摘要
为分析陇中黄土高原沟壑区不同保护性耕作措施的贮水效果,本研究利用春小麦/豌豆(W/P)、豌豆/春小麦(P/W)轮作的长期定位试验,分别设置传统耕作(T)、免耕(NT)、传统耕作秸秆覆盖(TS)和免耕覆盖(NTS)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、月作物耗水量为输入因子,以月土壤贮水量为输出,建立基于长短期记忆(Long Short-Term Memory,LSTM)神经网络的土壤贮水量预测模型,并对该模型的有效性进行评估。研究结果表明:1)基于LSTM神经网络建立的土壤贮水量模型对陇中黄土高原沟壑区保护性耕作下土壤贮水量预测具有较好的适用性,模型模拟结果的平均均方根误差为7.76mm,平均绝对误差为6.95mm,相对误差控制在5%^+5%的范围内。2)P/W轮作序列中各处理的土壤贮水量均比W/P轮作序列增加1.09%~1.43%。3)不同轮作序列,NTS处理的贮水效果均优于其他3种耕作措施,在W/P轮作序列中,NTS处理的年均土壤贮水量比T、NT和TS分别增加2.89%、1.70%和2.46%;在P/W轮作序列中,NTS处理的年均土壤贮水量比T、NT和TS分别增加3.03%、1.91%和2.57%。4)不同降水年型,NTS处理的土壤贮水量最高,且干旱年效果更加显著,其中丰水年NTS处理的土壤贮水量比T、NT和TS平均增加2.71%、1.48%和2.19%,而干旱年平均增加3.97%、2.54%和3.64%。5)保护性耕作措施的贮水效果随季节发生变化,作物生长前期(3—5月)保护性耕作措施的贮水优势较为明显,进入作物生长旺盛期(5—6月)保护性耕作措施与传统耕作的贮水效果差异不显著,而作物生长后期(7月)保护性耕作措施较传统耕作土壤贮水量明显增加。基于LSTM神经网络模拟环境下免耕覆盖的贮水保墒效果最好,为陇中黄土高原沟壑区最适宜的保护性耕作措施。
In order to analyze the effects of soil water storage for four different tillage measures [traditional tillage (T), no-tillage with no straw cover (NT), traditional tillage with straw incorporation (TS) and no-tillage with straw cover (NTS)], the field research was conducted in the Loess Plateau Gully Region of central Gansu. The objectives of the study were to establish a prediction model for soil water storage based on Long Short-Term Memory (LSTM), and to evaluate the model’s effectiveness using the long-term positioning experiment of the rotation sequence for spring wheat/pea (W/P) and pea/spring wheat (P/W) crops. In the experiment, monthly average temperature, monthly precipitation, monthly average radiation, monthly average evaporation and monthly crop water consumption constituted input factors, and value for soil water storage constituted the output factor in the prediction model. The results of the present study showed that: 1) The water storage model based on LSTM neural network showed good applicability for predicting soil water storage, particularly in conservation tillage practice, in the Loess Plateau Gully Region of central Gansu. The average root mean square error and mean absolute error of the model simulation were 7.76 mm and 6.95 mm, respectively;moreover, the relative error was controlled between 5% and +5%. 2) In P/W rotation sequence, the soil water storage of various treatments increased by 1.09%1.43% as compared to W/P. 3) Within different rotation sequences, water storage effect of NTS treatment turned out to be better than those for other three tillage measures. In W/P rotation sequence, the annual average soil water storage of NTS treatment was 2.89%, 1.70% and 2.46% higher than that of T, NT, and TS, respectively. In P/W rotation sequence, the average annual soil water storage of NTS treatment increased by 3.03%, 1.91% and 2.57%, respectively, compared to that of T, NT, and TS. 4) In the years with different precipitation, the soil water storage of NTS treatment was the highest, and
作者
王钧
李广
刘强
WANG Jun;LI Guang;LIU Qiang(College of Forestry,Gansu Agricultural University,Lanzhou 730070,China;College of Information Science and Technology,Gansu Agricultural University,Lanzhou 730070,China)
出处
《中国生态农业学报（中英文）》
CAS
CSCD
北大核心
2019年第8期1226-1237,共12页
Chinese Journal of Eco-Agriculture
基金
甘肃农业大学学科建设基金(GAU-XKJS2018258,GAU-XKJS2018254,GAU-XKJS2018255)
甘肃农业大学青年导师基金项目(GAU-QNDS-201702)资助
国家自然科学基金项目(31560343,31560378)~~
关键词
保护性耕作
春小麦/豌豆轮作
土壤贮水量
LSTM神经网络
预测模型
陇中黄土高原沟壑区
Conservation tillage
Spring wheat/pea rotation
Soil water storage
LSTM neural network
Prediction model
Loess Plateau Gully Region of central Gansu
