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This article in JEQ

  1. Vol. 37 No. 5, p. 1798-1809
     
    Received: Oct 3, 2007


    * Corresponding author(s): zme2@cornell.edu
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doi:10.2134/jeq2007.0522

Combined Monitoring and Modeling Indicate the Most Effective Agricultural Best Management Practices

  1. Zachary M. Easton *,
  2. M. Todd Walter and
  3. Tammo S. Steenhuis
  1. Dep. of Biological and Environmental Engineering, Cornell Univ., Ithaca, NY 14853

Abstract

Although water quality problems associated with agricultural nonpoint source (NPS) pollution have prompted the rapid and widespread adoption of a variety of so called “best management practices” (BMPs), there have been few realistic efforts to assess their combined effectiveness in reducing NPS pollution. This study used the Variable Source Loading Function (VSLF) model, a distributed watershed model, to simulate phosphorus (P) loading from an upstate New York dairy farm before and after the implementation of a suite of BMPs. With minimal calibration, the model calculates the dissolved P (DP) losses from impervious surfaces (e.g., barnyards), the plant/soil complex, field-applied manure, and loads associated with baseflow conditions. The simulated DP loads agreed well with measured loads for both the pre-BMP and post-BMP periods. More importantly, results showed that BMPs reduced DP loads by 35%, which is over half of the expected reduction if all manure was removed from the watershed, i.e., ∼50% reduction. The model results indicate that had no BMPs been installed DP loads would be ∼37% greater than observed at the watershed outlet. The most effective BMPs were those that disassociated pollutant loading areas from areas prone to generating runoff, i.e., hydrologically sensitive areas. By contrast, attempts to reduce P content in manure were somewhat less effective. This study demonstrates that a combination of distributed, mechanistic modeling and long-term monitoring provides better insights into the effectiveness of water quality protection efforts than either individually.

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Copyright © 2008. American Society of Agronomy, Crop Science Society of America, Soil Science SocietyAmerican Society of Agronomy, Crop Science Society of America, and Soil Science Society of America