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保护性耕作下土壤水分变化特征模拟研究
引用本文:王钧,李广,聂志刚,刘强,闫丽娟. 保护性耕作下土壤水分变化特征模拟研究[J]. 农业机械学报, 2021, 52(1): 263-274
作者姓名:王钧  李广  聂志刚  刘强  闫丽娟
作者单位:甘肃农业大学信息科学技术学院,兰州730070;甘肃农业大学林学院,兰州730070;甘肃农业大学农学院,兰州730070
基金项目:国家自然科学基金地区科学基金项目(31660348)、甘肃省重点研发计划项目(18YF1NA070)、甘肃省自然科学基金项目(20JR10RA509)、甘肃省财政专项(GSCZZ-20160909)、甘肃省高等学校创新基金项目(2020B-121)和甘肃农业大学信息科学技术学院发展基金项目(GAU-XKFZJJ-2012-12)
摘    要:为了对陇中黄土高原沟壑区不同保护性耕作措施下的土壤含水率进行差异性分析,利用长期定位试验,设置春小麦/豌豆、豌豆/春小麦轮作序列下传统耕作、免耕、传统耕作秸秆覆盖和免耕覆盖4种耕作措施,以当地月平均气温、月降水量、月平均辐射量、月平均蒸发量、月作物耗水量作为输入,以0~200 cm 土层土壤含水率作为输出,建立基于长短...

关 键 词:保护性耕作  轮作  土壤含水率  LSTM神经网络
收稿时间:2020-04-16

Simulation on Variation Characteristics of Soil Water Content under Conservation Tillage
WANG Jun,LI Guang,NIE Zhigang,LIU Qiang,YAN Lijuan. Simulation on Variation Characteristics of Soil Water Content under Conservation Tillage[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(1): 263-274
Authors:WANG Jun  LI Guang  NIE Zhigang  LIU Qiang  YAN Lijuan
Affiliation:Gansu Agricultural University
Abstract:Long-term positioning experiment was used to set up four sorts of tillage measures (traditional tillage, no-tillage, traditional tillage straw mulching and no-tillage with straw cover) for the rotation sequence of spring wheat/pea and pea/spring wheat. The monthly precipitation, monthly average radiation, monthly average evaporation, and monthly crop water consumption were used as input factors, and monthly average soil water content was used as an output to establish a prediction model of soil water content based on long short-term memory (LSTM) neural network, and the validity of the model was evaluated to analyze the differences of soil water content effect of different conservation tillage measures in the Loess Plateau gully region of central Gansu, then the model was applied to simulate the dynamics of the soil water content under four tillage measures in the 0~200cm soil layer. The results demonstrated that the soil water model based on LSTM neural network had good applicability for predicting soil water content under conservation tillage in the Loess Plateau gully region of central Gansu, the average root mean square error, mean relatively error and determination coefficient of the model were 2.29%, 6.79% and 0.82, respectively. In pea/spring wheat rotation sequence, the soil water content of four treatments was increased by 1.49%, 1.61%, 1.69% and 1.76%, respectively, compared with spring wheat/pea, the descending order of soil water content of the four tillage measures was as follows: no-tillage with straw cover, no-tillage, traditional tillage straw mulching, and traditional tillage in 0~200cm soil layer, the average soil water content of no-tillage with straw cover was increased by 1.27%, 1.75% and 2.81%, respectively, compared with no-tillage, traditional tillage straw mulching, and traditional tillage. The no-tillage with straw cover had the most significant effect on soil water content in 0~30cm soil layer, the average soil water content of no-tillage with straw cover was increased by 1.60%, 2.63% and 4.18%, respectively, compared with no-tillage, traditional tillage straw mulching, and traditional tillage. Soil water content of four tillage measures was changed with seasons, but the soil water content effect of no-tillage with straw cover was better than that of the other three tillage measures, the effects of water storage and soil moisture conservation were more significant during pre-crop growth. The LSTM neural network model achieved good simulation results on the soil water content in the Loess Plateau gully region of central Gansu, the soil water content of four tillage measures in the pea/spring wheat rotation sequence was relatively higher, no-tillage with straw cover was beneficial to improve the soil water content of farmland in the study area the under four tillage measures, and the most suitable one was conservation tillage measure in the Loess Plateau gully region of central Gansu.
Keywords:conservation tillage  rotation  soil water content  LSTM neural network
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