【摘要】：滴灌技術是一種局部灌溉方式,是目前提高農(nóng)業(yè)用水利用率最為有效的節(jié)水灌溉技術之一。掌握土壤水分運移規(guī)律是正確進行滴灌系統(tǒng)設計以及有效進行節(jié)水灌溉的前提,而對作物灌溉需水量的準確預測是進行有效節(jié)水的重要保障,對灌區(qū)農(nóng)業(yè)的可持續(xù)生產(chǎn)具有重要的指導和借鑒意義。本文主要從灌水方式以及灌溉預測模型兩個方面對節(jié)水灌溉進行了研究。主要研究內容概括如下:1)以室內無作物生長的燥紅壤土為研究對象,利用土壤濕度傳感器對單點源灌溉條件下土壤水分運移進行動態(tài)監(jiān)測和數(shù)據(jù)采集,主要考察了滴頭流量、灌水量以及初始含水量對土壤濕潤鋒運移的影響以及停灌后土壤含水量的再分布情況。2)提出了一種基于鍵逾滲模型的灌溉區(qū)基本控制單元自適應劃分方法。通過定義的連通性量化指標判斷灌區(qū)灌溉情況,并利用MATALB軟件進行該算法的仿真,驗證了該方法的有效性,最后在草坪地進行了實際驗證,結果證明了該算法的可行性及實用性。3)選取溫室黃瓜作為研究對象,采用遺傳算法優(yōu)化的BP神經(jīng)網(wǎng)絡構建了黃瓜灌溉需水量預測模型,并利用檢驗樣本驗證了該模型的預測效果。結果表明,該模型預測精度高,預測準確性好,可將其應用于溫室黃瓜需水量的預測。4)利用MATLAB的GUI界面設計了溫室內黃瓜需水量預測系統(tǒng),該系統(tǒng)具有友好的人機界面,能很好的方便用戶進行溫室黃瓜需水量的預測。
[Abstract]:Drip irrigation is a local irrigation method, which is one of the most effective irrigation techniques to improve the utilization of agricultural water. It is a prerequisite to correctly design drip irrigation system and to effectively carry out water-saving irrigation to master the law of soil moisture migration. The accurate prediction of crop irrigation water demand is an important guarantee for effective water-saving. It has important guidance and reference significance for sustainable agricultural production in irrigation district. In this paper, water-saving irrigation was studied from two aspects: irrigation mode and irrigation prediction model. The main research contents are summarized as follows: (1) the dry red loam growing without crops is used as the research object. The soil moisture transfer and data collection under single point source irrigation are carried out by using soil moisture sensor, and the flow rate of dripper is mainly investigated. The effects of irrigation amount and initial water content on soil moisture front migration and the redistribution of soil moisture content after irrigation closure (.2) an adaptive partition method of basic control unit of irrigation area based on key percolation model was proposed. The irrigation condition of irrigation area is judged by the defined connectivity quantitative index, and the simulation of the algorithm is carried out by using MATALB software. The validity of the method is verified. Finally, the validity of the method is verified in the lawn field. The results show that the algorithm is feasible and practical. 3) Cucumber in greenhouse is selected as the research object, and the forecast model of irrigation water demand of cucumber is constructed by BP neural network optimized by genetic algorithm. The prediction effect of the model is verified by test samples. The results show that the model has high prediction accuracy and good accuracy. It can be applied to the prediction of water demand of greenhouse cucumber. The GUI interface of MATLAB is used to design the water demand prediction system of cucumber in greenhouse. The system has friendly man-machine interface. It is convenient for users to forecast the water demand of cucumber in greenhouse.
【學位授予單位】：昆明理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：S274

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