基于P-M模型的棉田智能灌溉系统的设计与试验

doi:10.6048/j.issn.1001-4330.2024.02.005

新疆农业科学 ›› 2024, Vol. 61 ›› Issue (2): 300-309.DOI: 10.6048/j.issn.1001-4330.2024.02.005

• 作物遗传育种·种质资源·分子遗传学 • 上一篇下一篇

基于P-M模型的棉田智能灌溉系统的设计与试验

惠瑞晗(), 林丽(), 曹伟, 张梦珂, 林豪, 姚帅

新疆农业大学水利与土木工程学院,乌鲁木齐 830052

收稿日期:2023-06-15 出版日期:2024-02-20 发布日期:2024-03-19
通信作者: 林丽(1977-),女,吉林长春人,教授,博士,硕士生导师,研究方向为水利信息化、水资源规划与利用,(E-mail)klmhll@126.com
作者简介:惠瑞晗(1998-),女,河南郑州人,硕士,研究方向为智慧农业,(E-mail)hrhdyx1998@163.com
基金资助:
新疆维吾尔自治区“十四五”重大专项“智慧灌区与现代农业产业绿色发展模式研究与示范”(2020A01003-4)

Design and experiment of intelligent irrigation system for cotton field based on P-M model

HUI Ruihan(), LIN Li(), CAO Wei, ZHANG Mengke, LIN Hao, YAO Shuai

College of Hydraulic and Civil Engineering, Xinjiang Agricultural University, Urumqi 830052, China

Received:2023-06-15 Online:2024-02-20 Published:2024-03-19
Correspondence author: LIN Li(1977-), female, from Changchun, Jilin, professor, doctor, master tutor, research direction:water conservancy informatization, water resources planning and utilization,(E-mail)klmhll@126.com
Supported by:
The Major Project of the "Fourteenth Five-Year Plan" of Xinjiang Uygur Autonomous Region "Research and Demonstration of Green Development Model of Intelligent Irrigation Areas and Modern Agricultural Industry"(2020A01003-4)

摘要/Abstract

摘要：

【目的】研究并分析基于P-M模型棉田智能灌溉系统的试验设计。【方法】基于P-M模型设计一套棉田智能灌溉系统,由数据采集节点、无线通信节点、云平台决策终端、灌溉应用节点四部分组成。数据采集节点的气象设备采集到数据后无线传输至云平台决策终端,终端基于P-M模型计算单次灌溉量,在指定的灌溉时间自动发出灌溉指令,灌溉应用节点接收指令开启阀门精确灌溉,土壤墒情变化由数据采集节点的墒情设备实时监测后无线传输到云平台展现;以当地传统灌溉模式作为对照(CK),灌溉系统设置120%(W₁)、100%(W₂)和80%(W₃)3种灌溉模式,进行田间试验。【结果】3个试验组灌溉工作在无人为干预的条件下实现全智能化,系统有效精准执行灌溉指令;在灌溉水充足的情况下可选用W₂模式,总耗水量较传统模式增加16.85%的情况下土壤含盐量下降13.65%,籽棉产量提高20.84%,水分利用效率提高3.41%,能够大幅度提高产量的同时有效改善土壤环境;W₃总耗水量较传统灌溉减少6.52%,土壤含盐量上升0.16%,盐渍化速度较传统灌溉模式变缓,籽棉产量提高11.18%,水分利用效率大幅提高,可达到兼顾提高产量与节水的效果。【结论】验证了智能灌溉系统的有效性和可行性,增加了灌溉系统的可选参数范围。

关键词: 棉花; 灌溉系统; 产量; 水分利用效率

Abstract:

【Objective】 Design and experiment of intelligent irrigation system for cotton field based on P-M model.【Methods】 Based on P-M model, a set of intelligent irrigation system for cotton field was designed, which consisted of four parts:data acquisition node, wireless communication node, cloud platform decision terminal, and irrigation application node.The data collected by the meteorological equipment of the data acquisition node was wirelessly transmitted to the cloud platform decision terminal.Then the terminal calculated the single irrigation amount based on the P-M model, automatically sent irrigation instructions at the specified irrigation time, and the irrigation application node received the instructions to open the valve for precise irrigation.The soil moisture change was monitored and wirelessly transmitted to the cloud platform by the moisture equipment of the data acquisition node in real time; The local traditional irrigation mode was taken as the control(CK), the irrigation system was set with 120%(W₁), 100%(W₂)and 80%(W₃)irrigation modes, and the actual test of three treatments was carried out in the field to verify the system effect.【Results】 The irrigation work of the three experimental groups was fully intelligent under the condition of no human intervention, and the system effectively and accurately executed the irrigation instructions; W₂ mode could be selected when the irrigation water was sufficient.When the total water consumption was 16.85% higher than that of the traditional mode, the soil salt content decreases by 13.65%, the seed cotton yield increases by 20.84%, and the water use efficiency increases by 3.41%.It significantly increased the yield and effectively improved the soil environment; Compared with traditional irrigation, the total water consumption of W₃ was reduced by 6.52%, the soil salt content was increased by 0.16%, the salinization rate slowed, the yield of seed cotton increased by 11.18%, and the water use efficiency greatly improved, which achieved the effects of both improving yield and saving water.【Conclusion】 The effectiveness and feasibility of the intelligent irrigation system has been verified in practice, which increases the range of optional parameters of the irrigation system.

Key words: cotton; irrigation system; yield; water use efficiency

中图分类号:

S274.2

惠瑞晗, 林丽, 曹伟, 张梦珂, 林豪, 姚帅. 基于P-M模型的棉田智能灌溉系统的设计与试验[J]. 新疆农业科学, 2024, 61(2): 300-309.

HUI Ruihan, LIN Li, CAO Wei, ZHANG Mengke, LIN Hao, YAO Shuai. Design and experiment of intelligent irrigation system for cotton field based on P-M model[J]. Xinjiang Agricultural Sciences, 2024, 61(2): 300-309.

图/表 11

表1 智能灌溉系统硬件参数

Tab.1 Hardware parameters of intelligent irrigation system

分部 Division	设备构成 Equipment of composition	型号规格 Specifications	性能 Performance	数量 Number
无线通信 Wireless communication	4G DUT模块	USR-DR154	RS485/RS232/TTL转4G Cat1	1
无线通信 Wireless communication	DUT模组	wH-LTE-7S1	串口转4G Cat1全网通、移动联通2G	6
数据采集 Data collection	净辐射仪	NR-LITE 2	量程±2 000 W/m²,灵敏度10 μV/(W/m²)	1
	聚碳风速变送器	RS-FSJT-^*	量程0~70 m/s,精度±(0.2+0.03风速)m/s	1
	多要素百叶盒	RS-BYH-M	湿度量程0~99%RH,温度量程-40~+120℃, 大气压力量程0~120 kPa	1
	气象站太阳能板	DZRC-M-35W-G18	最大:功率35 W,电流1.94 A,电压18 V	1
	铅蓄电池	6-FMD-12.0	电压12 V,电流12.0 Ah	1
	墒情终端太阳能板	290mm×350mm	最大:功率12 W,电流2 A,电压6 V	3
	土壤墒情传感器	RS-ECTH-N01-TR	电导率:量程0~20000 μs/cm,分辨率10 μs/cm, 精度±5%;土壤水分:量程0%~100%,分辨率0.1%, 精度±3%;温度:量程-40~80℃,分辨率0.1℃, 精度±0.5℃(25℃)	9
灌溉应用 Irrigation application	潜水泵	QY 25-32-4	功率:4 kW,扬程:32 m,流量:25 m³/h	1
	PE输水主管软带	PE材料,内径90 mm	—	150 m
	滴灌毛管	PE材料,内径16 mm	—	若干
	过滤器	Y型叠片式过滤器	灌溉系统杂质过滤120目	3
	施肥罐	压差式	容量25 L	3
	电磁阀	大流量直流脉冲电磁阀	90外丝,直流脉冲24 V,ARTHAS电磁头	3
	智能水表	DN80	常用流量63 m³/h,最小流量3.15 m³/h, 读数范围0.01~999 999 m³	3

图1 灌溉系统组件布置注:1.气象站;2.主管;3.水表;4.电磁阀;5.过滤器;6.施肥罐;7.潜水泵;8.墒情传感器终端;9.滴灌毛管;10.沉砂池

Fig.1 Irrigation system component layout Note:1.Weather stations; 2.Main Pipe; 3.Water meter;4.Solenoid valve; 5.The filter; 6.Fertilization can;7.Submersible pump; 8.Moisture sensor terminal; 9.Drip capillary; 10.Sand sink

表2 试验区土壤基础性质

Tab.2 Soil foundation properties in the experimental area

深度 Depth (cm)	容重 Bulk density (g/cm³)	质量含水率 Mass moisture content (%)	田间持水率 Field water holding rate (%)	含盐量 Salt content (g/kg)
20	1.43	19.30	28.04	0.23
40	1.45	31.77	32.27	0.34
60	1.45	39.88	30.34	0.37

图2 智能灌溉系统架构注:MCU1:气象监测控制终端;MCU2:墒情监测控制终端;MCU3:灌溉应用控制终端;M1:辐射传感器;M2空气温度传感器;M3:空气湿度传感器;M4:风速传感器;M5:气压传感器;S1:20cm墒情传感器;S2:40cm墒情传感器;S3:60cm墒情传感器;V1:电磁阀;V1:智能远传水表

Fig.2 Intelligent irrigation system architecture Note:MCU1:Meteorological monitoring and control terminal; MCU2:Moisture monitoring and control terminal; MCU3:Irrigation application control terminal; M1:Radiation sensor; M2:Air temperature sensor; M3:Air humidity sensor; M4:Wind speed sensor; M5:Air pressure sensor; S1:20 cm moisture sensor; S2:40 cm moisture sensor; S3:60 cm moisture sensor; V1:Solenoid valve; V1:Intelligent remote water meter

图3 智能灌溉系统各节点终端连接注:1.20 cm墒情传感器接口;2.40 cm墒情传感器接口;3.60 cm墒情传感器接口;4.太阳能板接口;5.蓄电池;6.DUT模块;7.太阳能转换模块;8.墒情数据汇集节点;9.DUT模块;10.气象站控制终端;11.传感器及电源;12.蓄电池;13.水表接口;14.电磁阀接口;15.太阳能板接口;16.蓄电池;17.电磁阀数据转换模;18.DUT模块;19.太阳能转换模块;20.灌溉控制终端数据汇集节点

Fig.3 Terminal connection diagram of each node of the intelligent irrigation system Note:1.20 cm moisture sensor interface; 2.40 cm moisture sensor interface; 3.60 cm moisture sensor; 4.Solar panel connector; 5.Battery; 6.DUT module; 7.Solar panel conversion module; 8.Moisture sensor collection node; 9.DUT module; 10.Weather station control terminal; 11.Sensor and power supply; 12.Battery; 13.Water meter connection; 14.Solenoid valve interface; 15.Solar panel connector; 16.Battery; 17.Solenoid valve data conversion module; 18.DUT Module; 19.Solar panel conversion module; 20.Irrigation control terminal data collection node

图4 云平台上机界面

Fig.4 Cloud Platform Hands-on Interface

图5 土壤墒情传感器布设位置注:1.墒情站;2.滴灌带;3.覆膜;4.20 cm墒情传感器;5.40 cm墒情传感器;6.60 cm墒情传感器

Fig.5 Position of the soil moisture sensor Note:1.Moisture content station; 2.Drip irrigation belt; 3.Film coating; 4.20 cm moisture sensor; 5.40 cm moisture sensor; 6.60 cm moisture sensor

图6 土壤墒情传感器拟合曲线

Fig.6 Fitting curve of soil moisture sensor

图7 不同灌溉模式下土壤体积含水率及含盐量变化

Fig.7 Changes of soil water content and salt content under different irrigation modes

表3 不同灌溉模式下棉花的产量、产量构成和水分利用效率变化

Tab.3 Effects of different irrigation modes on yield, yield composition and water use efficiency of cotton

处理 Treatments	单铃质量 The quality of single boll (g)	单株铃数 Boll number per	收获密度 Harvested density (10⁴株/hm²)	籽棉产量 Seed cotton yield (kg/hm²)	总耗水量 The total water consumption (mm)	水分利用效率 WUE (kg/m³)
W₁	5.60±0.07^a	7.80±0.30^d	15.99±0.55^a	6 291.96±198.42^c	591.09	1.065±0.034^c
W₂	5.59±0.09^a	9.45±0.13^a	16.32±0.25^a	7 755.27±247.16^a	492.58	1.574±0.050^b
W₃	5.40±0.05^b	9.16±0.13^b	16.02±0.25^a	7 135.28±159.97^b	394.06	1.811±0.041^a
CK	5.51±0.05^a	8.14±0.08^c	15.90±0.30^a	6 418.03±121.45^c	421.56	1.522±0.029^b

图8 不同灌溉模式下棉花不同生长阶段株高、茎粗和干物质积累的变化注:不同字母表示不同处理间0.05水平下差异显著,(P<0.05),下同

Fig.8 Changes of plant height, stem diameter and dry matter accumulation in different growth stages of cotton under different irrigation modes Note:Different letters indicate significant differences between treatments at the 0.05 level, (P<0.05),the same as below

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基于P-M模型的棉田智能灌溉系统的设计与试验

Design and experiment of intelligent irrigation system for cotton field based on P-M model

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