Abstract
Scientific dredging of river and lake sediments is crucial for ensuring the sustainable development of water environments. Meanwhile, ecological risk assessment serves as a core tool for balancing dredging benefits with ecological risks, facilitating precise management and resource utilisation. In this study, the Analytic Hierarchy Process (AHP) was improved by introducing an optimal transfer matrix to construct a consistent judgment matrix, thereby enhancing the accuracy of ecological risk assessment for sediment dredging. Taking the coal mining subsidence areas of Zhuxianzhuang and Luling in Suzhou City, Anhui Province, as case studies, the pollution levels of nutrients, organic matter, and heavy metals in the sediments were analysed. Based on the improved AHP, the assessment results categorised ecological risks into three levels: mild, moderate, and severe pollution. In the Zhuxianzhuang mining area, the comprehensive risk score was 3.90, indicating a mild pollution level; Total Phosphorus (467mg/kg), Nickel (32mg/kg), and Cadmium (0.6667mg/kg) were at moderate levels, while Mercury (0.1285mg/kg) and Total Nitrogen (817mg/kg) presented higher risks. In the Luling mining area, the comprehensive risk score was 3.98, also indicating mild pollution; the contents of phosphorus and organic matter were relatively low, whereas the mercury content was relatively high (0.112mg/kg). This study provides a novel approach for sediment ecological risk assessment, offering a valuable reference for sustainable water environment management and the optimisation of dredging strategies.
Keywords:
- Keyword: River and Lake Sediments; Sediment Dredging Projects; Ecological Risk Assessment; Improved Analytic Hierarchy Process; Assessment Framework
- Keyword: River and Lake Sediments;
- Keyword: Sediment Dredging Projects;
- Keyword: Ecological Risk Assessment;
- Keyword: Improved Analytic Hierarchy Process;
- Keyword: Assessment Framework
How to Cite:
Zhang, H., Li, L., Qiu, H., Chen, J. & Chen, W., (2026) “Enhanced Objectivity and Efficiency in Sediment Ecological Risk Assessment: An Improved AHP Approach”, Journal of Intelligent and Sustainable Systems (JISS) 2(1).