Irrigation plays an important role for agricultural sustainability in U.S. and around the globe. In particular, the agricultural economy in the state of Nebraska, the largest U.S. state in terms of irrigated area, highly relies on irrigation in the growing season. With insufficient precipitation that has never met the demand for crop growth, the rural areas in Nebraska faces a central challenge to best utilize limited underground water in the Ogallala Aquifer for irrigation to sustain the growth of economy in the state. While irrigation can often help increase crop production, its cost and environmental effects are significant, especially during drought years. Furthermore, excessive irrigation can decrease harvestable yield, increase the coast for farming, and contribute to environmental degradation (such as nitrate leaching and soil erosion). Hence, irrigation scheduling is a key component for agricultural sustainability and growth in many rural areas in Nebraska.This proposed project will establish a smart and connected system to help rural communities' irrigation scheduling in Nebraska. The system will include intensive low-cost and smart sensor networks to measure soil moisture and 2-meter meteorological parameters in Scotts Bluffs county in western Nebraska, respectively. A citizen-science network with the same set of smart sensors will also be established by engaging with citizens outside of intensive network. The data collected from these sensors will be seamlessly assimilated into a modeling system that integrates weather forecast model, crop model, and irrigation scheduling optimization algorithm to assist farmers to maximize their crop profits, as well as to reduce excess water use. Observation data and model outputs will be delivered to the rural communities through smart-phone apps and on-demand web services that enable the users to access and visualize these data (including recommendations for irrigation schedule) to serve their customized needs (for any particular farm). By engaging communities through our proposed smart and connected system and planned activities, this project will help rural communities to embrace the opportunity of using smart technologies to address their economic challenges.Intellectual Merits:A smart and connected system is proposed that combines recent advances in environmental sensing and modeling to provide the recommendation of irrigation scheduling on the daily basis for farmers in two rural areas in Nebraska. This system will be used to test the hypothesis that data-driven approach and dedicated engagement with communities can be integrated to increase farms' profit and reduce engineering and environmental costs through optimizing irrigation scheduling in rural communities. A positive feedback loop is also hypothesized in which the smart-connected system can augment existing engagement and social acceptance of smart systems within the rural communities, and such augment in turn further strengthen the data-driven approach for improving system smartness, robustness, and the connections between communities. By providing solutions for seamless environmental sensor array design and communications, weather forecast with assimilation of sensor data at regional scale, and irrigation scheduling optimized for farm profits, the system in this project can be viewed as a prototype for future precision farming in many rural areas over the Southern Great Plains where the regional economy heavily depends on irrigation.Broader ImpactsThe proposed project will have broader impacts to rural communities by functioning as an accessible resource through our collaboration partners to outreach citizens in Nebraska, Iowa, and Illinois. This project will also provide training to students via updated courses and labs for interdisciplinary research that intersects biological science and engineering, environmental science and engineering, computer science and engineering, and social science. Research findings and data will be disseminated broadly at scientific meetings, public lectures, in publications, web sites, smartphone apps, and community engagement activities, thereby further broadening impacts of this project globally, especially for the regions where irrigated agriculture is dominant.
Abstract
Jun Wang
Jun Wang is a Professor in the University of Iowa (UI), with joint appointments in the Department of Chemical and Biochemical Engineering and the Iowa Informatics Initiative, and secondary affiliation with the Center for Global and Regional Environmental Studies, Department of Civil and Environmental Engineering, Department of Physics and Astronomy, and Center for Computer-Aided Design. Prior to joining UIowa in 2016, he worked in University of Nebraska – Lincoln for nine years, first as Assistant Professor and then Associate Professor. His current research focuses on the integration of satellite remote sensing and chemistry transport model to study air quality, wildfires, aerosol-cloud interaction, and land-air interaction. Having worked as a short-term visiting scientist/faculty in NASA GSFC, NOAA STAR, and NCAR, he also enjoys interdisciplinary research and has worked in in areas related to public health, agriculture, climate change, renewable (solar and wind) energy, supercomputing, visualization, data mining, and education in Earth Science. Jun Wang has authored or co-authored 100+ citable works in the peer-reviewed literature. He has been a science team member of several NASA satellite missions. His projects have been funded by NASA, NOAA, DoD, USDA, NSF, state agencies, and private industries.
In 2005, Jun Wang received his Ph.D. degree in Atmospheric Sciences from University of Alabama –Huntsville. In 2005-2007, he was a postdoctoral researcher in Harvard University. He also holds a B.S. in Meteorology from Nanjing Meteorology Institute (now Nanjing University of Information Science and Technology) and a M.S. in Atmospheric Sciences in Institute of Atmospheric Physics, Chinese Academy of Sciences. He was a recipient of NASA Earth System Science Graduate Student Fellowship in 2004, NOAA Climate and Global Change Postdoctoral Fellowship in 2005, NASA New Investigator Award in 2008, and NASA’s group achievement award for TEMPO satellite in 2013 and SNPP satellite in 2014. He also sits in “Atmospheric Environment” editorial advisory board and served as the section editor for its “New Directions” column in 2012 - 2017. Since 2018, he serves as an associate editor for Atmospheric Measurement Technique, and as an editor for Earth-Science Reviews.
Jun Wang grew up in a small village near the Yangze river’s entry to the ocean. Since his childhood, Jun Wang is always fascinated by different weather phenomena, and recognizes the importance of weather for the crop yield. This childhood experience has shaped Jun Wang's research projects that always strive to link the ending points (of research) toward real applications. A recent manifestation in this regard is his team’s latest development of real-time weather and quality forecast for the mid-west region (http://esmc.uiowa.edu), which has aided farmers in their decision planning for irrigation, fertilization, aerial pesticide application, and harvesting.
Jun Wang enjoys working with students and young scientists. In his view, One of the most joyful things for a faculty, is to see the students' progresses, achievements, and successes. His students have won various awards from different organizations at local, state, and national levels, and have gained valuable working experiences in national labs. They also traveled many places to present their exciting research results. In 2009, he received “Academic Star” award from University of Nebraska - Lincoln for “taking the art of mentoring to new height”
Performance Period: 03/01/2019 - 02/28/2023
Institution: University of Iowa
Sponsor: National Institute of Food and Agriculture
Award Number: 1831639
Core Areas:
Water, Energy, and Food,
Food Security and Agriculture
Project Material