生态护坡生境基材土壤肥力动态变化研究
Soil Fertility Dynamics of Substrate Used for Ecological Slope Protection
投稿时间:2015-08-14  修订日期:2017-04-13
DOI:10.15928/j.1674-3075.2017.02.005
中文关键词:边坡  生境基材  土壤肥力  动态变化  T-S模糊神经网络
英文关键词:slope protection  ecological substrate  soil fertility  dynamic change  T-S fuzzy neural network
基金项目:国家“十二五”科技支撑项目(2012BAC06B02-04);国家自然科学基金项目(51278281)
作者单位E-mail
丁瑜 三峡大学 土木与建筑学院湖北 宜昌 443002三峡地区地质灾害与生态环境湖北省协同创新中心湖北 宜昌 443002 thirdding@163.com 
胡文静 三峡大学 土木与建筑学院湖北 宜昌 443002 huerde@163.com 
夏振尧 三峡大学 土木与建筑学院湖北 宜昌 443002三峡地区地质灾害与生态环境湖北省协同创新中心湖北 宜昌 443002 xzy_yc@126.com 
李博 三峡大学 土木与建筑学院湖北 宜昌 443002 492417894@qq.com 
姚小月 三峡大学 水利与环境学院湖北 宜昌 443002 523009901@qq.com 
许文年* 三峡大学 土木与建筑学院湖北 宜昌 443002三峡地区地质灾害与生态环境湖北省协同创新中心湖北 宜昌 443002 xwn@ctgu.edu.cn 
摘要点击次数: 2018
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中文摘要:
      分析植被恢复过程中基材土壤肥力,可为改进生境基材性能、完善植被混凝土生态防护技术提供科学依据。在湖北省宜昌市选取清江水布垭电站公路边坡(S样地)、高坝洲电站进厂公路边坡(G样地)和三峡大学图书馆后边坡(T样地)等3个植被混凝土生态修复边坡,采用系统布点法,在坡面5~10cm深度处取环刀样,对生境基材多年份(2007-2012年)土壤主要肥力因子进行定量测定,并采用T-S模糊神经网络模型对肥力水平进行综合评价分析。监测结果表明:有机质S样地由13.34 g/kg增加至32.89 g/kg,G样地由14.78 g/kg增加至35.02 g/kg,T样地在5.65~22.87 g/kg缓慢、波动增长;土壤全氮含量S样地0.12~2.27 g/kg,G样地0.13~1.64 g/kg,T样地0.08~0.84 g/kg;速效氮含量S样地23.94~170.87 mg/kg,G样地31.70~237.51 mg/kg,T样地20.88~122.28 mg/kg;全磷变化范围S样地2.30~2.66 g/kg,G样地1.64~2.06 g/kg,T样地1.63~2.18 g/kg; 速效磷S样地2007、2009年异常丰富,均在300 mg/kg以上,其余年度为36.23~154.29mg/kg,G、T样地变化规律与S样地类似;速效钾G样地波动范围在59.87~207.03mg/kg,S样地、T样地波动幅度较小且总体处于丰富水平。模型计算结果显示,随着监测时间推移,各样地综合肥力指数逐渐减小趋于稳定,综合肥力指数S样地3.14~2.69,G样地3.25~2.73,T样地3.47~2.74。总体上,各样地综合肥力水平呈现先增长后稳定的发展趋势,肥力综合等级处于中等向上水平。
英文摘要:
      Analysis of substrate soil fertility during the process of vegetation restoration provides a scientific basis for improving substrate soil performance and the vegetation concrete technique used for ecological restoration. In this study, we analyzed substrate soil fertility on three slopes where vegetated concrete was used for ecological restoration: a slope on the Shuibuya Power Station highway on Qingjiang River (Plot S, established April, 2000), a slope on the Gaobazhou power station highway (Plot G, established March, 2002) and the slope behind the library of China Three Gorges University in Yichang city, Hubei Province (Plot T, established March, 2004). Soil samples were collected at a depth of 5-10 cm using the cutting ring method and the major fertility factors were determined annually from 2007 to 2012. The substrate soil fertility was evaluated using a T-S fuzzy neural network and the dynamics and succession of substrate soil fertility were analyzed. The substrates used at the three experimental plots were of similar composition; For Plots S and T, the soil:concrete:organic matter?additive ratio was 100?7.8?5?4.6 and, for Plot G, the ratio was 100?8?5?5. From 2007 to 2012, the fertility factors of the soils were determined annually, including soil bulk density, organic matter, available nitrogen, total nitrogen, available phosphorus, total phosphorus and available potassium. Soil organic matter increased from 13.34 g/kg to 32.89 g/kg in Plot S, from 14.78 g/kg to 35.02 g/kg in Plot G and, with fluctuation, from 5.65 to 22.87 g/kg in Plot T. In the same order of experimental plots (S, G, T), total nitrogen ranges were 0.12-2.27 g/kg, 0.13-1.64 g/kg and 0.08-0.84 g/kg, while available nitrogen ranges were 23.94-170.87 mg/kg, 31.70-237.51 mg/kg, 20.88-122.28 mg/kg and total phosphorus ranges were 2.30-2.66 g/kg, 1.64-2.06 g/kg, and 1.63-2.18 g/kg. Rapidly available phosphorus in all three plots was unusually high in 2007 and 2009 ,especially for Plot S (>300 mg/kg) and averaged 36.23-154.29 mg/kg in other years. Available potassium was adequate in all plots, fluctuating from 59.87 to 207.03 mg/kg in Plot G and within smaller ranges in Plots S and T. The comprehensive index of substrate soil fertility calculated using the T-S fuzzy neural network model was 3.14-2.69 for Plot S, 3.25-2.73 for Plot G and 3.47-2.74 for Plot T. During the vegetated concrete ecological restoration, soil bulk density tended to decrease, available and total nitrogen tended to increase, and organic matter, available potassium, and available and total phosphorus fluctuated. The comprehensive fertility of the three slopes increased initially and then stabilized at an adequate level. The comprehensive fertility level evaluation using the T-S fuzzy neural network model was consistent with observed slope conditions, indicating that the T-S fuzzy neural network model effectively predicts the results of ecological slope restoration using vegetated concrete.
丁瑜,胡文静,夏振尧,李博,姚小月,许文年.2017.生态护坡生境基材土壤肥力动态变化研究[J].水生态学杂志,38(2):31-37.
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