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Environmental engineering research v.15 no.2, 2010년, pp.123 - 126  
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

Assessment of Scale Effects on Dynamics of Water Quality and Quantity for Sustainable Paddy Field Agriculture

Kim, Min-Young    (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration   ); Kim, Min-Kyeong    (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration   ); Lee, Sang-Bong    (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration   ); Jeon, Jong-Gil    (Department of Agricultural Engineering, National Academy of Agricultural Science, Rural Development Administration  );
  • 초록

    Modeling non-point pollution across multiple scales has become an important environmental issue. As a more representative and practical approach in quantifying and qualifying surface water, a modular neural network (MNN) was implemented in this study. Two different site-scales ( $1.5\;{\times}\;10^5$ and $1.62\;{\times}\;10^6\;m^2$ ) with the same plants, soils, and paddy field management practices, were selected. Hydrologic data (rainfall, irrigation and surface discharge) and water quality data (time-series nutrient loadings) were continuously monitored and then used for the verification of MNN performance. Correlation coefficients (R) for the results predicted from the networks versus measured values were within the range of 0.41 to 0.95. The small block could be extrapolated to the large field for the rainfall-surface drainage process. Nutrient prediction produced less favorable results due to the complex phenomena of nutrients in the drainage water. However, the feasibility of using MNN to generate improved prediction accuracy was demonstrated if more hydrologic and environmental data are provided. The study findings confirmed the estimation accuracy of the upscaling from a small-segment block to large-scale paddy field, thereby contributing to the establishment of water quality management for sustainable agriculture.


  • 주제어

    Scale-dependent modeling .   Total nitrogen .   Total phosphorus .   Rainfall-surface discharge .   Modular neural network .   Times-eries forecasting.  

  • 이미지/표/수식 (4)

    • Input parameters depending upon their application
    • Dynamics of monthly rainfall, irrigation, and surface discharge (2002-2004).
    • Comparison of rainfall and surface discharge over time in a large paddy field (L; 162 ha) and a small paddy plot (S; 15 ha).
    • The best model parameters and results for MNN’s performance and optimization.

    논문관련 이미지

  • 참고문헌 (20)

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