CN-121970671-A - Self-adaptive drip irrigation control system and method fused with optimal model of soil solution

CN121970671ACN 121970671 ACN121970671 ACN 121970671ACN-121970671-A

Abstract

The invention discloses a self-adaptive drip irrigation control system and method fused with an optimal model of a soil solution, and belongs to the field of agricultural irrigation. The system integrates five modules of layered soil and soil solution monitoring, meteorological and crop growth monitoring, data acquisition and management, fertigation execution and operation feedback. Through deep buried multi-layer soil sensing and solution collection, real-time monitoring of key parameters such as moisture, nutrients and the like of different soil layers is realized, and a dynamic target is set by combining crop growth requirements and meteorological data. The system adopts an optimal model of soil solution to perform dynamic balance analysis on the monitoring data and the target parameters, introduces a multi-factor linkage and layered regulation strategy, intelligently generates an optimal water and fertilizer scheme and accurately executes the optimal water and fertilizer scheme. The whole process automatically records and feeds back the quality, supports model self-learning and scheme optimization, improves the nutrient utilization rate of crops, reduces the resource waste, and realizes efficient and intelligent precise agricultural water and fertilizer management.

Inventors

WANG HANBO
WANG TIEQIANG
WANG YITENG
GONG DAOZHI
CHEN BAOQING
ZHAO LIHUA
Zhang daying
ZHANG WEIXIAN

Assignees

河北省水利科学研究院(河北省大坝安全技术中心、河北省堤防水闸技术中心)

Dates

Publication Date: 20260505
Application Date: 20260123

Claims (8)

1. A self-adaptive drip irrigation control system integrating an optimal model of soil solution is characterized by comprising the following components: The soil solution monitoring unit is formed by combining a deeply buried multi-parameter soil sensor and a soil solution collector and is arranged on different soil layers of a field, and the depth of the sensor is set according to the distribution of crop root systems; The weather and crop growth monitoring unit adopts an integrated field weather station and portable crop physiological parameter monitoring equipment, and comprises a temperature and humidity sensor, a rainfall meter, an anemoscope and a solar radiation sensor, and automatically acquires weather data and synchronizes the weather data to the data acquisition and management platform in a wireless mode; the data acquisition and management platform integrates data output of each sensing terminal and collector based on the Internet of things architecture, and transmits the data to the cloud server through a 4G/5G or LoRa wireless network after gathering and preliminary processing by utilizing the edge computing gateway; The irrigation and fertilization executing system consists of a control host, a distributed electromagnetic valve, a main/branch pipeline network and an automatic fertilizer distributor, wherein the control host automatically calculates the required water and fertilizer input amount based on the latest sensing data and a decision model and transmits the water and fertilizer input amount to a partition executor in a RS485, modbus or wireless mode; And the operation supervision and quality feedback module tracks the implementation effect of irrigation and fertilization operation and the growth condition of crops in the whole process.
2. An adaptive drip irrigation method integrated with an optimal model of soil solution, said method being applied to the system according to claim 1, said method comprising: actively monitoring the state of layered soil and solution, and monitoring the water content, main nutrient ions, pH value and salinity of each deep soil layer to ensure that a main root system area and a leaching layer are covered; Setting target parameters of a crop growing period, determining an optimum soil solution comprehensive threshold interval (moisture, nitrogen, phosphorus, potassium concentration and pH) of each period according to crop varieties and growing stages, and combining meteorological conditions and historical yield increasing experience to set a staged nutrient supply and soil moisture content target; Generating a dynamic balance analysis and optimal regulation scheme, adopting a soil solution optimal model, introducing a layered dynamic weight mechanism to link with weather-crop-soil ternary factors, carrying out weight-division regulation on the actual water and fertilizer requirement conditions of different soil layer root areas, and improving the crop nutrient utilization rate by combining weather prediction and correcting soil water and fertilizer scheduling parameters, so as to reduce nutrient leaching loss and resource waste; The whole process of the precise execution and operation is recorded, the regulation and control result is issued to the intelligent control host, the irrigation valve is driven to be started in a partitioned mode, the water and fertilizer integrated machine is precisely proportioned, and the consumption of each area is regulated and controlled in a layered mode according to a target threshold; and (3) the result feedback and the scheme re-optimization, continuously tracking the crop growth index, comparing with the initial target, and adjusting the solution parameters and the management scheme for the substandard land.
3. The self-adaptive drip irrigation method for fusing the optimal model of the soil solution according to claim 2, wherein the active monitoring of the layered soil and the solution state comprises the steps of selecting monitoring points in different representative areas of a field according to the root system distribution and the soil heterogeneity of crops, and burying a multi-parameter soil sensor and a soil solution collector in a main root system area, a lower seepage layer and a necessary deeper soil layer respectively; Soil moisture, pH, salinity and main nutrient ion data of different soil layers are actively collected at regular time through a high-precision soil moisture, pH, conductivity and temperature integrated sensor and a negative pressure ceramic cup or a high-molecular membrane permeation device, and are transmitted to a cloud platform for analysis through the Internet of things.
4. The self-adaptive drip irrigation method for fusing the optimal model of the soil solution according to claim 2, wherein the setting of the target parameters of the crop growth period comprises the steps of according to the variety characteristics of the planted crops and the requirements of each growth stage, taking relevant scientific research documents, soil fertility test results and local planting experience, and combining real-time and historical meteorological data; And dynamically setting the comprehensive threshold intervals of soil moisture, nitrogen, phosphorus, potassium, pH and conductivity in each stage by utilizing a crop water and fertilizer requirement model and a soil-crop-meteorological ternary balance analysis.
5. The self-adaptive drip irrigation method for fusing the optimal model of the soil solution according to claim 2, wherein the generation of the dynamic balance analysis and optimal regulation scheme comprises the steps of receiving and integrating real-time soil solution monitoring data from different depths, and automatically comparing the real-time soil solution monitoring data with a target parameter interval to obtain a current dynamic gap; adopting a soil solution optimal model, layering a soil profile, introducing a layered dynamic weight mechanism, combining meteorological input and crop growth data, establishing a meteorological-crop-soil ternary regulation equation, and coupling soil moisture migration and ion concentration dynamic mass balance; Through an information feedback mechanism, the self-adaptive regulation and control are realized based on historical data and crop growth reaction dynamic regulation and control weight parameters and leaching loss penalty; And solving the optimal layering input quantity by utilizing the improved particle swarm algorithm, generating the most economical and effective water and fertilizer scheduling scheme of the batch, and issuing the water and fertilizer scheduling scheme to an execution system for implementation.
6. The self-adaptive drip irrigation method based on the optimal model of the soil solution, as set forth in claim 2, wherein the accurate execution and operation whole-course record comprises the steps that the optimized water and fertilizer input command is automatically issued to each regional intelligent control host through the Internet of things platform, each group of irrigation valves is intelligently called by the host, the regional layered irrigation control is realized, and the optimal fertilization solution is accurately input to the appointed soil layer and region through the automatic proportioning system of the water and fertilizer integrated machine.
7. The self-adaptive drip irrigation method for fusing the optimal model of the soil solution according to claim 2, wherein the result feedback and scheme re-optimization comprises the steps of carrying out omnibearing tracking on multiple indexes of crop growth conditions, final yield and quality of a target area, comparing and analyzing with target parameters, actively correcting solution model parameters aiming at a land block with deviation, and dynamically adjusting strategies.
8. The method for self-adaptive drip irrigation with the optimal model of the soil solution as claimed in claim 5, wherein the improved particle swarm algorithm comprises the steps of encoding the water and fertilizer input quantity of each layer at each moment into the dimension of particles, and introducing the knowledge of the weight distribution and gradient migration fields into a self-adaptive updating mechanism of the particle speed and the inertia weight; And combining individual and global optimal guidance, domain gradient influence correction, and dynamic optimization under a multi-target condition; The objective function considers the minimum requirements of nutrient sufficiency, leaching loss and cost, and the threshold value of the constraint penalty function processing interval and the maximum input agronomic constraint are adopted to prevent the overrun of objective parameters and the waste of resources; and each round of automatic screening of the current optimal scheme adopts random disturbance and dynamic parameter adjustment, so that the searching precision and the convergence speed are improved.

Description

Self-adaptive drip irrigation control system and method fused with optimal model of soil solution Technical Field The invention belongs to the field of agricultural irrigation, and particularly relates to a self-adaptive drip irrigation control system and method for fusing an optimal model of a soil solution. Background Along with the continuous pursuit of modern agriculture on high yield, high quality and efficient resource utilization of crops, refined water and fertilizer management has become a core link for improving farmland productivity and sustainable development of environment. The traditional irrigation and fertilization mode depends on manual experience or single soil moisture index, and lack of system monitoring on soil solution nutrient dynamic and soil layer differential conditions easily causes low nutrient utilization rate, unbalanced crop supply and demand and water and fertilizer waste, and even aggravates environmental problems such as soil secondary salinization. In recent years, the rapid development of the technologies of the sensor and the Internet of things provides a technical foundation for the intellectualization and automation of the field water and fertilizer management. However, the existing intelligent drip irrigation system is often focused on the feedback regulation and control of surface layer single-point soil moisture or simple meteorological factors, lacks comprehensive linkage capability of multiple soil layers and multiple factors, and is difficult to realize accurate response to heterogeneity of different crops, different periods and different soil layers. Meanwhile, the soil solution is used as a medium for directly absorbing nutrients by plants, and the parameters such as moisture, main nutrient ion concentration, pH, salt state and the like are monitored and dynamically regulated in real time and in layers, so that the soil solution has important significance in guaranteeing efficient absorption of crops and reducing nutrient leaching loss and environmental risks. Therefore, development of a novel intelligent drip irrigation control system which integrates a layered soil solution optimal model, gives consideration to meteorological and crop growth states and has self-adaptive feedback optimization capability is needed, and powerful support is provided for efficient agricultural production and resource environment collaborative development. Disclosure of Invention The invention aims to solve the problems that the existing irrigation and fertilization system lacks accurate monitoring and dynamic regulation and control on soil solution states of different soil layers, cannot consider weather changes and crop growth requirements, causes low water and fertilizer utilization efficiency, resource waste and the like, and provides an intelligent drip irrigation control technology capable of integrating a layered soil solution optimal model, adaptively adjusting irrigation and fertilization schemes, realizing accurate and efficient supply of water and nutrients in root areas of crops, remarkably improving the utilization rate of agricultural resources and reducing environmental risks. In order to achieve the above purpose, the present invention is realized by adopting the following technical scheme: The system comprises: The soil solution monitoring unit is formed by combining a deeply buried multi-parameter soil sensor and a soil solution collector and is arranged on different soil layers of a field, and the depth of the sensor is set according to the distribution of crop root systems; The weather and crop growth monitoring unit adopts an integrated field weather station and portable crop physiological parameter monitoring equipment, and comprises a temperature and humidity sensor, a rainfall meter, an anemoscope and a solar radiation sensor, and automatically acquires weather data and synchronizes the weather data to the data acquisition and management platform in a wireless mode; the data acquisition and management platform integrates data output of each sensing terminal and collector based on the Internet of things architecture, and transmits the data to the cloud server through a 4G/5G or LoRa wireless network after gathering and preliminary processing by utilizing the edge computing gateway; The irrigation and fertilization executing system consists of a control host, a distributed electromagnetic valve, a main/branch pipeline network and an automatic fertilizer distributor, wherein the control host automatically calculates the required water and fertilizer input amount based on the latest sensing data and a decision model and transmits the water and fertilizer input amount to a partition executor in a RS485, modbus or wireless mode; And the operation supervision and quality feedback module tracks the implementation effect of irrigation and fertilization operation and the growth condition of crops in the whole process. In one aspect, the method comprises: actively moni