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ARS Home » Research » Publications at this Location » Publication #183530


item Jaynes, Dan
item Dinnes, Dana

Submitted to: Ecological Modeling
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/22/2005
Publication Date: 7/10/2006
Citation: Li, C., Farahbakhshazad, N., Jaynes, D.B., Dinnes, D.L., Salas, W., Mclaughlin, D. 2006. Modeling nitrate leaching with a biogeochemical model modified based on observations in a row-crop field in Iowa. Ecological Modeling. 196:116-130.

Interpretive Summary: Prediction of nitrate leaching from cropland is crucial for preventing surface or ground water resources from contamination. Accurate modeling of nitrate leaching requires simulation of both soil hydrological and biogeochemical processes. Few existing models are strong in both aspects. In this project we describe the modification and testing of the Denitrification-Decomposition or DNDC model for predicting the fate and transport of nitrogen in a tile drained agricultural field in Iowa. The results showed that the modeled effects of precipitation, soil texture, soil organic carbon content, and fertilizer application rates on nitrate leaching rates were consistent with observations. Further work on this model will result in a tool that will help farmers, researchers, and action agency personnel to assess impacts of alternative management practices on agricultural production and water quality degradation.

Technical Abstract: Prediction of nitrate leaching risk from cropland is crucial for preventing contamination of surface or ground water resources of this chemical. Modeling of nitrate leaching requires a capacity for simulating soil hydrological and biogeochemical processes, but few models are strong in both aspects. This paper reports an attempt to improve an existing biogeochemical model, with limited modifications, for the estimation of nitrate leaching from tile-drained crop fields. Datasets of four-year intensive measurements from a corn-soybean rotation field in Iowa were utilized for the model innovation. The target model, Denitrification-Decomposition or DNDC, was equipped with detailed biogeochemical processes of nitrogen turnover and a simple module for one-dimensional movement of soil water. Preliminary tests indicated that the original DNDC missed the water leaching recession character that was demonstrated by observed tile discharge flow at the experimental site. To correct the deviation, we added new water retention features to DNDC by (1) adopting a recession curve to regulate gravity drainage flow in the simulated soil profile (0-50 cm), and (2) setting up a virtual water pool for the space between the bottom of the modeled soil profile (50 cm) and the tile lines depth of placement (145 cm) to control tile discharge flow. The recession curve defines the magnitude and pattern of water flow discharged from the bottom of the soil profile and the deep water pool is used to estimate the water efflux from the virtual pool after rainfall events. With the two modifications, DNDC predicted water leaching fluxes from the tile lines with improved magnitudes and patterns that matched observations. An adsorbed N pool was created in DNDC to simulate the buffering effect of soil on the amount of nitrate available for leaching. The Longmuir equation was adopted to simulate adsorption and desorption of ammonium ions on the soil absorbents. This modification enhanced DNDC's capacity for simulating free ammonium dynamics, nitrification, and nitrate leaching. The measured datasets from nine drainage tiles with three different fertilizer treatments in four years (1996-1999) at the experimental field in Iowa were used to guide the model modifications. A single treatment (high fertilizer rate) from one year (1998) was randomly selected for model calibration and the other 11 treatment-year combinations were used for model tests. The results indicated that the modified DNDC was capable of simulating the tile nitrate leaching fluxes. Sensitivity tests were conducted to examine general behaviors of the modified DNDC. The results showed that the modeled effects of precipitation, soil texture, soil organic carbon content, and fertilizer application rates on nitrate leaching rates were consistent with observed measures. This work proved that a biogeochemical model with limited modifications in hydrology may be a useful tool for estimating the effects of alternative crop management practice on nitrate leaching.