Location: National Soil Erosion ResearchTitle: State of science of phosphorus modeling in tile drained agricultural systems using APEX
|WILLIAMS, CANDISS - Natural Resources Conservation Service (NRCS, USDA)|
|WILLIAMS, JIMMY - Blackland Research And Extension Center|
|JEONG, JAEHAK - Blackland Research And Extension Center|
Submitted to: Journal of Environmental Quality
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/6/2014
Publication Date: N/A
Interpretive Summary: Given the persistent eutrophication processes observed in the receiving water of agricultural landscapes, phosphorus (P) modeling may serve as a tool for evaluating conservation practices and strategies that can help reduced nutrient losses. Using the Agricultural Policy/ Environmental eXtender model, two new features were examined for P modeling in artificially drained agricultural fields. The inclusions of a non-linear (Langmuir) adsorption option (1), and of soluble P estimations in tile flow (2), were evaluated using monitoring data collected at a no-till corn-soybean rotation field site located at the St. Joseph River watershed. The inclusion of the Langmuir option proved to be successful when estimating P output values under high fertilizer application conditions. Yet, the results suggest that the estimation of P losses through tile still needs improvements as preferential flow processes, which may be an important transfer mechanisms, are currently not adequately simulated by the model.
Technical Abstract: Phosphorus losses through tile drained systems in agricultural landscapes may be causing the persistent eutrophication problems observed in surface water. The purpose of this paper is to evaluate the state of the science in the Agricultural Policy/Environmental eXtender (APEX) model related to surface and tile P transport. This was accomplished using data from a monitored corn-soybean rotation field in the St. Joseph River watershed, IN. The estimation of SP in surface runoff and tile flow in APEX includes a user defined linear (GLEAMS) and non-linear (Langmuir) sorption option. The results suggest that the inclusion of the Langmuir isotherm improved (18%) SP sorption estimates in surface runoff during the corn year only when P inputs were added, whereas the linear method was more appropriate during the soybean year when no fertilizers were applied. Similarly, SP estimates in tile flow were improved (30%) when using the Langmuir option during the corn year, though the overall model performance predicting this variable were very poor. Modeling improvements of P partitioning processes in APEX can help predict more realistic outputs. Yet to achieve this in tile flow, water percolation processes need to be improved to reflect preferential flow conditions often found in long-term no-till fields and in soils with high clay content. Greater accuracy in the estimation of the effect of artificial drainage systems, common in the US Midwest, should result in the improved evaluation of agricultural conservation practices in order to examine strategies that could reduce P losses for water quality purposes.