School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland.
School of Engineering, University of Galway, Ireland; Ryan Institute, University of Galway, Ireland; MaREI Research Centre, University of Galway, Ireland.
Sci Total Environ. 2023 Apr 10;868:161614. doi: 10.1016/j.scitotenv.2023.161614. Epub 2023 Jan 18.
Here, we present the Irish Water Quality Index (IEWQI) model for assessing transitional and coastal water quality in an effort to improve the method and develop a tool that can be used by environmental regulators to abate water pollution in Ireland. The developed model has been associated with the adoption of water quality standards formulated for coastal and transitional waterbodies according to the water framework directive legislation by the environmental regulator of Irish water. The model consists of five identical components, including (i) indicator selection technique is to select the crucial water quality indicator; (ii) sub-index (SI) function for rescaling various water quality indicators' information into a uniform scale; (iii) indicators' weight method for estimating the weight values based on the relative significance of real-time information on water quality; (iii) aggregation function for computing the water quality index (WQI) score; and (v) score interpretation scheme for assessing the state of water quality. The IEWQI model was developed based on Cork Harbour, Ireland. The developed IEWQI model was applied to four coastal waterbodies in Ireland, for assessing water quality using 2021 water quality data for the summer and winter seasons in order to evaluate model sensitivity in terms of spatio-temporal resolution of various waterbodies. The model efficiency and uncertainty were also analysed in this research. In terms of different spatio-temporal magnitudes of various domains, the model shows higher sensitivity in four application domains during the summer and winter. In addition, the results of uncertainty reveal that the IEWQI model architecture may be effective for reducing model uncertainty in order to avoid model eclipsing and ambiguity problems. The findings of this study reveal that the IEWQI model could be an efficient and reliable technique for the assessment of transitional and coastal water quality more accurately in any geospatial domain.
在这里，我们提出了爱尔兰水质指数（IEWQI）模型，以评估过渡区和沿海区的水质，旨在改进方法并开发一种可被爱尔兰环境监管机构用于减轻水污染的工具。所开发的模型与根据水框架指令立法为沿海和过渡水体制定的水质标准的采用相关联，该模型由五个相同的组件组成，包括 (i) 指标选择技术，用于选择关键的水质指标；(ii) 子指数 (SI) 函数，用于将各种水质指标的信息重新调整到统一的尺度；(iii) 指标权重方法，用于根据实时水质信息的相对重要性估算权重值；(iii) 聚合函数，用于计算水质指数 (WQI) 得分；和 (v) 得分解释方案，用于评估水质状况。IEWQI 模型是基于爱尔兰科克港开发的。所开发的 IEWQI 模型应用于爱尔兰的四个沿海水体，用于评估 2021 年夏季和冬季水质数据的水质，以评估模型在不同水体时空分辨率方面的敏感性。本研究还分析了模型效率和不确定性。就不同水体的不同时空幅度而言，该模型在夏季和冬季的四个应用领域表现出更高的敏感性。此外，不确定性的结果表明，IEWQI 模型架构可能对减少模型不确定性有效，以避免模型遮罩和模糊问题。本研究的结果表明，IEWQI 模型可能是一种高效、可靠的技术，可更准确地评估任何地理空间域的过渡区和沿海区水质。
