Information entropy as a tool in surface water quality assessment

Singh, Kunwar Raghvendra; Dutta, Rahul; Kalamdhad, Ajay S.; Kumar, Bimlesh

doi:10.1007/s12665-018-7998-x

Cited by 49 publications

(12 citation statements)

References 55 publications

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“…It then utilizes the entropy weight to align each index, and then calculates the weight of each index. Compared with the subjective weighting method, the entropy weight method has high objectivity and can reasonably explain the final result [25][26][27]. In addition, compared with other objective weighting methods, the entropy weight method has no complicated linear relationship, which is simpler and has a wider scope of application.…”

Section: Multi-level Entropy Weight Methodsmentioning

confidence: 99%

Evaluation of Water Use Efficiency of 31 Provinces and Municipalities in China Using Multi-Level Entropy Weight Method Synthesized Indexes and Data Envelopment Analysis

et al. 2019

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China’s water shortage problem is becoming increasingly severe. Improving water use efficiency is crucial to alleviating China’s water crisis. This paper evaluates the water use efficiency of 31 provinces and municipalities in China by using the data envelopment analysis (DEA) method. When the usual DEA model has too many indexes selected, it will cause the majority of the decision making units (DMUs) efficiency values be one, which leads to invalid evaluation results. Therefore, by using the entropy weight method, a new synthetic set of indexes is constructed based on the original indexes. The new synthetic set of indexes retains the full information of the original indexes, and the goal of simplifying the number of indexes is achieved. Simultaneously, by empowering the original indexes, the evaluation using synthetic indexes can also avoid the impact of industrial structure and labor division on water use efficiency. The results show that in China’s northeastern grain producing areas, water use efficiency is higher due to the high level of agricultural modernization. The provinces in the middle reaches of the Yangtze River have the lowest water use efficiency due to water pollution and water waste. In general, China’s overall water use efficiency is low, and there is still much room for improvement.

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Section: Multi-level Entropy Weight Methodsmentioning

confidence: 99%

Evaluation of Water Use Efficiency of 31 Provinces and Municipalities in China Using Multi-Level Entropy Weight Method Synthesized Indexes and Data Envelopment Analysis

et al. 2019

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“…6 Regarding the effects of As(III), Pb(II), Cd(II), and Cr(VI) on human being, these heavy metals are capable of damaging materials at molecular and cellular levels aer penetrated into body through water or food chain. [9][10][11][12] In other words, they cause the degeneration of vital organs and neurological disorders, facilitating related diseases. More severely, they can alter hereditary materials like DNA, causing unwanted harmful mutations to the suffering bodies and, possibly, their descendants.…”

Section: Introductionmentioning

confidence: 99%

“…[13][14][15][16] Besides, not only does heavy metal contaminated water affect humanity, it inicts negative impacts to ecosystems as well. 10,12,17 As a result, studies on treatments to eliminate As(III), Pb(II), Cd(II), and Cr(VI) from aqueous environments should be highly considered. Until now, there have been numerous studies introducing many techniques for removing heavy metal contamination from water.…”

Section: Introductionmentioning

confidence: 99%

Enhanced simultaneous adsorption of As(iii), Cd(ii), Pb(ii) and Cr(vi) ions from aqueous solution using cassava root husk-derived biochar loaded with ZnO nanoparticles

et al. 2021

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“…Anthropogenic activities and natural processes deteriorate surface water quality and adversely affect their importance (Singh et al 2004;Dash et al 2020;Prasad et al 2020). Due to domestic and industrial wastewater discharges, agricultural runoff and uncontrolled dumping of municipal solid waste near the river banks, the surface water quality has been gravely affected (Singh et al 2004(Singh et al , 2018(Singh et al , 2019Shrestha & Kazama 2007;Dash et al 2018;Zavaleta et al 2021). In the past few decades, surface water quality has gained utmost importance, especially in developing countries like India, and has become a sensitive issue (Simeonov et al 2003;Singh et al 2019;Borah et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)

Singh

Goswami

Kalamdhad

et al. 2021

Water Practice and Technology

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Water quality monitoring programs are indispensable for developing water conservation strategies, but elucidation of large and random datasets generated in these monitoring programs has become a global challenge. Rapid urbanization, industrialization and population growth pose a threat of pollution for the surface water bodies of the Assam, state in northeastern India. This calls for strict water quality monitoring programs, which would thereby help in understanding the status of water bodies.In this study, the water quality of Baralia and Puthimari River of Assam was assessed using cluster analysis (CA), information entropy, and principal component analysis (PCA) to derive useful information from observed data. 15 sampling sites were selected for collection of samples during the period May 2016- June 2017. Collected samples were analysed for 20 physicochemical parameters. Hierarchal CA was used to classify the sampling sites in different clusters. CA grouped all the sites into 3 clusters based on observed variables. Water quality of rivers was evaluated using entropy weighted water quality index (EWQI). EWQI of rivers varied from 61.62 to 314.68. PCA was applied to recognise various pollution sources. PCA identified six principal components that elucidated 87.9% of the total variance and represented surface runoff, untreated domestic wastewater and illegally dumped municipal solid waste (MSW) as major factors affecting the water quality. This study will help policymakers and managers for making better decisions in allocating funds and determining priorities. It will also assist in effective and efficient policies for the improvement of water quality.

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Information entropy as a tool in surface water quality assessment

Cited by 49 publications

References 55 publications

Evaluation of Water Use Efficiency of 31 Provinces and Municipalities in China Using Multi-Level Entropy Weight Method Synthesized Indexes and Data Envelopment Analysis

Evaluation of Water Use Efficiency of 31 Provinces and Municipalities in China Using Multi-Level Entropy Weight Method Synthesized Indexes and Data Envelopment Analysis

Enhanced simultaneous adsorption of As(iii), Cd(ii), Pb(ii) and Cr(vi) ions from aqueous solution using cassava root husk-derived biochar loaded with ZnO nanoparticles

Water quality evaluation and apportionment of pollution sources: a case study of the Baralia and Puthimari River (India)

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