With the large-scale farming area of cotton expanding and labor force cost increasing, applying intelligent irrigation control system in traditional drip irrigation under plastic mulch had become a new method and trend to improve the mechanization and automation level of Xinjiang region’s cotton field water management. Soil water content monitoring is an important part of intelligent irrigation control system, and its measurement precision directly determines irrigation decision reasonability. However, with the mechanical-harvesting cotton field, there are relatively few reports which centered on the soil content spatial and temporal variability and reasonable monitoring sensor placement method. This study chooses mechanical-harvesting cotton field with typical soil textile as research object. Through applying different watering scheduling in main irrigation seasons, the spatial and temporal distribution of soil water content and crop roots are observed and the relationship between them is analyzed. With the help of error analytic method, the soil moisture sensor position on one profile could be determined. On the basis of this work, the soil water content and its spatial variation on the profile sensor placement spot in a typical rotation irrigation cotton field was measured The relationship between soil water content sensor number and measurement precision is analyzed. In the end, appropriate soil moisture sensor number and distribution method could be acquired, and the irrigation control threshold at cotton main watering stage is also given. This study will be very significant for soil moisture sensors reasonable placement and intelligent irrigation control system’s scientific watering decision.
随着棉花规模化种植面积的扩大与劳动力成本的提高,在传统膜下滴灌中引进智能灌溉控制系统,提高棉田水分管理的自动化水平,是未来新疆应用膜下滴灌技术新的发展方向。墒情监测是智能灌溉控制系统的重要组成部分,其测墒精度直接影响灌溉决策的合理性,但关于机采膜下滴灌棉田水分时空变异规律及其测墒点布设方法的研究报道较少。本项目选择典型土壤质地下的机采棉田为研究对象,通过实施不同灌水频率与灌水量处理,测定土壤剖面含水率与作物根系在主要灌水期内的时空分布规律,阐明水分与根系的相互作用,应用误差分析方法,确定土壤剖面测墒传感器的适宜埋设位置。在此基础上,研究一个典型轮灌条田内传感器埋设位置处土壤含水率的空间变异规律,探讨布设数量与测墒精度的相互关系,明确适宜的测墒传感器布设数量及布置方法,给出棉花灌水期墒情监测值的灌溉控制下限指标。本项目为提高智能灌溉控制系统测墒传感器布设合理性与灌溉决策科学性提供理论依据。
新疆地区是我国的主要棉区。近年来,随着种植规模化、集约化与自动化水平的提高,采用智能灌溉或自动控制灌溉以提高生产效率成为棉田水分管理的发展趋势。墒情监测是智能灌溉系统灌水决策的基础和依据。本项目以不同土壤质地机采棉田为研究对象,通过设置不同的灌水频率和灌水定额,研究不同条件下的墒情时空变异规律与根系分布规律,确定监测传感器的适宜埋设位置、数量和布设间距,根据优选灌溉制度的灌前土壤剖面平均含水率及其与测墒点墒情的回归计算公式,确定出适宜的灌溉测墒控制指标。取得的主要结论如下:.(1)膜下滴灌棉田土壤剖面水分沿横向和垂向呈不均匀分布;灌水频率、灌溉水量和土壤质地对棉田土壤剖面水分分布影响显著。不同灌水量对不同质地土壤的影响深度和宽度差异显著,F80对粘壤土各层次的含水率影响显著,F40影响深度有限,沙壤土的水分分布较粉质壤土和粘壤土复杂。.(2)棉花0~20cm土层根干物质占总根干物质的64.4%~85.1%。根长和根表面积主要集中在0~40cm土层,高中低三个水分处理的根长占总根长比例分别为88%(粗根:细=3:97)、80%(粗根:细根=2:98)和69%(粗根:细根=4:96),根表面积分别占总根表面积的88%(粗根:细跟=23:77)、78%(粗根:细跟=14:86)和69%(粗根:细跟=15:85)。.(3)膜下滴灌适宜测墒点布设位置与水分处理、种植方式及测墒范围有很大关系,同时也受土壤质地的影响。粉砂壤土机采棉田(1膜2带6行)膜下0~60cm土层的最优测墒点位置坐标为(47,-28),膜+裸地0~100cm土层最优测墒点位置坐标为(49,-29)。沙壤土棉田在该测墒范围的最优测墒点坐标分别为(72,-28)和(62,-29)。粘壤土分别为(65,-28)和(60,-29),测墒相对误差均小于5%。最优测墒点布设数量与允许误差精度成反比,与置信水平成正比,典型大小(200亩)棉田的测墒传感器适宜布设数量为6个,布置间距大于122m。.(4)采用高频小定额灌溉更有利于提高机采棉的籽棉和皮棉产量,从产量及水分利用效率看,F5T60是机采棉田较合理的灌水处理组合。不同土壤质地棉田蕾期、花铃前期和花铃后期的灌前测墒土壤含水率控制下限指标分别为31%、34%和33%(粉沙壤土);38%、38%和37%(沙壤土);34%、39%和39%(粘壤土)。
{{i.achievement_title}}
数据更新时间:2023-05-31
路基土水分传感器室内标定方法与影响因素分析
涡度相关技术及其在陆地生态系统通量研究中的应用
宁南山区植被恢复模式对土壤主要酶活性、微生物多样性及土壤养分的影响
疏勒河源高寒草甸土壤微生物生物量碳氮变化特征
货币政策与汇率制度对国际收支的影响研究
miR-155、miR-192调控Rho A/Rho GTPase信号通路对原发性开角型青光眼的干预
滴灌棉田土壤水分空间变异机理及水分传感器布设方法研究
非灌溉季节长期膜下滴灌棉田土壤盐分时空迁移机理研究
基于无限制水分区间的南疆膜下滴灌棉田土壤水分调控机理研究
典型绿洲区长期膜下滴灌棉田盐碱土壤离子时空迁移机理研究