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黄土丘陵区不同植被带典型小流域生态脆弱性评价 被引量:16

Eco-environment vulnerability assessment of typical small watersheds in different vegetation zones of loess hilly area
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摘要 以位于黄土丘陵区延河流域不同植被带的6个典型小流域为研究对象,采用空间主成分分析法,对小流域生态脆弱性进行了评价。结果表明,不同植被带典型小流域间的生态脆弱性程度差异明显,森林带整体处于轻度脆弱水平,森林草原带整体处于中度脆弱水平,草原带整体处于重度脆弱水平。各植被带典型小流域生态脆弱等级随坡度变化均表现出一定的规律,微度脆弱主要分布在3°以下,而后随坡度增大呈现"减小-增大-减小"的波浪式变化趋势,其他各脆弱等级随坡度变化均呈现先增大后减小的变化趋势,且均在15°~35°之间达到最大值。典型小流域生态最脆弱的地方不在海拔最高的地方,而在中低海拔段,这与延河流域特殊的地貌特征和侵蚀环境有关。研究结果可为延河流域的土地资源合理配置、生态恢复及相关研究提供参考。 The eco-environmental vulnerability was assessed taking six typical small watersheds of different vegetation zones in Yanhe River Basin as study cases, and spatial principal component analysis (SPCA) as the method. The results show that significant differences existed among typical small watersheds in different vegetation zones. The eco-environmental vulnerability is at light level in forest zone, at medial level in forest steppe zone and at heavy level in steppe zone. The vulnerability grades of typical small watershed in different vegetation zones all show certain regularity with the slope change. Slight vulnerability is mainly distributed within 3 degree, and then appears wavy changing trend of "decreasing -increasing -decreasing", while other grades of vulnerability first increase and then decrease with slopes and all reach the maximum between 15 degree and 35 degree. The most vulnerable of the typical small watersheds is not at the highest elevation section but the mid-to-lower elevation section. This is related to the special geomorphic characteristic and erosion environment in Yanhe River Basin. The research results can provide a reference of reasonable allocation of land resources, eco-environment restoration of the Yanhe River Basin, and correlative researches.
出处 《自然灾害学报》 CSCD 北大核心 2013年第5期149-159,共11页 Journal of Natural Disasters
基金 国家自然科学基金资助项目(41271043) 中科院知识创新重要方向项目(KZCX2-EW-406) 中国科学院重点部署项目(KZZD-EW-04-03) 西北农林科技大学科技创新重点项目(QN2011073)
关键词 延河流域 植被带 小流域 生态脆弱性 空间主成分分析 Yanhe River Basin vegetation zone small watershed eco-environment vulnerability spatial principal component analysis
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