An Automated Data-Driven Irrigation Scheduling Approach Using Model Simulated Soil Moisture and Evapotranspiration
نویسندگان
چکیده
Given the increasing prevalence of droughts, unpredictable rainfall patterns, and limited access to dependable water sources in United States worldwide, it has become crucial implement effective irrigation scheduling strategies. Irrigation is triggered when some variables, such as soil moisture or accumulated deficit, exceed a given threshold most common approaches applied scheduling. A High-Resolution Land Data Assimilation System (HRLDAS) was used this study generate timely accurate evapotranspiration (ET) data for management. By integrating HRLDAS products crop growth model (AquaCrop), an automated data-driven approach developed evaluated. For ET moisture, ET-water balance (ET-WB)-based method soil-moisture-based were accordingly. The ET-WB-based showed 10.6~33.5% water-saving result dry set seasons, whereas moisture-based saved 7.2~37.4% different weather conditions. Both these methods demonstrated good results saving (with varying range 10~40%) without harming yield. optimized thresholds two partially consistent with default values from Food Agriculture Organization similar trend growing season. Furthermore, forecasted integrated into see its effect. that additional 10% water, which 20~50%, can be This by taking advantage products, generated near-real-time manner. indicated great potential decision making.
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ژورنال
عنوان ژورنال: Sustainability
سال: 2023
ISSN: ['2071-1050']
DOI: https://doi.org/10.3390/su151712908