Comparison between the WFD approaches and newly developed water quality model for monitoring transitional and coastal water quality in Northern Ireland

Uddin, Md Galal; Jackson, A.Y.; Rahman, Azizur; Olbert, Agnieszka Indiana

doi:10.1016/j.scitotenv.2023.165960

Cited by 30 publications

(6 citation statements)

References 62 publications

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“…Turning to the practical standpoint of this research work, it is worth mentioning that the sustainable management of water resources in often challenging due to financial compliance, institutional framework, requirement of sophisticated analytical procedure and establishment, lack of skilled human resources [ [ 31 , [114] , [115] , [116] , [117] , [118] , [119] ]]. Developed countries in the world mitigate these challenges through regional management tools (e.g., Water Framework Directive for European countries) but it remains as a tremendous challenge for developing countries like Bangladesh.…”

Section: Resultsmentioning

confidence: 99%

Assessment of hydrogeochemistry in groundwater using water quality index model and indices approaches

Uddin,

Diganta,

Sajib

et al. 2023

Heliyon

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Section: Resultsmentioning

confidence: 99%

Assessment of hydrogeochemistry in groundwater using water quality index model and indices approaches

Uddin,

Diganta,

Sajib

et al. 2023

Heliyon

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“…Each of the four main processes involved in a WQI model can contribute to the model uncertainty ( Gupta and Gupta, 2021 ; Uddin et al, 2023a , b , c ). In this research, the correlation analysis between water quality parameters showed that there were significant correlations among some parameters ( Figure 7 ).…”

Section: Discussionmentioning

confidence: 99%

“…The WFD and other similar frameworks for water quality management rely mostly on collected datasets to assess water quality. In recent years, many tools and techniques have been developed to assess water quality, the water quality index (WQI) models are one of the most widely used tools ( Sun et al, 2016 ; Sutadian et al, 2018 ; Uddin et al, 2020 , 2022 , 2023a , b ; Lukhabi et al, 2023 ). WQI is a tool that describes the overall water quality by converting available water quality parameter data into a single unitless number by mathematical algorithms ( Horton, 1965 ).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal pattern of coastal water pollution and its driving factors: implications for improving water environment along Hainan Island, China

Du,

Ren,

Zhong

et al. 2024

Front. Microbiol.

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In the context of human activities and climate change, the gradual degradation of coastal water quality seriously threatens the balance of coastal and marine ecosystems. However, the spatiotemporal patterns of coastal water quality and its driving factors were still not well understood. Based on 31 water quality parameters from 2015 to 2020, a new approach of optimizing water quality index (WQI) model was proposed to quantitatively assess the spatial and temporal water quality along tropical Hainan Island, China. In addition, pollution sources were further identified by factor analysis and the effects of pollution source on water quality was finally quantitatively in our study. The results showed that the average water quality was moderate. Water quality at 86.36% of the monitoring stations was good while 13.53% of the monitoring stations has bad or very bad water quality. Besides, the coastal water quality had spatial and seasonal variation, along Hainan Island, China. The water quality at “bad” level was mainly appeared in the coastal waters along large cities (Haikou and Sanya) and some aquaculture regions. Seasonally, the average water quality in March, October and November was worse than in other months. Factor analysis revealed that water quality in this region was mostly affected by urbanization, planting and breeding factor, industrial factor, and they played the different role in different coastal zones. Waters at 10.23% of monitoring stations were at the greatest risk of deterioration due to severe pressure from environmental factors. Our study has significant important references for improving water quality and managing coastal water environment.

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“…The main advantages of LOWESS include its robustness to outliers, as it assigns them lower weights, and its capacity to reveal the underlying structure of the data without the need for specifying a global function. This method is particularly beneficial when dealing with indicators that are influenced by multiple and potentially interacting factors, making it a powerful tool for policymakers and researchers seeking to derive actionable insights from complex datasets 39,40 .…”

Section: Locally Weighted Scatterplot Smoothing (Lowess)mentioning

confidence: 99%

Advancing Personal Well-Being Analysis through the Integration of Instance-Based Learning with Interpretable AI Techniques

Kamal,

Sultana,

Bewong

et al. 2024

Preprint

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Understanding factors that affect Personal Well-Being Index (PWI) is crucial for developing strategies that enhance quality of life at both individual and community levels. This research introduces a novel approach to PWI analysis by integrating Instance-Based Learning (IBL) with interpretable Artificial Intelligence (AI) methods. Utilizing IBL, the study creates tailored matrices for individual instances, enabling a dynamic and specific analysis of well-being factors. It leverages advanced AI techniques, notably the graph-based clustering and Locally Weighted Scatterplot Smoothing (LOWESS), to provide transparent and comprehensible insights. Key innovations include the use of sophisticated feature selection techniques like Random Forest (RF), and Permutation Importance (PI) to identify critical PWI indicators. The research also employs LOWESS for state-of-the-art prediction modeling, providing adaptable forecasts for future trends in PWI indicators. The application of graph-based clustering offers a comprehensive analysis of the current state of PWI, generating detailed scenarios and enhancing the understanding of well-being. This integrative methodology positions the study at the forefront of PWI research, offering new pathways for enhancing well-being in diverse settings.

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Comparison between the WFD approaches and newly developed water quality model for monitoring transitional and coastal water quality in Northern Ireland

Cited by 30 publications

References 62 publications

Assessment of hydrogeochemistry in groundwater using water quality index model and indices approaches

Assessment of hydrogeochemistry in groundwater using water quality index model and indices approaches

Spatiotemporal pattern of coastal water pollution and its driving factors: implications for improving water environment along Hainan Island, China

Advancing Personal Well-Being Analysis through the Integration of Instance-Based Learning with Interpretable AI Techniques

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