed by volcanic aquifer system, which lie over clay-sand layers which contains large masses of intercalated evaporites. Due to these conditions, the hydrochemical composition of the volcanic springs is relatively variable. In this study a hydrogeochemical characterization of the aquifer is undertaken to identify the aquifer system and the shifting of pysico-chemical properties, based on 140 samples collected from the volcanic springs. The identification was performed by studying hydrographs, the temporal evolution of physico-chemical parameters, and by means of multivariate statistical analyses with ifteen (15) hydrochemical parameters were considered (pH, EC., TDS., Twater, Tair, elevation, lithology, aquifer medium, Ca, Mg, Na, K, HCO3, Cl, SO4). Principal Component Analysis (PCA) and Cluster Analysis (CA) were applied in order to examine the importance of each parameter, investigate correlations among them, and separate them into groups. CA recognizes two clusters. Cluster 1 consists of mesothermal and hypothermal waters which are circulating in the volcanic aquifer system. This cluster is divided in to Cluster 1a which consists of 131 springs, with Ca-HCO3 from plagioclase rocks and Cluster 2b constitutes 3 springs with Mg-HCO3 ferromagnesian rocks. These samples are closely related with meteoric water. Cluster 2 consists of two springs circulating in the volcanic rock aquifer system. Both springs are hyperthermal, with high Na-K-Cl and TDS/DHL contents from volcanic activities. PCA identifies the neutral parameters on Quadrant I and IV which consists of mesothermal and hypothermal groundwater samples located on higher altitude. Neutral parameters change to dominant pH, Mg, Ca, HCO3 in Quadrant III. The three quadrants are controlled by volcanic rock aquifer system with relatively fast circulation in fractured aquifers. The prevailing parameters alter to dominant TDS/EC, Na, K, Cl, and SO4 in Quadrant II which contains volcanic – hyperthermal groundwater samples. Along the direction of flow, hydrochemical trends are seen as the groundwater type changes from neutral type to Ca-HCO3, Mg-HCO3; then to Na-K-Cl derived from the mixture between cold waters and thermal water. Cibulan spring shows different pattern of groundwater and surface temperature graphs. It indicates closed aquifer system, un-associated with surface environment. More similar curve pattern is shown at Telaga Remis spring. It indicates that the groundwater flows in open aquifer system, associated with surface environment. Gradual curve indicates the control of porous aquifer system, while the sharp one indicates the role of fractured aquifers. The estimated time residence of groundwater is within 3-7 months period. The calculation of spring’s recharge area from the charts are 3725 km2 with 8.2x109 m3/year of recharge for Cibulan, 6188 km2 with 14.5x109 m3/year of recharge for Telaga Remis.The application of PCA and CA of hydrochemical and hydrodynamic data can be used to extract the conceptual model of hydrochemical evolution of volcanic waters. Moreover, the use of both approaches allows better establishment of volcanic aquifer characterization. Key word: volcanic aquifer system, physical and chemical properties, cluster analysis, principal component analysisTotal words: 500

scholarly journals Magnetic susceptibility to identify landscape segments on a detailed scale in the region of Jaboticabal, São Paulo, Brazil

2012 ◽  
Vol 36 (4) ◽  
pp. 1073-1082 ◽  
Author(s):  
Mariana dos Reis Barrios ◽  
José Marques Junior ◽  
Alan Rodrigo Panosso ◽  
Diego Silva Siqueira ◽  
Newton La Scala Junior
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Magnetic Susceptibility ◽  
Clay Fraction ◽  
Chemical Properties ◽  
Principal Component ◽  
Component Analysis ◽  
Sao Paulo ◽  
São Paulo ◽  
Agricultural Potential

The agricultural potential is generally assessed and managed based on a one-dimensional vision of the soil profile, however, the increased appreciation of sustainable production has stimulated studies on faster and more accurate evaluation techniques and methods of the agricultural potential on detailed scales. The objective of this study was to investigate the possibility of using soil magnetic susceptibility for the identification of landscape segments on a detailed scale in the region of Jaboticabal, São Paulo State. The studied area has two slope curvatures: linear and concave, subdivided into three landscape segments: upper slope (US, concave), middle slope (MS, linear) and lower slope (LS, linear). In each of these segments, 20 points were randomly sampled from a database with 207 samples forming a regular grid installed in each landscape segment. The soil physical and chemical properties, CO2 emissions (FCO2) and magnetic susceptibility (MS) of the samples were evaluated represented by: magnetic susceptibility of air-dried fine earth (MS ADFE), magnetic susceptibility of the total sand fraction (MS TS) and magnetic susceptibility of the clay fraction (MS Cl) in the 0.00 - 0.15 m layer. The principal component analysis showed that MS is an important property that can be used to identify landscape segments, because the correlation of this property within the first principal component was high. The hierarchical cluster analysis method identified two groups based on the variables selected by principal component analysis; of the six selected variables, three were related to magnetic susceptibility. The landscape segments were differentiated similarly by the principal component analysis and by the cluster analysis using only the properties with higher discriminatory power. The cluster analysis of MS ADFE, MS TS and MS Cl allowed the formation of three groups that agree with the segment division established in the field. The grouping by cluster analysis indicated MS as a tool that could facilitate the identification of landscape segments and enable the mapping of more homogeneous areas at similar locations.

scholarly journals Groundwater quality variations in Precambrian hard rock aquifers: a case study from Kerala, India

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
P. Nandakumaran ◽  
K. Balakrishnan
Keyword(s):  
Groundwater Quality ◽  
Analytical Data ◽  
Principal Component ◽  
Anthropogenic Sources ◽  
Exchange Reactions ◽  
Rock Interaction ◽  
Fractured Aquifers ◽  
Groundwater Samples ◽  
Hard Rock Aquifers ◽  
Hydrochemical Composition

Abstract Analytical data of groundwater samples collected from weathered and deep fractured zones in the Precambrian charnockite aquifers in Kerala, India, have been studied to understand their hydrochemical variations and reasons thereof. Concentrations of the majority of the constituents analyzed were found to increase with increasing depth of aquifers, with the exception of nitrate. Studies indicate that various processes such as ion exchange reactions, carbonate weathering and silicate weathering are active in both the aquifers which influence the hydrochemical composition of groundwater in them. The prevailing groundwater quality in the aquifers is dependent on the dominance of each process in relation to others. Principal component analysis of the data suggests that contamination from anthropogenic sources has a major role in determining the hydrochemical characteristics of groundwater in the weathered zone unlike in the case of fractured aquifers where water–rock interaction is the major factor responsible. The study also indicates limited hydraulic connection between the weathered and fractured aquifers at the local scale.

Classification of Observations through Combination of the Dimension Reduction and the Cluster Analysis

2017 ◽  
Vol 7 (8) ◽  
pp. 30
Author(s):  
Hyeuk Kim
Keyword(s):  
Machine Learning ◽  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Unsupervised Learning ◽  
Principal Component ◽  
Component Analysis ◽  
Baseball Players ◽  
Partitioning Around Medoids ◽  
Different Characteristics

Unsupervised learning in machine learning divides data into several groups. The observations in the same group have similar characteristics and the observations in the different groups have the different characteristics. In the paper, we classify data by partitioning around medoids which have some advantages over the k-means clustering. We apply it to baseball players in Korea Baseball League. We also apply the principal component analysis to data and draw the graph using two components for axis. We interpret the meaning of the clustering graphically through the procedure. The combination of the partitioning around medoids and the principal component analysis can be used to any other data and the approach makes us to figure out the characteristics easily.

STUDY ON PLANKTON OF DIFFERENT CATEGORIES OF LAKES IN SUMMER BY MEANS OF PRINCIPAL COMPONENT ANALYSIS, FACTOR ANALYSIS AND CLUSTER ANALYSIS

2010 ◽  
Vol 36 (1) ◽  
pp. 43-50
Author(s):  
Luo-Jun GONG ◽  
Shi-Ping ZHANG ◽  
Bang-Xi XIONG ◽  
Ding-Zhu LIU ◽  
Jin-Zhong LI ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
And Cluster Analysis

Identification of COVID-19 Clinical Phenotypes by Principal Component Analysis-Based Cluster Analysis

2020 ◽  
Author(s):  
Wenjing Ye ◽  
Lu Weiwei ◽  
Yanping Tang ◽  
Chen Guoxi ◽  
Li Xiaopan ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Clinical Phenotypes

Quality evaluation of tugaksheeree samples by ATR-FTIR spectroscopy using multicomponent analysis

2020 ◽  
Vol 10 ◽  
Author(s):  
Nikunj D. Patel ◽  
Niranjan S. Kanaki
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Quality Evaluation ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Attenuated Total Reflectance ◽  
Chemometric Methods ◽  
Total Reflectance ◽  
Fingerprint Region ◽  
Ftir Technique

Background: Numerous Ayurvedic formulations contains tugaksheeree as key ingredient. Tugaksheereeis the starch gained from the rhizomes of two plants, Curcuma angustifoliaRoxb. (Zingiberaceae) and Marantaarundinacea (MA) Linn. (Marantaceae). Objective: The primary concerns in quality assessment of Tugaksheeree occur due to adulteration or substitution. Method: In current study, Fourier transform infrared (FTIR) technique with attenuated total reflectance (ATR) facility was used to evaluate tugaksheeree samples. Total 10 different samples were studied and transmittance mode was kept to record the spectra devoid of pellets of KBR. Further treatment was given with multi component tools by considering fingerprint region of the spectra. Multivariate analysis was performed by various chemometric methods. Result: Multi component methods like Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA)were used to discriminate the tugaksheeree samples using Minitab software. Conclusion: This method can be used as a tool to differentiate samples of tugaksheeree from its adulterants and substitutes.

scholarly journals COVID-19 Pandemic and Adaptive Shopping Patterns: An Insight from Indonesian Consumers

2021 ◽  
pp. 097215092110135
Author(s):  
Arif Hartono ◽  
Asma'i Ishak ◽  
Agus Abdurrahman ◽  
Budi Astuti ◽  
Endy Gunanto Marsasi ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Demographic Characteristics ◽  
Depth Information ◽  
Factor Scores ◽  
Consumer Spending ◽  
Consumer Responses ◽  
Buying Behaviour ◽  
Manova Analysis

Although existing studies on consumers typology are extensively conducted, insights on consumers typology in adapting their shopping attitude and behaviour during the COVID-19 pandemic remain unexplored. Current studies on consumer responses to the COVID-19 pandemic tend to focus on the following themes: panic buying behaviour, consumer spending and consumer consumption. This study explores a typology of adaptive shopping patterns in response to the COVID-19 pandemic. The study involved a survey of 465 Indonesian consumers. Principal component analysis is used to identify the variables related to adaptive shopping patterns. Cluster analysis of the factor scores obtained on the adaptive shopping attitude and behaviour revealed the typology of Indonesian shoppers’ adaptive patterns. Multivariate Analysis of Variance (MANOVA) analysis is used to profile the identified clusters based on attitude, behaviour and demographic characteristics. Results revealed five adaptive shopping patterns with substantial differences among them. This study provides in-depth information about the profile of Indonesian shoppers’ adaptive patterns that would help retailers in understanding consumers and choosing their target group. The major contribution of this study is providing segmentation on shopping adaptive patterns in the context of the COVID-19 pandemic which presents interesting differences compared with previous studies. This study reveals new insights on shoppers’ adaptive attitude and behaviour as consumers coped with the pandemic.

scholarly journals Hydrochemical Characterisation of High-Fluoride Groundwater and Development of a Conceptual Groundwater Flow Model Using a Combined Hydrogeological and Hydrochemical Approach on an Active Volcano: Mount Meru, Northern Tanzania

Water ◽  
2021 ◽  
Vol 13 (16) ◽  
pp. 2159
Author(s):  
George Bennett ◽  
Jill Van Reybrouck ◽  
Ceven Shemsanga ◽  
Mary Kisaka ◽  
Ines Tomašek ◽  
...  
Keyword(s):  
Drinking Water ◽  
Large Scale ◽  
Active Volcano ◽  
Aquifer System ◽  
Groundwater Samples ◽  
Northern Tanzania ◽  
Different Seasons ◽  
High Fluoride ◽  
Arusha National Park ◽  
The Impact

This study characterises high-fluoride groundwater in the aquifer system on the flanks of Mount Meru, focusing on parts of the flanks that were only partially or not at all covered by previous research. Additionally, we analyse the impact of rainwater recharge on groundwater chemistry by monitoring spring discharges during water sampling. The results show that the main groundwater type in the study area is NaHCO3 alkaline groundwater (average pH = 7.8). High F− values were recorded: in 175 groundwater samples, the concentrations range from 0.15 to 301 mg/L (mean: 21.89 mg/L, median: 9.67 mg/L), with 91% of the samples containing F− values above the WHO health-based guideline for drinking water (1.5 mg/L), whereas 39% of the samples have Na+ concentrations above the WHO taste-based guideline of 200 mg/L. The temporal variability in F− concentrations between different seasons is due to the impact of the local groundwater recharge. We recommend that a detailed ecohydrological study should be carried out for the low-fluoride springs from the high-altitude recharge areas on the eastern and northwestern flanks of Mount Meru inside Arusha National Park. These springs are extracted for drinking purposes. An ecohydrological study is required for the management of these springs and their potential enhanced exploitation to ensure the sustainability of this water extraction practice. Another strategy for obtaining safe drinking water could be to use a large-scale filtering system to remove F− from the groundwater.

Sign in / Sign up

Export Citation Format

Share Document