为地中海地区可持续水资源管理开发低成本智能灌溉系统

IF 6.3 Q1 AGRICULTURAL ENGINEERING Smart agricultural technology Pub Date : 2024-10-30 DOI:10.1016/j.atech.2024.100629
Salvatore Filippo Di Gennaro , Davide Cini , Andrea Berton , Alessandro Matese
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引用次数: 0

摘要

农业用水占全球用水量的 70-80%,由于气候变化、降雨量减少和人口激增,农业用水面临严峻挑战。本研究介绍了在意大利托斯卡纳地区为番茄和甜瓜作物开发和实施低成本自动智能灌溉系统的情况。该项目是 DATI 项目的一部分,旨在彻底改变农业用水管理,尤其是应对气候变化、干旱和人口膨胀带来的挑战。这项研究跨越三个植被季节(2021-2023 年),重点是通过创新技术优化灌溉效率。智能灌溉系统从传统设置发展为综合解决方案,集成了蒸散模型、无线传感器网络和先进的控制算法。采用了不同的灌溉处理方法,代表了不同程度的减水效果。结果表明耗水量大幅减少,尤其是在 2023 年的灌溉季节,与该地区的传统做法相比,智能系统的用水量减少了 50%。该系统的发展过程涉及解决和排除各种问题,包括传感器校准、硬件挑战和土壤水分变化。土壤水分传感器数据显示了该系统的影响,表明在用水较多的处理中,土壤水分水平较高。研究强调了智能灌溉系统的经济可行性,其总成本低于 6000 欧元。该系统可远程管理多条灌溉管线,其可扩展性凸显了在不同面积的田地中广泛应用的潜力。总之,所开发的智能灌溉系统由蒸散模型和无线传感器网络驱动,是一种前景广阔的可持续解决方案。该系统可根据作物对水的需求进行精确灌溉,提高用水效率和总体产量。虽然传感器校准和维护方面的挑战依然存在,但本研究强调了智能灌溉在解决水资源短缺和促进可持续农业实践方面的潜力。
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Development of a low-cost smart irrigation system for sustainable water management in the Mediterranean region
Agricultural water consumption, constituting 70–80 % of global water usage, faces critical challenges due to climate change, diminishing rainfall, and a burgeoning population. This research presents the development and implementation of a low-cost automatic smart irrigation system for tomato and melon crops in the Tuscany region, Italy. The initiative, embedded within the DATI project, aims to revolutionize water management in agriculture, particularly addressing challenges posed by climate change, drought, and an expanding population. The study spans three vegetative seasons (2021–2023) and focuses on optimizing irrigation efficiency through innovative technologies. The smart irrigation system evolved from a conventional setup to a comprehensive solution, integrating evapotranspiration models, wireless sensor networks, and advanced control algorithms. Different irrigation treatments were applied, representing varying levels of water reduction. Results demonstrate a significant reduction in water consumption, particularly in the 2023 season, where the smart system utilized 50 % less water compared to conventional practices in the area. The system's evolution involved addressing and troubleshooting various issues, including sensor calibration, hardware challenges, and soil moisture variations. Soil moisture sensor data revealed the system's impact, showcasing higher levels in treatments with more water. The study emphasizes the economic viability of the smart irrigation system, with total costs below €6000. The scalability of the system, capable of managing multiple irrigation lines remotely, underscores its potential for widespread adoption across different field sizes. In conclusion, the developed smart irrigation system, driven by evapotranspiration models and wireless sensor networks, emerges as a promising and sustainable solution. The system offers precise irrigation based on crop water needs, enhancing water use efficiency and overall yields. While challenges in sensor calibration and maintenance persist, the study highlights the potential of smart irrigation to address water scarcity and contribute to sustainable agriculture practices.
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