A comprehensive method for improvement of water quality index (WQI) models for coastal water quality assessment

Uddin, Md Galal; Nash, Stephen; Rahman, Azizur; Olbert, Agnieszka Indiana

doi:10.1016/j.watres.2022.118532

Cited by 145 publications

(174 citation statements)

References 41 publications

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“…With reference to the data split procedure in previous studies in Nong et al 24 , Wu et al 14 and Uddin et al 41 , the WQImin models in this study were established using the following steps: The WQI and Ci for each station in 2015 and 2016 were used as “training data” to calibrate the WQI min model while a test period in 2017 was used to verify the model performance.…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal variation evaluation of water quality in middle and lower Han River, China

Deng

Chen

Liu

et al. 2022

Sci Rep

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As the water source for the middle route of the South-to-North Water Transfer Project, the Han River in China plays a role of the world’s largest inter-basin water transfer project. However, this human-interfered area has suffered from over-standard pollution emission and water blooms in recent years, which necessitates urgent awareness at both national and provincial scales. To perform a comprehensive analysis of the water quality condition of this study area, we apply both the water quality index (WQI) and minimal WQI (WQImin) methods to investigate the spatiotemporal variation characteristics of water quality. The results show that 8 parameters consisting of permanganate index (PI), chemical oxygen demand (COD), total phosphorus (TP), fluoride (F-), arsenic (As), plumbum (Pb), copper (Cu), and zinc (Zn) have significant discrepancy in spatial scales, and the study basin also has a seasonal variation pattern with the lowest WQI values in summer and autumn. Moreover, compared to the traditional WQI, the WQImin model, with the assistance of stepwise linear regression analysis, could exhibit more accurate explanation with the coefficient of determination (R2) and percentage error (PE) values being 0.895 and 5.515%, respectively. The proposed framework is of great importance to improve the spatiotemporal recognition of water quality patterns and further helps develop efficient water management strategies at a reduced cost.

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Section: Methodsmentioning

confidence: 99%

Spatiotemporal variation evaluation of water quality in middle and lower Han River, China

Deng

Chen

Liu

et al. 2022

Sci Rep

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“…Compared with the commonly used water quality index (WQI) method and the single-factor evaluation method, the Nemerow pollution index method has a clear physical concept, high calculation e ciency, and nal classi cation of the water quality that depends on the corresponding national standards (Chen et al 2016b). The WQI method mainly relies on expert judgment or literature review to determine the parameters and weights, which renders the evaluation model overly complex and subjective and increases uncertainty during the model implementation (Uddin et al 2022). The single-factor evaluation method can quickly determine the gap between water quality and environmental standards.…”

Section: Establishment Of Npi Minmentioning

confidence: 99%

Water quality assessment and pollution source apportionment using multivariate statistical and PMF receptor modeling techniques in a sub-watershed of the upper Yangtze River, Southwest China

Ren

Yang

Zhao

et al. 2023

Environ Geochem Health

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The rapid industrial and agricultural development as well as urbanization signi cantly affect the water environment, especially in subwatersheds where the contaminants/constituents present in the pollution sources are complex and the ow is unstable. Water quality assessment and quantitative identi cation of pollution sources are the primary prerequisites for the improvement of water management and quality. In this work, 168 water samples were collected from seven stations throughout 2018-2019 along the Laixi River, which is an important pollution control unit in the upper reaches of the Yangtze River. Multivariate statistics and positive matrix factorization (PMF) receptor modeling techniques were used to evaluate the characteristics of the river-water quality and reveal the pollution sources. Principal component analysis (PCA) was used to screen the crucial parameters and establish an optimized water quality assessment procedure to reduce the analysis cost and improve the assessment e ciency. Cluster analysis (CA) further illustrates the spatiotemporal distribution characteristics of river water quality. Results indicated that high-pollution areas are concentrated in the tributaries, and the high-pollution periods are the spring and winter, which veri es the reliability of the evaluation system. The PMF model identi ed ve and six potential pollution sources in the cold and warm seasons, respectively. Among them, pollution from agricultural activities and domestic wastewater shows the highest contributions (33.2% and 30.3%, respectively) during the cold and warm seasons, respectively. The results of this study can provide corresponding theoretical support for pollutant control and water quality improvement, and avoid the ecological and health risks caused by the deterioration of water quality. IntroductionRiver-water quality is a serious problem, especially for urban managers and researchers worldwide. Clean rivers provide a safeguard for human health and the ecosystem and prevent the environmental, economic, and social risks associated with pollution (Liu et al. 2019a, Sener et al. 2017). However, with the increase in population, urbanization, and industrialization, pollution from industrial and domestic wastewaters as well as agricultural and urban runoffs has increased the load on surface water. Thus, water resource management faces serious challenges to reduce pollutants (Casillas-Garcia et al. 2021, Zhang et al. 2020a). In the sub-watersheds that lack supervision, the water quality is especially unstable, and the pollution sources are complicated. (Cheng et al. 2020, Huang et al. 2010. Therefore, rapid water quality assessment and accurate identi cation of pollution sources can help researchers develop strategies for water management and pollutant control (Zhang et al. 2022).Recently, China has mainly been relying on sampling analysis and automated monitoring stations to obtain water quality data. Various complex monitoring procedures are typically used, and additional physical and chemical parameters for wa...

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“…Recently, several studies have utilised the state-of-the-art WQI for assessing river water quality in India (Chakravarty and Gupta, 2021). In this research, the modified NSF-WQI model was used for the assessment of Mahananda River water quality because recent study have revealed that this modified techniques is effective to assess surface water quality in order to reduce model uncertainty (Uddin et al, 2022a(Uddin et al, , 2022c. In addition, this technique widely used for assessing different dynamics surface waterbodies (de Andrade Costa et al, 2020;Gradilla-Hernández et al, 2020;Matta et al, 2020).…”

Section: Assessing Water Quality Using Modified Nsf-wqi Modelmentioning

confidence: 99%

“…Surface water is considered as one of fundamental natural resources both for human survival and development related activities (Salem, 2021). Therefore, it is crucial to maintain the good status of surface water quality for sustainable development and safety to human health (Tripathi and Singal, 2019;Uddin et al, 2022a). However, in recent decades a continued deterioration in the quality of surface water is noticeable since surface water is more susceptible to pollutants from both natural and anthropogenic sources such as industrial sewages, disposed domestic waste, and irrigation drainage water (Asha et al, 2020;Rahman et al, 2021;Uddin et al, 2020aUddin et al, , 2022b.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Urban River Water Quality Using Modified NSF Water Quality Index Model at Siliguri City, West Bengal, India

et al. 2022

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A comprehensive method for improvement of water quality index (WQI) models for coastal water quality assessment

Cited by 145 publications

References 41 publications

Spatiotemporal variation evaluation of water quality in middle and lower Han River, China

Spatiotemporal variation evaluation of water quality in middle and lower Han River, China

Water quality assessment and pollution source apportionment using multivariate statistical and PMF receptor modeling techniques in a sub-watershed of the upper Yangtze River, Southwest China

Assessment of Urban River Water Quality Using Modified NSF Water Quality Index Model at Siliguri City, West Bengal, India

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