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Reallocating crop rotation patterns improves water quality and maintains crop yield

Author

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  • Jiang, Fei
  • Drohan, Patrick J.
  • Cibin, Raj
  • Preisendanz, Heather E.
  • White, Charles M.
  • Veith, Tamie L.

Abstract

Meeting the growing food production needs of a society, while simultaneously maintaining or improving water quality, is a challenge facing many watersheds around the world. Across many nations, the agricultural norm is for farmers to dictate what, when and where to plant based on market demand and the most economically efficient use of land resources for the individual farm enterprise. As an alternative, the European Union (EU) has explored the potential of a soil-based, land use framework to achieve economic and environmental targets in agriculturally dominated watersheds; however, this framework has not been explored in the United States (US). We investigated the potential for an EU style soil-based, land use framework to improve water quality, while maintaining crop yields, in a sub-watershed of the Chesapeake Bay. The Soil and Water Assessment Tool (SWAT) was utilized to model crop growth, and losses of total nitrogen (TN), total phosphorus (TP) and sediment for an 8-year period (2010 - 2017). Based on SWAT model results, an algorithm was developed to spatially reallocate crop rotations within existing agricultural land to reduce TN, TP, and sediment losses based on soil properties while maintaining a similar production area of each rotation. Hay was reallocated onto landscapes most vulnerable to erosion and nutrient loss, whereas corn-soybean rotations were reallocated onto less vulnerable areas. In the reallocated scenario, 28% of agricultural lands retained the same crop rotation as the baseline scenario while 72% were reassigned. In a SWAT simulation of the reallocated scenario, TN, TP and sediment losses were reduced by 15%, 14% and 39%, respectively at an average annual scale. These results suggest that simply redistributing crop rotations within an impaired watershed can make significant water quality improvements even without additional structural best management practices. Although watershed-scale benefits were evaluated here, future research is needed to understand how this approach affects farm-level factors, as implementation may require some farmers to change the type of crops they grow.

Suggested Citation

  • Jiang, Fei & Drohan, Patrick J. & Cibin, Raj & Preisendanz, Heather E. & White, Charles M. & Veith, Tamie L., 2021. "Reallocating crop rotation patterns improves water quality and maintains crop yield," Agricultural Systems, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:agisys:v:187:y:2021:i:c:s0308521x20308763
    DOI: 10.1016/j.agsy.2020.103015
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    References listed on IDEAS

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    1. Weizhe Weng & Kelly M. Cobourn & Armen R. Kemanian & Kevin J. Boyle & Yuning Shi & Jemma Stachelek & Charles White, 2024. "Quantifying co‐benefits of water quality policies: An integrated assessment model of land and nitrogen management," American Journal of Agricultural Economics, John Wiley & Sons, vol. 106(2), pages 547-572, March.
    2. Xue Yang & Yuzheng Li & Chunying Li & Qianqian Li & Bin Qiao & Sen Shi & Chunjian Zhao, 2021. "Enhancement of Interplanting of Ficus carica L. with Taxus cuspidata Sieb. et Zucc. on Growth of Two Plants," Agriculture, MDPI, vol. 11(12), pages 1-14, December.
    3. Femeena, P.V. & Costello, C. & Brennan, R.A., 2023. "Spatial optimization of nutrient recovery from dairy farms to support economically viable load reductions in the Chesapeake Bay Watershed," Agricultural Systems, Elsevier, vol. 207(C).
    4. Biarnès, Anne & Bailly, Jean-Stéphane & Mekki, Insaf & Ferchichi, Intissar, 2021. "Land use mosaics in Mediterranean rainfed agricultural areas as an indicator of collective crop successions: Insights from a land use time series study conducted in Cap Bon, Tunisia," Agricultural Systems, Elsevier, vol. 194(C).
    5. Eini, Mohammad Reza & Salmani, Haniyeh & Piniewski, Mikołaj, 2023. "Comparison of process-based and statistical approaches for simulation and projections of rainfed crop yields," Agricultural Water Management, Elsevier, vol. 277(C).

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