一种新的非线性直接映射方法,用于在强烈的人类干扰下对表面水质变化的多次时间尺度驱动力分析
Yelin Wang1, Yanpeng Cai1, Bowen Li1
1Guangdong Basic Research Center of Excellence for Ecological Security and Green Development, Guangdong Provincial Key Laboratory of Water Quality Improvement and Ecological Restoration for Watersheds, School of Ecology, Environment and Resources, Guangdong University of Technology, Guangzhou, Guangdong, 510006, China.
Journal of environmental management
|August 6, 2024
概括
一种新的非线性绘图方法有效地分析了地表水质量的驱动因素,精度提高了12.43%. 它确定了影响珠江三角洲 (PRD) 总 (TN) 和总 (TP) 的人类活动和自然因素.
科学领域:
- 环境科学 环境科学
- 水质管理水质管理
- 统计建模 统计建模
背景情况:
- 表面水质的变化对于城市管理至关重要,但传统方法在非线性关系和多个时间尺度上扎.
- 确定水质的驱动因素对于人口密集地区的有效环境管理至关重要.
研究的目的:
- 开发和验证一种非线性直接映射方法,用于在多个时间尺度上对地表水质量驱动因素进行定量分析.
- 将新方法的有效性与分析水质数据的传统统计方法进行比较.
主要方法:
- 开发了一种非线性直接映射方法,将波动和趋势信息与水质数据分开.
- 建立了直接映射关系,以创建可见的多层结构,捕获线性和非线性信息.
- 应用该方法分析珠江三角洲 (PRD) 的总 (TN) 和总 (TP).
主要成果:
- 与传统方法相比,新方法在合度上取得了12.43%的改善.
- 成功地确定了TN和TP的主导驱动因素,即人类活动 (NO2,PM) 和PRD中的自然因素.
- 在各种未来情景下,在PRD中表明TP的潜在风险增加.
结论:
- 开发的非线性直接映射方法提供了增强的解释性,并在水质数据中捕获复杂的非线性信息.
- 为短期污染预警和长期工业结构调整规划提供可靠的参考.
- 强调人类活动和自然因素对PRD水质的重大影响.
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