Sensitivity study of the Predictive Optimal Water and Energy Irrigation (POWEIr) controller’s schedules for sustainable agriculture systems in resource-constrained contexts
{"title":"Sensitivity study of the Predictive Optimal Water and Energy Irrigation (POWEIr) controller’s schedules for sustainable agriculture systems in resource-constrained contexts","authors":"","doi":"10.1016/j.compag.2024.109230","DOIUrl":null,"url":null,"abstract":"<div><p>It is imperative to meet the growing food demands of our expanding global population while safeguarding the Earth’s finite natural resources. This challenge becomes even more pressing for resource-constrained farmers residing in low- and middle-income countries (LMICs), who disproportionately bear the brunt of food insecurity. In response to this critical issue, the Predictive Optimal Water and Energy Irrigation (POWEIr) controller is a promising solution. The POWEIr controller was designed as an affordable precision irrigation controller for solar-powered drip irrigation (SPDI) systems and offers an avenue to widen access to SPDI and precision agriculture for low-income farmers. The POWEIr controller creates energy- and water-efficient irrigation schedules that aim to reduce overall system costs. Employing simple yet effective physics-based models alongside minimal sensors to maintain cost-effectiveness, the controller’s accuracy has, until now, remained unexplored. This paper investigates the sensitivity of the POWEIr controller’s optimized irrigation schedules to user and weather sensor accuracy errors in inputs, while also assessing their impact on simulated crop yields. The results reveal that, under the tested scenarios, opting for a low-cost weather station over a high-quality counterpart could potentially save farmers over $900 with negligible consequences to crop yields. This conclusion held steadfast across diverse crop and soil types. The most significant factor affecting the optimal irrigation schedule was found to be changes in the crop coefficient, pointing to the need for calibration of the controller. This research underscores the POWEIr controller’s capability to optimize irrigation schedules through the use of cost-effective sensors and minimal calibration efforts. In doing so, it opens the door to greater adoption of precision irrigation technology and sustainable irrigation practices among farmers in LMICs. Ultimately, this progress has the potential to catalyze sustainable agriculture intensification on a global scale, moving us closer to a more food-secure and environmentally responsible future.</p></div>","PeriodicalId":50627,"journal":{"name":"Computers and Electronics in Agriculture","volume":null,"pages":null},"PeriodicalIF":7.7000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0168169924006215/pdfft?md5=5983df41aa217953b9284dc86b530dcb&pid=1-s2.0-S0168169924006215-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Electronics in Agriculture","FirstCategoryId":"97","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0168169924006215","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
It is imperative to meet the growing food demands of our expanding global population while safeguarding the Earth’s finite natural resources. This challenge becomes even more pressing for resource-constrained farmers residing in low- and middle-income countries (LMICs), who disproportionately bear the brunt of food insecurity. In response to this critical issue, the Predictive Optimal Water and Energy Irrigation (POWEIr) controller is a promising solution. The POWEIr controller was designed as an affordable precision irrigation controller for solar-powered drip irrigation (SPDI) systems and offers an avenue to widen access to SPDI and precision agriculture for low-income farmers. The POWEIr controller creates energy- and water-efficient irrigation schedules that aim to reduce overall system costs. Employing simple yet effective physics-based models alongside minimal sensors to maintain cost-effectiveness, the controller’s accuracy has, until now, remained unexplored. This paper investigates the sensitivity of the POWEIr controller’s optimized irrigation schedules to user and weather sensor accuracy errors in inputs, while also assessing their impact on simulated crop yields. The results reveal that, under the tested scenarios, opting for a low-cost weather station over a high-quality counterpart could potentially save farmers over $900 with negligible consequences to crop yields. This conclusion held steadfast across diverse crop and soil types. The most significant factor affecting the optimal irrigation schedule was found to be changes in the crop coefficient, pointing to the need for calibration of the controller. This research underscores the POWEIr controller’s capability to optimize irrigation schedules through the use of cost-effective sensors and minimal calibration efforts. In doing so, it opens the door to greater adoption of precision irrigation technology and sustainable irrigation practices among farmers in LMICs. Ultimately, this progress has the potential to catalyze sustainable agriculture intensification on a global scale, moving us closer to a more food-secure and environmentally responsible future.
期刊介绍:
Computers and Electronics in Agriculture provides international coverage of advancements in computer hardware, software, electronic instrumentation, and control systems applied to agricultural challenges. Encompassing agronomy, horticulture, forestry, aquaculture, and animal farming, the journal publishes original papers, reviews, and applications notes. It explores the use of computers and electronics in plant or animal agricultural production, covering topics like agricultural soils, water, pests, controlled environments, and waste. The scope extends to on-farm post-harvest operations and relevant technologies, including artificial intelligence, sensors, machine vision, robotics, networking, and simulation modeling. Its companion journal, Smart Agricultural Technology, continues the focus on smart applications in production agriculture.