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Implementation of BMP Strategies for Adaptation to Climate Change and Land Use Change in a Pasture-Dominated Watershed

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  • Li-Chi Chiang

    (Department of Bioenvironmental Systems Engineering, National Taiwan University, 1, Section 4, Roosevelt Road, Da-an District, Taipei City 106, Taiwan)

  • Indrajeet Chaubey

    (Department of Agricultural and Biological Engineering, Purdue University, 225 South University Street West Lafayette, IN 47907, USA)

  • Nien-Ming Hong

    (Environment and Energy Management Center, Overseas Chinese University, No. 100, Chiao Kwang Road, Taichung 407, Taiwan)

  • Yu-Pin Lin

    (Department of Bioenvironmental Systems Engineering, National Taiwan University, 1, Section 4, Roosevelt Road, Da-an District, Taipei City 106, Taiwan)

  • Tao Huang

    (Department of Bioenvironmental Systems Engineering, National Taiwan University, 1, Section 4, Roosevelt Road, Da-an District, Taipei City 106, Taiwan)

Abstract

Implementing a suite of best management practices (BMPs) can reduce non-point source (NPS) pollutants from various land use activities. Watershed models are generally used to evaluate the effectiveness of BMP performance in improving water quality as the basis for watershed management recommendations. This study evaluates 171 management practice combinations that incorporate nutrient management, vegetated filter strips (VFS) and grazing management for their performances in improving water quality in a pasture-dominated watershed with dynamic land use changes during 1992–2007 by using the Soil and Water Assessment Tool (SWAT). These selected BMPs were further examined with future climate conditions (2010–2069) downscaled from three general circulation models (GCMs) for understanding how climate change may impact BMP performance. Simulation results indicate that total nitrogen (TN) and total phosphorus (TP) losses increase with increasing litter application rates. Alum-treated litter applications resulted in greater TN losses, and fewer TP losses than the losses from untreated poultry litter applications. For the same litter application rates, sediment and TP losses are greater for summer applications than fall and spring applications, while TN losses are greater for fall applications. Overgrazing management resulted in the greatest sediment and phosphorus losses, and VFS is the most influential management practice in reducing pollutant losses. Simulations also indicate that climate change impacts TSS losses the most, resulting in a larger magnitude of TSS losses. However, the performance of selected BMPs in reducing TN and TP losses was more stable in future climate change conditions than in the BMP performance in the historical climate condition. We recommend that selection of BMPs to reduce TSS losses should be a priority concern when multiple uses of BMPs that benefit nutrient reductions are considered in a watershed. Therefore, the BMP combination of spring litter application, optimum grazing management and filter strip with a VFS ratio of 42 could be a promising alternative for use in mitigating future climate change.

Suggested Citation

  • Li-Chi Chiang & Indrajeet Chaubey & Nien-Ming Hong & Yu-Pin Lin & Tao Huang, 2012. "Implementation of BMP Strategies for Adaptation to Climate Change and Land Use Change in a Pasture-Dominated Watershed," IJERPH, MDPI, vol. 9(10), pages 1-31, October.
    • Handle: RePEc:gam:jijerp:v:9:y:2012:i:10:p:3654-3684:d:20638
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    References listed on IDEAS

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    1. Taner, Mehmet Ümit & Carleton, James N. & Wellman, Marjorie, 2011. "Integrated model projections of climate change impacts on a North American lake," Ecological Modelling, Elsevier, vol. 222(18), pages 3380-3393.
    2. A. Kay & H. Davies & V. Bell & R. Jones, 2009. "Comparison of uncertainty sources for climate change impacts: flood frequency in England," Climatic Change, Springer, vol. 92(1), pages 41-63, January.
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    1. Li-Chi Chiang & Indrajeet Chaubey & Chetan Maringanti & Tao Huang, 2014. "Comparing the Selection and Placement of Best Management Practices in Improving Water Quality Using a Multiobjective Optimization and Targeting Method," IJERPH, MDPI, vol. 11(3), pages 1-23, March.

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