相关实验视频

Updated: Jan 9, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

使用可解释的机器学习解读流域中新出现的污染物的运输值

Wei Guo¹, Yimei Huang¹, Yudan Huang²

¹Key Laboratory of Plant Nutrition and Agri-environment in Northwest China, Ministry of Agriculture, College of Natural Resource and Environment, Northwest A&F University, Yangling 712100, China.

|December 4, 2025

概括

微塑料和抗生素等新出现的污染物威胁到黄河的水安全. 机器学习模型揭示了影响其运输的土地使用和气候因素,为流域管理提供了战略.

科学领域:

环境科学环境科学
水资源管理水资源管理
机器学习应用机器学习应用

背景情况:

了解流域新兴污染物 (EC) 运输对于污染控制至关重要,但受到复杂的土地气候相互作用和有限的预测模型的阻碍.
微塑料 (MP) 和抗生素是对水安全构成威胁的重要EC,需要对其传输机制进行详细调查.
现有的模型往往无法捕捉到土地利用,气候变量和河流系统中的EC运输之间的复杂关系.

研究的目的:

开发和验证一种新的机器学习框架 (ML-SHAP) 用于在黄河上建模EC运输.
在季节性水样中量化MP,抗生素,重金属和水质指标的含量.
确定影响流域内国会议员和抗生素运输的关键土地使用和气候驱动因素.

主要方法:

在2020-2024年期间从黄河收集了517个季节性水样,用于污染物分析.
开发了一个机器学习 (ML-SHAP) 框架,整合了多尺度的土地使用数据,景观指标 (PD,LPI,CONTIG-MN) 和11个气候变量.
模拟EC运输使用ML-SHAP框架,实现高准确度的培训数据 (R2 = 0.94) 和良好的表现测试数据 (R2 = 0.65).

主要成果:

微塑料含量达到1831个物品/L,抗生素度达到55.33 ng/L,这表明水安全存在重大风险.
议员的运输与分散的城市土地和连接的耕地有关,而抗生素运输则在连接较少的耕地中加剧.
森林和草原覆盖面,特别是增强的连通性,有效地减轻了EC的运输;特定的气候条件对MP和抗生素运输产生了不同的影响.

结论:

该ML-SHAP框架为了解和预测EC运输提供了一个强大的工具,整合了复杂的环境因素.
沿海森林和草原的增强,以及减少城市碎片化,是缓解ECs的关键战略.
气候变化场景 (SSP585) 预计将增加MP和抗生素负载,强调需要适应性流域管理策略,包括重新造林 (SSP245).

关键词:

气候变化气候变化气候变化新出现的污染物新出现的污染物土地使用情况土地使用情况机器学习机器学习值效应是一种值效应.

更多相关视频

Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics

Author Spotlight: Understanding and Detecting Environmental Antimicrobial Resistance by Combining Culture-Based Techniques and Genomics

Published on: July 19, 2024

Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology

Unraveling the Unseen Players in the Ocean - A Field Guide to Water Chemistry and Marine Microbiology

Published on: November 5, 2014

相关概念视频

Steps in Outbreak Investigation

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Design Example: Analyzing Capacity Contours for Flood Risk Assessment

Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...