Automated real-time irrigation analytics inform diversity in regional irrigator behavior and water withdrawal and use characteristics

Effective agricultural water management requires accurate, continuous, and transparent accounting of water use in irrigated agroecosystems, especially in water-limited regions where moratoriums may be imposed. Advances in sensor technologies, networking, and data analytics can aid in fulfilling this task by automatically collecting, analyzing and reporting real-time data to infer irrigators’ practices and behaviors, crop water requirements, water applications and use. In this research, an automated irrigation water withdrawal and water use monitoring and data collection system was deployed to monitor actual irrigation dynamics for 31 commercial and large-scale agricultural production fields for three consecutive years. Production scale fields (representing a total of 1050 ha) included center pivot (P), gravity (surface/furrow) (G) and subsurface drip-irrigated (S) fields. On average, irrigation was initiated 40–70 days after planting (DAP) and terminated by 120–140 DAP. The proportion of irrigation systems operating simultaneously and peak water abstraction were highest (70–90 %) during July and August. Mean depth of water applied across all fields was 243, 264 and 284 mm in 2013, 2014 and 2015, respectively. Site-specific monitoring of precipitation, soil moisture, and evaporative demand and a soil-water balance model resulted in mean seasonal irrigation requirement estimates of 394, 242 and 184 mm, in 2013, 2014 and 2015, respectively; for maize; and 307, 163 and 219 mm in 2013, 2014 and 2015, respectively, for soybean. Despite reduction of calculated mean irrigation requirement in 2014 and 2015 by 40–50 %, actual irrigation applications by producers did not change considerably and irrigation applied exceeded irrigation water requirements in 80 % of the fields, suggesting needs for irrigation water management technology implementation and associated educational programs in the region. Some fields showed irrigation applications exceeding the mean annual allocated (moratorium) irrigation depth (305 mm), implying that irrigation decisions are still largely driven by non-scientific and/or technical methods. While substantial farm-to-farm heterogeneity makes it challenging to robustly benchmarking regional water footprint and irrigator behavior, it also creates an opportunity for developing and implementing methodologies and strategies for real-time monitoring of farm-level irrigation dynamics. New advances in technologies with telemetry capabilities as well as internet of things (IoTs) can be leveraged to effectively create databases, track and compare water usage to better plan, allocate, distribute, monitor and manage limited water resources for enhancing agricultural productivity. These processes can also be used for education and demonstration for irrigation professionals to enhance adoption of such technologies. This research has the potential for technology and strategy transfer for advanced water management to other regions in the United States and globally.