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基于熵权法的林下土壤抗蚀性评价及影响因素分析 被引量:24

Evaluation of Forest Soil Anti-erodibility and Influencing Factors Analysis Based on Entropy Method
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摘要 针对南方红壤区林下水土流失的特征,以浙江省瓯江流域源头区为研究区域,经过2a近2 000km^2的野外考察,选择5种主要林地类型的林下土壤为评价对象,在系统采集土壤样品和多指标测试分析计算的基础上,建立了包含11项指标的评价体系,应用熵权法计算了各评价指标的权重,最后综合研究了试验区内不同林地林下土壤的抗蚀性差异和主要影响因素。结果表明:(1)5类林地林下土壤抗蚀性强弱的排序为灌木林>松树林>材用竹林>经济林>茶园;(2)影响林地林下土壤抗蚀性的主要因素为土壤机械组成的结构性、水稳性团聚体含量和有机质含量;(3)11项评价指标中的结构性颗粒指数、土壤团聚度和土壤结构体破坏率等指标能够很好的衡量土壤抗蚀性强弱。因此提出了在水源区控制经济林和茶园地面积、提高地上植被多层性结构、合理调控土壤机械组成的结构比例等有利于提高土壤抗蚀性能的建议。 In order to investigate the characteristics of soil and water loss of red soil area in southern China, we chose the headwater region of Oujiang River as the study area. Based on the field investigation across 2 000 km^2 in 2 years, we selected 5 main forest soils of different forest types as the evaluation objects. Through systematical sampling and multiple indexes testing, we established an evaluation system containing 11 indexes. By the use of entropy method, we studied on the differences and influencing factors of anti-erodibility of forest soil of different forest types. The results showed that: (1) soil anti-erodibilities of 5 forest types listed in the order of shrub〉pine forest〉bamboo forest〉economic forest〉tea garden; (2) The structure of soil mechanical composition, water-stable aggregate content and organic matter content were the main influencing factors of forest soil anti-erodibility; (3) Among 11 indexes, the structural particle index, soil aggregation, and ratio of soil structure destruction could measure the soil anti-erodibility well. Furthermore, we proposed several suggestions which aimed at improving soil anti-erodibility such as controlling the area of economic forest and tea garden, improving spatial structure of vegetation, and regulating structure proportion of soil mechanical composition.
出处 《水土保持学报》 CSCD 北大核心 2016年第4期74-79,共6页 Journal of Soil and Water Conservation
基金 瓯江源头生态健康评价与水保防护体系研究项目(H20132512)
关键词 熵权法 土壤抗蚀性 林下土壤 指标体系 信息熵 影响因素 entropy method soil anti-erodibility forest soil index system information entropy influencing factor
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