Informed decisions to optimize water use and irrigation investments
Harsh weather conditions and limited water access are driving research and technology innovation that will help farmers and producers make informed decisions about irrigation investments and how to optimize water use efficiency.
In Nevada, water is so limited that inefficient use of irrigation water can reduce crop yields and threaten a farm’s financial viability. Traditional irrigation systems assume uniform field conditions and cannot account for differences in soil type, crop stress or water needs that vary across a field. Variable rate irrigation systems capable of applying different water amounts to distinct parts of a field can help conserve water. However, their adoption has been limited by the lack of decision support systems. Researchers at the Nevada Agricultural Experiment Station in collaboration with the University of California, Davis, and the U.S. Department of Agriculture’s Agricultural Research Service in Bushland, Texas, are improving ARSPivot, an open-source irrigation decision support system, in an effort to help farmers apply water more efficiently under challenging arid conditions. The project integrates real-time weather, soil moisture, plant canopy temperature and plant height data to create site-specific irrigation maps for center pivot and linear move sprinkler irrigation systems. This work supports farmers by reducing water use with minimal or no yield reduction, and by helping them manage limited water supplies more effectively. Field experiments are underway in Reno, Davis and Bushland. Researchers expect that, as an open-source tool, ARSPivot will help to reduce barriers for the adoption of variable rate irrigation technology.
Nevada Agricultural Experiment Station; University of California, Davis | Project supported by USDA Capacity – Research; state appropriations.
Ohio’s agriculture is predominantly rain-fed, with less than 1% of farmland irrigated despite experiencing severe droughts in recent years that resulted in significant crop yield losses. Farmers lack data-driven information on when and where supplemental irrigation would provide economic benefits. Understanding the relationship between soil water deficit, weather patterns and crop yields is essential for farmers to make informed decisions about irrigation investments and to optimize water use efficiency. Researchers at Central State University in Ohio have developed an advanced framework that combines soil water balance modeling with machine learning algorithms to assess irrigation needs. The models evaluated monthly precipitation, temperature and soil moisture data to identify counties that would benefit most from targeted irrigation during summer months, providing farmers with region-specific recommendations for water management strategies. This research provides data-driven tools to help farmers make informed decisions about irrigation investments.
Central State University – Research | Project supported by Evans-Allen capacity funds. Photo courtesy of Nevada Agricultural Experiment Station.
