植被类型在极端降雨下主导斜坡级物质损失:机器学习揭示了非线性反应
Aipu Wu1, Chunzi Ma1, Shouliang Huo2
1School of Water Conservancy and Civil Engineering, Northeast Agricultural University, Harbin 150038, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
Journal of contaminant hydrology
|January 11, 2026
概括
气候变化加剧了极端降雨,增加了土壤侵蚀和污染. 植被类型和降雨强度是控制物质损失的关键因素,农田是最脆弱的.
科学领域:
- 环境科学 环境科学
- 水文学的水文学
- 气候变化的影响 气候变化的影响
背景情况:
- 气候变化加剧的极端降雨事件威胁到山区农业流域的土壤侵蚀和非点源污染 (NPS).
- 了解不同降雨模式下的物质损失对于流域管理至关重要.
研究的目的:
- 调查极端降雨对斜坡土壤侵蚀和NPS污染的影响.
- 在不同的植被和斜坡类型下量化物质损失 (土壤,TN,TP,COD).
- 确定控制极端降雨事件期间物质损失的主导因素.
主要方法:
- 利用了7年的实地观测 (2014-2020年) 来自四个冲流地块 (农田与灌木地,坡与温和坡).
- 采用机器学习框架,将随机森林 (RF) 与顺序向后选择 (SBS) 和相对重要性 (RI) 分析集成.
- 根据降雨深度和30分钟最大强度 (I30) 分析了61个下水事件,包括10个极端降雨事件.
主要成果:
- 极端降雨事件 (16.4%的总量) 显著导致土壤损失 (41.9%) 和COD (49.2%).
- 在极端降雨期间,农田地块的物质损失比灌木地块的物质损失高2-5倍.
- 植被类型和60分钟降雨强度 (I60) 是控制极端降雨下的损失的主要因素.
结论:
- 植被类型在控制斜坡尺度物质损失方面发挥着主导作用.
- 机器学习框架在解释复杂的水文过程和确定关键物质损失值方面是有效的.
- 这些发现强调了农业水域对极端降雨的脆弱性,并强调了植被管理的重要性.
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