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Ontology-based simulation of water flow in organic soils applied to Florida sugarcane

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  • Kwon, Ho-Young
  • Grunwald, Sabine
  • Beck, Howard W.
  • Jung, Yunchul
  • Daroub, Samira H.
  • Lang, Timothy A.
  • Morgan, Kelly T.

Abstract

An ontology-based simulation (OntoSim) is a unique data modeling environment where soil-plant-nutrient processes are represented as database objects and the user-defined relationships among objects are used to generate computer code (Java) for running the simulation. The aim of this study was to model hydrologic processes of sugarcane-grown organic soils utilizing OntoSim in the Everglades Agricultural Area (EAA) of South Florida. This OntoSim-Sugarcane model describes the complex hydrology of sub-irrigation and open ditch drainage commonly used on Florida farms. Model calibration was conducted by (i) selecting rectangular farm water management units ( 0.65; coefficient of residual mass 0.55 and coefficient of residual mass

Suggested Citation

  • Kwon, Ho-Young & Grunwald, Sabine & Beck, Howard W. & Jung, Yunchul & Daroub, Samira H. & Lang, Timothy A. & Morgan, Kelly T., 2010. "Ontology-based simulation of water flow in organic soils applied to Florida sugarcane," Agricultural Water Management, Elsevier, vol. 97(1), pages 112-122, January.
    • Handle: RePEc:eee:agiwat:v:97:y:2010:i:1:p:112-122
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    References listed on IDEAS

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    1. Helwig, Trevor G. & Madramootoo, Chandra A. & Dodds, Georges T., 2002. "Modelling nitrate losses in drainage water using DRAINMOD 5.0," Agricultural Water Management, Elsevier, vol. 56(2), pages 153-168, July.
    2. Singh, R. & Helmers, M.J. & Qi, Zhiming, 2006. "Calibration and validation of DRAINMOD to design subsurface drainage systems for Iowa's tile landscapes," Agricultural Water Management, Elsevier, vol. 85(3), pages 221-232, October.
    3. Rice, Ronald W. & Izuno, Forrest T. & Garcia, Raymond M., 2002. "Phosphorus load reductions under best management practices for sugarcane cropping systems in the Everglades Agricultural Area," Agricultural Water Management, Elsevier, vol. 56(1), pages 17-39, July.
    4. Wang, X. & Mosley, C.T. & Frankenberger, J.R. & Kladivko, E.J., 2006. "Subsurface drain flow and crop yield predictions for different drain spacings using DRAINMOD," Agricultural Water Management, Elsevier, vol. 79(2), pages 113-136, January.
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    1. Beck, Howard & Morgan, Kelly & Jung, Yunchul & Grunwald, Sabine & Kwon, Ho-young & Wu, Jin, 2010. "Ontology-based simulation in agricultural systems modeling," Agricultural Systems, Elsevier, vol. 103(7), pages 463-477, September.
    2. Li Zhao & Tong Heng & Lili Yang & Xuan Xu & Yue Feng, 2021. "Study on the Farmland Improvement Effect of Drainage Measures under Film Mulch with Drip Irrigation in Saline–Alkali Land in Arid Areas," Sustainability, MDPI, vol. 13(8), pages 1-18, April.

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