Location: Adaptive Cropping Systems Laboratory
Title: Optimizing irrigation and nitrogen use for potato production in Washington State under current and future climate conditionsAuthor
Paff, Kirsten | |
Fleisher, David | |
Timlin, Dennis |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 9/1/2021 Publication Date: N/A Citation: N/A Interpretive Summary: Technical Abstract: Most of the potato crop in Washington State is grown on well drained sandy soils under low rainfall conditions, which requires farmers to apply large quantities of nitrogen fertilizer and irrigation. Since sandy soils drain very quickly, they are at a higher risk of nitrogen leaching and subsequent groundwater contamination and lost investment for the farmers. Temperatures in the Pacific Northwest are expected to increase, which would not only directly impact the potato crop, but could also limit available irrigation water by causing less snowfall and earlier snowmelt. Therefore, it will become increasingly more important to optimize agricultural water use. SPUDSIM is a soil-plant-atmosphere model that can simulate potato growth, development, and yield on an hourly time step by taking into account the interactions of the growing environment, management practices, and genotype factors. This project has three goals. First, is to evaluate SPUDSIM’s ability to simulate the effects of varying levels of nitrogen fertilizer and irrigation on the potato crop as well as nitrogen leaching. This is achieved by comparing simulated versus experimental data from multiple years that cover a range of management options, including multiple N treatments and full and deficit irrigation treatments. The second goal is to find best management practices for potato grown on sandy soils in Washington State in order to minimize inputs and nitrogen loss and maximize yields. This will be done by simulating potato crops under a range of irrigation and fertilizer treatments over a thirty-year period using historical weather data. Third, is to evaluate whether such best management practices remain valid under future climate conditions. This will be achieved by re-running the simulations from the second step using future climate data. |