摘 要
水污染是全球面临的重大环境问题，对生态系统和人类健康构成严重威胁。本研究旨在系统识别主要水污染源并探索有效的治理技术，以期为水环境保护提供科学依据和技术支持。通过文献综述、实地调研与实验分析相结合的方法，全面梳理了工业废水、农业面源污染及生活污水等主要污染源的特征及其对水体的影响机制。创新性地构建了基于多源数据融合的污染源识别模型，实现了对复杂水环境中各类污染源的精准定位与定量评估。针对不同类型的污染源，提出了物理化学法、生物修复法以及生态工程技术相结合的综合治理方案，并在典型区域开展了应用示范。研究表明，所提出的识别模型能够准确区分不同来源的污染物，其精度达到90%以上；综合治理技术可使受污染水体的主要污染物浓度显著降低，水质明显改善。研究结果表明，该方法体系具有较强的适用性和有效性，为水污染防控提供了新的思路与方法，对于推动水环境质量提升具有重要意义。
关键词：水污染源识别 多源数据融合模型 综合治理技术
Abstract
Water pollution poses a significant environmental challenge globally, severely threatening ecosystems and human health. This study aims to systematically identify major sources of water pollution and explore effective remediation technologies to provide scientific evidence and technical support for water resource protection. By integrating literature review, field investigation, and experimental analysis, this research comprehensively examined the characteristics and impact mechanisms of primary pollution sources including industrial wastewater, agricultural non-point source pollution, and domestic sewage. An innovative multi-source data fusion-based pollution source identification model was constructed, achieving precise localization and quantitative assessment of various pollution sources in complex aquatic environments. For different types of pollution sources, integrated remediation strategies combining physicochemical methods, bioremediation, and ecological engineering techniques were proposed and demonstrated in typical regions. The findings indicate that the developed identification model can accurately differentiate pollutants from various sources with a precision exceeding 90%. The comprehensive remediation technologies significantly reduced concentrations of major pollutants in contaminated water bodies, leading to noticeable improvements in water quality. The results demonstrate that this methodological fr amework exhibits strong applicability and effectiveness, offering new approaches for water pollution control and contributing significantly to enhancing water environmental quality.
Keyword:Water Pollution Source Identification Multi-Source Data Fusion Model Comprehensive Management Technology
目 录
1绪论 1
1.1水污染源识别与治理的背景意义 1
1.2国内外研究现状综述 1
1.3本文研究方法与技术路线 2
2水污染源识别技术体系 2
2.1污染源分类与特征分析 2
2.2污染物追踪与溯源方法 3
2.3遥感与地理信息系统应用 3
3水污染治理关键技术 4
3.1物理化学处理工艺优化 4
3.2生物修复技术及其应用 4
3.3新型材料在水处理中的应用 5
4水污染防控综合策略 5
4.1源头控制与清洁生产 5
4.2污染预警与应急响应机制 6
4.3政策法规与管理措施完善 7
结论 7
参考文献 9
致谢 10
水污染是全球面临的重大环境问题，对生态系统和人类健康构成严重威胁。本研究旨在系统识别主要水污染源并探索有效的治理技术，以期为水环境保护提供科学依据和技术支持。通过文献综述、实地调研与实验分析相结合的方法，全面梳理了工业废水、农业面源污染及生活污水等主要污染源的特征及其对水体的影响机制。创新性地构建了基于多源数据融合的污染源识别模型，实现了对复杂水环境中各类污染源的精准定位与定量评估。针对不同类型的污染源，提出了物理化学法、生物修复法以及生态工程技术相结合的综合治理方案，并在典型区域开展了应用示范。研究表明，所提出的识别模型能够准确区分不同来源的污染物，其精度达到90%以上；综合治理技术可使受污染水体的主要污染物浓度显著降低，水质明显改善。研究结果表明，该方法体系具有较强的适用性和有效性，为水污染防控提供了新的思路与方法，对于推动水环境质量提升具有重要意义。
关键词：水污染源识别 多源数据融合模型 综合治理技术
Abstract
Water pollution poses a significant environmental challenge globally, severely threatening ecosystems and human health. This study aims to systematically identify major sources of water pollution and explore effective remediation technologies to provide scientific evidence and technical support for water resource protection. By integrating literature review, field investigation, and experimental analysis, this research comprehensively examined the characteristics and impact mechanisms of primary pollution sources including industrial wastewater, agricultural non-point source pollution, and domestic sewage. An innovative multi-source data fusion-based pollution source identification model was constructed, achieving precise localization and quantitative assessment of various pollution sources in complex aquatic environments. For different types of pollution sources, integrated remediation strategies combining physicochemical methods, bioremediation, and ecological engineering techniques were proposed and demonstrated in typical regions. The findings indicate that the developed identification model can accurately differentiate pollutants from various sources with a precision exceeding 90%. The comprehensive remediation technologies significantly reduced concentrations of major pollutants in contaminated water bodies, leading to noticeable improvements in water quality. The results demonstrate that this methodological fr amework exhibits strong applicability and effectiveness, offering new approaches for water pollution control and contributing significantly to enhancing water environmental quality.
Keyword:Water Pollution Source Identification Multi-Source Data Fusion Model Comprehensive Management Technology
目 录
1绪论 1
1.1水污染源识别与治理的背景意义 1
1.2国内外研究现状综述 1
1.3本文研究方法与技术路线 2
2水污染源识别技术体系 2
2.1污染源分类与特征分析 2
2.2污染物追踪与溯源方法 3
2.3遥感与地理信息系统应用 3
3水污染治理关键技术 4
3.1物理化学处理工艺优化 4
3.2生物修复技术及其应用 4
3.3新型材料在水处理中的应用 5
4水污染防控综合策略 5
4.1源头控制与清洁生产 5
4.2污染预警与应急响应机制 6
4.3政策法规与管理措施完善 7
结论 7
参考文献 9
致谢 10
