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ARS Home » Midwest Area » Ames, Iowa » National Laboratory for Agriculture and The Environment » Agroecosystems Management Research » Research » Publications at this Location » Publication #244689
Title: Soil-test N recommendations augmented with PEST optimized RZWQM simulations

Author
item Malone, Robert - Rob
item Jaynes, Dan
item Ma, Liwang
item NOLAN, B. TOM - Us Geological Survey (USGS)
item Meek, David
item Karlen, Douglas

Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/19/2010
Publication Date: 9/1/2010
Citation: Malone, R.W., Jaynes, D.B., Ma, L., Nolan, B., Meek, D.W., Karlen, D.L. 2010. Soil-test N recommendations augmented with PEST optimized RZWQM simulations. Journal of Environmental Quality. 39:1711-1723.

Interpretive Summary: Fertilizer application rates based on soil nitrate tests may help reduce nitrogen (N) loss to the environment without negatively impacting corn production. The late spring nitrate test (LSNT) is one such test and improving our understanding of year-to-year N rate differences may increase its use. Agricultural system models such as the Root Zone Water Quality Model (RZWQM) can accurately simulate year-to-year differences in field N dynamics and corn production based on weather. Therefore, we use RZWQM to investigate the long-term effect of LSNT on nitrate loss in subsurface drainage. The results show that RZWQM simulates significantly lower nitrate concentration in discharge from LSNT treatments compared to fall N fertilizer applications within the tile drained Walnut Creek Iowa watershed. These model results are similar to field measured data from the paired watershed experiment. A statistical model we developed using RZWQM simulations from 1970-2005 shows that early season precipitation and early season temperature account for 90% of the interannual variation in LSNT rates. These results suggest that: 1) RZWQM is a promising tool to accurately estimate the water quality effects of LSNT and; 2) year-to-year LSNT determined rates are mainly due to variation in early season precipitation and temperature. This research will help agricultural scientists more thoroughly understand the effect of weather patterns on spring fertilizer application rates and is a step toward development of simple tools to estimate optimum N application rates, all of which facilitates the design of more effective systems that maintain crop production while protecting the environment.

Technical Abstract: Fertilizer application rates based on soil nitrate tests may help reduce N loss to the environment. The late spring nitrate test (LSNT) is one such test and improving our understanding of year-to-year N rate differences may increase its use. It is known that annual plant available soil N is associated with early season temperature and precipitation. It is also known that calibrated models such as RZWQM can simulate year-to-year variability in field N dynamics and corn production based on weather. However, watershed scale research in Iowa that thoroughly addresses model response to the LSNT is lacking. We use autoregressive techniques and the automatic parameter calibration program PEST to show that RZWQM simulates significantly lower nitrate concentration in discharge from LSNT treatments compared to fall N fertilizer applications within the tile drained Walnut Creek Iowa watershed (> 5 mg N/L difference for the third year of the treatment, 1999). The model results are similar to field measured data from the paired watershed experiment. A statistical model we developed using RZWQM simulations from 1970-2005 shows that early season precipitation and early season temperature account for 90% of the interannual variation in LSNT rates. Long-term simulations with similar average N application rates to corn (150.7 kg N/ha) also reveal that annual average N loss in tile flow were 20.4, 22.2, and 27.3 kg N/ha for LSNT, single spring N application, and single fall application. These results suggest that: 1) RZWQM is a promising tool to accurately estimate the water quality effects of LSNT; 2) the vast majority of N loss difference between LSNT and fall applications is from over winter and preplant N losses; and 3) year-to-year LSNT determined rates are mainly due to variation in early season precipitation and temperature.