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Modeling and Monitoring the Water and Nitrate Transport and Potato Growth at a Vegetable Farm in the Suwannee River Basin, FL

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  Paper number  032127,  2003 ASAE Annual Meeting . (doi: 10.13031/2013.14006) @2003
Authors:   Frank W. McKinnie, Wendy D. Graham, James W. Jones, Donald A. Graetz
Keywords:   Nitrate, leaching, DSSAT, HYDRUS

The ultimate goal of this research was to develop Best Management Practices (BMP) to reduce nutrient loadings to ground water from vegetable farms in the Suwannee River Basin. To achieve this objective nitrogen and water movement through the vadose zone was monitored and modeled under one 56.7 ha center pivot at a 2020 ha vegetable farm just west of OBrien, FL. This farm lies just a few miles from the Suwannee River in the upstream direction of groundwater flow. The sandy soils on this farm are extremely susceptible to leaching nitrogen through the soil and then into the Floridan Aquifer. Monitoring wells, soil samples, and plant samples were used to obtain onsite nitrogen, plant and soil moisture information over time to track nitrogen movement and calibrate mathematical models. Soil analysis, crop management and weather information provided inputs necessary for existing vadose zone and crop models. The DSSAT35 crop model and the HYDRUS2D vadose zone model were used to produce an estimate of the load and concentration of nitrogen and the quantity of water leaching through the vadose zone to the Floridan Aquifer. The DSSAT model was also used to predict crop growth, nitrogen uptake and crop yield. The DSSAT model was calibrated using the spring 2002 potato crop. The results from DSSAT were used to predict nitrogen leaching and crop yield to aid in the development of the BMP. Results from the 2002 calibration illustrate the importance of incorporating multi-dimensional water and nutrient transport and the need to replace or improve upon the current methods implemented by the DSSAT plant model.

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