干旱区研究 ›› 2018, Vol. 35 ›› Issue (6): 1487-1495.doi: 10.13866/j.azr.2018.06.27

• 生态与环境 • 上一篇    下一篇

长期膜下滴灌棉田残膜变化趋势研究

贺怀杰1,2, 王振华1,2, 郑旭荣1,2, 张金珠1,2, 李文昊1,2   

  1. 1.石河子大学水利建筑工程学院,新疆 石河子 832000;
    2.现代节水灌溉兵团重点实验室,新疆 石河子 832000
  • 收稿日期:2018-03-27 修回日期:2018-07-23 出版日期:2018-11-15 发布日期:2025-11-18
  • 通讯作者: 王振华. E-mail:wzh2002027@163.com
  • 作者简介:贺怀杰(1993-),男,硕士研究生,主要从事干旱区节水灌溉理论与技术研究. E-mail:hehuaijie2016@163.com
  • 基金资助:
    国家科技支撑计划(2015BAD20B03);国家重点研发计划(2017YFD0201506);兵团中青年科技创新领军人才计划(2015BC001)

Change Trend of Residual Film in Soil in Cotton Field under the Long-term Mulched Drip Irrigation

HE Huai-jie1,2, WANG Zhen-hua1,2, ZHENG Xu-rong1,2, ZHANG Jin-zhu1,2, LI Wen-hao1,2   

  1. 1. College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi 832000, Xinjiang, China;
    2. Key Laboratory of Modern Water-saving Irrigation of Xinjiang Corps of Production and Construction, Shihezi University, Shihezi 832000, Xinjiang,China
  • Received:2018-03-27 Revised:2018-07-23 Published:2018-11-15 Online:2025-11-18

摘要: 为探寻棉田土壤中残膜污染状况以及覆膜30 a棉田土壤中的残膜分布趋势,对试验区121团覆膜年限分别为5 a、9 a、11 a、13 a、15 a和19 a共6块棉田进行取样研究。运用Matlab程序构建BP神经网络模型,对取样数据进行分层预测和整体预测,结果表明:运用模型对残膜面积和质量数据进行整体预测,能够更好地反映实际情况下残膜在棉田土壤中的分布趋势,能够精准地预测本地区覆膜30 a棉田土壤中地膜残留状况;同时随着覆膜年限的增加,土壤表层大面积残膜在耕地作业下逐年碎裂,并向深层土壤移动,在30~40 cm深度的土壤中逐年残留。通过预测得到覆膜30 a棉田残膜密度达到419.19 kg·hm-2,超出国家标准限值75.0 kg·hm-2近6倍,为解决此问题可以覆盖厚度大于0.010 mm的农用地膜,并提高地膜回收率来保证棉田的可持续发展。

关键词: 典型绿洲区, BP神经网络, 棉田, 残膜污染, 残膜密度, 可持续发展, 石河子

Abstract: In order to explore the pollution and distribution of residual mulching plastic film in soil in cotton field in recent 30 years, the sample plots in 121st State Farm of Xinjiang Corps of Production and Construction were selected as the experimental areas, where the mulching film was used for 5, 9, 11, 13, 15 and 19 years respectively. The Matlab program was used to develop the BP neural network model for hierarchical prediction and overall prediction of sample data. The results showed that the residual film area and quality data predicted with the model could be used to perfectly reflect the distribution of residual film in soil in cotton field in recent 30 years. The residual film in topsoil was broken year by year with the time increase of mulching plastic film and moved down to deep soil (30-40 cm). The predicted result revealed that the residual film density in cotton field would reach 419.19 kg·hm-2 after mulching plastic film was used for 30 years, which would be nearly 6 times of the national standard limit (75.0 kg·hm-2). In order to solve this problem, it is suggested to use the plastic film thicker than 0.010 mm, increase the recovery of mulching plastic film, and ensure the sustainable development of cotton field.

Key words: typical oasis, BP Neural Network, cotton field, residual film pollution, residual film density, sustainable development, Shihezi