Smart Irrigation Manager: A Simple User-Friendly Software for Determining Irrigation Scheduling
Smart Irrigation Manager (SIM) is a user-friendly standalone software run on Windows, which is developed to help growers, agronomists and irrigation engineers to develop irrigation schedules using basic information of soil water balance, crop characteristics and atmospheric conditions. SIM can be used to 1) Estimate reference evapotranspiration ( E T 0 ) using three different approaches, including the modified FAO Penman-Monteith (FAO-PM), Hargreaves model and the Blaney‒Criddle equation; 2) Estimate irrigation water requirements for single irrigation events using the K c - E T 0 and soil water depletion methods; and 3) develop irrigation schedules using the K c - E T 0 and Evapotranspiration–Soil Water Balance (ET-SWB) methods. The performance of SIM has been tested using data from three different climatic zones: arid (ICBA, UAE), humid continental (ALRC, Japan) and Mediterranean (ICARDA, Morocco), while the daily E T 0 estimated by SIM was compared to that calculated by the FAO E T 0 calculator. SIM fairly estimated the daily E T 0 using the FAO-PM method with average root mean squared error (RMSE) of 0.05 mm d ‒1 , while the daily estimates using the Hargreaves and Blaney‒Criddle methods were overestimated with average RMSE of 0.45 mm d ‒1 and 2.1 mm d ‒1 , respectively. Local calibration of daily E T 0 estimated by these two methods resulted in similar estimates of crop water requirements to those of the FAO-PM across all sites. SIM can be potentially used to develop irrigation scheduling scenarios; however, it is highly recommended to use the FAO K c - E T 0 instead of the ET-SWB for coarse soil or desert regions with low precipitation.
Authors
- Haruyuki Fujimaki (ORCID: https://orcid.org/0000-0003-0175-1773)
- Asad Sarwar Qureshi (ORCID: https://orcid.org/0000-0001-9966-4445)
- Hassan M. Abd El Baki
Publication Details
- Journal
- Smart Agricultural Technology
- Published
- 2025-08-08
- DOI
- https://doi.org/10.1016/j.atech.2025.101287
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00