Examining the impacts of increased corn production on groundwater quality using a coupled modeling system

Abstract

This study demonstrates the value of a coupled chemical transport modeling system for investigating groundwater nitrate contamination responses associated with nitrogen (N) fertilizer application and increased corn production. The coupled Community Multiscale Air Quality Bidirectional and Environmental Policy Integrated Climate modeling system incorporates agricultural management practices and N exchange processes between the soil and atmosphere to estimate levels of N that may volatilize into the atmosphere, re-deposit, and seep or flow into surface and groundwater. Simulated values from this modeling system were used in a land-use regression model to examine associations between groundwater nitrate-N measurements and a suite of factors related to N fertilizer and groundwater nitrate contamination. Multi-variable modeling analysis revealed that the N-fertilizer rate (versus total) applied to irrigated (versus rainfed) grain corn (versus other crops) was the strongest N-related predictor variable of groundwater nitrate-N concentrations. Application of this multi-variable model considered groundwater nitrate-N concentration responses under two corn production scenarios. Findings suggest that increased corn production between 2002 and 2022 could result in 56% to 79% increase in areas vulnerable to groundwater nitrate-N concentrations ≥5mg/L. These above-threshold areas occur on soils with a hydraulic conductivity 13% higher than the rest of the domain. Additionally, the average number of animal feeding operations (AFOs) for these areas was nearly 5 times higher, and the mean N-fertilizer rate was 4 times higher. Finally, we found that areas prone to high groundwater nitrate-N concentrations attributable to the expansion scenario did not occur in new grid cells of irrigated grain-corn croplands, but were clustered around areas of existing corn crops. This application demonstrates the value of the coupled modeling system in developing spatially refined multi-variable models to provide information for geographic locations lacking complete observational data; and in projecting possible groundwater nitrate-N concentration outcomes under alternative future crop production scenarios.

Keywords: Agricultural impacts; Biosphere modeling; Groundwater quality; Regression modeling.

Fig. 1.

Location of groundwater nitrate well locations overlain on total N fertilizer placed on all corn crops in 2002 (panel a); extent of rainfed versus irrigated grain-corn domains for 2002 and 2022_BASE (same extent), and 2022_CORN scenarios (panel b).

Fig. 2.

High groundwater nitrate measurements and predictions overlain on soil hydraulic conductivity (panel a), aquifer type (panel b), and high density animal feeding operations (panel c).

Fig. 3.

N fertilizer rate predicted by coupled modeling system for 2002 (panel a), and for the 2022_CORN crop expansion scenario (panel b).

Fig. 4.

Residuals (observed-fitted) resulting from generalized least squares model prediction.

Fig. 5.

N fertilizer rate predicted by coupled modeling system for the 2022_CORN expansion scenario (panel a), and the change between scenarios (2022_CORN—2002; panel b).

Fig. 6.

Predictions of groundwater nitrate-N overlain with above-threshold grid cells for the 2022_CORN (panel a). Change in Above-threshold groundwater nitrate-N added by each scenario. Magenta squares are cells above-threshold in 2002, visible yellow squares are grid cells added by the 2022_BASE scenario, and black cells are added by the 2022_CORN scenario (panel b).