Application of Principal Components Analysis for Interpretation and Grouping of Water Quality Parameters

Gajbhiye, Sarita; Sharma, Shailesh; Awasthi, MK

doi:10.14257/ijhit.2015.8.4.11

Cited by 29 publications

(12 citation statements)

References 16 publications

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“…They are designed to reduce the number of variables to a small number of indices while attempting to preserve the relationships present in the original data. In recent years, many studies have been done using PCA in the interpretation of water quality parameters (Gajbhiye et al 2010(Gajbhiye et al , 2015b, geomorphometric parameters (Sharma et al 2009), etc.…”

Section: Introductionmentioning

confidence: 99%

Prioritization of watershed through morphometric parameters: a PCA-based approach

2015

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Remote sensing (RS) and Geographic Information Systems (GIS) techniques have become very important these days as they aid planners and decision makers to make effective and correct decisions and designs. Principal Component Analysis (PCA) involves a mathematical procedure that transforms a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. It reduces the dimensionality of the data set and identifies a new meaningful underlying variable. Morphometric analysis and prioritization of the subwatersheds of Shakkar River Catchment, Narsinghpur district in Madhya Pradesh State, India, is carried out using RS and GIS techniques as discussed in Gajbhiye et al. (Appl Water Sci 4(1):51-61, 2013b). In this study we apply PCA technique in Shakkar River Catchment for redundancy of morphometric parameters and find the more effective parameters for prioritization of the watershed and discuss the comparison between Gajbhiye et al. (Appl Water Sci 4(1):51-61, 2013b) and the present prioritization scheme.

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Section: Introductionmentioning

confidence: 99%

Prioritization of watershed through morphometric parameters: a PCA-based approach

2015

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“…Soil erosion is considered one of the most important degradation processes in the world [1,2]. The soil resource is limited and its wide use is of utmost importance; it sustains biogeochemical processes and is the habitat for a great diversity of microorganisms [3]. Sustained soil development, conservation, and restoration is one of today's main challenges for humankind.…”

Section: Introductionmentioning

confidence: 99%

A Multivariate Geomorphometric Approach to Prioritize Erosion-Prone Watersheds

et al. 2019

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Soil erosion is considered one of the main degradation processes in ecosystems located in developing countries. In northern Mexico, one of the most important hydrological regions is the Conchos River Basin (CRB) due to its utilization as a runoff source. However, the CRB is subjected to significant erosion processes due to natural and anthropogenic causes. Thus, classifying the CRB’s watersheds based on their erosion susceptibility is of great importance. This study classified and then prioritized the 31 watersheds composing the CRB. For that, multivariate techniques such as principal component analysis (PCA), group analysis (GA), and the ranking methodology known as compound parameter (Cp) were used. After a correlation analysis, the values of 26 from 33 geomorphometric parameters estimated from each watershed served for the evaluation. The PCA defined linear-type parameters as the main source of variability among the watersheds. The GA and the Cp were effective for grouping the watersheds in five groups, and provided the information for the spatial analysis. The GA methodology best classified the watersheds based on the variance of their parameters. The group with the highest prioritization and erosion susceptibility included watersheds RH24Lf, RH24Lb, RH24Nc, and RH24Jb. These watersheds are potential candidates for the implementation of soil conservation practices.

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“…Various researches has been conducted in India and aboard to indexes for spatial estimation of surface runoff considering variables such as rainfall, drought frequency, available moisture content, extent and percent of degraded and wastelands, irrigation intensity, extent and percent of rainfed areas and groundwater status (National Rainfed Area Authority ). Gajbhiye et al (, ) developed the geomorphological erosion index using PCA for Shakkar Watershed, Madhya Pradesh, and Matthew () developed a hydrological index by using HEC‐ResSim model for stream flow in watershed and for ecologically acceptable water‐level range in lake ecosystems by using water level fluctuations parameters (Liang et al ); evapotranspiration (ET) index for monitoring surface moisture status using Aqua/MODIS model (Nishida et al ); water resources vulnerability index using TOPSIS model (Jun et al ); and runoff based drought index was developed using statistical distribution (Wang et al ).…”

Section: Introductionmentioning

confidence: 99%

“…5-Groundwater-September-October 2019 (pages 749-755) available moisture content, extent and percent of degraded and wastelands, irrigation intensity, extent and percent of rainfed areas and groundwater status (National Rainfed Area Authority 2012). Gajbhiye et al (2015aGajbhiye et al ( , 2015b developed the geomorphological erosion index using PCA for Shakkar Watershed, Madhya Pradesh, and Matthew (2012) developed a hydrological index by using HEC-ResSim model for stream flow in watershed and for ecologically acceptable water-level range in lake ecosystems by using water level fluctuations parameters (Liang et al 2014); evapotranspiration (ET) index for monitoring surface moisture status using Aqua/MODIS model (Nishida et al 2003); water resources vulnerability index using TOPSIS model (Jun et al 2011); and runoff based drought index was developed using statistical distribution (Wang et al 2009). Earlier, indices were developed for characterization of spatial problems like composite hydrological drought index (Karamouz et al 2009;Waseem et al 2015) for areas where rainfall is not a primary source of water (Shafer and Dezman 1982); soil moisture deficit index and evapotranspiration deficit index for soil moisture deficit and ET deficit conditions (Narasimhan and Srinivasan 2005); multimetric index for river biological conditions (Emery et al 2003;Pont et al 2007); groundwater quality index (Saeedi et al 2010; Kumar and James 2013) for sea water intrusion in coastal aquifers (Tomaszkiewicz et al 2014), for lakes (Chow-Fraser 2006) and such as developed a watershed sustainability index for a watershed (Chandniha et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Development of a Composite Hydrologic Index for Semi‐Arid Region of India

Jeet¹,

Singh

Sarangi

2019

Groundwater

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Rainfall is the major source for groundwater recharge in basins areas of central region of India. Now a day, the river basins are experiencing acute shortage of water which has resulted in lowering of groundwater level and drying up of water bodies. In order to maintain water sustainability; a composite hydrologic index was developed in the Betwa basin of Madhya Pradesh and Uttar Pradesh states, India. The index was developed using principal component analysis through hydrologic, topographic as well as geographic parameters derived from the Soil and Water Assessment Tool and MODFLOW model. The geomorphological parameters were categorized, on the basis of groundwater recharge potential and weight ranged from 1 to 4. The geomorphologic parameters, that is, soil type (T), slope (S), runoff ratio (R), and evapotranspiration (ET) were integrated into a single indicator of composite hydrologic index. Soil type and ET were the major factors that directly affected the groundwater recharge. These two parameters together explained 86% of total variability in the data. Based on the analysis of the four parameters that affected groundwater recharge, composite hydrologic index (CHI) was classified into very good, good, moderate, and low grade. The CHI was statistically validated using standardization methods. The index was developed as a water management tool to measure a sustainability state relative to a groundwater recharge potential, which allows for spatial and temporal comparison. This index will be helpful in natural resource management and will improve socioeconomic status of human population inhibiting in the semi‐arid region.

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Application of Principal Components Analysis for Interpretation and Grouping of Water Quality Parameters

Abstract: Water samples were collected from two sites (Urdana Nala and Moti Nala)

Cited by 29 publications

References 16 publications

Prioritization of watershed through morphometric parameters: a PCA-based approach

Prioritization of watershed through morphometric parameters: a PCA-based approach

A Multivariate Geomorphometric Approach to Prioritize Erosion-Prone Watersheds

Development of a Composite Hydrologic Index for Semi‐Arid Region of India

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