Journal article
Real‐Time Irrigation Scheduling Based on Weather Forecasts, Field Observations, and Human‐Machine Interactions
Water resources research, Vol.59(12), e2023WR035810
12/2023
DOI: 10.1029/2023WR035810
Abstract
Abstract Real‐time irrigation schedules have been shown to outperform predetermined irrigation schedules that do not consider the present state and requirements. However, implementing real‐time irrigation scheduling requires reliable present soil‐crop‐atmosphere dynamics and weather predictions; moreover, enabling farmers to adopt recommended water applications remains challenging as they rely on personal experience and knowledge. Farmers and computer‐based tools are rarely connected in a closed‐loop and farmers' feedback are usually not incorporated into a real‐time modeling procedure. To resolve these critical issues, this paper addresses the feasibility of a real‐time irrigation scheduling tool (RTIST) based on weather forecasts, field observations, and human‐machine interactions. RTIST integrates a simulation & optimization model, a data assimilation (DA) technique, and a human‐computer interaction method, and enables optimality, accuracy, and applicability of the tool. The principle of the RTIST is to engage farmers directly into computer modeling, and support irrigation scheduling decisions jointly based on model provided information and farmers' own justification. The optimization and simulation are validated by running the tool on two crop fields, showing the accuracy of present estimation and future prediction of soil moisture and leaf area index, taking advantage of field observation and DA. The applicability of RTIST is tested via virtual irrigation exercises with a group of farmers for a corn field in Eastern Nebraska. RTIST with farmers' direct engagement shows increased productivity in comparison to traditional practices. Especially, farmers' feedbacks show interest in using the tool in real‐world irrigation scheduling and providing meaningful suggestions to improve the tool for real‐world application.
Key Points Simulation‐optimization, data assimilation, and human‐computer interaction are integrated into a real‐time irrigation scheduling tool Human‐computer interaction facilitates practical application of the tool through farmer's engagement Using the tool leads to more accurate state estimations and higher profits in comparison to traditional techniques and practices
Details
- Title: Subtitle
- Real‐Time Irrigation Scheduling Based on Weather Forecasts, Field Observations, and Human‐Machine Interactions
- Creators
- A. Jamal - University of Illinois Urbana-ChampaignX. Cai - University of Illinois Urbana-ChampaignX. Qiao - Panhandle Research & Extension Center University of Nebraska‐Lincoln Lincoln NE USAL. Garcia - University of IowaJ. Wang - University of IowaA. Amori - University of Nebraska–LincolnH. Yang - University of Nebraska–Lincoln
- Resource Type
- Journal article
- Publication Details
- Water resources research, Vol.59(12), e2023WR035810
- DOI
- 10.1029/2023WR035810
- ISSN
- 0043-1397
- eISSN
- 1944-7973
- Grant note
- DOI: 10.13039/100000199, name: U.S. Department of Agriculture, award: MD.W‐2019‐08298, IOWW‐2018‐09055
- Language
- English
- Date published
- 12/2023
- Academic Unit
- Electrical and Computer Engineering; Civil and Environmental Engineering; Physics and Astronomy; Chemical and Biochemical Engineering
- Record Identifier
- 9984539652102771
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