Smartphone Apps for Irrigation Scheduling

Abstract

SmartIrrigation apps were developed to provide real-time irrigation schedules for selected crops (i.e., avocado, citrus, cotton, peanut, strawberry, and vegetables). Irrigation schedules in the smartphone apps are based on evapotranspiration (ET) or a water balance methodology using real-time weather data from the Florida Automated Weather Network and the Georgia Environmental Monitoring Network. The FAO Penman-Monteith method is used for calculating reference ET, and crop coefficients (K c) are applied based on time after planting, calendar month, or a crop's phenological stage. The functionality of each app was customized for each user group considering the most common irrigation systems used. Custom features include water conservation options, splitting irrigation events, spreadsheet output emails, and notifications. App inputs vary by crop (primarily due to the irrigation system used); however, all apps require root depth, irrigation rate, and soil type except the strawberry app. App outputs also vary and include estimated reference ET, days between irrigation events, irrigation depth and duration, accumulated rain for previous seven days, and growing degree days. National Weather Service forecast data are also provided in the apps. The apps are available in Android and iOS stores. A limitation to the app irrigation schedules is the spatial variation in rainfall, given the finite set of weather stations. Future efforts will focus on more accurate inclusion of rainfall into the irrigation schedules generated by the SmartIrrigation apps.

Advances in Hass avocado irrigation scheduling under digital agriculture approach

“…Multiple causes explain why irrigators do not implement new irrigation technologies (Abdullah and Samah, 2013;Mottaleb, 2018). Irrigation scheduling decision-support applications such as smartphone apps, web-based platforms, and desktop programs bridge the existing timing and water-related knowledge gap in irrigation methods (Migliaccio et al, 2016). Thousands of valuable irrigation-related data can currently be retrieved in a publicly available and near-real-time manner through online applications.…”

“…The IS smartphone app used by the avocado growers detailed above goes by the name Smartirrigation Avocado and can be found in the Google Play and Apple App Stores (Migliaccio et al, 2016). This app requires input parameters such as the irrigation system, the crop, the soil type, and IS characteristics to output the accumulated precipitation for the seven previous days, the applied irrigation events timing, and the reached moisture depth.…”

Emerging Technologies for Sustainable Irrigation: Selected Papers from the 2015 ASABE and IA Irrigation Symposium

“…Although modern sciencebased irrigation scheduling has existed for approximately 60 years, with one of the first reports by Van Bavel (1956), the long-term and consistent adoption of appropriate irrigation scheduling has been dismal (Shearer and Vomacil, 1981;Lamm and Rogers, 2015). To facilitate better adoption rates and improved irrigation scheduling, Migliaccio et al (2016) developed a software application (i.e., smartphone and tablet app) to provide real-time irrigation schedules for various crops (avocado, citrus, cotton, peanut, strawberry, urban turf, cabbage, squash, tomato, and watermelon) in the southeastern U.S. The application can use real-time weather data from both the Florida Automated Weather Network and the Georgia Environmental Monitoring Network to calculate crop ET using a water balance method for scheduling irrigation.…”

Assessment of Irrigation Scheduling Systems in Germany: Survey of the Users and Comparative Study

“…In some cases, remote sensing observations are also integrated (Thysen and Detlefsen, 2006;D'Urso et al, 2010;Melton et al, 2012;Montgomery et al, 2015;Vuolo et al, 2015). Services are usually provided as online applications (Montoro et al, 2011;Palmer, 2011;Kaloxylos et al, 2014;Giannerini and Genovesi, 2015) or by a specific app available for end-users (Li et al, 2013;Bartlett et al, 2015;Migliaccio, 2016). Despite some difficulties identified for the integration of the service in some contexts (Walker, 2002;Bjornlund et al, 2009;Lorite et al, 2012;Tapsuwan et al, 2015;Giannakis et al, 2016), the systems were shown to be a relevant support for the improvement and assessment of the agricultural water management.…”